Author: "Kals, Mart" / Publisher: uppsala universitet, science for life laboratory, scilifelab - Searchworks@Jio Institute Digital Library Search Results

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Start Over Author "Kals, Mart" Publisher uppsala universitet, science for life laboratory, scilifelab

26 results on '"Kals, Mart"'

1. 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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2. 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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3. 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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4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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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17. 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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18. 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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19. 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
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20. 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
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21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

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1. Phylogenetic history of patrilineages rare in northern and eastern Europe from large-scale re-sequencing of human Y-chromosomes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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18. Age- and sex-specific causal effects of adiposity on cardiovascular risk factors

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

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

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

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

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

24. Evidence of Inbreeding Depression on Human Height

25. Evidence of Inbreeding Depression on Human Height

26. Evidence of Inbreeding Depression on Human Height

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