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1. High incidence and geographic distribution of cleft palate in Finland are associated with the IRF6 gene.

Author: Rahimov, Fedik, Rahimov, Fedik, Nieminen, Pekka, Kumari, Priyanka, Juuri, Emma, Nikopensius, Tiit, Paraiso, Kitt, German, Jakob, Karvanen, Antti, Kals, Mart, Elnahas, Abdelrahman, Karjalainen, Juha, Kurki, Mitja, Palotie, Aarno, Heliövaara, Arja, Esko, Tõnu, Jukarainen, Sakari, Palta, Priit, Ganna, Andrea, Patni, Anjali, Mar, Daniel, Bomsztyk, Karol, Mathieu, Julie, Ruohola-Baker, Hannele, Visel, Axel, Fakhouri, Walid, Schutte, Brian, Cornell, Robert, Rice, David, Rahimov, Fedik, Rahimov, Fedik, Nieminen, Pekka, Kumari, Priyanka, Juuri, Emma, Nikopensius, Tiit, Paraiso, Kitt, German, Jakob, Karvanen, Antti, Kals, Mart, Elnahas, Abdelrahman, Karjalainen, Juha, Kurki, Mitja, Palotie, Aarno, Heliövaara, Arja, Esko, Tõnu, Jukarainen, Sakari, Palta, Priit, Ganna, Andrea, Patni, Anjali, Mar, Daniel, Bomsztyk, Karol, Mathieu, Julie, Ruohola-Baker, Hannele, Visel, Axel, Fakhouri, Walid, Schutte, Brian, Cornell, Robert, and Rice, David
Abstract: In Finland, the frequency of isolated cleft palate (CP) is higher than that of isolated cleft lip with or without cleft palate (CL/P). This trend contrasts to that in other European countries but its genetic underpinnings are unknown. We conducted a genome-wide association study in the Finnish population and identified rs570516915, a single nucleotide polymorphism highly enriched in Finns, as strongly associated with CP (P = 5.25 × 10-34, OR = 8.65, 95% CI 6.11-12.25), but not with CL/P (P = 7.2 × 10-5), with genome-wide significance. The risk allele frequency of rs570516915 parallels the regional variation of CP prevalence in Finland, and the association was replicated in independent cohorts of CP cases from Finland (P = 8.82 × 10-28) and Estonia (P = 1.25 × 10-5). The risk allele of rs570516915 alters a conserved binding site for the transcription factor IRF6 within an enhancer (MCS-9.7) upstream of the IRF6 gene and diminishes the enhancer activity. Oral epithelial cells derived from CRISPR-Cas9 edited induced pluripotent stem cells demonstrate that the CP-associated allele of rs570516915 concomitantly decreases the binding of IRF6 and the expression level of IRF6, suggesting impaired IRF6 autoregulation as a molecular mechanism underlying the risk for CP.
Published: 2024

2. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Author: Suzuki, Ken, Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry, Yin, Xianyong, Lorenz, Kim, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio, Kanoni, Stavroula, Rayner, Nigel, Bocher, Ozvan, Arruda, Ana, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon, Preuss, Michael, Petty, Lauren, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert, Cook, James, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban, Chai, Jin-Fang, Bielak, Lawrence, Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj, Noordam, Raymond, Lim, Victor, Tam, Claudia, Joo, Yoonjung, Chen, Chien-Hsiun, Raffield, Laura, Prins, Bram, Nicolas, Aude, Yanek, Lisa, Chen, Guanjie, Brody, Jennifer, Kabagambe, Edmond, An, Ping, Xiang, Anny, Choi, Hyeok, Cade, Brian, Tan, Jingyi, Broadaway, K, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda, Adeyemo, Adebowale, Aguilar-Salinas, Carlos, Ahluwalia, Tarunveer, Anand, Sonia, Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas, Burant, Charles, Butterworth, Adam, Canouil, Mickaël, Chan, Juliana, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Suzuki, Ken, Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry, Yin, Xianyong, Lorenz, Kim, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio, Kanoni, Stavroula, Rayner, Nigel, Bocher, Ozvan, Arruda, Ana, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon, Preuss, Michael, Petty, Lauren, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert, Cook, James, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban, Chai, Jin-Fang, Bielak, Lawrence, Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj, Noordam, Raymond, Lim, Victor, Tam, Claudia, Joo, Yoonjung, Chen, Chien-Hsiun, Raffield, Laura, Prins, Bram, Nicolas, Aude, Yanek, Lisa, Chen, Guanjie, Brody, Jennifer, Kabagambe, Edmond, An, Ping, Xiang, Anny, Choi, Hyeok, Cade, Brian, Tan, Jingyi, Broadaway, K, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda, Adeyemo, Adebowale, Aguilar-Salinas, Carlos, Ahluwalia, Tarunveer, Anand, Sonia, Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas, Burant, Charles, Butterworth, Adam, Canouil, Mickaël, Chan, Juliana, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, and Cushman, Mary
Abstract: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
Published: 2024

3. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author: Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J, Yin, Xianyong, Lorenz, Kim M, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E M, Kanoni, Stavroula, Rayner, Nigel W, Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S K, Preuss, Michael H, Petty, Lauren E, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A, Cook, James P, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J, Grarup, Niels, Chen, Wei-Min, Bork-Jensen, Jette, Islam, Md Tariqul, Jørgensen, Torben, Linneberg, Allan, Witte, Daniel R, Lind, Lars, Hansen, Torben, Pedersen, Oluf, Loos, Ruth J F, Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J, Yin, Xianyong, Lorenz, Kim M, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E M, Kanoni, Stavroula, Rayner, Nigel W, Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S K, Preuss, Michael H, Petty, Lauren E, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A, Cook, James P, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J, Grarup, Niels, Chen, Wei-Min, Bork-Jensen, Jette, Islam, Md Tariqul, Jørgensen, Torben, Linneberg, Allan, Witte, Daniel R, Lind, Lars, Hansen, Torben, Pedersen, Oluf, and Loos, Ruth J F
Abstract: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
Published: 2024

4. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author: Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J, Yin, Xianyong, Lorenz, Kim M, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E M, Kanoni, Stavroula, Rayner, Nigel W, Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S K, Preuss, Michael H, Petty, Lauren E, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A, Cook, James P, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J, Grarup, Niels, Chen, Wei-Min, Bork-Jensen, Jette, Islam, Md Tariqul, Jørgensen, Torben, Linneberg, Allan, Witte, Daniel R, Lind, Lars, Hansen, Torben, Pedersen, Oluf, Loos, Ruth J F, Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J, Yin, Xianyong, Lorenz, Kim M, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E M, Kanoni, Stavroula, Rayner, Nigel W, Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S K, Preuss, Michael H, Petty, Lauren E, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A, Cook, James P, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J, Grarup, Niels, Chen, Wei-Min, Bork-Jensen, Jette, Islam, Md Tariqul, Jørgensen, Torben, Linneberg, Allan, Witte, Daniel R, Lind, Lars, Hansen, Torben, Pedersen, Oluf, and Loos, Ruth J F
Abstract: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
Published: 2024

5. A genome-wide association study of outcome from traumatic brain injury.

Author: Kals, Mart, Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D, Puccio, Ava M, Okonkwo, David O, Temkin, Nancy, Steyerberg, Ewout W, Stein, Murray B, Manley, Geoff T, Maas, Andrew IR, Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K, Genetic Associations In Neurotrauma (GAIN) Consortium (with contribution from the CENTER-TBI, TRACK-TBI, CABI, MGB, and TBIcare studies), Kals, Mart, Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D, Puccio, Ava M, Okonkwo, David O, Temkin, Nancy, Steyerberg, Ewout W, Stein, Murray B, Manley, Geoff T, Maas, Andrew IR, Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K, and Genetic Associations In Neurotrauma (GAIN) Consortium (with contribution from the CENTER-TBI, TRACK-TBI, CABI, MGB, and TBIcare studies)
Abstract: BackgroundFactors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias.MethodsWe performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography.FindingsThe estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4).InterpretationWhile multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available.FundingA full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022

6. A genome-wide association study of outcome from traumatic brain injury.

Author: Kals, Mart, Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D, Puccio, Ava M, Okonkwo, David O, Temkin, Nancy, Steyerberg, Ewout W, Stein, Murray B, Manley, Geoff T, Maas, Andrew IR, Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K, Genetic Associations In Neurotrauma (GAIN) Consortium (with contribution from the CENTER-TBI, TRACK-TBI, CABI, MGB, and TBIcare studies), Kals, Mart, Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D, Puccio, Ava M, Okonkwo, David O, Temkin, Nancy, Steyerberg, Ewout W, Stein, Murray B, Manley, Geoff T, Maas, Andrew IR, Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K, and Genetic Associations In Neurotrauma (GAIN) Consortium (with contribution from the CENTER-TBI, TRACK-TBI, CABI, MGB, and TBIcare studies)
Abstract: BackgroundFactors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias.MethodsWe performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography.FindingsThe estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4).InterpretationWhile multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available.FundingA full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022

7. A genome-wide association study of outcome from traumatic brain injury

Author: Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K., Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, and Menon, David K.
Abstract: BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4). INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022
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8. A genome-wide association study of outcome from traumatic brain injury

Author: Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K., Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, and Menon, David K.
Abstract: BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4). INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022
Full Text: View/download PDF

9. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author: Mahajan, Anubha, Spracklen, Cassandra N., Zhang, Weihua, Ng, Maggie C. Y., Petty, Lauren E., Kitajima, Hidetoshi, Yu, Grace Z., Rueger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M., Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R., Rayner, Nigel W., Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, Parolo, Pietro della Briotta, Lin, Kuang, Bragg, Fiona, Preuss, Michael H., Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A., Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J., Yao, Jie, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P., Kals, Mart, Grarup, Niels, Schmidt, Ellen M., Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Lecoeur, Cecile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Jensen, Richard A., Tajuddin, Salman, Kabagambe, Edmond K., An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Akiyama, Masato, Anand, Sonia S., Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Brummett, Chad M., Buchanan, Thomas A., Canouil, Mickael, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry, I, Fuchsberger, Christian, Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, Gonzalez-Villalpando, Clicerio, Gonzalez-Villalpando, Maria Elena, Goodarzi, Mark O., Gordon-Larsen, Penny, Gorkin, David, Gross, Myron, Guo, Yu, Hackinger, Sophie, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jorgensen, Marit E., Jorgensen, Torben, Kamatani, Yoichiro, Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kohara, Katsuhiko, Kriebel, Jennifer, Kronenberg, Florian, Kuusisto, Johanna, Lall, Kristi, Lange, Leslie A., Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian'an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lyssenko, Valeriya, Mamakou, Vasiliki, Mani, K. Radha, Meitinger, Thomas, Metspalu, Andres, Morris, Andrew D., Nadkarni, Girish N., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Nongmaithem, Suraj S., Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Porneala, Bianca, Prasad, Gauri, Preissl, Sebastian, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Kathryn, Sabanayagam, Charumathi, Sander, Maike, Sandow, Kevin, Sattar, Naveed, Schonherr, Sebastian, Schurmann, Claudia, Shahriar, Mohammad, Shi, Jinxiu, Shin, Dong Mun, Shriner, Daniel, Smith, Jennifer A., So, Wing Yee, Stancakova, Alena, Stilp, Adrienne M., Strauch, Konstantin, Suzuki, Ken, Takahashi, Atsushi, Taylor, Kent D., Thorand, Barbara, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tomlinson, Brian, Torres, Jason M., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Vujkovic, Marijana, Wacher-Rodarte, Niels, Wheeler, Eleanor, Whitsel, Eric A., Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamauchi, Toshimasa, Yengo, Loic, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Hanis, Craig L., Peyser, Patricia A., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Zeggini, Eleftheria, Yokota, Mitsuhiro, Rich, Stephen S., Kooperberg, Charles, Pankow, James S., Engert, James C., Chen, Yii-Der Ida, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Kardia, Sharon L. R., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Groop, Leif, Mook-Kanamori, Dennis O., Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Pare, Guillaume, Sale, Michele M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Bottinger, Erwin P., Dehghan, Abbas, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Kottgen, Anna, Koh, Woon-Puay, Palmer, Colin N. A., Liu, Simin, Abecasis, Goncalo, Kooner, Jaspal S., Loos, Ruth J. F., North, Kari E., Haiman, Christopher A., Florez, Jose C., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Magi, Reedik, Langenberg, Claudia, Wareham, Nicholas J., Maeda, Shiro, Kadowaki, Takashi, Lee, Juyoung, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Myers, Simon R., Ferrer, Jorge, Gaulton, Kyle J., Meigs, James B., Mohlke, Karen L., Gloyn, Anna L., Bowden, Donald W., Below, Jennifer E., Chambers, John C., Sim, Xueling, Boehnke, Michael, Rotter, Jerome, I, McCarthy, Mark, I, Morris, Andrew P., Mahajan, Anubha, Spracklen, Cassandra N., Zhang, Weihua, Ng, Maggie C. Y., Petty, Lauren E., Kitajima, Hidetoshi, Yu, Grace Z., Rueger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M., Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R., Rayner, Nigel W., Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, Parolo, Pietro della Briotta, Lin, Kuang, Bragg, Fiona, Preuss, Michael H., Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A., Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J., Yao, Jie, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P., Kals, Mart, Grarup, Niels, Schmidt, Ellen M., Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Lecoeur, Cecile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Jensen, Richard A., Tajuddin, Salman, Kabagambe, Edmond K., An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Akiyama, Masato, Anand, Sonia S., Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Brummett, Chad M., Buchanan, Thomas A., Canouil, Mickael, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry, I, Fuchsberger, Christian, Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, Gonzalez-Villalpando, Clicerio, Gonzalez-Villalpando, Maria Elena, Goodarzi, Mark O., Gordon-Larsen, Penny, Gorkin, David, Gross, Myron, Guo, Yu, Hackinger, Sophie, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jorgensen, Marit E., Jorgensen, Torben, Kamatani, Yoichiro, Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kohara, Katsuhiko, Kriebel, Jennifer, Kronenberg, Florian, Kuusisto, Johanna, Lall, Kristi, Lange, Leslie A., Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian'an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lyssenko, Valeriya, Mamakou, Vasiliki, Mani, K. Radha, Meitinger, Thomas, Metspalu, Andres, Morris, Andrew D., Nadkarni, Girish N., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Nongmaithem, Suraj S., Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Porneala, Bianca, Prasad, Gauri, Preissl, Sebastian, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Kathryn, Sabanayagam, Charumathi, Sander, Maike, Sandow, Kevin, Sattar, Naveed, Schonherr, Sebastian, Schurmann, Claudia, Shahriar, Mohammad, Shi, Jinxiu, Shin, Dong Mun, Shriner, Daniel, Smith, Jennifer A., So, Wing Yee, Stancakova, Alena, Stilp, Adrienne M., Strauch, Konstantin, Suzuki, Ken, Takahashi, Atsushi, Taylor, Kent D., Thorand, Barbara, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tomlinson, Brian, Torres, Jason M., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Vujkovic, Marijana, Wacher-Rodarte, Niels, Wheeler, Eleanor, Whitsel, Eric A., Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamauchi, Toshimasa, Yengo, Loic, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Hanis, Craig L., Peyser, Patricia A., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Zeggini, Eleftheria, Yokota, Mitsuhiro, Rich, Stephen S., Kooperberg, Charles, Pankow, James S., Engert, James C., Chen, Yii-Der Ida, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Kardia, Sharon L. R., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Groop, Leif, Mook-Kanamori, Dennis O., Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Pare, Guillaume, Sale, Michele M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Bottinger, Erwin P., Dehghan, Abbas, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Kottgen, Anna, Koh, Woon-Puay, Palmer, Colin N. A., Liu, Simin, Abecasis, Goncalo, Kooner, Jaspal S., Loos, Ruth J. F., North, Kari E., Haiman, Christopher A., Florez, Jose C., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Magi, Reedik, Langenberg, Claudia, Wareham, Nicholas J., Maeda, Shiro, Kadowaki, Takashi, Lee, Juyoung, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Myers, Simon R., Ferrer, Jorge, Gaulton, Kyle J., Meigs, James B., Mohlke, Karen L., Gloyn, Anna L., Bowden, Donald W., Below, Jennifer E., Chambers, John C., Sim, Xueling, Boehnke, Michael, Rotter, Jerome, I, McCarthy, Mark, I, and Morris, Andrew P.
Abstract: We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
Published: 2022
Full Text: View/download PDF

10. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

Author: Mahajan, Anubha, Mahajan, Anubha, Spracklen, Cassandra N, Zhang, Weihua, Ng, Maggie CY, Petty, Lauren E, Kitajima, Hidetoshi, Yu, Grace Z, Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M, Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R, Rayner, Nigel W, Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, Della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H, Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A, Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J, Yao, Jie, Bielak, Lawrence F, Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P, Kals, Mart, Grarup, Niels, Schmidt, Ellen M, Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor JY, Tam, Claudia HT, Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M, Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R, Chen, Guanjie, Jensen, Richard A, Tajuddin, Salman, Kabagambe, Edmond K, An, Ping, Xiang, Anny H, Choi, Hyeok Sun, Cade, Brian E, Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S, Adeyemo, Adebowale, Aguilar-Salinas, Carlos A, Akiyama, Masato, Anand, Sonia S, Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A, Brummett, Chad M, Buchanan, Thomas A, Canouil, Mickaël, Chan, Juliana CN, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Mahajan, Anubha, Mahajan, Anubha, Spracklen, Cassandra N, Zhang, Weihua, Ng, Maggie CY, Petty, Lauren E, Kitajima, Hidetoshi, Yu, Grace Z, Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M, Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R, Rayner, Nigel W, Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, Della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H, Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A, Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J, Yao, Jie, Bielak, Lawrence F, Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P, Kals, Mart, Grarup, Niels, Schmidt, Ellen M, Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor JY, Tam, Claudia HT, Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M, Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R, Chen, Guanjie, Jensen, Richard A, Tajuddin, Salman, Kabagambe, Edmond K, An, Ping, Xiang, Anny H, Choi, Hyeok Sun, Cade, Brian E, Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S, Adeyemo, Adebowale, Aguilar-Salinas, Carlos A, Akiyama, Masato, Anand, Sonia S, Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A, Brummett, Chad M, Buchanan, Thomas A, Canouil, Mickaël, Chan, Juliana CN, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, and Cushman, Mary
Abstract: We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
Published: 2022

11. A genome-wide association study of outcome from traumatic brain injury

Author: Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K., Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, and Menon, David K.
Abstract: BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4). INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022
Full Text: View/download PDF

12. A genome-wide association study of outcome from traumatic brain injury

Author: Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, Menon, David K., Kals, Mart, Kunzmann, Kevin, Parodi, Livia, Radmanesh, Farid, Wilson, Lindsay, Izzy, Saef, Anderson, Christopher D., Puccio, Ava M., Okonkwo, David O., Temkin, Nancy, Steyerberg, Ewout W., Stein, Murray B., Manley, Geoff T., Maas, Andrew I. R., Richardson, Sylvia, Diaz-Arrastia, Ramon, Palotie, Aarno, Ripatti, Samuli, Rosand, Jonathan, and Menon, David K.
Abstract: BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4). INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
Published: 2022
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13. Phylogenetic history of patrilineages rare in northern and eastern Europe from large-scale re-sequencing of human Y-chromosomes

Author: Ilumae, Anne-Mai, Post, Helen, Flores, Rodrigo, Karmin, Monika, Sahakyan, Hovhannes, Mondal, Mayukh, Montinaro, Francesco, Saag, Lauri, Bormans, Concetta, Sanchez, Luisa Fernanda, Ameur, Adam, Gyllensten, Ulf B., Kals, Mart, Magi, Reedik, Pagani, Luca, Behar, Doron M., Rootsi, Siiri, Villems, Richard, Ilumae, Anne-Mai, Post, Helen, Flores, Rodrigo, Karmin, Monika, Sahakyan, Hovhannes, Mondal, Mayukh, Montinaro, Francesco, Saag, Lauri, Bormans, Concetta, Sanchez, Luisa Fernanda, Ameur, Adam, Gyllensten, Ulf B., Kals, Mart, Magi, Reedik, Pagani, Luca, Behar, Doron M., Rootsi, Siiri, and Villems, Richard
Abstract: The most frequent Y-chromosomal (chrY) haplogroups in northern and eastern Europe (NEE) are well-known and thoroughly characterised. Yet a considerable number of men in every population carry rare paternal lineages with estimated frequencies around 5%. So far, limited sample-sizes and insufficient resolution of genotyping have obstructed a truly comprehensive look into the variety of rare paternal lineages segregating within populations and potential signals of population history that such lineages might convey. Here we harness the power of massive re-sequencing of human Y chromosomes to identify previously unknown population-specific clusters among rare paternal lineages in NEE. We construct dated phylogenies for haplogroups E2-M215, J2-M172, G-M201 and Q-M242 on the basis of 421 (of them 282 novel) high-coverage chrY sequences collected from large-scale databases focusing on populations of NEE. Within these otherwise rare haplogroups we disclose lineages that began to radiate similar to 1-3 thousand years ago in Estonia and Sweden and reveal male phylogenetic patterns testifying of comparatively recent local demographic expansions. Conversely, haplogroup Q lineages bear evidence of ancient Siberian influence lingering in the modern paternal gene pool of northern Europe. We assess the possible direction of influx of ancestral carriers for some of these male lineages. In addition, we demonstrate the congruency of paternal haplogroup composition of our dataset with two independent population-based cohorts from Estonia and Sweden.
Published: 2021
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14. A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

Author: Guo, Yanjun, Rist, Pamela M., Daghlas, Iyas, Giulianini, Franco, Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H.H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Ridker, Paul M., Hrafnsdottir, Maria Gudlaug, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, Duijn, Cornelia M.van, Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Christensen, Anne Francke, Hansen, Thomas Folkmann, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, M. Arfan, Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel D., Belin, Andrea C., Dichgans, Martin, Wessman, Maija, Maagdenberg, Arn M.J.M.van den, Zwart, John Anker, Boomsma, Dorret I., Smith, George Davey, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Chasman, Daniel I., Nyholt, Dale R., Palotie, Aarno, Agee, Michelle, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, other, and, Guo, Yanjun, Rist, Pamela M., Daghlas, Iyas, Giulianini, Franco, Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H.H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Ridker, Paul M., Hrafnsdottir, Maria Gudlaug, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, Duijn, Cornelia M.van, Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Christensen, Anne Francke, Hansen, Thomas Folkmann, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, M. Arfan, Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel D., Belin, Andrea C., Dichgans, Martin, Wessman, Maija, Maagdenberg, Arn M.J.M.van den, Zwart, John Anker, Boomsma, Dorret I., Smith, George Davey, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Chasman, Daniel I., Nyholt, Dale R., Palotie, Aarno, Agee, Michelle, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, and other, and
Abstract: Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10−06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = −0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10−08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15–1.25]/10 mmHg; P = 5.57 × 10−25) on migraine than SBP (1.05 [1.03–1.07]/10 mmHg; P = 2.60 × 10−07) and a corresponding opposite effect for PP (0.92 [0.88–0.95]/10 mmHg; P = 3.65 × 10−07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine.
Published: 2020

15. Cerebral small vessel disease genomics and its implications across the lifespan

Author: Sargurupremraj, Muralidharan, Suzuki, Hideaki, Jian, Xueqiu, Sarnowski, Chloé, Evans, Tavia E., Bis, Joshua C., Eiriksdottir, Gudny, Sakaue, Saori, Terzikhan, Natalie, Habes, Mohamad, Zhao, Wei, Armstrong, Nicola J., Hofer, Edith, Yanek, Lisa R., Hagenaars, Saskia P., Kumar, Rajan B., van den Akker, Erik B., McWhirter, Rebekah E., Trompet, Stella, Mishra, Aniket, Saba, Yasaman, Satizabal, Claudia L., Beaudet, Gregory, Petit, Laurent, Tsuchida, Ami, Zago, Laure, Schilling, Sabrina, Sigurdsson, Sigurdur, Gottesman, Rebecca F., Lewis, Cora E., Aggarwal, Neelum T., Lopez, Oscar L., Smith, Jennifer A., Valdés Hernández, Maria C., van der Grond, Jeroen, Wright, Margaret J., Knol, Maria J., Dörr, Marcus, Thomson, Russell J., Bordes, Constance, Le Grand, Quentin, Duperron, Marie Gabrielle, Smith, Albert V., Knopman, David S., Schreiner, Pamela J., Evans, Denis A., Rotter, Jerome I., Beiser, Alexa S., Maniega, Susana Muñoz, Beekman, Marian, Trollor, Julian, Stott, David J., Vernooij, Meike W., Wittfeld, Katharina, Niessen, Wiro J., Soumaré, Aicha, Boerwinkle, Eric, Sidney, Stephen, Turner, Stephen T., Davies, Gail, Thalamuthu, Anbupalam, Völker, Uwe, van Buchem, Mark A., Bryan, R. Nick, Dupuis, Josée, Bastin, Mark E., Ames, David, Teumer, Alexander, Amouyel, Philippe, Kwok, John B., Bülow, Robin, Deary, Ian J., Schofield, Peter R., Brodaty, Henry, Jiang, Jiyang, Tabara, Yasuharu, Setoh, Kazuya, Miyamoto, Susumu, Yoshida, Kazumichi, Nagata, Manabu, Kamatani, Yoichiro, Matsuda, Fumihiko, Psaty, Bruce M., Bennett, David A., De Jager, Philip L., Mosley, Thomas H., Sachdev, Perminder S., Schmidt, Reinhold, Warren, Helen R., Evangelou, Evangelos, Trégouët, David Alexandre, de Andrade, Mariza, Basu, Saonli, Berr, Claudine, Brody, Jennifer A., Chasman, Daniel I., Dartigues, Jean Francois, Folsom, Aaron R., Germain, Marine, de Haan, Hugoline, Heit, John, Houwing-Duitermaat, Jeanine, Kabrhel, Christopher, Kraft, Peter, Legal, Grégoire, Lindström, Sara, Monajemi, Ramin, Morange, Pierre Emmanuel, Reitsma, Pieter H., Ridker, Paul M., Rose, Lynda M., Rosendaal, Frits R., Saut, Noémie, Slagboom, Eline, Smadja, David, Smith, Nicholas L., Suchon, Pierre, Tang, Weihong, Taylor, Kent D., Tzourio, Christophe, de Visser, Marieke C.H., van Hylckama Vlieg, Astrid, Weng, Lu Chen, Wiggins, Kerri L., Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Gudlaug Hrafnsdottir, Maria, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, Van Duijn, Cornelia M., Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Francke Christensen, Anne, Folkmann Hansen, Thomas, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, Mohammad A., Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel D., Belin, Andrea C., Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M.J.M., Zwart, John Anker, Boomsma, Dorret I., Davey Smith, George, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Nyholt, Dale R., Palotie, Aarno, Wen, Wei, DeCarli, Charles, Srikanth, Velandai K., Jukema, J. Wouter, Slagboom, Eline P., Kardia, Sharon L.R., Okada, Yukinori, Mazoyer, Bernard, Wardlaw, Joanna M., Nyquist, Paul A., Mather, Karen A., Grabe, Hans J., Schmidt, Helena, Gudnason, Vilmundur, Longstreth, William T., other, and, Sargurupremraj, Muralidharan, Suzuki, Hideaki, Jian, Xueqiu, Sarnowski, Chloé, Evans, Tavia E., Bis, Joshua C., Eiriksdottir, Gudny, Sakaue, Saori, Terzikhan, Natalie, Habes, Mohamad, Zhao, Wei, Armstrong, Nicola J., Hofer, Edith, Yanek, Lisa R., Hagenaars, Saskia P., Kumar, Rajan B., van den Akker, Erik B., McWhirter, Rebekah E., Trompet, Stella, Mishra, Aniket, Saba, Yasaman, Satizabal, Claudia L., Beaudet, Gregory, Petit, Laurent, Tsuchida, Ami, Zago, Laure, Schilling, Sabrina, Sigurdsson, Sigurdur, Gottesman, Rebecca F., Lewis, Cora E., Aggarwal, Neelum T., Lopez, Oscar L., Smith, Jennifer A., Valdés Hernández, Maria C., van der Grond, Jeroen, Wright, Margaret J., Knol, Maria J., Dörr, Marcus, Thomson, Russell J., Bordes, Constance, Le Grand, Quentin, Duperron, Marie Gabrielle, Smith, Albert V., Knopman, David S., Schreiner, Pamela J., Evans, Denis A., Rotter, Jerome I., Beiser, Alexa S., Maniega, Susana Muñoz, Beekman, Marian, Trollor, Julian, Stott, David J., Vernooij, Meike W., Wittfeld, Katharina, Niessen, Wiro J., Soumaré, Aicha, Boerwinkle, Eric, Sidney, Stephen, Turner, Stephen T., Davies, Gail, Thalamuthu, Anbupalam, Völker, Uwe, van Buchem, Mark A., Bryan, R. Nick, Dupuis, Josée, Bastin, Mark E., Ames, David, Teumer, Alexander, Amouyel, Philippe, Kwok, John B., Bülow, Robin, Deary, Ian J., Schofield, Peter R., Brodaty, Henry, Jiang, Jiyang, Tabara, Yasuharu, Setoh, Kazuya, Miyamoto, Susumu, Yoshida, Kazumichi, Nagata, Manabu, Kamatani, Yoichiro, Matsuda, Fumihiko, Psaty, Bruce M., Bennett, David A., De Jager, Philip L., Mosley, Thomas H., Sachdev, Perminder S., Schmidt, Reinhold, Warren, Helen R., Evangelou, Evangelos, Trégouët, David Alexandre, de Andrade, Mariza, Basu, Saonli, Berr, Claudine, Brody, Jennifer A., Chasman, Daniel I., Dartigues, Jean Francois, Folsom, Aaron R., Germain, Marine, de Haan, Hugoline, Heit, John, Houwing-Duitermaat, Jeanine, Kabrhel, Christopher, Kraft, Peter, Legal, Grégoire, Lindström, Sara, Monajemi, Ramin, Morange, Pierre Emmanuel, Reitsma, Pieter H., Ridker, Paul M., Rose, Lynda M., Rosendaal, Frits R., Saut, Noémie, Slagboom, Eline, Smadja, David, Smith, Nicholas L., Suchon, Pierre, Tang, Weihong, Taylor, Kent D., Tzourio, Christophe, de Visser, Marieke C.H., van Hylckama Vlieg, Astrid, Weng, Lu Chen, Wiggins, Kerri L., Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Gudlaug Hrafnsdottir, Maria, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, Van Duijn, Cornelia M., Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Francke Christensen, Anne, Folkmann Hansen, Thomas, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, Mohammad A., Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel D., Belin, Andrea C., Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M.J.M., Zwart, John Anker, Boomsma, Dorret I., Davey Smith, George, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Nyholt, Dale R., Palotie, Aarno, Wen, Wei, DeCarli, Charles, Srikanth, Velandai K., Jukema, J. Wouter, Slagboom, Eline P., Kardia, Sharon L.R., Okada, Yukinori, Mazoyer, Bernard, Wardlaw, Joanna M., Nyquist, Paul A., Mather, Karen A., Grabe, Hans J., Schmidt, Helena, Gudnason, Vilmundur, Longstreth, William T., and other, and
Abstract: White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
Published: 2020

16. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions

Author: Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, Milani, Lili, Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, and Milani, Lili
Abstract: Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Published: 2019
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17. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author: Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, Milani, Lili, Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, and Milani, Lili
Abstract: Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
Published: 2019
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18. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions

Author: Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, Milani, Lili, Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, and Milani, Lili
Abstract: Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Published: 2019
Full Text: View/download PDF

19. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions

Author: Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, Milani, Lili, Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, and Milani, Lili
Abstract: Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Published: 2019
Full Text: View/download PDF

20. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author: Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, Milani, Lili, Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, and Milani, Lili
Abstract: Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
Published: 2019
Full Text: View/download PDF

21. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author: Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, Milani, Lili, Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, and Milani, Lili
Abstract: Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
Published: 2019
Full Text: View/download PDF

22. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions

Author: Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, Milani, Lili, Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, and Milani, Lili
Abstract: Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Published: 2019
Full Text: View/download PDF

23. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author: Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, Milani, Lili, Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, and Milani, Lili
Abstract: Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
Published: 2019
Full Text: View/download PDF

24. Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions

Author: Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, Milani, Lili, Reisberg, Sulev, Krebs, Kristi, Lepamets, Maarja, Kals, Mart, Magi, Reedik, Metsalu, Kristjan, Lauschke, Volker M., Vilo, Jaak, and Milani, Lili
Abstract: Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
Published: 2019
Full Text: View/download PDF

25. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author: Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, Milani, Lili, Tasa, Tonis, Krebs, Kristi, Kals, Mart, Mägi, Reedik, Lauschke, Volker M., Haller, Toomas, Puurand, Tarmo, Remm, Maido, Esko, Tonu, Metspalu, Andres, Vilo, Jaak, and Milani, Lili
Abstract: Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
Published: 2019
Full Text: View/download PDF

26. Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel

Author: Broad Institute of MIT and Harvard, Massachusetts Institute of Technology. Department of Biology, Gabriel, Stacey, Lander, Eric Steven, Palotie, Aarno, Mitt, Mario, Kals, Mart, Pärn, Kalle, Ripatti, Samuli, Morris, Andrew P, Metspalu, Andres, Esko, Tõnu, Mägi, Reedik, Palta, Priit, Broad Institute of MIT and Harvard, Massachusetts Institute of Technology. Department of Biology, Gabriel, Stacey, Lander, Eric Steven, Palotie, Aarno, Mitt, Mario, Kals, Mart, Pärn, Kalle, Ripatti, Samuli, Morris, Andrew P, Metspalu, Andres, Esko, Tõnu, Mägi, Reedik, and Palta, Priit
Abstract: Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies.
Published: 2018

27. Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms.

Author: Guo, Michael H, Guo, Michael H, Nandakumar, Satish K, Ulirsch, Jacob C, Zekavat, Seyedeh M, Buenrostro, Jason D, Natarajan, Pradeep, Salem, Rany M, Chiarle, Roberto, Mitt, Mario, Kals, Mart, Pärn, Kalle, Fischer, Krista, Milani, Lili, Mägi, Reedik, Palta, Priit, Gabriel, Stacey B, Metspalu, Andres, Lander, Eric S, Kathiresan, Sekar, Hirschhorn, Joel N, Esko, Tõnu, Sankaran, Vijay G, Guo, Michael H, Guo, Michael H, Nandakumar, Satish K, Ulirsch, Jacob C, Zekavat, Seyedeh M, Buenrostro, Jason D, Natarajan, Pradeep, Salem, Rany M, Chiarle, Roberto, Mitt, Mario, Kals, Mart, Pärn, Kalle, Fischer, Krista, Milani, Lili, Mägi, Reedik, Palta, Priit, Gabriel, Stacey B, Metspalu, Andres, Lander, Eric S, Kathiresan, Sekar, Hirschhorn, Joel N, Esko, Tõnu, and Sankaran, Vijay G
Abstract: Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.
Published: 2017

28. Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Author: Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Broad Institute of MIT and Harvard, Massachusetts Institute of Technology. Department of Biological Engineering, Massachusetts Institute of Technology. Department of Biology, Zekavat, Seyedeh M., Gabriel, Stacey, Lander, Eric Steven, Kathiresan, Sekar, Hirschhorn, Joel N, Sankaran, Vijay G., Guo, Michael H., Nandakumar, Satish K., Ulirsch, Jacob C., Buenrostro, Jason D., Natarajan, Pradeep, Salem, Rany M., Chiarle, Roberto, Mitt, Mario, Kals, Mart, Pärn, Kalle, Fischer, Krista, Milani, Lili, Mägi, Reedik, Palta, Priit, Metspalu, Andres, Esko, Tõnu, Hirschhorn, Joel N., Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Broad Institute of MIT and Harvard, Massachusetts Institute of Technology. Department of Biological Engineering, Massachusetts Institute of Technology. Department of Biology, Zekavat, Seyedeh M., Gabriel, Stacey, Lander, Eric Steven, Kathiresan, Sekar, Hirschhorn, Joel N, Sankaran, Vijay G., Guo, Michael H., Nandakumar, Satish K., Ulirsch, Jacob C., Buenrostro, Jason D., Natarajan, Pradeep, Salem, Rany M., Chiarle, Roberto, Mitt, Mario, Kals, Mart, Pärn, Kalle, Fischer, Krista, Milani, Lili, Mägi, Reedik, Palta, Priit, Metspalu, Andres, Esko, Tõnu, and Hirschhorn, Joel N.
Abstract: Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high-coverage whole-genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional 14,904 samples. Using up to 7,134 samples with available phenotype data, our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic datasets provided evidence for causal mechanisms at several loci, including at a previously undiscovered basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance., United States. National Institutes of Health (R01 DK103794), United States. National Institutes of Health (R33 HL120791), United States. National Institutes of Health (R01 DK075787)
Published: 2017

29. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
Full Text: View/download PDF

30. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications., QC 20161007
Published: 2016
Full Text: View/download PDF

31. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
Full Text: View/download PDF

32. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
Full Text: View/download PDF

33. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Käller, Max, Axelsson, Tomas, Lehtiö, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Käller, Max, Axelsson, Tomas, Lehtiö, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
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34. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Author: Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H.H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Ridker, Paul M., Hrafnsdottir, Maria Gudlaug, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hamalainen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, van Duijn, Cornelia, Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Christensen, Anne Francke, Hansen, Thomas Folkmann, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, M. Arfan, Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel, Belin, Andrea Carmine, Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M.J.M., Zwart, John Anker, Boomsma, Dorret I., Smith, George Davey, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Chasman, Daniel I., Nyholt, Dale R., Palotie, Aarno, Børte, Sigrid, Cormand, Bru, Eising, Else, Frants, Rune R., Griffiths, Lyn, Hiekkala, Marjo, Kajanne, Risto, Launer, Lenore, Lehtimaki, Terho, Lessel, Davor, Litterman, Nadia, Macaya, Alfons, Mangino, Massimo, Northover, Carrie, Pedersen, Nancy, Posthuma, Danielle, Pozo-Rosich, Patricia, Pressman, Alice, Sintas, Celia, Strachan, David, Vila-Pueyo, Marta, Wrenthal, William, Zhao, Huiying, other, and, Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., Kallela, Mikko, Freilinger, Tobias M., Ran, Caroline, Gordon, Scott G., Stam, Anine H., Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H.H., Lehtimäki, Terho, Sarin, Antti Pekka, Wedenoja, Juho, Hinds, David A., Buring, Julie E., Schürks, Markus, Ridker, Paul M., Hrafnsdottir, Maria Gudlaug, Stefansson, Hreinn, Ring, Susan M., Hottenga, Jouke Jan, Penninx, Brenda W.J.H., Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C., Madden, Pamela A.F., Martin, Nicholas G., Montgomery, Grant W., Kurki, Mitja, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hamalainen, Eija, Huang, Hailiang, Byrnes, Andrea E., Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H., Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G., Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G., Hofman, Albert, van Duijn, Cornelia, Cherkas, Lynn, Pedersen, Linda M., Stubhaug, Audun, Nielsen, Christopher S., Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann Louise, Christensen, Anne Francke, Hansen, Thomas Folkmann, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J., Raitakari, Olli, Ikram, M. Arfan, Spector, Tim, Järvelin, Marjo Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P., Ferrari, Michel, Belin, Andrea Carmine, Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M.J.M., Zwart, John Anker, Boomsma, Dorret I., Smith, George Davey, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J., Neale, Benjamin M., Olesen, Jes, Chasman, Daniel I., Nyholt, Dale R., Palotie, Aarno, Børte, Sigrid, Cormand, Bru, Eising, Else, Frants, Rune R., Griffiths, Lyn, Hiekkala, Marjo, Kajanne, Risto, Launer, Lenore, Lehtimaki, Terho, Lessel, Davor, Litterman, Nadia, Macaya, Alfons, Mangino, Massimo, Northover, Carrie, Pedersen, Nancy, Posthuma, Danielle, Pozo-Rosich, Patricia, Pressman, Alice, Sintas, Celia, Strachan, David, Vila-Pueyo, Marta, Wrenthal, William, Zhao, Huiying, and other, and
Abstract: Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10-8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.
Published: 2016

35. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
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36. Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes : implications for hepatic gene expression

Author: Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, Ingelman-Sundberg, Magnus, Ivanov, Maxim, Kals, Mart, Lauschke, Volker, Barragan, Isabel, Ewels, Philip, Kaller, Max, Axelsson, Tomas, Lehtio, Janne, Milani, Lili, and Ingelman-Sundberg, Magnus
Abstract: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene-and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
Published: 2016
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37. Adiposity as a cause of cardiovascular disease : a Mendelian randomization study

Author: Hägg, Sara, Fall, Tove, Ploner, Alexander, Maegi, Reedik, Fischer, Krista, Draisma, Harmen H. M., Kals, Mart, de Vries, Paul S., Dehghan, Abbas, Willems, Sara M., Sarin, Antti-Pekka, Kristiansson, Kati, Nuotio, Marja-Liisa, Havulinna, Aki S., de Bruijn, Renee F. A. G., Ikram, M. Arfan, Kuningas, Maris, Stricker, Bruno H., Franco, Oscar H., Benyamin, Beben, Gieger, Christian, Hall, Alistair S., Huikari, Ville, Jula, Antti, Jarvelin, Marjo-Riitta, Kaakinen, Marika, Kaprio, Jaakko, Kobl, Michael, Mangino, Massimo, Nelson, Christopher P., Palotie, Aarno, Samani, Nilesh J., Spector, Tim D., Strachan, David P., Tobin, Martin D., Whitfield, John B., Uitterlinden, Andre G., Salomaa, Veikko, Syvänen, Ann-Christine, Kuulasmaa, Kari, Magnusson, Patrik K., Esko, Tonu, Hofman, Albert, de Geus, Eco J. C., Lind, Lars, Giedraitis, Vilmantas, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Gianfagna, Francesco, Brambilla, Paolo, Ripatti, Samuli, van Duijn, Cornelia M., Metspalu, Andres, Prokopenko, Inga, McCarthy, Mark I., Pedersen, Nancy L., Ingelsson, Erik, Hägg, Sara, Fall, Tove, Ploner, Alexander, Maegi, Reedik, Fischer, Krista, Draisma, Harmen H. M., Kals, Mart, de Vries, Paul S., Dehghan, Abbas, Willems, Sara M., Sarin, Antti-Pekka, Kristiansson, Kati, Nuotio, Marja-Liisa, Havulinna, Aki S., de Bruijn, Renee F. A. G., Ikram, M. Arfan, Kuningas, Maris, Stricker, Bruno H., Franco, Oscar H., Benyamin, Beben, Gieger, Christian, Hall, Alistair S., Huikari, Ville, Jula, Antti, Jarvelin, Marjo-Riitta, Kaakinen, Marika, Kaprio, Jaakko, Kobl, Michael, Mangino, Massimo, Nelson, Christopher P., Palotie, Aarno, Samani, Nilesh J., Spector, Tim D., Strachan, David P., Tobin, Martin D., Whitfield, John B., Uitterlinden, Andre G., Salomaa, Veikko, Syvänen, Ann-Christine, Kuulasmaa, Kari, Magnusson, Patrik K., Esko, Tonu, Hofman, Albert, de Geus, Eco J. C., Lind, Lars, Giedraitis, Vilmantas, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Gianfagna, Francesco, Brambilla, Paolo, Ripatti, Samuli, van Duijn, Cornelia M., Metspalu, Andres, Prokopenko, Inga, McCarthy, Mark I., Pedersen, Nancy L., and Ingelsson, Erik
Abstract: Background: Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods. Methods: The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22 193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes. Results: There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9.10(-7)), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9.10(-19)) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (beta = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3.10(-107)). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD. Conclusions: Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke., De två första författarna delar förstaförfattarskapet.
Published: 2015
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38. Age- and sex-specific causal effects of adiposity on cardiovascular risk factors

Author: Fall, Tove, Hägg, Sara, Ploner, Alexander, Mägi, Reedik, Fischer, Krista, Draisma, Harmen H M, Sarin, Antti-Pekka, Benyamin, Beben, Ladenvall, Claes, Åkerlund, Mikael, Kals, Mart, Esko, Tõnu, Nelson, Christopher P, Kaakinen, Marika, Huikari, Ville, Mangino, Massimo, Meirhaeghe, Aline, Kristiansson, Kati, Nuotio, Marja-Liisa, Kobl, Michael, Grallert, Harald, Dehghan, Abbas, Kuningas, Maris, de Vries, Paul S, de Bruijn, Renée F A G, Willems, Sara M, Heikkilä, Kauko, Silventoinen, Karri, Pietiläinen, Kirsi H, Legry, Vanessa, Giedraitis, Vilmantas, Goumidi, Louisa, Syvänen, Ann-Christine, Strauch, Konstantin, Koenig, Wolfgang, Lichtner, Peter, Herder, Christian, Palotie, Aarno, Menni, Cristina, Uitterlinden, André G, Kuulasmaa, Kari, Havulinna, Aki S, Moreno, Luis A, Gonzalez-Gross, Marcela, Evans, Alun, Tregouet, David-Alexandre, Yarnell, John W G, Virtamo, Jarmo, Ferrières, Jean, Veronesi, Giovanni, Perola, Markus, Arveiler, Dominique, Brambilla, Paolo, Lind, Lars, Kaprio, Jaakko, Hofman, Albert, Stricker, Bruno H, van Duijn, Cornelia M, Ikram, M Arfan, Franco, Oscar H, Cottel, Dominique, Dallongeville, Jean, Hall, Alistair S, Jula, Antti, Tobin, Martin D, Penninx, Brenda W, Peters, Annette, Gieger, Christian, Samani, Nilesh J, Montgomery, Grant W, Whitfield, John B, Martin, Nicholas G, Groop, Leif, Spector, Tim D, Magnusson, Patrik K, Amouyel, Philippe, Boomsma, Dorret I, Nilsson, Peter M, Järvelin, Marjo-Riitta, Lyssenko, Valeriya, Metspalu, Andres, Strachan, David P, Salomaa, Veikko, Ripatti, Samuli, Pedersen, Nancy L, Prokopenko, Inga, McCarthy, Mark I, Ingelsson, Erik, Fall, Tove, Hägg, Sara, Ploner, Alexander, Mägi, Reedik, Fischer, Krista, Draisma, Harmen H M, Sarin, Antti-Pekka, Benyamin, Beben, Ladenvall, Claes, Åkerlund, Mikael, Kals, Mart, Esko, Tõnu, Nelson, Christopher P, Kaakinen, Marika, Huikari, Ville, Mangino, Massimo, Meirhaeghe, Aline, Kristiansson, Kati, Nuotio, Marja-Liisa, Kobl, Michael, Grallert, Harald, Dehghan, Abbas, Kuningas, Maris, de Vries, Paul S, de Bruijn, Renée F A G, Willems, Sara M, Heikkilä, Kauko, Silventoinen, Karri, Pietiläinen, Kirsi H, Legry, Vanessa, Giedraitis, Vilmantas, Goumidi, Louisa, Syvänen, Ann-Christine, Strauch, Konstantin, Koenig, Wolfgang, Lichtner, Peter, Herder, Christian, Palotie, Aarno, Menni, Cristina, Uitterlinden, André G, Kuulasmaa, Kari, Havulinna, Aki S, Moreno, Luis A, Gonzalez-Gross, Marcela, Evans, Alun, Tregouet, David-Alexandre, Yarnell, John W G, Virtamo, Jarmo, Ferrières, Jean, Veronesi, Giovanni, Perola, Markus, Arveiler, Dominique, Brambilla, Paolo, Lind, Lars, Kaprio, Jaakko, Hofman, Albert, Stricker, Bruno H, van Duijn, Cornelia M, Ikram, M Arfan, Franco, Oscar H, Cottel, Dominique, Dallongeville, Jean, Hall, Alistair S, Jula, Antti, Tobin, Martin D, Penninx, Brenda W, Peters, Annette, Gieger, Christian, Samani, Nilesh J, Montgomery, Grant W, Whitfield, John B, Martin, Nicholas G, Groop, Leif, Spector, Tim D, Magnusson, Patrik K, Amouyel, Philippe, Boomsma, Dorret I, Nilsson, Peter M, Järvelin, Marjo-Riitta, Lyssenko, Valeriya, Metspalu, Andres, Strachan, David P, Salomaa, Veikko, Ripatti, Samuli, Pedersen, Nancy L, Prokopenko, Inga, McCarthy, Mark I, and Ingelsson, Erik
Abstract: Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors., T.V. and S.H. contributed equally to this work.
Published: 2015
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39. The Role of Adiposity in Cardiometabolic Traits : A Mendelian Randomization Analysis

Author: Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimat, De fyra sista författarna delar sistaförfattarskapet.
Published: 2013
Full Text: View/download PDF

40. The Role of Adiposity in Cardiometabolic Traits : A Mendelian Randomization Analysis

Author: Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimat, De fyra sista författarna delar sistaförfattarskapet.
Published: 2013
Full Text: View/download PDF

41. The Role of Adiposity in Cardiometabolic Traits : A Mendelian Randomization Analysis

Author: Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimat, De fyra sista författarna delar sistaförfattarskapet.
Published: 2013
Full Text: View/download PDF

42. The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis

Author: University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Hjelt Institute, University of Helsinki, Department of Medicine, Fall, Tove, Hagg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkilä, Kauko Veli, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvanen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, Tiinamaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, ENGAGE Consortium, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Hjelt Institute, University of Helsinki, Department of Medicine, Fall, Tove, Hagg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkilä, Kauko Veli, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvanen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, Tiinamaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, and ENGAGE Consortium
Published: 2013

43. The Role of Adiposity in Cardiometabolic Traits : A Mendelian Randomization Analysis

Author: Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimat, De fyra sista författarna delar sistaförfattarskapet.
Published: 2013
Full Text: View/download PDF

44. The Role of Adiposity in Cardiometabolic Traits : A Mendelian Randomization Analysis

Author: Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hägg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvänen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimat, De fyra sista författarna delar sistaförfattarskapet.
Published: 2013
Full Text: View/download PDF

45. The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis

Author: Fall, Tove, Hagg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvanen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, Prokopenko, Inga, Fall, Tove, Hagg, Sara, Maegi, Reedik, Ploner, Alexander, Fischer, Krista, Horikoshi, Momoko, Sarin, Antti-Pekka, Thorleifsson, Gudmar, Ladenvall, Claes, Kals, Mart, Kuningas, Maris, Draisma, Harmen H. M., Ried, Janina S., van Zuydam, Natalie R., Huikari, Ville, Mangino, Massimo, Sonestedt, Emily, Benyamin, Beben, Nelson, Christopher P., Rivera, Natalia V., Kristiansson, Kati, Shen, Huei-yi, Havulinna, Aki S., Dehghan, Abbas, Donnelly, Louise A., Kaakinen, Marika, Nuotio, Marja-Liisa, Robertson, Neil, de Bruijn, Renee F. A. G., Ikram, M. Arfan, Amin, Najaf, Balmforth, Anthony J., Braund, Peter S., Doney, Alexander S. F., Doering, Angela, Elliott, Paul, Esko, Tonu, Franco, Oscar H., Gretarsdottir, Solveig, Hartikainen, Anna-Liisa, Heikkila, Kauko, Herzig, Karl-Heinz, Holm, Hilma, Hottenga, Jouke Jan, Hypponen, Elina, Illig, Thomas, Isaacs, Aaron, Isomaa, Bo, Karssen, Lennart C., Kettunen, Johannes, Koenig, Wolfgang, Kuulasmaa, Kari, Laatikainen, Tiina, Laitinen, Jaana, Lindgren, Cecilia, Lyssenko, Valeriya, Laara, Esa, Rayner, Nigel W., Mannisto, Satu, Pouta, Anneli, Rathmann, Wolfgang, Rivadeneira, Fernando, Ruokonen, Aimo, Savolainen, Markku J., Sijbrands, Eric J. G., Small, Kerrin S., Smit, Jan H., Steinthorsdottir, Valgerdur, Syvanen, Ann-Christine, Taanila, Anja, Tobin, Martin D., Uitterlinden, Andre G., Willems, Sara M., Willemsen, Gonneke, Witteman, Jacqueline, Perola, Markus, Evans, Alun, Ferrieres, Jean, Virtamo, Jarmo, Kee, Frank, Tregouet, David-Alexandre, Arveiler, Dominique, Amouyel, Philippe, Ferrario, Marco M., Brambilla, Paolo, Hall, Alistair S., Heath, AndrewC., Madden, Pamela A. F., Martin, Nicholas G., Montgomery, Grant W., Whitfield, John B., Jula, Antti, Knekt, Paul, Oostra, Ben, van Duijn, Cornelia M., Penninx, Brenda W. J. H., Smith, George Davey, Kaprio, Jaakko, Samani, Nilesh J., Gieger, Christian, Peters, Annette, Wichmann, H. -Erich, Boomsma, Dorret I., de Geus, Eco J. C., Tuomi, TiinaMaija, Power, Chris, Hammond, Christopher J., Spector, Tim D., Lind, Lars, Orho-Melander, Marju, Palmer, Colin Neil Alexander, Morris, Andrew D., Groop, Leif, Jarvelin, Marjo-Riitta, Salomaa, Veikko, Vartiainen, Erkki, Hofman, Albert, Ripatti, Samuli, Metspalu, Andres, Thorsteinsdottir, Unnur, Stefansson, Kari, Pedersen, Nancy L., McCarthy, Mark I., Ingelsson, Erik, and Prokopenko, Inga
Abstract: Background: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age-and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p =
Published: 2013

46. Evidence of Inbreeding Depression on Human Height

Author: McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, Wilson, James F, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, and Wilson, James F
Published: 2012
Full Text: View/download PDF

47. Evidence of Inbreeding Depression on Human Height

Author: McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, Wilson, James F, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, and Wilson, James F
Abstract: Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Published: 2012
Full Text: View/download PDF

48. Evidence of Inbreeding Depression on Human Height

Author: McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, Wilson, James F, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, and Wilson, James F
Abstract: Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Published: 2012
Full Text: View/download PDF

49. Evidence of Inbreeding Depression on Human Height

Author: McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, Wilson, James F, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P, Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S, Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H, Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M, Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G, Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M, Hicks, Andrew A, Esposito, Laura, Kolčić, Ivana, Farrington, Susan M, Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I, Rivadeneira, Fernando, Montgomery, Grant W, Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A F, d'Adamo, Pio, Hastie, Nicholas D, Gyllensten, Ulf, Wright, Alan F, van Duijn, Cornelia M, Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P, Deary, Ian J, Toniolo, Daniela, Eriksson, Johan G, Jula, Antti, Raitakari, Olli T, Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M, and Wilson, James F
Abstract: Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Published: 2012
Full Text: View/download PDF

50. Evidence of Inbreeding Depression on Human Height

Author: Gibson, Greg, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P., Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S., Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H., Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M., Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G., Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M., Hicks, Andrew A., Esposito, Laura, Kolčić, Ivana, Farrington, Susan M., Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I., Rivadeneira, Fernando, Montgomery, Grant W., Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A. F., d'Adamo, Pio, Hastie, Nicholas D., Gyllensten, Ulf, Wright, Alan F., van Duijn, Cornelia M., Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P., Deary, Ian J., Toniolo, Daniela, Eriksson, Johan G., Jula, Antti, Raitakari, Olli T., Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M., Wilson, James F., Gibson, Greg, McQuillan, Ruth, Eklund, Niina, Pirastu, Nicola, Kuningas, Maris, McEvoy, Brian P., Esko, Tõnu, Corre, Tanguy, Davies, Gail, Kaakinen, Marika, Lyytikäinen, Leo-Pekka, Kristiansson, Kati, Havulinna, Aki S., Gögele, Martin, Vitart, Veronique, Tenesa, Albert, Aulchenko, Yurii, Hayward, Caroline, Johansson, Åsa, Boban, Mladen, Ulivi, Sheila, Robino, Antonietta, Boraska, Vesna, Igl, Wilmar, Wild, Sarah H., Zgaga, Lina, Amin, Najaf, Theodoratou, Evropi, Polašek, Ozren, Girotto, Giorgia, Lopez, Lorna M., Sala, Cinzia, Lahti, Jari, Laatikainen, Tiina, Prokopenko, Inga, Kals, Mart, Viikari, Jorma, Yang, Jian, Pouta, Anneli, Estrada, Karol, Hofman, Albert, Freimer, Nelson, Martin, Nicholas G., Kähönen, Mika, Milani, Lili, Heliövaara, Markku, Vartiainen, Erkki, Räikkönen, Katri, Masciullo, Corrado, Starr, John M., Hicks, Andrew A., Esposito, Laura, Kolčić, Ivana, Farrington, Susan M., Oostra, Ben, Zemunik, Tatijana, Campbell, Harry, Kirin, Mirna, Pehlic, Marina, Faletra, Flavio, Porteous, David, Pistis, Giorgio, Widén, Elisabeth, Salomaa, Veikko, Koskinen, Seppo, Fischer, Krista, Lehtimäki, Terho, Heath, Andrew, McCarthy, Mark I., Rivadeneira, Fernando, Montgomery, Grant W., Tiemeier, Henning, Hartikainen, Anna-Liisa, Madden, Pamela A. F., d'Adamo, Pio, Hastie, Nicholas D., Gyllensten, Ulf, Wright, Alan F., van Duijn, Cornelia M., Dunlop, Malcolm, Rudan, Igor, Gasparini, Paolo, Pramstaller, Peter P., Deary, Ian J., Toniolo, Daniela, Eriksson, Johan G., Jula, Antti, Raitakari, Olli T., Metspalu, Andres, Perola, Markus, Järvelin, Marjo-Riitta, Uitterlinden, André, Visscher, Peter M., and Wilson, James F.
Abstract: Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (x2 = 83.89, df = 1; p = 5.2610220). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Published: 2012

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