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1. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis

Author: Udler, Miriam S., Kim, Jaegil, von Grotthuss, Marcin, Bonàs-Guarch, Sílvia, Cole, Joanne B., Chiou, Joshua, Boehnke, Michael, Laakso, Markku, Atzmon, Gil, Glaser, Benjamin, Mercader, Josep M., Gaulton, Kyle, Flannick, Jason, Getz, Gad, and Florez, Jose C.
Subjects: Type 2 diabetes -- Care and treatment -- Genetic aspects -- Development and progression, Patient care -- Management, Treatment outcome -- Analysis, Biological markers -- Usage, Diabetics -- Care and treatment, Company business management, Biological sciences
Abstract: Background Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D. Methods and findings In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), 'lipodystrophy-like' fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry. Conclusion Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management., Author(s): Miriam S. Udler 1,2,3,4, Jaegil Kim 3, Marcin von Grotthuss 3, Sílvia Bonàs-Guarch 5, Joanne B. Cole 2,3, Joshua Chiou 6, Christopher D. Anderson on behalf of METASTROKE and [...]
Published: 2018
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2. Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

Author: Wheeler, Eleanor, Leong, Aaron, Liu, Ching-Ti, Hivert, Marie-France, Strawbridge, Rona J., Podmore, Clara, Li, Man, Yao, Jie, Sim, Xueling, Hong, Jaeyoung, Chu, Audrey Y., Zhang, Weihua, Wang, Xu, Chen, Peng, Maruthur, Nisa M., Porneala, Bianca C., Sharp, Stephen J., Jia, Yucheng, Kabagambe, Edmond K., Chang, Li-Ching, Chen, Wei-Min, Elks, Cathy E., Evans, Daniel S., Fan, Qiao, Giulianini, Franco, Go, Min Jin, Hottenga, Jouke-Jan, Hu, Yao, Jackson, Anne U., Kanoni, Stavroula, Kim, Young Jin, Kleber, Marcus E., Ladenvall, Claes, Lecoeur, Cecile, Lim, Sing-Hui, Lu, Yingchang, Mahajan, Anubha, Marzi, Carola, Nalls, Mike A., Navarro, Pau, Nolte, Ilja M., Rose, Lynda M., Rybin, Denis V., Sanna, Serena, Shi, Yuan, Stram, Daniel O., Takeuchi, Fumihiko, Tan, Shu Pei, van der Most, Peter J., Van Vliet-Ostaptchouk, Jana V., Wong, Andrew, Yengo, Loic, Zhao, Wanting, Goel, Anuj, Martinez Larrad, Maria Teresa, Radke, Dörte, Salo, Perttu, Tanaka, Toshiko, van Iperen, Erik P. A., Abecasis, Goncalo, Afaq, Saima, Alizadeh, Behrooz Z., Bertoni, Alain G., Bonnefond, Amelie, Böttcher, Yvonne, Bottinger, Erwin P., Campbell, Harry, Carlson, Olga D., Chen, Chien-Hsiun, Cho, Yoon Shin, Garvey, W. Timothy, Gieger, Christian, Goodarzi, Mark O., Grallert, Harald, Hamsten, Anders, Hartman, Catharina A., Herder, Christian, Hsiung, Chao Agnes, Huang, Jie, Igase, Michiya, Isono, Masato, Katsuya, Tomohiro, Khor, Chiea-Chuen, Kiess, Wieland, Kohara, Katsuhiko, Kovacs, Peter, Lee, Juyoung, Lee, Wen-Jane, Lehne, Benjamin, Li, Huaixing, Liu, Jianjun, Lobbens, Stephane, Luan, Jian'an, Lyssenko, Valeriya, Meitinger, Thomas, Miki, Tetsuro, Miljkovic, Iva, Moon, Sanghoon, Mulas, Antonella, Müller, Gabriele, Müller-Nurasyid, Martina, Nagaraja, Ramaiah, Nauck, Matthias, Pankow, James S., Polasek, Ozren, Prokopenko, Inga, Ramos, Paula S., Rasmussen-Torvik, Laura, Rathmann, Wolfgang, Rich, Stephen S., Robertson, Neil R., Roden, Michael, Roussel, Ronan, Rudan, Igor, Scott, Robert A., Scott, William R., Sennblad, Bengt, Siscovick, David S., Strauch, Konstantin, Sun, Liang, Swertz, Morris, Tajuddin, Salman M., Taylor, Kent D., Teo, Yik-Ying, Tham, Yih Chung, Tönjes, Anke, Wareham, Nicholas J., Willemsen, Gonneke, Wilsgaard, Tom, Hingorani, Aroon D., Egan, Josephine, Ferrucci, Luigi, Hovingh, G. Kees, Jula, Antti, Kivimaki, Mika, Kumari, Meena, Njølstad, Inger, Palmer, Colin N. A., Serrano Ríos, Manuel, Stumvoll, Michael, Watkins, Hugh, Aung, Tin, Blüher, Matthias, Boehnke, Michael, Boomsma, Dorret I., Bornstein, Stefan R., Chambers, John C., Chasman, Daniel I., Chen, Yii-Der Ida, Chen, Yduan-Tsong, Cheng, Ching-Yu, Cucca, Francesco, de Geus, Eco J. C., Deloukas, Panos, Evans, Michele K., Fornage, Myriam, Friedlander, Yechiel, Froguel, Philippe, Groop, Leif, Gross, Myron D., Harris, Tamara B., Hayward, Caroline, Heng, Chew-Kiat, Ingelsson, Erik, Kato, Norihiro, Kim, Bong-Jo, Koh, Woon-Puay, Kooner, Jaspal S., Körner, Antje, Kuh, Diana, Kuusisto, Johanna, Laakso, Markku, Lin, Xu, Liu, Yongmei, Loos, Ruth J. F., Magnusson, Patrik K. E., März, Winfried, McCarthy, Mark I., Oldehinkel, Albertine J., Ong, Ken K., Pedersen, Nancy L., Pereira, Mark A., Peters, Annette, Ridker, Paul M., Sabanayagam, Charumathi, Sale, Michele, Saleheen, Danish, Saltevo, Juha, Schwarz, Peter EH., Sheu, Wayne H. H., Snieder, Harold, Spector, Timothy D., Tabara, Yasuharu, Tuomilehto, Jaakko, van Dam, Rob M., Wilson, James G., Wilson, James F., Wolffenbuttel, Bruce H. R., Wong, Tien Yin, Wu, Jer-Yuarn, Yuan, Jian-Min, Zonderman, Alan B., Soranzo, Nicole, Guo, Xiuqing, Roberts, David J., Florez, Jose C., Sladek, Robert, Dupuis, Josée, Morris, Andrew P., Tai, E-Shyong, Selvin, Elizabeth, Rotter, Jerome I., Langenberg, Claudia, Barroso, Inês, and Meigs, James B.
Subjects: Genotypes -- Research, African Americans -- Analysis -- Health aspects, Type 2 diabetes -- Risk factors -- Diagnosis, Biological sciences
Abstract: Background Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes. Methods & findings Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 x 10.sup.-29 ); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants. Conclusions As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses., Author(s): Eleanor Wheeler 1, Aaron Leong 2,3, Ching-Ti Liu 4, Marie-France Hivert 5,6, Rona J. Strawbridge 7,8, Clara Podmore 9,10, Man Li 11,12,13, Jie Yao 14, Xueling Sim 15, Jaeyoung [...]
Published: 2017
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3. Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis.

Author: Quick, Corbin, Wen, Xiaoquan, Abecasis, Gonçalo, Boehnke, Michael, and Kang, Hyun Min
Subjects: REGULATOR genes, GENETIC regulation, MINERAL aggregate testing, ANNOTATIONS, NEURAL codes, TEST methods
Abstract: Gene-based association tests aggregate genotypes across multiple variants for each gene, providing an interpretable gene-level analysis framework for genome-wide association studies (GWAS). Early gene-based test applications often focused on rare coding variants; a more recent wave of gene-based methods, e.g. TWAS, use eQTLs to interrogate regulatory associations. Regulatory variants are expected to be particularly valuable for gene-based analysis, since most GWAS associations to date are non-coding. However, identifying causal genes from regulatory associations remains challenging and contentious. Here, we present a statistical framework and computational tool to integrate heterogeneous annotations with GWAS summary statistics for gene-based analysis, applied with comprehensive coding and tissue-specific regulatory annotations. We compare power and accuracy identifying causal genes across single-annotation, omnibus, and annotation-agnostic gene-based tests in simulation studies and an analysis of 128 traits from the UK Biobank, and find that incorporating heterogeneous annotations in gene-based association analysis increases power and performance identifying causal genes. Author summary: Gene-based association tests are statistical methods used in genome-wide association studies (GWAS) to identify genes that affect heritable traits. Gene-based tests are formed by aggregating genotypes across multiple genetic variants for each gene, often including only variants that are likely to affect gene function or regulation. In this work, we present a unified framework to integrate heterogeneous classes of functional variants in gene-based association analysis. This approach enables us to simultaneously assess multiple distinct biological mechanisms underlying GWAS association signals, and to construct powerful omnibus tests by aggregating across functional classes for each gene. We evaluated the performance of gene-based association test methods and strategies to identify causal genes by conducting extensive simulation studies, and by analyzing 128 human traits from the UK Biobank and comparing our results against lists of high-confidence putative causal genes. Our analysis suggests that incorporating heterogeneous functional variants in gene-based association tests increases power to detect gene-based association and helps identify causal genes. [ABSTRACT FROM AUTHOR]
Published: 2020
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4. Genomic correlates of glatiramer acetate adverse cardiovascular effects lead to a novel locus mediating coronary risk

Author: Brænne, I, Zeng, L, Willenborg, C, Tragante, V, Kessler, T, Willer, C, Laakso, M, Wallentin, L, Franks, P, Salomaa, V, Dehghan, A, Meitinger, T, Samani, N, Asselbergs, F, Erdmann, J, Schunkert, H, Deloukas, P, Kanoni, S, Farrall, M, Assimes, T, Thompson, J, Ingelsson, E, Saleheen, D, Goldstein, B, Absher, D, König, I, Cazier, J, Johansson, Å, Hall, A, Lee, J, Chambers, J, Esko, T, Folkersen, L, Goel, A, Grundberg, E, Havulinna, A, Ho, W, Hopewell, J, Eriksson, N, Kleber, M, Kristiansson, K, Lundmark, P, Lyytikäinen, L, Rafelt, S, Shun, D, Strawbridge, R, Thorleifsson, G, Tikkanen, E, Van Zuydam, N, Voight, B, Waite, L, Zhang, W, Zieg, A, Altshuler, D, Balmforth, A, Barroso, I, Braund, P, Burgdorf, C, Claudi-Boehm, S, Cox, D, Dimitriou, M, Do, R, Doney, A, El Mokhtari, N, Eriksson, P, Fischer, K, Fontanillas, P, Franco-Cereceda, A, Gigante, B, Groop, L, Gustafsson, S, Hager, J, Hallmans, G, Han, B, Ehunt, S, Kang, H, Illig, T, Knowles, J, Kolovou, G, Kuusisto, J, Langenberg, C, Langford, C, Leander, K, Lokki, M, Lundmark, A, Mccarthy, M, Meisinger, C, Melander, O, Mihailov, E, Maouche, S, Morris, A, Müller-Nurasyid, M, Nikus, K, Peden, J, Rayner, N, Rasheed, A, Rosinger, S, Rubin, D, Rumpf, M, Schäfer, A, Sivananthan, M, Song, C, Stewart, A, Tan, S, Thorgeirsson, G, Van Der Schoot, C, Wagner, P, Wells, G, Wild, P, Yang, T, Amouyel, P, Arveiler, D, Basart, H, Boehnke, M, Boerwinkle, E, Brambilla, P, Cambien, F, Cupples, A, De Faire, U, Diemert, P, Epstein, S, Evans, A, Ferrario, M, Ferrières, J, Gauguier, D, Go, A, Goodall, A, Gudnason, V, Hazen, S, Holm, H, Iribarren, C, Jang, Y, Kähönen, M, Kee, F, Kim, H, Klopp, N, Koenig, W, Kratzer, W, Kuulasmaa, K, Laaksonen, R, Lind, L, Ouwehand, W, Parish, S, Park, J, Pedersen, N, Peters, A, Quertermous, T, Rader, D, Schadt, E, Shah, S, Sinisalo, J, Stark, K, Stefansson, K, Trégouët, D, Virtamo, J, Wareham, N, Zimmermann, M, Nieminen, M, Hengsten, C, Sandhu, M, Pastinen, T, Syvänen, A, Hovingh, G, Dedoussis, G, Lehtimäki, T, Metspalu, A, Zalloua, P, Siegbahn, A, Schreiber, S, Ripatti, S, Blankenberg, S, Perola, M, Clarke, R, Oboehm, B, O’Donnell, C, Reilly, M, März, W, Collins, R, Kathiresan, S, Hamsten, A, Kooner, J, Thorsteinsdottir, U, Danesh, J, Palmer, C, Roberts, R, Watkins, H, Hengstenberg, C, Mcpherson, R, Ziegler, A, Brænne, Ingrid, Zeng, Lingyao, Willenborg, Christina, Tragante, Vinicius, Kessler, Thorsten, Willer, Cristen J., Laakso, Markku, Wallentin, Lars, Franks, Paul W., Salomaa, Veikko, Dehghan, Abbas, Meitinger, Thomas, Samani, Nilesh J., Asselbergs, Folkert W., Erdmann, Jeanette, Schunkert, Heribert, Deloukas, Panos, Kanoni, Stavroula, Farrall, Martin, Assimes, Themistocles L., Thompson, John R., Ingelsson, Erik, Saleheen, Danish, Goldstein, Benjamin A., Absher, Devin, König, Inke R., Cazier, Jean-Baptiste, Johansson, Åsa, Hall, Alistair S., Lee, Jong-Young, Chambers, John C., Esko, Tõnu, Folkersen, Lasse, Goel, Anuj, Grundberg, Elin, Havulinna, Aki S., Ho, Weang K., Hopewell, Jemma C., Eriksson, Niclas, Kleber, Marcus E., Kristiansson, Kati, Lundmark, Per, Lyytikäinen, Leo-Pekka, Rafelt, Suzanne, Shun, Dmitry, Strawbridge, Rona J., Thorleifsson, Gudmar, Tikkanen, Emmi, Van Zuydam, Natalie, Voight, Benjamin F., Waite, Lindsay L., Zhang, Weihua, Zieg, Andreas, Altshuler, David, Balmforth, Anthony J., Barroso, Inês, Braund, Peter S., Burgdorf, Christof, Claudi-Boehm, Simone, Cox, David, Dimitriou, Maria, Do, Ron, Doney, Alex S. F., El Mokhtari, Nour Eddine, Eriksson, Per, Fischer, Krista, Fontanillas, Pierre, Franco-Cereceda, Anders, Gigante, Bruna, Groop, Leif, Gustafsson, Stefan, Hager, Jörg, Hallmans, Göran, Han, Bok-Ghee, Ehunt, Sarah, Kang, Hyun M., Illig, Thomas, Knowles, Joshua W., Kolovou, Genovefa, Kuusisto, Johanna, Langenberg, Claudia, Langford, Cordelia, Leander, Karin, Lokki, Marja-Liisa, Lundmark, Anders, McCarthy, Mark I., Meisinger, Christa, Melander, Olle, Mihailov, Evelin, Maouche, Seraya, Morris, Andrew D., Müller-Nurasyid, Martina, Nikus, Kjell, Peden, John F., Rayner, N. William, Rasheed, Asif, Rosinger, Silke, Rubin, Diana, Rumpf, Moritz P., Schäfer, Arne, Sivananthan, Mohan, Song, Ci, Stewart, Alexandre F. R., Tan, Sian-Tsung, Thorgeirsson, Gudmundur, Van Der Schoot, C. Ellen, Wagner, Peter J., Wells, George A., Wild, Philipp S., Yang, Tsun-Po, Amouyel, Philippe, Arveiler, Dominique, Basart, Hanneke, Boehnke, Michael, Boerwinkle, Eric, Brambilla, Paolo, Cambien, Francois, Cupples, Adrienne L., De Faire, Ulf, Diemert, Patrick, Epstein, Stephen E., Evans, Alun, Ferrario, Marco M., Ferrières, Jean, Gauguier, Dominique, Go, Alan S., Goodall, Alison H., Gudnason, Villi, Hazen, Stanley L., Holm, Hilma, Iribarren, Carlos, Jang, Yangsoo, Kähönen, Mika, Kee, Frank, Kim, Hyo-Soo, Klopp, Norman, Koenig, Wolfgang, Kratzer, Wolfgang, Kuulasmaa, Kari, Laaksonen, Reijo, Lee, Ji-Young, Lind, Lars, Ouwehand, Willem H., Parish, Sarah, Park, Jeong E., Pedersen, Nancy L., Peters, Annette, Quertermous, Thomas, Rader, Daniel J., Schadt, Eric, Shah, Svati H., Sinisalo, Juha, Stark, Klaus, Stefansson, Kari, Trégouët, David-Alexandre, Virtamo, Jarmo, Wareham, Nicholas, Zimmermann, Martina E., Nieminen, Markku S., Hengsten, Christian, Sandhu, Manjinder S., Pastinen, Tomi, Syvänen, Ann-Christine, Hovingh, G. Kees, Dedoussis, George, Lehtimäki, Terho, Metspalu, Andres, Zalloua, Pierre A., Siegbahn, Agneta, Schreiber, Stefan, Ripatti, Samuli, Blankenberg, Stefan S., Perola, Markus, Clarke, Robert, Oboehm, Bernhard, O’Donnell, Christopher, Reilly, Muredach P., März, Winfried, Collins, Rory, Kathiresan, Sekar, Hamsten, Anders, Kooner, Jaspal S., Thorsteinsdottir, Unnur, Danesh, John, Palmer, Colin N. A., Roberts, Robert, Watkins, Hugh, Hall, Alistair, Hengstenberg, Christian, McPherson, Ruth, Ziegler, Andreas, Brænne, I, Zeng, L, Willenborg, C, Tragante, V, Kessler, T, Willer, C, Laakso, M, Wallentin, L, Franks, P, Salomaa, V, Dehghan, A, Meitinger, T, Samani, N, Asselbergs, F, Erdmann, J, Schunkert, H, Deloukas, P, Kanoni, S, Farrall, M, Assimes, T, Thompson, J, Ingelsson, E, Saleheen, D, Goldstein, B, Absher, D, König, I, Cazier, J, Johansson, Å, Hall, A, Lee, J, Chambers, J, Esko, T, Folkersen, L, Goel, A, Grundberg, E, Havulinna, A, Ho, W, Hopewell, J, Eriksson, N, Kleber, M, Kristiansson, K, Lundmark, P, Lyytikäinen, L, Rafelt, S, Shun, D, Strawbridge, R, Thorleifsson, G, Tikkanen, E, Van Zuydam, N, Voight, B, Waite, L, Zhang, W, Zieg, A, Altshuler, D, Balmforth, A, Barroso, I, Braund, P, Burgdorf, C, Claudi-Boehm, S, Cox, D, Dimitriou, M, Do, R, Doney, A, El Mokhtari, N, Eriksson, P, Fischer, K, Fontanillas, P, Franco-Cereceda, A, Gigante, B, Groop, L, Gustafsson, S, Hager, J, Hallmans, G, Han, B, Ehunt, S, Kang, H, Illig, T, Knowles, J, Kolovou, G, Kuusisto, J, Langenberg, C, Langford, C, Leander, K, Lokki, M, Lundmark, A, Mccarthy, M, Meisinger, C, Melander, O, Mihailov, E, Maouche, S, Morris, A, Müller-Nurasyid, M, Nikus, K, Peden, J, Rayner, N, Rasheed, A, Rosinger, S, Rubin, D, Rumpf, M, Schäfer, A, Sivananthan, M, Song, C, Stewart, A, Tan, S, Thorgeirsson, G, Van Der Schoot, C, Wagner, P, Wells, G, Wild, P, Yang, T, Amouyel, P, Arveiler, D, Basart, H, Boehnke, M, Boerwinkle, E, Brambilla, P, Cambien, F, Cupples, A, De Faire, U, Diemert, P, Epstein, S, Evans, A, Ferrario, M, Ferrières, J, Gauguier, D, Go, A, Goodall, A, Gudnason, V, Hazen, S, Holm, H, Iribarren, C, Jang, Y, Kähönen, M, Kee, F, Kim, H, Klopp, N, Koenig, W, Kratzer, W, Kuulasmaa, K, Laaksonen, R, Lind, L, Ouwehand, W, Parish, S, Park, J, Pedersen, N, Peters, A, Quertermous, T, Rader, D, Schadt, E, Shah, S, Sinisalo, J, Stark, K, Stefansson, K, Trégouët, D, Virtamo, J, Wareham, N, Zimmermann, M, Nieminen, M, Hengsten, C, Sandhu, M, Pastinen, T, Syvänen, A, Hovingh, G, Dedoussis, G, Lehtimäki, T, Metspalu, A, Zalloua, P, Siegbahn, A, Schreiber, S, Ripatti, S, Blankenberg, S, Perola, M, Clarke, R, Oboehm, B, O’Donnell, C, Reilly, M, März, W, Collins, R, Kathiresan, S, Hamsten, A, Kooner, J, Thorsteinsdottir, U, Danesh, J, Palmer, C, Roberts, R, Watkins, H, Hengstenberg, C, Mcpherson, R, Ziegler, A, Brænne, Ingrid, Zeng, Lingyao, Willenborg, Christina, Tragante, Vinicius, Kessler, Thorsten, Willer, Cristen J., Laakso, Markku, Wallentin, Lars, Franks, Paul W., Salomaa, Veikko, Dehghan, Abbas, Meitinger, Thomas, Samani, Nilesh J., Asselbergs, Folkert W., Erdmann, Jeanette, Schunkert, Heribert, Deloukas, Panos, Kanoni, Stavroula, Farrall, Martin, Assimes, Themistocles L., Thompson, John R., Ingelsson, Erik, Saleheen, Danish, Goldstein, Benjamin A., Absher, Devin, König, Inke R., Cazier, Jean-Baptiste, Johansson, Åsa, Hall, Alistair S., Lee, Jong-Young, Chambers, John C., Esko, Tõnu, Folkersen, Lasse, Goel, Anuj, Grundberg, Elin, Havulinna, Aki S., Ho, Weang K., Hopewell, Jemma C., Eriksson, Niclas, Kleber, Marcus E., Kristiansson, Kati, Lundmark, Per, Lyytikäinen, Leo-Pekka, Rafelt, Suzanne, Shun, Dmitry, Strawbridge, Rona J., Thorleifsson, Gudmar, Tikkanen, Emmi, Van Zuydam, Natalie, Voight, Benjamin F., Waite, Lindsay L., Zhang, Weihua, Zieg, Andreas, Altshuler, David, Balmforth, Anthony J., Barroso, Inês, Braund, Peter S., Burgdorf, Christof, Claudi-Boehm, Simone, Cox, David, Dimitriou, Maria, Do, Ron, Doney, Alex S. F., El Mokhtari, Nour Eddine, Eriksson, Per, Fischer, Krista, Fontanillas, Pierre, Franco-Cereceda, Anders, Gigante, Bruna, Groop, Leif, Gustafsson, Stefan, Hager, Jörg, Hallmans, Göran, Han, Bok-Ghee, Ehunt, Sarah, Kang, Hyun M., Illig, Thomas, Knowles, Joshua W., Kolovou, Genovefa, Kuusisto, Johanna, Langenberg, Claudia, Langford, Cordelia, Leander, Karin, Lokki, Marja-Liisa, Lundmark, Anders, McCarthy, Mark I., Meisinger, Christa, Melander, Olle, Mihailov, Evelin, Maouche, Seraya, Morris, Andrew D., Müller-Nurasyid, Martina, Nikus, Kjell, Peden, John F., Rayner, N. William, Rasheed, Asif, Rosinger, Silke, Rubin, Diana, Rumpf, Moritz P., Schäfer, Arne, Sivananthan, Mohan, Song, Ci, Stewart, Alexandre F. R., Tan, Sian-Tsung, Thorgeirsson, Gudmundur, Van Der Schoot, C. Ellen, Wagner, Peter J., Wells, George A., Wild, Philipp S., Yang, Tsun-Po, Amouyel, Philippe, Arveiler, Dominique, Basart, Hanneke, Boehnke, Michael, Boerwinkle, Eric, Brambilla, Paolo, Cambien, Francois, Cupples, Adrienne L., De Faire, Ulf, Diemert, Patrick, Epstein, Stephen E., Evans, Alun, Ferrario, Marco M., Ferrières, Jean, Gauguier, Dominique, Go, Alan S., Goodall, Alison H., Gudnason, Villi, Hazen, Stanley L., Holm, Hilma, Iribarren, Carlos, Jang, Yangsoo, Kähönen, Mika, Kee, Frank, Kim, Hyo-Soo, Klopp, Norman, Koenig, Wolfgang, Kratzer, Wolfgang, Kuulasmaa, Kari, Laaksonen, Reijo, Lee, Ji-Young, Lind, Lars, Ouwehand, Willem H., Parish, Sarah, Park, Jeong E., Pedersen, Nancy L., Peters, Annette, Quertermous, Thomas, Rader, Daniel J., Schadt, Eric, Shah, Svati H., Sinisalo, Juha, Stark, Klaus, Stefansson, Kari, Trégouët, David-Alexandre, Virtamo, Jarmo, Wareham, Nicholas, Zimmermann, Martina E., Nieminen, Markku S., Hengsten, Christian, Sandhu, Manjinder S., Pastinen, Tomi, Syvänen, Ann-Christine, Hovingh, G. Kees, Dedoussis, George, Lehtimäki, Terho, Metspalu, Andres, Zalloua, Pierre A., Siegbahn, Agneta, Schreiber, Stefan, Ripatti, Samuli, Blankenberg, Stefan S., Perola, Markus, Clarke, Robert, Oboehm, Bernhard, O’Donnell, Christopher, Reilly, Muredach P., März, Winfried, Collins, Rory, Kathiresan, Sekar, Hamsten, Anders, Kooner, Jaspal S., Thorsteinsdottir, Unnur, Danesh, John, Palmer, Colin N. A., Roberts, Robert, Watkins, Hugh, Hall, Alistair, Hengstenberg, Christian, McPherson, Ruth, and Ziegler, Andreas
Abstract: Glatiramer acetate is used therapeutically in multiple sclerosis but also known for adverse effects including elevated coronary artery disease (CAD) risk. The mechanisms underlying the cardiovascular side effects of the medication are unclear. Here, we made use of the chromosomal variation in the genes that are known to be affected by glatiramer treatment. Focusing on genes and gene products reported by drug-gene interaction database to interact with glatiramer acetate we explored a large meta-analysis on CAD genome-wide association studies aiming firstly, to investigate whether variants in these genes also affect cardiovascular risk and secondly, to identify new CAD risk genes. We traced association signals in a 200-kb region around genomic positions of genes interacting with glatiramer in up to 60 801 CAD cases and 123 504 controls. We validated the identified association in additional 21 934 CAD cases and 76 087 controls. We identified three new CAD risk alleles within the TGFB1 region on chromosome 19 that independently affect CAD risk. The lead SNP rs12459996 was genome-wide significantly associated with CAD in the extended meta-analysis (odds ratio 1.09, p = 1.58×10−12). The other two SNPs at the locus were not in linkage disequilibrium with the lead SNP and by a conditional analysis showed p-values of 4.05 × 10−10 and 2.21 × 10−6. Thus, studying genes reported to interact with glatiramer acetate we identified genetic variants that concordantly with the drug increase the risk of CAD. Of these, TGFB1 displayed signal for association. Indeed, the gene has been associated with CAD previously in both in vivo and in vitro studies. Here we establish genome-wide significant association with CAD in large human samples.
Published: 2017

5. Variants in myelin regulatory factor (MYRF) cause autosomal dominant and syndromic nanophthalmos in humans and retinal degeneration in mice.

Author: Garnai, Sarah J., Brinkmeier, Michelle L., Emery, Ben, Aleman, Tomas S., Pyle, Louise C., Veleva-Rotse, Biliana, Sisk, Robert A., Rozsa, Frank W., Ozel, Ayse Bilge, Li, Jun Z., Moroi, Sayoko E., Archer, Steven M., Lin, Cheng-mao, Sheskey, Sarah, Wiinikka-Buesser, Laurel, Eadie, James, Urquhart, Jill E., Black, Graeme C.M., Othman, Mohammad I., and Boehnke, Michael
Subjects: MYELIN regulatory factor, MICROPHTHALMIA, GLAUCOMA, STRABISMUS, RHODOPSIN
Abstract: Nanophthalmos is a rare, potentially devastating eye condition characterized by small eyes with relatively normal anatomy, a high hyperopic refractive error, and frequent association with angle closure glaucoma and vision loss. The condition constitutes the extreme of hyperopia or farsightedness, a common refractive error that is associated with strabismus and amblyopia in children. NNO1 was the first mapped nanophthalmos locus. We used combined pooled exome sequencing and strong linkage data in the large family used to map this locus to identify a canonical splice site alteration upstream of the last exon of the gene encoding myelin regulatory factor (MYRF c.3376-1G>A), a membrane bound transcription factor that undergoes autoproteolytic cleavage for nuclear localization. This variant produced a stable RNA transcript, leading to a frameshift mutation p.Gly1126Valfs*31 in the C-terminus of the protein. In addition, we identified an early truncating MYRF frameshift mutation, c.769dupC (p.S264QfsX74), in a patient with extreme axial hyperopia and syndromic features. Myrf conditional knockout mice (CKO) developed depigmentation of the retinal pigment epithelium (RPE) and retinal degeneration supporting a role of this gene in retinal and RPE development. Furthermore, we demonstrated the reduced expression of Tmem98, another known nanophthalmos gene, in Myrf CKO mice, and the physical interaction of MYRF with TMEM98. Our study establishes MYRF as a nanophthalmos gene and uncovers a new pathway for eye growth and development. [ABSTRACT FROM AUTHOR]
Published: 2019
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6. Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Author: University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Department of Medicine, University of Helsinki, Hjelt Institute, Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A., Highland, Heather M., Locke, Adam E., Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J., Teslovich, Tanya M., Rayner, N. William, Robertson, Neil R., Beer, Nicola L., Rundle, Jana K., Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noel P., Gabriel, Stacey, Gjesing, Anette P., Groves, Christopher J., Hollensted, Mette, Huyghe, Jeroen R., Jackson, Anne U., Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S., Stringham, Heather M., Syvanen, Ann-Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I., Blangero, John, Cox, Nancy J., Duggirala, Ravindranath, Hanis, Craig L., Seielstad, Mark, Wilson, James G., Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L., Doney, Alex S. F., Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jorgensen, Marit E., Jorgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D., Morris, Andrew D., Palmer, Colin N. A., Collins, Francis S., Mohlke, Karen L., Bergman, Richard N., Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M., Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C., Morris, Andrew P., Altshuler, David, Meigs, James B., Boehnke, Michael, McCarthy, Mark I., Lindgren, Cecilia M., Gloyn, Anna L., T2D-GENES Consortium, Go T2D Consortium, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Department of Medicine, University of Helsinki, Hjelt Institute, Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A., Highland, Heather M., Locke, Adam E., Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J., Teslovich, Tanya M., Rayner, N. William, Robertson, Neil R., Beer, Nicola L., Rundle, Jana K., Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noel P., Gabriel, Stacey, Gjesing, Anette P., Groves, Christopher J., Hollensted, Mette, Huyghe, Jeroen R., Jackson, Anne U., Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S., Stringham, Heather M., Syvanen, Ann-Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I., Blangero, John, Cox, Nancy J., Duggirala, Ravindranath, Hanis, Craig L., Seielstad, Mark, Wilson, James G., Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L., Doney, Alex S. F., Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jorgensen, Marit E., Jorgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D., Morris, Andrew D., Palmer, Colin N. A., Collins, Francis S., Mohlke, Karen L., Bergman, Richard N., Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M., Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C., Morris, Andrew P., Altshuler, David, Meigs, James B., Boehnke, Michael, McCarthy, Mark I., Lindgren, Cecilia M., Gloyn, Anna L., T2D-GENES Consortium, and Go T2D Consortium
Published: 2015

7. Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes.

Author: Jiang, Yu, Chen, Sai, McGuire, Daniel, Chen, Fang, Liu, Mengzhen, Iacono, William G., Hewitt, John K., Hokanson, John E., Krauter, Kenneth, Laakso, Markku, Li, Kevin W., Lutz, Sharon M., McGue, Matthew, Pandit, Anita, Zajac, Gregory J. M., Boehnke, Michael, Abecasis, Goncalo R., Vrieze, Scott I., Zhan, Xiaowei, and Jiang, Bibo
Subjects: TOBACCO use, NUCLEOTIDE sequencing, PHENOTYPES, HUMAN genetics, GENE mapping
Abstract: Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants. [ABSTRACT FROM AUTHOR]
Published: 2018
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8. Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.

Author: Davis, James P., Huyghe, Jeroen R., Locke, Adam E., Jackson, Anne U., Sim, Xueling, Stringham, Heather M., Teslovich, Tanya M., Welch, Ryan P., Fuchsberger, Christian, Narisu, Narisu, Chines, Peter S., Kangas, Antti J., Soininen, Pasi, Ala-Korpela, Mika, Kuusisto, Johanna, Collins, Francis S., Laakso, Markku, Boehnke, Michael, and Mohlke, Karen L.
Subjects: LIPOPROTEINS, LIPIDS, METABOLIC disorders, GENOTYPES, DYSLIPIDEMIA
Abstract: Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005−10) support a role for coding variants in LIPC and LIPG with lipoprotein subclass traits. 30 established lipid-associated loci had a stronger association for a subclass trait than any conventional trait. These novel association signals provide further insight into the molecular basis of dyslipidemia and the etiology of metabolic disorders. [ABSTRACT FROM AUTHOR]
Published: 2017
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9. Gene x physical activity interactions in obesity : combined analysis of 111,421 individuals of European ancestry

Author: Ahmad, Shafqat, Rukh, Gull, Varga, Tibor V, Ali, Ashfaq, Kurbasic, Azra, Shungin, Dmitry, Ericson, Ulrika, Koivula, Robert W, Chu, Audrey Y, Rose, Lynda M, Ganna, Andrea, Qi, Qibin, Stancakova, Alena, Sandholt, Camilla H, Elks, Cathy E, Curhan, Gary, Jensen, Majken K, Tamimi, Rulla M, Allin, Kristine H, Jorgensen, Torben, Brage, Soren, Langenberg, Claudia, Aadahl, Mette, Grarup, Niels, Linneberg, Allan, Pare, Guillaume, Magnusson, Patrik KE, Pedersen, Nancy L, Boehnke, Michael, Hamsten, Anders, Mohlke, Karen L, Pasquale, Louis T, Pedersen, Oluf, Scott, Robert A, Ridker, Paul M, Ingelsson, Erik, Laakso, Markku, Hansen, Torben, Qi, Lu, Wareham, Nicholas J, Chasman, Daniel I, Hallmans, Göran, Hu, Frank B, Renström, Frida, Orho-Melander, Marju, Franks, Paul W., Ahmad, Shafqat, Rukh, Gull, Varga, Tibor V, Ali, Ashfaq, Kurbasic, Azra, Shungin, Dmitry, Ericson, Ulrika, Koivula, Robert W, Chu, Audrey Y, Rose, Lynda M, Ganna, Andrea, Qi, Qibin, Stancakova, Alena, Sandholt, Camilla H, Elks, Cathy E, Curhan, Gary, Jensen, Majken K, Tamimi, Rulla M, Allin, Kristine H, Jorgensen, Torben, Brage, Soren, Langenberg, Claudia, Aadahl, Mette, Grarup, Niels, Linneberg, Allan, Pare, Guillaume, Magnusson, Patrik KE, Pedersen, Nancy L, Boehnke, Michael, Hamsten, Anders, Mohlke, Karen L, Pasquale, Louis T, Pedersen, Oluf, Scott, Robert A, Ridker, Paul M, Ingelsson, Erik, Laakso, Markku, Hansen, Torben, Qi, Lu, Wareham, Nicholas J, Chasman, Daniel I, Hallmans, Göran, Hu, Frank B, Renström, Frida, Orho-Melander, Marju, and Franks, Paul W.
Abstract: Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age(2), sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS x physical activity interaction effect estimate (P-interaction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, P-interaction = 0.014 vs. n = 71,611, P-interaction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (P-interaction = 0.003) and the SEC16B rs10913469 (P-interaction = 0.025) variants showed evidence of SNP x physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
Published: 2013
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10. Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Author: University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Department of Public Health, University of Helsinki, Haartman Institute, University of Helsinki, Clinicum, University of Helsinki, Diabetes and Obesity Research Program, University of Helsinki, Department of Public Health (-2009), Randall, Joshua C., Winkler, Thomas W., Kutalik, Zoltan, Berndt, Sonja I., Jackson, Anne U., Monda, Keri L., Kilpelaeinen, Tuomas O., Esko, Tonu, Maegi, Reedik, Li, Shengxu, Workalemahu, Tsegaselassie, Feitosa, Mary F., Croteau-Chonka, Damien C., Day, Felix R., Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Locke, Adam E., Mathieson, Iain, Scherag, Andre, Vedantam, Sailaja, Wood, Andrew R., Liang, Liming, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Dermitzakis, Emmanouil T., Dimas, Antigone S., Karpe, Fredrik, Min, Josine L., Nicholson, George, Clegg, Deborah J., Person, Thomas, Krohn, Jon P., Bauer, Sabrina, Buechler, Christa, Eisinger, Kristina, Bonnefond, Amelie, Froguel, Philippe, Hottenga, Jouke-Jan, Prokopenko, Inga, Waite, Lindsay L., Harris, Tamara B., Smith, Albert Vernon, Shuldiner, Alan R., McArdle, Wendy L., Caulfield, Mark J., Munroe, Patricia B., Gronberg, Henrik, Chen, Yii-Der Ida, Li, Guo, Beckmann, Jacques S., Johnson, Toby, Thorsteinsdottir, Unnur, Teder-Laving, Maris, Khaw, Kay-Tee, Wareham, Nicholas J., Zhao, Jing Hua, Amin, Najaf, Oostra, Ben A., Kraja, Aldi T., Province, Michael A., Cupples, L. Adrienne, Heard-Costa, Nancy L., Kaprio, Jaakko, Ripatti, Samuli, Surakka, Ida, Collins, Francis S., Saramies, Jouko, Tuomilehto, Jaakko, Jula, Antti, Salomaa, Veikko, Erdmann, Jeanette, Hengstenberg, Christian, Loley, Christina, Schunkert, Heribert, Lamina, Claudia, Wichmann, H. Erich, Albrecht, Eva, Gieger, Christian, Hicks, Andrew A., Johansson, Asa, Pramstaller, Peter P., Kathiresan, Sekar, Speliotes, Elizabeth K., Penninx, Brenda, Hartikainen, Anna-Liisa, Jarvelin, Marjo-Riitta, Gyllensten, Ulf, Boomsma, Dorret I., Campbell, Harry, Wilson, James F., Chanock, Stephen J., Farrall, Martin, Goel, Anuj, Medina-Gomez, Carolina, Rivadeneira, Fernando, Estrada, Karol, Uitterlinden, Andre G., Hofman, Albert, Zillikens, M. Carola, den Heijer, Martin, Kiemeney, Lambertus A., Maschio, Andrea, Hall, Per, Tyrer, Jonathan, Teumer, Alexander, Voelzke, Henry, Kovacs, Peter, Toenjes, Anke, Mangino, Massimo, Spector, Tim D., Hayward, Caroline, Rudan, Igor, Hall, Alistair S., Samani, Nilesh J., Attwood, Antony Paul, Sambrook, Jennifer G., Hung, Joseph, Palmer, Lyle J., Lokki, Marja-Liisa, Sinisalo, Juha-Pekka, Boucher, Gabrielle, Huikuri, Heikki, Lorentzon, Mattias, Ohlsson, Claes, Eklund, Niina, Eriksson, Johan G., Barlassina, Cristina, Rivolta, Carlo, Nolte, Ilja M., Snieder, Harold, Van der Klauw, Melanie M., Van Vliet-Ostaptchouk, Jana V., Gejman, Pablo V., Shi, Jianxin, Jacobs, Kevin B., Wang, Zhaoming, Bakker, Stephan J. L., Leach, Irene Mateo, Navis, Gerjan, van der Harst, Pim, Martin, Nicholas G., Medland, Sarah E., Montgomery, Grant W., Yang, Jian, Chasman, Daniel I., Ridker, Paul M., Rose, Lynda M., Lehtimaki, Terho, Raitakari, Olli, Absher, Devin, Iribarren, Carlos, Basart, Hanneke, Hovingh, Kees G., Hyppoenen, Elina, Power, Chris, Anderson, Denise, Beilby, John P., Hui, Jennie, Jolley, Jennifer, Sager, Hendrik, Bornstein, Stefan R., Schwarz, Peter E. H., Kristiansson, Kati, Perola, Markus, Lindstrom, Jaana, Swift, Amy J., Uusitupa, Matti, Atalay, Mustafa, Lakka, Timo A., Rauramaa, Rainer, Bolton, Jennifer L., Fowkes, Gerry, Fraser, Ross M., Price, Jackie F., Fischer, Krista, KrjutAikov, Kaarel, Metspalu, Andres, Mihailov, Evelin, Langenberg, Claudia, Luan, Jian'an, Ong, Ken K., Chines, Peter S., Keinanen-Kiukaanniemi, Sirkka M., Saaristo, Timo E., Edkins, Sarah, Franks, Paul W., Hallmans, Goran, Shungin, Dmitry, Morris, Andrew David, Palmer, Colin N. A., Erbel, Raimund, Moebus, Susanne, Noethen, Markus M., Pechlivanis, Sonali, Hveem, Kristian, Narisu, Narisu, Hamsten, Anders, Humphries, Steve E., Strawbridge, Rona J., Tremoli, Elena, Grallert, Harald, Thorand, Barbara, Illig, Thomas, Koenig, Wolfgang, Mueller-Nurasyid, Martina, Peters, Annette, Boehm, Bernhard O., Kleber, Marcus E., Maerz, Winfried, Winkelmann, Bernhard R., Kuusisto, Johanna, Laakso, Markku, Arveiler, Dominique, Cesana, Giancarlo, Kuulasmaa, Kari, Virtamo, Jarmo, Yarnell, John W. G., Kuh, Diana, Wong, Andrew, Lind, Lars, de Faire, Ulf, Gigante, Bruna, Magnusson, Patrik K. E., Pedersen, Nancy L., Dedoussis, George, Dimitriou, Maria, Kolovou, Genovefa, Kanoni, Stavroula, Stirrups, Kathleen, Bonnycastle, Lori L., Njolstad, Inger, Wilsgaard, Tom, Ganna, Andrea, Rehnberg, Emil, Hingorani, Aroon, Kivimäki, Mika, Kumari, Meena, Assimes, Themistocles L., Barroso, Ine S., Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Frayling, Timothy, Groop, Leif C., Haritunians, Talin, Hunter, David, Ingelsson, Erik, Kaplan, Robert, Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Goncalo R., McCarthy, Mark I., Hirschhorn, Joel N., Qi, Lu, Loos, Ruth J. F., Lindgren, Cecilia M., North, Kari E., Heid, Iris M., Consortium, DIAGRAM, Investigators, MAGIC, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Department of Public Health, University of Helsinki, Haartman Institute, University of Helsinki, Clinicum, University of Helsinki, Diabetes and Obesity Research Program, University of Helsinki, Department of Public Health (-2009), Randall, Joshua C., Winkler, Thomas W., Kutalik, Zoltan, Berndt, Sonja I., Jackson, Anne U., Monda, Keri L., Kilpelaeinen, Tuomas O., Esko, Tonu, Maegi, Reedik, Li, Shengxu, Workalemahu, Tsegaselassie, Feitosa, Mary F., Croteau-Chonka, Damien C., Day, Felix R., Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Locke, Adam E., Mathieson, Iain, Scherag, Andre, Vedantam, Sailaja, Wood, Andrew R., Liang, Liming, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Dermitzakis, Emmanouil T., Dimas, Antigone S., Karpe, Fredrik, Min, Josine L., Nicholson, George, Clegg, Deborah J., Person, Thomas, Krohn, Jon P., Bauer, Sabrina, Buechler, Christa, Eisinger, Kristina, Bonnefond, Amelie, Froguel, Philippe, Hottenga, Jouke-Jan, Prokopenko, Inga, Waite, Lindsay L., Harris, Tamara B., Smith, Albert Vernon, Shuldiner, Alan R., McArdle, Wendy L., Caulfield, Mark J., Munroe, Patricia B., Gronberg, Henrik, Chen, Yii-Der Ida, Li, Guo, Beckmann, Jacques S., Johnson, Toby, Thorsteinsdottir, Unnur, Teder-Laving, Maris, Khaw, Kay-Tee, Wareham, Nicholas J., Zhao, Jing Hua, Amin, Najaf, Oostra, Ben A., Kraja, Aldi T., Province, Michael A., Cupples, L. Adrienne, Heard-Costa, Nancy L., Kaprio, Jaakko, Ripatti, Samuli, Surakka, Ida, Collins, Francis S., Saramies, Jouko, Tuomilehto, Jaakko, Jula, Antti, Salomaa, Veikko, Erdmann, Jeanette, Hengstenberg, Christian, Loley, Christina, Schunkert, Heribert, Lamina, Claudia, Wichmann, H. Erich, Albrecht, Eva, Gieger, Christian, Hicks, Andrew A., Johansson, Asa, Pramstaller, Peter P., Kathiresan, Sekar, Speliotes, Elizabeth K., Penninx, Brenda, Hartikainen, Anna-Liisa, Jarvelin, Marjo-Riitta, Gyllensten, Ulf, Boomsma, Dorret I., Campbell, Harry, Wilson, James F., Chanock, Stephen J., Farrall, Martin, Goel, Anuj, Medina-Gomez, Carolina, Rivadeneira, Fernando, Estrada, Karol, Uitterlinden, Andre G., Hofman, Albert, Zillikens, M. Carola, den Heijer, Martin, Kiemeney, Lambertus A., Maschio, Andrea, Hall, Per, Tyrer, Jonathan, Teumer, Alexander, Voelzke, Henry, Kovacs, Peter, Toenjes, Anke, Mangino, Massimo, Spector, Tim D., Hayward, Caroline, Rudan, Igor, Hall, Alistair S., Samani, Nilesh J., Attwood, Antony Paul, Sambrook, Jennifer G., Hung, Joseph, Palmer, Lyle J., Lokki, Marja-Liisa, Sinisalo, Juha-Pekka, Boucher, Gabrielle, Huikuri, Heikki, Lorentzon, Mattias, Ohlsson, Claes, Eklund, Niina, Eriksson, Johan G., Barlassina, Cristina, Rivolta, Carlo, Nolte, Ilja M., Snieder, Harold, Van der Klauw, Melanie M., Van Vliet-Ostaptchouk, Jana V., Gejman, Pablo V., Shi, Jianxin, Jacobs, Kevin B., Wang, Zhaoming, Bakker, Stephan J. L., Leach, Irene Mateo, Navis, Gerjan, van der Harst, Pim, Martin, Nicholas G., Medland, Sarah E., Montgomery, Grant W., Yang, Jian, Chasman, Daniel I., Ridker, Paul M., Rose, Lynda M., Lehtimaki, Terho, Raitakari, Olli, Absher, Devin, Iribarren, Carlos, Basart, Hanneke, Hovingh, Kees G., Hyppoenen, Elina, Power, Chris, Anderson, Denise, Beilby, John P., Hui, Jennie, Jolley, Jennifer, Sager, Hendrik, Bornstein, Stefan R., Schwarz, Peter E. H., Kristiansson, Kati, Perola, Markus, Lindstrom, Jaana, Swift, Amy J., Uusitupa, Matti, Atalay, Mustafa, Lakka, Timo A., Rauramaa, Rainer, Bolton, Jennifer L., Fowkes, Gerry, Fraser, Ross M., Price, Jackie F., Fischer, Krista, KrjutAikov, Kaarel, Metspalu, Andres, Mihailov, Evelin, Langenberg, Claudia, Luan, Jian'an, Ong, Ken K., Chines, Peter S., Keinanen-Kiukaanniemi, Sirkka M., Saaristo, Timo E., Edkins, Sarah, Franks, Paul W., Hallmans, Goran, Shungin, Dmitry, Morris, Andrew David, Palmer, Colin N. A., Erbel, Raimund, Moebus, Susanne, Noethen, Markus M., Pechlivanis, Sonali, Hveem, Kristian, Narisu, Narisu, Hamsten, Anders, Humphries, Steve E., Strawbridge, Rona J., Tremoli, Elena, Grallert, Harald, Thorand, Barbara, Illig, Thomas, Koenig, Wolfgang, Mueller-Nurasyid, Martina, Peters, Annette, Boehm, Bernhard O., Kleber, Marcus E., Maerz, Winfried, Winkelmann, Bernhard R., Kuusisto, Johanna, Laakso, Markku, Arveiler, Dominique, Cesana, Giancarlo, Kuulasmaa, Kari, Virtamo, Jarmo, Yarnell, John W. G., Kuh, Diana, Wong, Andrew, Lind, Lars, de Faire, Ulf, Gigante, Bruna, Magnusson, Patrik K. E., Pedersen, Nancy L., Dedoussis, George, Dimitriou, Maria, Kolovou, Genovefa, Kanoni, Stavroula, Stirrups, Kathleen, Bonnycastle, Lori L., Njolstad, Inger, Wilsgaard, Tom, Ganna, Andrea, Rehnberg, Emil, Hingorani, Aroon, Kivimäki, Mika, Kumari, Meena, Assimes, Themistocles L., Barroso, Ine S., Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Frayling, Timothy, Groop, Leif C., Haritunians, Talin, Hunter, David, Ingelsson, Erik, Kaplan, Robert, Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Goncalo R., McCarthy, Mark I., Hirschhorn, Joel N., Qi, Lu, Loos, Ruth J. F., Lindgren, Cecilia M., North, Kari E., Heid, Iris M., Consortium, DIAGRAM, and Investigators, MAGIC
Published: 2013

11. Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals

Author: University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Chan, Yingleong, Holmen, Oddgeir L., Dauber, Andrew, Vatten, Lars, Havulinna, Aki S., Skorpen, Frank, Kvaloy, Kirsti, Silander, Kaisa, Nguyen, Thutrang T., Willer, Cristen, Boehnke, Michael, Perola, Markus, Palotie, Aarno, Salomaa, Veikko, Hveem, Kristian, Frayling, Timothy M., Hirschhorn, Joel N., Weedon, Michael N., University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Chan, Yingleong, Holmen, Oddgeir L., Dauber, Andrew, Vatten, Lars, Havulinna, Aki S., Skorpen, Frank, Kvaloy, Kirsti, Silander, Kaisa, Nguyen, Thutrang T., Willer, Cristen, Boehnke, Michael, Perola, Markus, Palotie, Aarno, Salomaa, Veikko, Hveem, Kristian, Frayling, Timothy M., Hirschhorn, Joel N., and Weedon, Michael N.
Published: 2011

12. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

Author: Feitosa, Mary F., Kraja, Aldi T., Chasman, Daniel I., Sung, Yun J., Winkler, Thomas W., Ntalla, Ioanna, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Marten, Jonathan, Musani, Solomon K., Li, Changwei, Bentley, Amy R., Brown, Michael R., Schwander, Karen, Richard, Melissa A., Noordam, Raymond, Aschard, Hugues, Bartz, Traci M., Bielak, Lawrence F., Dorajoo, Rajkumar, Fisher, Virginia, Hartwig, Fernando P., Horimoto, Andrea R. V. R., Lohman, Kurt K., Manning, Alisa K., Rankinen, Tuomo, Smith, Albert V., Tajuddin, Salman M., Wojczynski, Mary K., Alver, Maris, Boissel, Mathilde, Cai, Qiuyin, Campbell, Archie, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E., He, Meian, Hsu, Fang-Chi, Jackson, Anne U., Kähönen, Mika, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Luan, Jian'an, Matoba, Nana, Nolte, Ilja M., Padmanabhan, Sandosh, Riaz, Muhammad, Rueedi, Rico, Robino, Antonietta, Said, M. Abdullah, Scott, Robert A., Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O., van der Most, Peter J., Varga, Tibor V., Vitart, Veronique, Wang, Yajuan, Ware, Erin B., Warren, Helen R., Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R., Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E., Aung, Tin, Boerwinkle, Eric, Borecki, Ingrid, Broeckel, Ulrich, Brown, Morris, Brumat, Marco, Burke, Gregory L., Canouil, Mickaël, Chakravarti, Aravinda, Charumathi, Sabanayagam, Ida Chen, Yii-Der, Connell, John M., Correa, Adolfo, de las Fuentes, Lisa, de Mutsert, Renée, de Silva, H. Janaka, Deng, Xuan, Ding, Jingzhong, Duan, Qing, Eaton, Charles B., Ehret, Georg, Eppinga, Ruben N., Evangelou, Evangelos, Faul, Jessica D., Felix, Stephan B., Forouhi, Nita G., Forrester, Terrence, Franco, Oscar H., Friedlander, Yechiel, Gandin, Ilaria, Gao, He, Ghanbari, Mohsen, Gigante, Bruna, Gu, C. Charles, Gu, Dongfeng, Hagenaars, Saskia P., Hallmans, Göran, Harris, Tamara B., He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Howard, Barbara V., Ikram, M. Arfan, John, Ulrich, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpeläinen, Tuomas O., Koh, Woon-Puay, Krieger, José E., Kritchevsky, Stephen B., Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A., Langefeld, Carl D., Langenberg, Claudia, Launer, Lenore J., Lehne, Benjamin, Lewis, Cora E., Li, Yize, Lin, Shiow, Liu, Jianjun, Liu, Jingmin, Loh, Marie, Louie, Tin, Mägi, Reedik, McKenzie, Colin A., Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L., Momozawa, Yukihide, Nalls, Mike A., Nelson, Christopher P., Sotoodehnia, Nona, Norris, Jill M., O'Connell, Jeff R., Palmer, Nicholette D., Perls, Thomas, Pedersen, Nancy L., Peters, Annette, Peyser, Patricia A., Poulter, Neil, Raffel, Leslie J., Raitakari, Olli T., Roll, Kathryn, Rose, Lynda M., Rosendaal, Frits R., Rotter, Jerome I., Schmidt, Carsten O., Schreiner, Pamela J., Schupf, Nicole, Scott, William R., Sever, Peter S., Shi, Yuan, Sidney, Stephen, Sims, Mario, Sitlani, Colleen M., Smith, Jennifer A., Snieder, Harold, Starr, John M., Strauch, Konstantin, Stringham, Heather M., Tan, Nicholas Y. Q., Tang, Hua, Taylor, Kent D., Teo, Yik Ying, Tham, Yih Chung, Turner, Stephen T., Uitterlinden, André G., Vollenweider, Peter, Waldenberger, Melanie, Wang, Lihua, Wang, Ya Xing, Wei, Wen Bin, Williams, Christine, Yao, Jie, Yu, Caizheng, Yuan, Jian-Min, Zhao, Wei, Zonderman, Alan B., Becker, Diane M., Boehnke, Michael, Bowden, Donald W., Chambers, John C., Deary, Ian J., Esko, Tõnu, Farrall, Martin, Franks, Paul W., Freedman, Barry I., Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Jonas, Jost Bruno, Kamatani, Yoichiro, Kato, Norihiro, Kooner, Jaspal S., Kutalik, Zoltán, Laakso, Markku, Laurie, Cathy C., Leander, Karin, Lehtimäki, Terho, Study, Lifelines Cohort, Magnusson, Patrik K. E., Oldehinkel, Albertine J., Penninx, Brenda W. J. H., Polasek, Ozren, Porteous, David J., Rauramaa, Rainer, Samani, Nilesh J., Scott, James, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E., Wareham, Nicholas J., Watkins, Hugh, Weir, David R., Wickremasinghe, Ananda R., Wu, Tangchun, Zheng, Wei, Bouchard, Claude, Christensen, Kaare, Evans, Michele K., Gudnason, Vilmundur, Horta, Bernardo L., Kardia, Sharon L. R., Liu, Yongmei, Pereira, Alexandre C., Psaty, Bruce M., Ridker, Paul M., van Dam, Rob M., Gauderman, W. James, Zhu, Xiaofeng, Mook-Kanamori, Dennis O., Fornage, Myriam, Rotimi, Charles N., Cupples, L. Adrienne, Kelly, Tanika N., Fox, Ervin R., Hayward, Caroline, van Duijn, Cornelia M., Tai, E Shyong, Wong, Tien Yin, Kooperberg, Charles, Palmas, Walter, Rice, Kenneth, Morrison, Alanna C., Elliott, Paul, Caulfield, Mark J., Munroe, Patricia B., Rao, Dabeeru C., Province, Michael A., and Levy, Daniel
Subjects: Biology and Life Sciences, Nutrition, Diet, Alcohol Consumption, Medicine and Health Sciences, Mathematical and Statistical Techniques, Statistical Methods, Meta-Analysis, Physical Sciences, Mathematics, Statistics (Mathematics), Computational Biology, Genome Complexity, Introns, Genetics, Genomics, Vascular Medicine, Blood Pressure, Genetic Loci, Molecular Biology, Molecular Biology Techniques, Gene Mapping, Alleles, Psychology, Addiction, Alcoholism, Social Sciences, Mental Health and Psychiatry, Substance-Related Disorders, Public and Occupational Health
Abstract: Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
Published: 2018
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13. The Power of Gene-Based Rare Variant Methods to Detect Disease-Associated Variation and Test Hypotheses About Complex Disease.

Author: Moutsianas, Loukas, Agarwala, Vineeta, Fuchsberger, Christian, Flannick, Jason, Rivas, Manuel A., Gaulton, Kyle J., Albers, Patrick K., null, null, McVean, Gil, Boehnke, Michael, Altshuler, David, and McCarthy, Mark I.
Subjects: NUCLEOTIDE sequence, HUMAN genetics, ALLELES, HUMAN phenotype, MEDICAL genetics
Abstract: Genome and exome sequencing in large cohorts enables characterization of the role of rare variation in complex diseases. Success in this endeavor, however, requires investigators to test a diverse array of genetic hypotheses which differ in the number, frequency and effect sizes of underlying causal variants. In this study, we evaluated the power of gene-based association methods to interrogate such hypotheses, and examined the implications for study design. We developed a flexible simulation approach, using 1000 Genomes data, to (a) generate sequence variation at human genes in up to 10K case-control samples, and (b) quantify the statistical power of a panel of widely used gene-based association tests under a variety of allelic architectures, locus effect sizes, and significance thresholds. For loci explaining ~1% of phenotypic variance underlying a common dichotomous trait, we find that all methods have low absolute power to achieve exome-wide significance (~5-20% power at α=2.5×10-6) in 3K individuals; even in 10K samples, power is modest (~60%). The combined application of multiple methods increases sensitivity, but does so at the expense of a higher false positive rate. MiST, SKAT-O, and KBAC have the highest individual mean power across simulated datasets, but we observe wide architecture-dependent variability in the individual loci detected by each test, suggesting that inferences about disease architecture from analysis of sequencing studies can differ depending on which methods are used. Our results imply that tens of thousands of individuals, extensive functional annotation, or highly targeted hypothesis testing will be required to confidently detect or exclude rare variant signals at complex disease loci. [ABSTRACT FROM AUTHOR]
Published: 2015
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14. Genome-wide physical activity interactions in adiposity ― A meta-analysis of 200,452 adults

Author: Graff, Mariaelisa, Scott, Robert A., Justice, Anne E., Young, Kristin L., Feitosa, Mary F., Barata, Llilda, Winkler, Thomas W., Chu, Audrey Y., Mahajan, Anubha, Hadley, David, Xue, Luting, Workalemahu, Tsegaselassie, Heard-Costa, Nancy L., den Hoed, Marcel, Ahluwalia, Tarunveer S., Qi, Qibin, Ngwa, Julius S., Renström, Frida, Quaye, Lydia, Eicher, John D., Hayes, James E., Cornelis, Marilyn, Kutalik, Zoltan, Lim, Elise, Luan, Jian’an, Huffman, Jennifer E., Zhang, Weihua, Zhao, Wei, Griffin, Paula J., Haller, Toomas, Ahmad, Shafqat, Marques-Vidal, Pedro M., Bien, Stephanie, Yengo, Loic, Teumer, Alexander, Smith, Albert Vernon, Kumari, Meena, Harder, Marie Neergaard, Justesen, Johanne Marie, Kleber, Marcus E., Hollensted, Mette, Lohman, Kurt, Rivera, Natalia V., Whitfield, John B., Zhao, Jing Hua, Stringham, Heather M., Lyytikäinen, Leo-Pekka, Huppertz, Charlotte, Willemsen, Gonneke, Peyrot, Wouter J., Wu, Ying, Kristiansson, Kati, Demirkan, Ayse, Fornage, Myriam, Hassinen, Maija, Bielak, Lawrence F., Cadby, Gemma, Tanaka, Toshiko, Mägi, Reedik, van der Most, Peter J., Jackson, Anne U., Bragg-Gresham, Jennifer L., Vitart, Veronique, Marten, Jonathan, Navarro, Pau, Bellis, Claire, Pasko, Dorota, Johansson, Åsa, Snitker, Søren, Cheng, Yu-Ching, Eriksson, Joel, Lim, Unhee, Aadahl, Mette, Adair, Linda S., Amin, Najaf, Balkau, Beverley, Auvinen, Juha, Beilby, John, Bergman, Richard N., Bergmann, Sven, Bertoni, Alain G., Blangero, John, Bonnefond, Amélie, Bonnycastle, Lori L., Borja, Judith B., Brage, Søren, Busonero, Fabio, Buyske, Steve, Campbell, Harry, Chines, Peter S., Collins, Francis S., Corre, Tanguy, Smith, George Davey, Delgado, Graciela E., Dueker, Nicole, Dörr, Marcus, Ebeling, Tapani, Eiriksdottir, Gudny, Esko, Tõnu, Faul, Jessica D., Fu, Mao, Færch, Kristine, Gieger, Christian, Gläser, Sven, Gong, Jian, Gordon-Larsen, Penny, Grallert, Harald, Grammer, Tanja B., Grarup, Niels, van Grootheest, Gerard, Harald, Kennet, Hastie, Nicholas D., Havulinna, Aki S., Hernandez, Dena, Hindorff, Lucia, Hocking, Lynne J., Holmens, Oddgeir L., Holzapfel, Christina, Hottenga, Jouke Jan, Huang, Jie, Huang, Tao, Hui, Jennie, Huth, Cornelia, Hutri-Kähönen, Nina, James, Alan L., Jansson, John-Olov, Jhun, Min A., Juonala, Markus, Kinnunen, Leena, Koistinen, Heikki A., Kolcic, Ivana, Komulainen, Pirjo, Kuusisto, Johanna, Kvaløy, Kirsti, Kähönen, Mika, Lakka, Timo A., Launer, Lenore J., Lehne, Benjamin, Lindgren, Cecilia M., Lorentzon, Mattias, Luben, Robert, Marre, Michel, Milaneschi, Yuri, Monda, Keri L., Montgomery, Grant W., De Moor, Marleen H. M., Mulas, Antonella, Müller-Nurasyid, Martina, Musk, A. W., Männikkö, Reija, Männistö, Satu, Narisu, Narisu, Nauck, Matthias, Nettleton, Jennifer A., Nolte, Ilja M., Oldehinkel, Albertine J., Olden, Matthias, Ong, Ken K., Padmanabhan, Sandosh, Paternoster, Lavinia, Perez, Jeremiah, Perola, Markus, Peters, Annette, Peters, Ulrike, Peyser, Patricia A., Prokopenko, Inga, Puolijoki, Hannu, Raitakari, Olli T., Rankinen, Tuomo, Rasmussen-Torvik, Laura J., Rawal, Rajesh, Ridker, Paul M., Rose, Lynda M., Rudan, Igor, Sarti, Cinzia, Sarzynski, Mark A., Savonen, Kai, Scott, William R., Sanna, Serena, Shuldiner, Alan R., Sidney, Steve, Silbernagel, Günther, Smith, Blair H., Smith, Jennifer A., Snieder, Harold, Stančáková, Alena, Sternfeld, Barbara, Swift, Amy J., Tammelin, Tuija, Tan, Sian-Tsung, Thorand, Barbara, Thuillier, Dorothée, Vandenput, Liesbeth, Vestergaard, Henrik, van Vliet-Ostaptchouk, Jana V., Vohl, Marie-Claude, Völker, Uwe, Waeber, Gérard, Walker, Mark, Wild, Sarah, Wong, Andrew, Wright, Alan F., Zillikens, M. Carola, Zubair, Niha, Haiman, Christopher A., Lemarchand, Loic, Gyllensten, Ulf, Ohlsson, Claes, Hofman, Albert, Rivadeneira, Fernando, Uitterlinden, André G., Pérusse, Louis, Wilson, James F., Hayward, Caroline, Polasek, Ozren, Cucca, Francesco, Hveem, Kristian, Hartman, Catharina A., Tönjes, Anke, Bandinelli, Stefania, Palmer, Lyle J., Kardia, Sharon L. R., Rauramaa, Rainer, Sørensen, Thorkild I. A., Tuomilehto, Jaakko, Salomaa, Veikko, Penninx, Brenda W. J. H., de Geus, Eco J. C., Boomsma, Dorret I., Lehtimäki, Terho, Mangino, Massimo, Laakso, Markku, Bouchard, Claude, Martin, Nicholas G., Kuh, Diana, Liu, Yongmei, Linneberg, Allan, März, Winfried, Strauch, Konstantin, Kivimäki, Mika, Harris, Tamara B., Gudnason, Vilmundur, Völzke, Henry, Qi, Lu, Järvelin, Marjo-Riitta, Chambers, John C., Kooner, Jaspal S., Froguel, Philippe, Kooperberg, Charles, Vollenweider, Peter, Hallmans, Göran, Hansen, Torben, Pedersen, Oluf, Metspalu, Andres, Wareham, Nicholas J., Langenberg, Claudia, Weir, David R., Porteous, David J., Boerwinkle, Eric, Chasman, Daniel I., Abecasis, Gonçalo R., Barroso, Inês, McCarthy, Mark I., Frayling, Timothy M., O’Connell, Jeffrey R., van Duijn, Cornelia M., Boehnke, Michael, Heid, Iris M., Mohlke, Karen L., Strachan, David P., Fox, Caroline S., Liu, Ching-Ti, Hirschhorn, Joel N., Klein, Robert J., Johnson, Andrew D., Borecki, Ingrid B., Franks, Paul W., North, Kari E., Cupples, L. Adrienne, Loos, Ruth J. F., and Kilpeläinen, Tuomas O.
Subjects: Mathematical and Statistical Techniques, Statistical Methods, Meta-Analysis, Physical Sciences, Mathematics, Statistics (Mathematics), Medicine and Health Sciences, Public and Occupational Health, Physical Activity, Biology and Life Sciences, Genetics, Genetic Loci, Computational Biology, Genome Analysis, Genome-Wide Association Studies, Genomics, Human Genetics, Physiology, Physiological Parameters, Body Weight, Obesity, Functional Genomics, Epigenomics, Cell Biology, Signal Transduction, Cell Signaling, Genomic Signal Processing
Abstract: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Published: 2017
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15. Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals.

Author: Yingleong Chan, Holmen, Oddgeir L., Dauber, Andrew, Vatten, Lars, Havulinna, Aki S., Skorpen, Frank, Kvaløy, Kirsti, Silander, Kaisa, Nguyen, Thutrang T., Willer, Cristen, Boehnke, Michael, Perola, Markus, Palotie, Aarno, Salomaa, Veikko, Hveem, Kristian, Frayling, Timothy M., Hirschhorn, Joel N., and Weedon, Michael N.
Subjects: GENETIC research, HUMAN genetic variation, STATURE, SHORT stature, PHENOTYPES, GENETICS
Abstract: Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest ~1.5%), drawn from >78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p<5x10-28), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p<0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p<10-6) in the most extreme individuals (height<0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme. [ABSTRACT FROM AUTHOR]
Published: 2011
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16. Fine Mapping of Five Loci Associated with Low-Density Lipoprotein Cholesterol Detects Variants That Double the Explained Heritability.

Author: Sanna, Serena, Bingshan Li, Mulas, Antonella, Sidore, Carlo, Kang, Hyun M., Jackson, Anne U., Piras, Maria Grazia, Usala, Gianluca, Maninchedda, Giuseppe, Sassu, Alessandro, Serra, Fabrizio, Palmas, Maria Antonietta, Wood III, William H., Njølstad, Inger, Laakso, Markku, Hveem, Kristian, Tuomilehto, Jaakko, Lakka, Timo A., Rauramaa, Rainer, and Boehnke, Michael
Subjects: LOCUS (Genetics), LOW density lipoproteins, GENE mapping, CHOLESTEROL, HERITABILITY, GENETIC polymorphisms, NORWEGIANS, DISEASES
Abstract: Complex trait genome-wide association studies (GWAS) provide an efficient strategy for evaluating large numbers of common variants in large numbers of individuals and for identifying trait-associated variants. Nevertheless, GWAS often leave much of the trait heritability unexplained. We hypothesized that some of this unexplained heritability might be due to common and rare variants that reside in GWAS identified loci but lack appropriate proxies in modern genotyping arrays. To assess this hypothesis, we re-examined 7 genes (APOE, APOC1, APOC2, SORT1, LDLR, APOB, and PCSK9) in 5 loci associated with low-density lipoprotein cholesterol (LDL-C) in multiple GWAS. For each gene, we first catalogued genetic variation by re-sequencing 256 Sardinian individuals with extreme LDL-C values. Next, we genotyped variants identified by us and by the 1000 Genomes Project (totaling 3,277 SNPs) in 5,524 volunteers. We found that in one locus (PCSK9) the GWAS signal could be explained by a previously described low-frequency variant and that in three loci (PCSK9, APOE, and LDLR) there were additional variants independently associated with LDL-C, including a novel and rare LDLR variant that seems specific to Sardinians. Overall, this more detailed assessment of SNP variation in these loci increased estimates of the heritability of LDL-C accounted for by these genes from 3.1% to 6.5%. All association signals and the heritability estimates were successfully confirmed in a sample of ,10,000 Finnish and Norwegian individuals. Our results thus suggest that focusing on variants accessible via GWAS can lead to clear underestimates of the trait heritability explained by a set of loci. Further, our results suggest that, as prelude to large-scale sequencing efforts, targeted re-sequencing efforts paired with large-scale genotyping will increase estimates of complex trait heritability explained by known loci. [ABSTRACT FROM AUTHOR]
Published: 2011
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17. Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia.

Author: Sim, Xueling, Ong, Rick Twee-Hee, Chen Suo, Wan-Ting Tay, Jianjun Liu, Ng, Daniel Peng-Keat, Boehnke, Michael, Kee-Seng Chia, Tien-Yin Wong, Seielstad, Mark, Yik-Ying Teo, and E-Shyong Tai
Subjects: TYPE 2 diabetes, GENETICS education, GENETIC code, BIOETHICS, BIODIVERSITY, GENE mapping, COHORT analysis
Published: 2011
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18. Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Author: Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A., Highland, Heather M., Locke, Adam E., Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J., Teslovich, Tanya M., Rayner, N. William, Robertson, Neil R., Beer, Nicola L., Rundle, Jana K., Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noël P., Gabriel, Stacey, Gjesing, Anette P., Groves, Christopher J., Hollensted, Mette, Huyghe, Jeroen R., Jackson, Anne U., Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S., Stringham, Heather M., Syvänen, Ann-Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I., Blangero, John, Cox, Nancy J., Duggirala, Ravindranath, Hanis, Craig L., Seielstad, Mark, Wilson, James G., Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L., Doney, Alex S. F., Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jørgensen, Marit E., Jørgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D., Morris, Andrew D., Palmer, Colin N. A., Collins, Francis S., Mohlke, Karen L., Bergman, Richard N., Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M., Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C., Morris, Andrew P., Altshuler, David, Meigs, James B., Boehnke, Michael, McCarthy, Mark I., Lindgren, Cecilia M., and Gloyn, Anna L.
Abstract: Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
Published: 2015
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19. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Author: Winkler, Thomas W., Justice, Anne E., Graff, Mariaelisa, Barata, Llilda, Feitosa, Mary F., Chu, Su, Czajkowski, Jacek, Esko, Tõnu, Fall, Tove, Kilpeläinen, Tuomas O., Lu, Yingchang, Mägi, Reedik, Mihailov, Evelin, Pers, Tune H., Rüeger, Sina, Teumer, Alexander, Ehret, Georg B., Ferreira, Teresa, Heard-Costa, Nancy L., Karjalainen, Juha, Lagou, Vasiliki, Mahajan, Anubha, Neinast, Michael D., Prokopenko, Inga, Simino, Jeannette, Teslovich, Tanya M., Jansen, Rick, Westra, Harm-Jan, White, Charles C., Absher, Devin, Ahluwalia, Tarunveer S., Ahmad, Shafqat, Albrecht, Eva, Alves, Alexessander Couto, Bragg-Gresham, Jennifer L., de Craen, Anton J. M., Bis, Joshua C., Bonnefond, Amélie, Boucher, Gabrielle, Cadby, Gemma, Cheng, Yu-Ching, Chiang, Charleston W. K., Delgado, Graciela, Demirkan, Ayse, Dueker, Nicole, Eklund, Niina, Eiriksdottir, Gudny, Eriksson, Joel, Feenstra, Bjarke, Fischer, Krista, Frau, Francesca, Galesloot, Tessel E., Geller, Frank, Goel, Anuj, Gorski, Mathias, Grammer, Tanja B., Gustafsson, Stefan, Haitjema, Saskia, Hottenga, Jouke-Jan, Huffman, Jennifer E., Jackson, Anne U., Jacobs, Kevin B., Johansson, Åsa, Kaakinen, Marika, Kleber, Marcus E., Lahti, Jari, Leach, Irene Mateo, Lehne, Benjamin, Liu, Youfang, Lo, Ken Sin, Lorentzon, Mattias, Luan, Jian'an, Madden, Pamela A. F., Mangino, Massimo, McKnight, Barbara, Medina-Gomez, Carolina, Monda, Keri L., Montasser, May E., Müller, Gabriele, Müller-Nurasyid, Martina, Nolte, Ilja M., Panoutsopoulou, Kalliope, Pascoe, Laura, Paternoster, Lavinia, Rayner, Nigel W., Renström, Frida, Rizzi, Federica, Rose, Lynda M., Ryan, Kathy A., Salo, Perttu, Sanna, Serena, Scharnagl, Hubert, Shi, Jianxin, Smith, Albert Vernon, Southam, Lorraine, Stančáková, Alena, Steinthorsdottir, Valgerdur, Strawbridge, Rona J., Sung, Yun Ju, Tachmazidou, Ioanna, Tanaka, Toshiko, Thorleifsson, Gudmar, Trompet, Stella, Pervjakova, Natalia, Tyrer, Jonathan P., Vandenput, Liesbeth, van der Laan, Sander W, van der Velde, Nathalie, van Setten, Jessica, van Vliet-Ostaptchouk, Jana V., Verweij, Niek, Vlachopoulou, Efthymia, Waite, Lindsay L., Wang, Sophie R., Wang, Zhaoming, Wild, Sarah H., Willenborg, Christina, Wilson, James F., Wong, Andrew, Yang, Jian, Yengo, Loïc, Yerges-Armstrong, Laura M., Yu, Lei, Zhang, Weihua, Zhao, Jing Hua, Andersson, Ehm A., Bakker, Stephan J. L., Baldassarre, Damiano, Banasik, Karina, Barcella, Matteo, Barlassina, Cristina, Bellis, Claire, Benaglio, Paola, Blangero, John, Blüher, Matthias, Bonnet, Fabrice, Bonnycastle, Lori L., Boyd, Heather A., Bruinenberg, Marcel, Buchman, Aron S, Campbell, Harry, Chen, Yii-Der Ida, Chines, Peter S., Claudi-Boehm, Simone, Cole, John, Collins, Francis S., de Geus, Eco J. C., de Groot, Lisette C. P. G. M., Dimitriou, Maria, Duan, Jubao, Enroth, Stefan, Eury, Elodie, Farmaki, Aliki-Eleni, Forouhi, Nita G., Friedrich, Nele, Gejman, Pablo V., Gigante, Bruna, Glorioso, Nicola, Go, Alan S., Gottesman, Omri, Gräßler, Jürgen, Grallert, Harald, Grarup, Niels, Gu, Yu-Mei, Broer, Linda, Ham, Annelies C., Hansen, Torben, Harris, Tamara B., Hartman, Catharina A., Hassinen, Maija, Hastie, Nicholas, Hattersley, Andrew T., Heath, Andrew C., Henders, Anjali K., Hernandez, Dena, Hillege, Hans, Holmen, Oddgeir, Hovingh, Kees G, Hui, Jennie, Husemoen, Lise L., Hutri-Kähönen, Nina, Hysi, Pirro G., Illig, Thomas, De Jager, Philip L., Jalilzadeh, Shapour, Jørgensen, Torben, Jukema, J. Wouter, Juonala, Markus, Kanoni, Stavroula, Karaleftheri, Maria, Khaw, Kay Tee, Kinnunen, Leena, Kittner, Steven J., Koenig, Wolfgang, Kolcic, Ivana, Kovacs, Peter, Krarup, Nikolaj T., Kratzer, Wolfgang, Krüger, Janine, Kuh, Diana, Kumari, Meena, Kyriakou, Theodosios, Langenberg, Claudia, Lannfelt, Lars, Lanzani, Chiara, Lotay, Vaneet, Launer, Lenore J., Leander, Karin, Lindström, Jaana, Linneberg, Allan, Liu, Yan-Ping, Lobbens, Stéphane, Luben, Robert, Lyssenko, Valeriya, Männistö, Satu, Magnusson, Patrik K., McArdle, Wendy L., Menni, Cristina, Merger, Sigrun, Milani, Lili, Montgomery, Grant W., Morris, Andrew P., Narisu, Narisu, Nelis, Mari, Ong, Ken K., Palotie, Aarno, Pérusse, Louis, Pichler, Irene, Pilia, Maria G., Pouta, Anneli, Rheinberger, Myriam, Ribel-Madsen, Rasmus, Richards, Marcus, Rice, Kenneth M., Rice, Treva K., Rivolta, Carlo, Salomaa, Veikko, Sanders, Alan R., Sarzynski, Mark A., Scholtens, Salome, Scott, Robert A., Scott, William R., Sebert, Sylvain, Sengupta, Sebanti, Sennblad, Bengt, Seufferlein, Thomas, Silveira, Angela, Slagboom, P. Eline, Smit, Jan H., Sparsø, Thomas H., Stirrups, Kathleen, Stolk, Ronald P., Stringham, Heather M., Swertz, Morris A, Swift, Amy J., Syvänen, Ann-Christine, Tan, Sian-Tsung, Thorand, Barbara, Tönjes, Anke, Tremblay, Angelo, Tsafantakis, Emmanouil, van der Most, Peter J., Völker, Uwe, Vohl, Marie-Claude, Vonk, Judith M., Waldenberger, Melanie, Walker, Ryan W., Wennauer, Roman, Widén, Elisabeth, Willemsen, Gonneke, Wilsgaard, Tom, Wright, Alan F., Zillikens, M. Carola, van Dijk, Suzanne C., van Schoor, Natasja M., Asselbergs, Folkert W., de Bakker, Paul I. W., Beckmann, Jacques S., Beilby, John, Bennett, David A., Bergman, Richard N., Bergmann, Sven, Böger, Carsten A., Boehm, Bernhard O., Boerwinkle, Eric, Boomsma, Dorret I., Bornstein, Stefan R., Bottinger, Erwin P., Bouchard, Claude, Chambers, John C., Chanock, Stephen J., Chasman, Daniel I., Cucca, Francesco, Cusi, Daniele, Dedoussis, George, Erdmann, Jeanette, Eriksson, Johan G., Evans, Denis A., de Faire, Ulf, Farrall, Martin, Ferrucci, Luigi, Ford, Ian, Franke, Lude, Franks, Paul W., Froguel, Philippe, Gansevoort, Ron T., Gieger, Christian, Grönberg, Henrik, Gudnason, Vilmundur, Gyllensten, Ulf, Hall, Per, Hamsten, Anders, van der Harst, Pim, Hayward, Caroline, Heliövaara, Markku, Hengstenberg, Christian, Hicks, Andrew A, Hingorani, Aroon, Hofman, Albert, Hu, Frank, Huikuri, Heikki V., Hveem, Kristian, James, Alan L., Jordan, Joanne M., Jula, Antti, Kähönen, Mika, Kajantie, Eero, Kathiresan, Sekar, Kiemeney, Lambertus A. L. M., Kivimaki, Mika, Knekt, Paul B., Koistinen, Heikki A., Kooner, Jaspal S., Koskinen, Seppo, Kuusisto, Johanna, Maerz, Winfried, Martin, Nicholas G, Laakso, Markku, Lakka, Timo A., Lehtimäki, Terho, Lettre, Guillaume, Levinson, Douglas F., Lind, Lars, Lokki, Marja-Liisa, Mäntyselkä, Pekka, Melbye, Mads, Metspalu, Andres, Mitchell, Braxton D., Moll, Frans L., Murray, Jeffrey C., Musk, Arthur W., Nieminen, Markku S., Njølstad, Inger, Ohlsson, Claes, Oldehinkel, Albertine J., Oostra, Ben A., Palmer, Lyle J, Pankow, James S., Pasterkamp, Gerard, Pedersen, Nancy L., Pedersen, Oluf, Penninx, Brenda W., Perola, Markus, Peters, Annette, Polašek, Ozren, Pramstaller, Peter P., Psaty, Bruce M., Qi, Lu, Quertermous, Thomas, Raitakari, Olli T., Rankinen, Tuomo, Rauramaa, Rainer, Ridker, Paul M., Rioux, John D., Rivadeneira, Fernando, Rotter, Jerome I., Rudan, Igor, den Ruijter, Hester M., Saltevo, Juha, Sattar, Naveed, Schunkert, Heribert, Schwarz, Peter E. H., Shuldiner, Alan R., Sinisalo, Juha, Snieder, Harold, Sørensen, Thorkild I. A., Spector, Tim D., Staessen, Jan A., Stefania, Bandinelli, Thorsteinsdottir, Unnur, Stumvoll, Michael, Tardif, Jean-Claude, Tremoli, Elena, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, Verbeek, André L. M., Vermeulen, Sita H., Viikari, Jorma S., Vitart, Veronique, Völzke, Henry, Vollenweider, Peter, Waeber, Gérard, Walker, Mark, Wallaschofski, Henri, Wareham, Nicholas J., Watkins, Hugh, Zeggini, Eleftheria, Chakravarti, Aravinda, Clegg, Deborah J., Cupples, L. Adrienne, Gordon-Larsen, Penny, Jaquish, Cashell E., Rao, D. C., Abecasis, Goncalo R., Assimes, Themistocles L., Barroso, Inês, Berndt, Sonja I., Boehnke, Michael, Deloukas, Panos, Fox, Caroline S., Groop, Leif C., Hunter, David J., Ingelsson, Erik, Kaplan, Robert C., McCarthy, Mark I., Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Hirschhorn, Joel N., Lindgren, Cecilia M., Heid, Iris M., North, Kari E., Borecki, Ingrid B., Kutalik, Zoltán, and Loos, Ruth J. F.
Abstract: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
Published: 2015
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20. Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population

Author: Lim, Elaine T., Würtz, Peter, Havulinna, Aki S., Palta, Priit, Tukiainen, Taru, Rehnström, Karola, Esko, Tõnu, Mägi, Reedik, Inouye, Michael, Lappalainen, Tuuli, Chan, Yingleong, Salem, Rany M., Lek, Monkol, Flannick, Jason, Sim, Xueling, Manning, Alisa, Ladenvall, Claes, Bumpstead, Suzannah, Hämäläinen, Eija, Aalto, Kristiina, Maksimow, Mikael, Salmi, Marko, Blankenberg, Stefan, Ardissino, Diego, Shah, Svati, Horne, Benjamin, McPherson, Ruth, Hovingh, Gerald K., Reilly, Muredach P., Watkins, Hugh, Goel, Anuj, Farrall, Martin, Girelli, Domenico, Reiner, Alex P., Stitziel, Nathan O., Kathiresan, Sekar, Gabriel, Stacey, Barrett, Jeffrey C., Lehtimäki, Terho, Laakso, Markku, Groop, Leif, Kaprio, Jaakko, Perola, Markus, McCarthy, Mark I., Boehnke, Michael, Altshuler, David M., Lindgren, Cecilia M., Hirschhorn, Joel N., Metspalu, Andres, Freimer, Nelson B., Zeller, Tanja, Jalkanen, Sirpa, Koskinen, Seppo, Raitakari, Olli, Durbin, Richard, MacArthur, Daniel G., Salomaa, Veikko, Ripatti, Samuli, Daly, Mark J., and Palotie, Aarno
Subjects: Biology and Life Sciences, Computational Biology, Genome Analysis, Genome-Wide Association Studies, Evolutionary Biology, Population Genetics, Genetics, Genetics of Disease, Genetic Disorders, Heredity, Quantitative Traits, Human Genetics, Genetic Association Studies, Gene Disruption, Genomics, Phenotypes
Abstract: Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10−8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10−117). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10−4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.
Published: 2014
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21. Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

Author: Ahmad, Shafqat, Rukh, Gull, Varga, Tibor V., Ali, Ashfaq, Kurbasic, Azra, Shungin, Dmitry, Ericson, Ulrika, Koivula, Robert W., Chu, Audrey Y., Rose, Lynda M., Ganna, Andrea, Qi, Qibin, Stančáková, Alena, Sandholt, Camilla H., Elks, Cathy E., Curhan, Gary, Jensen, Majken K., Tamimi, Rulla M., Allin, Kristine H., Jørgensen, Torben, Brage, Soren, Langenberg, Claudia, Aadahl, Mette, Grarup, Niels, Linneberg, Allan, Paré, Guillaume, Magnusson, Patrik K. E., Pedersen, Nancy L., Boehnke, Michael, Hamsten, Anders, Mohlke, Karen L., Pasquale, Louis T., Pedersen, Oluf, Scott, Robert A., Ridker, Paul M., Ingelsson, Erik, Laakso, Markku, Hansen, Torben, Qi, Lu, Wareham, Nicholas J., Chasman, Daniel I., Hallmans, Göran, Hu, Frank B., Renström, Frida, Orho-Melander, Marju, and Franks, Paul W.
Subjects: Biology, Genetics, Human Genetics, Genetic Association Studies, Genome-Wide Association Studies, Population Genetics, Population Biology, Systems Biology, Medicine, Clinical Research Design, Cohort Studies, Meta-Analyses, Observational Studies, Epidemiology, Clinical Epidemiology, Genetic Epidemiology, Nutrition, Obesity
Abstract: Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.
Published: 2013
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22. Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Author: Randall, Joshua C., Winkler, Thomas W., Kutalik, Zoltán, Berndt, Sonja I., Jackson, Anne U., Monda, Keri L., Kilpeläinen, Tuomas O., Esko, Tõnu, Mägi, Reedik, Li, Shengxu, Workalemahu, Tsegaselassie, Feitosa, Mary F., Croteau-Chonka, Damien C., Day, Felix R., Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Locke, Adam E., Mathieson, Iain, Scherag, Andre, Vedantam, Sailaja, Wood, Andrew R., Liang, Liming, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Dermitzakis, Emmanouil T., Dimas, Antigone S., Karpe, Fredrik, Min, Josine L., Nicholson, George, Clegg, Deborah J., Person, Thomas, Krohn, Jon P., Bauer, Sabrina, Buechler, Christa, Eisinger, Kristina, Bonnefond, Amélie, Froguel, Philippe, Hottenga, Jouke-Jan, Prokopenko, Inga, Waite, Lindsay L., Harris, Tamara B., Smith, Albert Vernon, Shuldiner, Alan R., McArdle, Wendy L., Caulfield, Mark J., Munroe, Patricia B., Grönberg, Henrik, Chen, Yii-Der Ida, Li, Guo, Beckmann, Jacques S., Johnson, Toby, Thorsteinsdottir, Unnur, Teder-Laving, Maris, Khaw, Kay-Tee, Wareham, Nicholas J., Zhao, Jing Hua, Amin, Najaf, Oostra, Ben A., Kraja, Aldi T., Province, Michael A., Cupples, L. Adrienne, Heard-Costa, Nancy L., Kaprio, Jaakko, Ripatti, Samuli, Surakka, Ida, Collins, Francis S., Saramies, Jouko, Tuomilehto, Jaakko, Jula, Antti, Salomaa, Veikko, Erdmann, Jeanette, Hengstenberg, Christian, Loley, Christina, Schunkert, Heribert, Lamina, Claudia, Wichmann, H. Erich, Albrecht, Eva, Gieger, Christian, Hicks, Andrew A., Johansson, Åsa, Pramstaller, Peter P., Kathiresan, Sekar, Speliotes, Elizabeth K., Penninx, Brenda, Hartikainen, Anna-Liisa, Jarvelin, Marjo-Riitta, Gyllensten, Ulf, Boomsma, Dorret I., Campbell, Harry, Wilson, James F., Chanock, Stephen J., Farrall, Martin, Goel, Anuj, Medina-Gomez, Carolina, Rivadeneira, Fernando, Estrada, Karol, Uitterlinden, André G., Hofman, Albert, Zillikens, M. Carola, den Heijer, Martin, Kiemeney, Lambertus A., Maschio, Andrea, Hall, Per, Tyrer, Jonathan, Teumer, Alexander, Völzke, Henry, Kovacs, Peter, Tönjes, Anke, Mangino, Massimo, Spector, Tim D., Hayward, Caroline, Rudan, Igor, Hall, Alistair S., Samani, Nilesh J., Attwood, Antony Paul, Sambrook, Jennifer G., Hung, Joseph, Palmer, Lyle J., Lokki, Marja-Liisa, Sinisalo, Juha, Boucher, Gabrielle, Huikuri, Heikki, Lorentzon, Mattias, Ohlsson, Claes, Eklund, Niina, Eriksson, Johan G., Barlassina, Cristina, Rivolta, Carlo, Nolte, Ilja M., Snieder, Harold, Van der Klauw, Melanie M., Van Vliet-Ostaptchouk, Jana V., Gejman, Pablo V., Shi, Jianxin, Jacobs, Kevin B., Wang, Zhaoming, Bakker, Stephan J. L., Mateo Leach, Irene, Navis, Gerjan, van der Harst, Pim, Martin, Nicholas G., Medland, Sarah E., Montgomery, Grant W., Yang, Jian, Chasman, Daniel I., Ridker, Paul M., Rose, Lynda M., Lehtimäki, Terho, Raitakari, Olli, Absher, Devin, Iribarren, Carlos, Basart, Hanneke, Hovingh, Kees G., Hyppönen, Elina, Power, Chris, Anderson, Denise, Beilby, John P., Hui, Jennie, Jolley, Jennifer, Sager, Hendrik, Bornstein, Stefan R., Schwarz, Peter E. H., Kristiansson, Kati, Perola, Markus, Lindström, Jaana, Swift, Amy J., Uusitupa, Matti, Atalay, Mustafa, Lakka, Timo A., Rauramaa, Rainer, Bolton, Jennifer L., Fowkes, Gerry, Fraser, Ross M., Price, Jackie F., Fischer, Krista, KrjutÅ¡kov, Kaarel, Metspalu, Andres, Mihailov, Evelin, Langenberg, Claudia, Luan, Jian'an, Ong, Ken K., Chines, Peter S., Keinanen-Kiukaanniemi, Sirkka M., Saaristo, Timo E., Edkins, Sarah, Franks, Paul W., Hallmans, Göran, Shungin, Dmitry, Morris, Andrew David, Palmer, Colin N. A., Erbel, Raimund, Moebus, Susanne, Nöthen, Markus M., Pechlivanis, Sonali, Hveem, Kristian, Narisu, Narisu, Hamsten, Anders, Humphries, Steve E., Strawbridge, Rona J., Tremoli, Elena, Grallert, Harald, Thorand, Barbara, Illig, Thomas, Koenig, Wolfgang, Müller-Nurasyid, Martina, Peters, Annette, Boehm, Bernhard O., Kleber, Marcus E., März, Winfried, Winkelmann, Bernhard R., Kuusisto, Johanna, Laakso, Markku, Arveiler, Dominique, Cesana, Giancarlo, Kuulasmaa, Kari, Virtamo, Jarmo, Yarnell, John W. G., Kuh, Diana, Wong, Andrew, Lind, Lars, de Faire, Ulf, Gigante, Bruna, Magnusson, Patrik K. E., Pedersen, Nancy L., Dedoussis, George, Dimitriou, Maria, Kolovou, Genovefa, Kanoni, Stavroula, Stirrups, Kathleen, Bonnycastle, Lori L., Njølstad, Inger, Wilsgaard, Tom, Ganna, Andrea, Rehnberg, Emil, Hingorani, Aroon, Kivimaki, Mika, Kumari, Meena, Assimes, Themistocles L., Barroso, Inês, Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Frayling, Timothy, Groop, Leif C., Haritunians, Talin, Hunter, David, Ingelsson, Erik, Kaplan, Robert, Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Gonçalo R., McCarthy, Mark I., Hirschhorn, Joel N., Qi, Lu, Loos, Ruth J. F., Lindgren, Cecilia M., North, Kari E., and Heid, Iris M.
Subjects: Medicine, Epidemiology, Genetic Epidemiology
Abstract: Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Published: 2013
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23. The Metabochip, a Custom Genotyping Array for Genetic Studies of Metabolic, Cardiovascular, and Anthropometric Traits

Author: Voight, Benjamin F., Ding, Jun, Sidore, Carlo, Chines, Peter S., Burtt, Noël P., Fuchsberger, Christian, Li, Yanming, Erdmann, Jeanette, Frayling, Timothy M., Heid, Iris M., Jackson, Anne U., Johnson, Toby, Kilpeläinen, Tuomas O., Lindgren, Cecilia M., Morris, Andrew P., Prokopenko, Inga, Randall, Joshua C., Soranzo, Nicole, Speliotes, Elizabeth K., Teslovich, Tanya M., Wheeler, Eleanor, Maguire, Jared, Potter, Simon, Rayner, N. William, Robertson, Neil, Stirrups, Kathleen, Winckler, Wendy, Sanna, Serena, Mulas, Antonella, Nagaraja, Ramaiah, Cucca, Francesco, Barroso, Inês, Deloukas, Panos, Loos, Ruth J. F., Kathiresan, Sekar, Munroe, Patricia B., Pfeufer, Arne, Samani, Nilesh J., Schunkert, Heribert, McCarthy, Mark I., Abecasis, Gonçalo R., Boehnke, Michael, Kang, Hyun Min, Palmer, Cameron Douglas, Saxena, Richa, Parkin, Melissa, Newton-Cheh, Christopher Holmes, Hirschhorn, Joel Naom, and Altshuler, David Matthew
Subjects: Biology, Genetics, Human Genetics, Mathematics, Statistics, Medicine, Cardiovascular, Endocrinology, Diabetic Endocrinology, Diabetes Mellitus Type 2, Metabolic Disorders
Abstract: Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the “Metabochip,” a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.
Published: 2012
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24. Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

Author: Perry, John R. B., Voight, Benjamin F., Yengo, Loïc, Amin, Najaf, Dupuis, Josée, Ganser, Martha, Grallert, Harald, Navarro, Pau, Li, Man, Steinthorsdottir, Valgerdur, Almgren, Peter, Arking, Dan E., Aulchenko, Yurii, Balkau, Beverley, Benediktsson, Rafn, Bergman, Richard N., Boerwinkle, Eric, Bonnycastle, Lori, Burtt, Noël P., Campbell, Harry, Charpentier, Guillaume, Collins, Francis S., Gieger, Christian, Green, Todd, Hadjadj, Samy, Hattersley, Andrew T., Herder, Christian, Kottgen, Anna, Labrune, Yann, Langenberg, Claudia, Mohlke, Karen L., Morris, Andrew P., Oostra, Ben, Pankow, James, Petersen, Ann-Kristin, Pramstaller, Peter P., Prokopenko, Inga, Rathmann, Wolfgang, Rayner, William, Roden, Michael, Rudan, Igor, Rybin, Denis, Sigurdsson, Gunnar, Sladek, Rob, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tuomilehto, Jaakko, Uitterlinden, Andre G., Vivequin, Sidonie, Weedon, Michael N., Wright, Alan F., Illig, Thomas, Kao, Linda, Wilson, James F., Stefansson, Kari, van Duijn, Cornelia, Altschuler, David, Morris, Andrew D., Boehnke, Michael, McCarthy, Mark I., Froguel, Philippe, Palmer, Colin N. A., Wareham, Nicholas J., Groop, Leif, Frayling, Timothy M., Cauchi, Stéphane, Qi, Lu, Scott, Robert A., Hofman, Albert, Johnson, Andrew D., Kraft, Peter, Manning, Alisa K., Scott, Laura J., Hu, Frank B., and Meigs, James Benjamin
Subjects: Biology, Genetics, Heredity, Complex Traits, Phenotypes, Human Genetics, Genome-Wide Association Studies, Medicine, Endocrinology, Diabetic Endocrinology, Diabetes Mellitus Type 2, Epidemiology, Genetic Epidemiology, Molecular Epidemiology
Abstract: Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m\(^2\)) compared to obese cases (BMI\(\geq\)30 Kg/m\(^2\)). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m\(^2\)) or 4,123 obese cases (BMI\(\geq\)30 kg/m\(^2\)), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10\(^{-9}\), OR = 1.13 [95% CI 1.09–1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00–1.06]). A variant in HMG20A—previously identified in South Asians but not Europeans—was associated with type 2 diabetes in obese cases (P = 1.3×10\(^{-8}\), OR = 1.11 [95% CI 1.07–1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02–1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10–1.17], P = 3.2×10\(^{-14}\) This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05–1.08], P = 2.2×10\(^{-16}\). This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
Published: 2012
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25. Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals

Author: Chan, Yingleong, Holmen, Oddgeir L., Havulinna, Aki S., Skorpen, Frank, Kvaløy, Kirsti, Silander, Kaisa, Nguyen, Thutrang T., Willer, Cristen, Boehnke, Michael, Perola, Markus, Palotie, Aarno, Salomaa, Veikko, Hveem, Kristian, Frayling, Timothy M., Weedon, Michael N., Dauber, Andrew Nahum, Vatten, Lars Johan, and Hirschhorn, Joel Naom
Subjects: biology, genetics, human genetics
Abstract: Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest \(\sim\)1.5%), drawn from \(\sim\)78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p<5×10\(^{-28}\)), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p<0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p<10\(^{−6}\)) in the most extreme individuals (height<0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme.
Published: 2011
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26. Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution

Author: Lindgren, Cecilia M., Heid, Iris M., Randall, Joshua C., Lamina, Claudia, Steinthorsdottir, Valgerdur, Speliotes, Elizabeth K., Thorleifsson, Gudmar, Willer, Cristen J., Herrera, Blanca M., Jackson, Anne U., Lim, Noha, Scheet, Paul, Soranzo, Nicole, Amin, Najaf, Aulchenko, Yurii S., Chambers, John C., Drong, Alexander, Luan, Jian'an, Rivadeneira, Fernando, Sanna, Serena, Timpson, Nicholas J., Zillikens, M. Carola, Almgren, Peter, Bandinelli, Stefania, Bennett, Amanda J., Bergman, Richard N., Bonnycastle, Lori L., Bumpstead, Suzannah J., Chanock, Stephen J., Cherkas, Lynn, Chines, Peter, Coin, Lachlan, Cooper, Cyrus, Crawford, Gabriel, Doering, Angela, Dominiczak, Anna, Doney, Alex S. F., Ebrahim, Shah, Elliott, Paul, Erdos, Michael R., Estrada, Karol, Ferrucci, Luigi, Fischer, Guido, Forouhi, Nita G., Gieger, Christian, Grallert, Harald, Groves, Christopher J., Grundy, Scott, Guiducci, Candace, Hadley, David, Hamsten, Anders, Havulinna, Aki S., Holle, Rolf, Holloway, John W., Illig, Thomas, Isomaa, Bo, Jacobs, Leonie C., Jameson, Karen, Jousilahti, Pekka, Karpe, Fredrik, Kuusisto, Johanna, Laitinen, Jaana, Lathrop, G. Mark, Lawlor, Debbie A., Mangino, Massimo, McArdle, Wendy L., Meitinger, Thomas, Morken, Mario A., Morris, Andrew P., Munroe, Patricia, Narisu, Narisu, Nordström, Anna, Nordström, Peter, Oostra, Ben A., Palmer, Colin N. A., Payne, Felicity, Peden, John F., Prokopenko, Inga, Renström, Frida, Ruokonen, Aimo, Salomaa, Veikko, Sandhu, Manjinder S., Scuteri, Angelo, Silander, Kaisa, Song, Kijoung, Stringham, Heather M., Swift, Amy J., Tuomi, Tiinamaija, Uda, Manuela, Vollenweider, Peter, Waeber, Gerard, Wallace, Chris, Walters, G. Bragi, Weedon, Michael N., Witteman, Jacqueline C. M., Zhang, Cuilin, Zhang, Weihua, Caulfield, Mark J., Collins, Francis S., Davey Smith, George, Day, Ian N. M., Franks, Paul W., Hattersley, Andrew T., Jarvelin, Marjo-Riitta, Kong, Augustine, Kooner, Jaspal S., Laakso, Markku, Lakatta, Edward, Mooser, Vincent, Morris, Andrew D., Peltonen, Leena, Samani, Nilesh J., Spector, Timothy D., Strachan, David P., Tanaka, Toshiko, Tuomilehto, Jaakko, Uitterlinden, André G., van Duijn, Cornelia M., Wareham, Nicholas J., Waterworth, Dawn M., Boehnke, Michael, Deloukas, Panos, Groop, Leif, Thorsteinsdottir, Unnur, Schlessinger, David, Wichmann, H.-Erich, Frayling, Timothy M., Abecasis, Gonçalo R., Loos, Ruth J. F., Stefansson, Kari, Mohlke, Karen L., Barroso, Inês, Hirschhorn, Joel Naom, McCarthy, Mark I., Watkins, Hugh, The Wellcome Trust Case Control Consortium, Hunter, David J., Hu, Frank B., Yuan, Xin, Scott, Laura J., Hofman, Albert, Zhao, Jing Hua, Lyon, Helen N, and Qi, Lu
Subjects: diabetes and endocrinology, obesity, type 2 diabetes, complex traits, genetics and genomics
Abstract: To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×\(10^{-11}\)) and MSRA (WC, P = 8.9×\(10^{-9}\)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×\(10^{-8}\)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Published: 2009
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27. Concept, Design and Implementation of a Cardiovascular Gene-centric 50 K SNP Array for Large-scale Genomic Association Studies

Author: Keating, Brendan J., Tischfield, Sam, Murray, Sarah S., Bhangale, Tushar, Price, Thomas S., Glessner, Joseph T., Galver, Luana, Barrett, Jeffrey C., Grant, Struan F. A., Farlow, Deborah N., Chandrupatla, Hareesh R., Ajmal, Saad, Papanicolaou, George J., Guo, Yiran, Li, Mingyao, DerOhannessian, Stephanie, Bailey, Swneke D., Montpetit, Alexandre, Edmondson, Andrew C., Taylor, Kent, Gai, Xiaowu, Wang, Susanna S., Fornage, Myriam, Shaikh, Tamim, Groop, Leif, Boehnke, Michael, Hall, Alistair S., Hattersley, Andrew T., Frackelton, Edward, Patterson, Nick, Chiang, Charleston W. K., Kim, Cecelia E., Fabsitz, Richard R., Ouwehand, Willem, Munroe, Patricia, Caulfield, Mark, Drake, Thomas, Boerwinkle, Eric, Whitehead, A. Stephen, Cappola, Thomas P., Samani, Nilesh J., Lusis, A. Jake, Schadt, Eric, Wilson, James G., Koenig, Wolfgang, McCarthy, Mark I., Kathiresan, Sekar, Gabriel, Stacey B., Hakonarson, Hakon, Anand, Sonia S., Reilly, Muredach, Engert, James C., Nickerson, Deborah A., Rader, Daniel J., FitzGerald, Garret A., Reitsma, Pieter H., Hansen, Mark, de Bakker, Paul I Wen, Price, Alkes, Reich, David Emil, and Hirschhorn, Joel Naom
Subjects: biotechnology, cardiovascular disorders, genetics and genomics
Abstract: A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a “cosmopolitan” tagging approach to capture the genetic diversity across ∼2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.
Published: 2008
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28. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits

Author: Randall, Joshua C., Winkler, Thomas W., Kutalik, Zoltán, Berndt, Sonja I., Jackson, Anne U., Monda, Keri L., Kilpeläinen, Tuomas O., Esko, Tõnu, Mägi, Reedik, Li, Shengxu, Workalemahu, Tsegaselassie, Feitosa, Mary F., Croteau-Chonka, Damien C., Day, Felix R., Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Locke, Adam E., Mathieson, Iain, Scherag, Andre, Vedantam, Sailaja, Wood, Andrew R., Liang, Liming, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Dermitzakis, Emmanouil T., Dimas, Antigone S., Karpe, Fredrik, Min, Josine L., Nicholson, George, Clegg, Deborah J., Person, Thomas, Krohn, Jon P., Bauer, Sabrina, Buechler, Christa, Eisinger, Kristina, Diagram Consortium, Bonnefond, Amélie, Froguel, Philippe, Magic Investigators, Hottenga, Jouke-Jan, Prokopenko, Inga, Waite, Lindsay L., Harris, Tamara B., Smith, Albert Vernon, Shuldiner, Alan R., McArdle, Wendy L., Caulfield, Mark J., Munroe, Patricia B., Grönberg, Henrik, Chen, Yii-Der Ida, Li, Guo, Beckmann, Jacques S., Johnson, Toby, Thorsteinsdottir, Unnur, Teder-Laving, Maris, Khaw, Kay-Tee, Wareham, Nicholas J., Zhao, Jing Hua, Amin, Najaf, Oostra, Ben A., Kraja, Aldi T., Province, Michael A., Cupples, L. Adrienne, Heard-Costa, Nancy L., Kaprio, Jaakko, Ripatti, Samuli, Surakka, Ida, Collins, Francis S., Saramies, Jouko, Tuomilehto, Jaakko, Jula, Antti, Salomaa, Veikko, Erdmann, Jeanette, Hengstenberg, Christian, Loley, Christina, Schunkert, Heribert, Lamina, Claudia, Wichmann, H. Erich, Albrecht, Eva, Gieger, Christian, Hicks, Andrew A., Johansson, Asa, Pramstaller, Peter P., Kathiresan, Sekar, Speliotes, Elizabeth K., Penninx, Brenda, Hartikainen, Anna-Liisa, Jarvelin, Marjo-Riitta, Gyllensten, Ulf, Boomsma, Dorret I., Campbell, Harry, Wilson, James F., Chanock, Stephen J., Farrall, Martin, Goel, Anuj, Medina-Gomez, Carolina, Rivadeneira, Fernando, Estrada, Karol, Uitterlinden, André G., Hofman, Albert, Zillikens, M. Carola, den Heijer, Martin, Kiemeney, Lambertus A., Maschio, Andrea, Hall, Per, Tyrer, Jonathan, Teumer, Alexander, Völzke, Henry, Kovacs, Peter, Tönjes, Anke, Mangino, Massimo, Spector, Tim D., Hayward, Caroline, Rudan, Igor, Hall, Alistair S., Samani, Nilesh J., Attwood, Antony Paul, Sambrook, Jennifer G., Hung, Joseph, Palmer, Lyle J., Lokki, Marja-Liisa, Sinisalo, Juha, Boucher, Gabrielle, Huikuri, Heikki, Lorentzon, Mattias, Ohlsson, Claes, Eklund, Niina, Eriksson, Johan G., Barlassina, Cristina, Rivolta, Carlo, Nolte, Ilja M., Snieder, Harold, Van der Klauw, Melanie M., Van Vliet-Ostaptchouk, Jana V., Gejman, Pablo V., Shi, Jianxin, Jacobs, Kevin B., Wang, Zhaoming, Bakker, Stephan J. L., Mateo Leach, Irene, Navis, Gerjan, van der Harst, Pim, Martin, Nicholas G., Medland, Sarah E., Montgomery, Grant W., Yang, Jian, Chasman, Daniel I., Ridker, Paul M., Rose, Lynda M., Lehtimäki, Terho, Raitakari, Olli, Absher, Devin, Iribarren, Carlos, Basart, Hanneke, Hovingh, Kees G., Hyppönen, Elina, Power, Chris, Anderson, Denise, Beilby, John P., Hui, Jennie, Jolley, Jennifer, Sager, Hendrik, Bornstein, Stefan R., Schwarz, Peter E. H., Kristiansson, Kati, Perola, Markus, Lindström, Jaana, Swift, Amy J., Uusitupa, Matti, Atalay, Mustafa, Lakka, Timo A., Rauramaa, Rainer, Bolton, Jennifer L., Fowkes, Gerry, Fraser, Ross M., Price, Jackie F., Fischer, Krista, Krjutå Kov, Kaarel, Metspalu, Andres, Mihailov, Evelin, Langenberg, Claudia, Luan, Jian'an, Ong, Ken K., Chines, Peter S., Keinanen-Kiukaanniemi, Sirkka M., Saaristo, Timo E., Edkins, Sarah, Franks, Paul W., Hallmans, Göran, Shungin, Dmitry, Morris, Andrew David, Palmer, Colin N. A., Erbel, Raimund, Moebus, Susanne, Nöthen, Markus M., Pechlivanis, Sonali, Hveem, Kristian, Narisu, Narisu, Hamsten, Anders, Humphries, Steve E., Strawbridge, Rona J., Tremoli, Elena, Grallert, Harald, Thorand, Barbara, Illig, Thomas, Koenig, Wolfgang, Müller-Nurasyid, Martina, Peters, Annette, Boehm, Bernhard O., Kleber, Marcus E., März, Winfried, Winkelmann, Bernhard R., Kuusisto, Johanna, Laakso, Markku, Arveiler, Dominique, Cesana, Giancarlo, Kuulasmaa, Kari, Virtamo, Jarmo, Yarnell, John W. G., Kuh, Diana, Wong, Andrew, Lind, Lars, de Faire, Ulf, Gigante, Bruna, Magnusson, Patrik K. E., Pedersen, Nancy L., Dedoussis, George, Dimitriou, Maria, Kolovou, Genovefa, Kanoni, Stavroula, Stirrups, Kathleen, Bonnycastle, Lori L., Njølstad, Inger, Wilsgaard, Tom, Ganna, Andrea, Rehnberg, Emil, Hingorani, Aroon, Kivimaki, Mika, Kumari, Meena, Assimes, Themistocles L., Barroso, Inês, Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Frayling, Timothy, Groop, Leif C., Haritunians, Talin, Hunter, David, Ingelsson, Erik, Kaplan, Robert, Mohlke, Karen L., O'Connell, Jeffrey R., Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Gonçalo R., McCarthy, Mark I., Hirschhorn, Joel N., Qi, Lu, Loos, Ruth J. F., Lindgren, Cecilia M., North, Kari E., and Heid, Iris M.
Subjects: 2. Zero hunger

29. Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences.

Author: Spracklen CN, Iyengar AK, Vadlamudi S, Raulerson CK, Jackson AU, Brotman SM, Wu Y, Cannon ME, Davis JP, Crain AT, Currin KW, Perrin HJ, Narisu N, Stringham HM, Fuchsberger C, Locke AE, Welch RP, Kuusisto JK, Pajukanta P, Scott LJ, Li Y, Collins FS, Boehnke M, Laakso M, and Mohlke KL
Subjects: Alleles, Cadherins genetics, Cadherins metabolism, DNA-Binding Proteins genetics, DNA-Binding Proteins metabolism, Gene Frequency genetics, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Humans, Insulin Receptor Substrate Proteins genetics, Insulin Receptor Substrate Proteins metabolism, Male, Metabolic Syndrome genetics, Phenotype, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Regulatory Sequences, Nucleic Acid, Transcription Factors genetics, Transcription Factors metabolism, Adiponectin genetics, Adiponectin metabolism, Adipose Tissue metabolism
Abstract: Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms., Competing Interests: The authors have declared that no competing interests exist.
Published: 2020
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30. Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

Author: Taylor DL, Knowles DA, Scott LJ, Ramirez AH, Casale FP, Wolford BN, Guan L, Varshney A, Albanus RD, Parker SCJ, Narisu N, Chines PS, Erdos MR, Welch RP, Kinnunen L, Saramies J, Sundvall J, Lakka TA, Laakso M, Tuomilehto J, Koistinen HA, Stegle O, Boehnke M, Birney E, and Collins FS
Subjects: Energy Metabolism, Genetic Association Studies, Genotype, Humans, Muscle, Skeletal cytology, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Cellular Microenvironment, Gene Expression Regulation, Gene-Environment Interaction, Genetic Variation, Muscle Fibers, Skeletal metabolism, Muscle, Skeletal metabolism
Abstract: From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.
Published: 2018
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31. Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author: Graff M, Scott RA, Justice AE, Young KL, Feitosa MF, Barata L, Winkler TW, Chu AY, Mahajan A, Hadley D, Xue L, Workalemahu T, Heard-Costa NL, den Hoed M, Ahluwalia TS, Qi Q, Ngwa JS, Renström F, Quaye L, Eicher JD, Hayes JE, Cornelis M, Kutalik Z, Lim E, Luan J, Huffman JE, Zhang W, Zhao W, Griffin PJ, Haller T, Ahmad S, Marques-Vidal PM, Bien S, Yengo L, Teumer A, Smith AV, Kumari M, Harder MN, Justesen JM, Kleber ME, Hollensted M, Lohman K, Rivera NV, Whitfield JB, Zhao JH, Stringham HM, Lyytikäinen LP, Huppertz C, Willemsen G, Peyrot WJ, Wu Y, Kristiansson K, Demirkan A, Fornage M, Hassinen M, Bielak LF, Cadby G, Tanaka T, Mägi R, van der Most PJ, Jackson AU, Bragg-Gresham JL, Vitart V, Marten J, Navarro P, Bellis C, Pasko D, Johansson Å, Snitker S, Cheng YC, Eriksson J, Lim U, Aadahl M, Adair LS, Amin N, Balkau B, Auvinen J, Beilby J, Bergman RN, Bergmann S, Bertoni AG, Blangero J, Bonnefond A, Bonnycastle LL, Borja JB, Brage S, Busonero F, Buyske S, Campbell H, Chines PS, Collins FS, Corre T, Smith GD, Delgado GE, Dueker N, Dörr M, Ebeling T, Eiriksdottir G, Esko T, Faul JD, Fu M, Færch K, Gieger C, Gläser S, Gong J, Gordon-Larsen P, Grallert H, Grammer TB, Grarup N, van Grootheest G, Harald K, Hastie ND, Havulinna AS, Hernandez D, Hindorff L, Hocking LJ, Holmens OL, Holzapfel C, Hottenga JJ, Huang J, Huang T, Hui J, Huth C, Hutri-Kähönen N, James AL, Jansson JO, Jhun MA, Juonala M, Kinnunen L, Koistinen HA, Kolcic I, Komulainen P, Kuusisto J, Kvaløy K, Kähönen M, Lakka TA, Launer LJ, Lehne B, Lindgren CM, Lorentzon M, Luben R, Marre M, Milaneschi Y, Monda KL, Montgomery GW, De Moor MHM, Mulas A, Müller-Nurasyid M, Musk AW, Männikkö R, Männistö S, Narisu N, Nauck M, Nettleton JA, Nolte IM, Oldehinkel AJ, Olden M, Ong KK, Padmanabhan S, Paternoster L, Perez J, Perola M, Peters A, Peters U, Peyser PA, Prokopenko I, Puolijoki H, Raitakari OT, Rankinen T, Rasmussen-Torvik LJ, Rawal R, Ridker PM, Rose LM, Rudan I, Sarti C, Sarzynski MA, Savonen K, Scott WR, Sanna S, Shuldiner AR, Sidney S, Silbernagel G, Smith BH, Smith JA, Snieder H, Stančáková A, Sternfeld B, Swift AJ, Tammelin T, Tan ST, Thorand B, Thuillier D, Vandenput L, Vestergaard H, van Vliet-Ostaptchouk JV, Vohl MC, Völker U, Waeber G, Walker M, Wild S, Wong A, Wright AF, Zillikens MC, Zubair N, Haiman CA, Lemarchand L, Gyllensten U, Ohlsson C, Hofman A, Rivadeneira F, Uitterlinden AG, Pérusse L, Wilson JF, Hayward C, Polasek O, Cucca F, Hveem K, Hartman CA, Tönjes A, Bandinelli S, Palmer LJ, Kardia SLR, Rauramaa R, Sørensen TIA, Tuomilehto J, Salomaa V, Penninx BWJH, de Geus EJC, Boomsma DI, Lehtimäki T, Mangino M, Laakso M, Bouchard C, Martin NG, Kuh D, Liu Y, Linneberg A, März W, Strauch K, Kivimäki M, Harris TB, Gudnason V, Völzke H, Qi L, Järvelin MR, Chambers JC, Kooner JS, Froguel P, Kooperberg C, Vollenweider P, Hallmans G, Hansen T, Pedersen O, Metspalu A, Wareham NJ, Langenberg C, Weir DR, Porteous DJ, Boerwinkle E, Chasman DI, Abecasis GR, Barroso I, McCarthy MI, Frayling TM, O'Connell JR, van Duijn CM, Boehnke M, Heid IM, Mohlke KL, Strachan DP, Fox CS, Liu CT, Hirschhorn JN, Klein RJ, Johnson AD, Borecki IB, Franks PW, North KE, Cupples LA, Loos RJF, and Kilpeläinen TO
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1006528.].
Published: 2017
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32. Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author: Winkler TW, Justice AE, Graff M, Barata L, Feitosa MF, Chu S, Czajkowski J, Esko T, Fall T, Kilpeläinen TO, Lu Y, Mägi R, Mihailov E, Pers TH, Rüeger S, Teumer A, Ehret GB, Ferreira T, Heard-Costa NL, Karjalainen J, Lagou V, Mahajan A, Neinast MD, Prokopenko I, Simino J, Teslovich TM, Jansen R, Westra HJ, White CC, Absher D, Ahluwalia TS, Ahmad S, Albrecht E, Alves AC, Bragg-Gresham JL, de Craen AJ, Bis JC, Bonnefond A, Boucher G, Cadby G, Cheng YC, Chiang CW, Delgado G, Demirkan A, Dueker N, Eklund N, Eiriksdottir G, Eriksson J, Feenstra B, Fischer K, Frau F, Galesloot TE, Geller F, Goel A, Gorski M, Grammer TB, Gustafsson S, Haitjema S, Hottenga JJ, Huffman JE, Jackson AU, Jacobs KB, Johansson Å, Kaakinen M, Kleber ME, Lahti J, Mateo Leach I, Lehne B, Liu Y, Lo KS, Lorentzon M, Luan J, Madden PA, Mangino M, McKnight B, Medina-Gomez C, Monda KL, Montasser ME, Müller G, Müller-Nurasyid M, Nolte IM, Panoutsopoulou K, Pascoe L, Paternoster L, Rayner NW, Renström F, Rizzi F, Rose LM, Ryan KA, Salo P, Sanna S, Scharnagl H, Shi J, Smith AV, Southam L, Stančáková A, Steinthorsdottir V, Strawbridge RJ, Sung YJ, Tachmazidou I, Tanaka T, Thorleifsson G, Trompet S, Pervjakova N, Tyrer JP, Vandenput L, van der Laan SW, van der Velde N, van Setten J, van Vliet-Ostaptchouk JV, Verweij N, Vlachopoulou E, Waite LL, Wang SR, Wang Z, Wild SH, Willenborg C, Wilson JF, Wong A, Yang J, Yengo L, Yerges-Armstrong LM, Yu L, Zhang W, Zhao JH, Andersson EA, Bakker SJ, Baldassarre D, Banasik K, Barcella M, Barlassina C, Bellis C, Benaglio P, Blangero J, Blüher M, Bonnet F, Bonnycastle LL, Boyd HA, Bruinenberg M, Buchman AS, Campbell H, Chen YI, Chines PS, Claudi-Boehm S, Cole J, Collins FS, de Geus EJ, de Groot LC, Dimitriou M, Duan J, Enroth S, Eury E, Farmaki AE, Forouhi NG, Friedrich N, Gejman PV, Gigante B, Glorioso N, Go AS, Gottesman O, Gräßler J, Grallert H, Grarup N, Gu YM, Broer L, Ham AC, Hansen T, Harris TB, Hartman CA, Hassinen M, Hastie N, Hattersley AT, Heath AC, Henders AK, Hernandez D, Hillege H, Holmen O, Hovingh KG, Hui J, Husemoen LL, Hutri-Kähönen N, Hysi PG, Illig T, De Jager PL, Jalilzadeh S, Jørgensen T, Jukema JW, Juonala M, Kanoni S, Karaleftheri M, Khaw KT, Kinnunen L, Kittner SJ, Koenig W, Kolcic I, Kovacs P, Krarup NT, Kratzer W, Krüger J, Kuh D, Kumari M, Kyriakou T, Langenberg C, Lannfelt L, Lanzani C, Lotay V, Launer LJ, Leander K, Lindström J, Linneberg A, Liu YP, Lobbens S, Luben R, Lyssenko V, Männistö S, Magnusson PK, McArdle WL, Menni C, Merger S, Milani L, Montgomery GW, Morris AP, Narisu N, Nelis M, Ong KK, Palotie A, Pérusse L, Pichler I, Pilia MG, Pouta A, Rheinberger M, Ribel-Madsen R, Richards M, Rice KM, Rice TK, Rivolta C, Salomaa V, Sanders AR, Sarzynski MA, Scholtens S, Scott RA, Scott WR, Sebert S, Sengupta S, Sennblad B, Seufferlein T, Silveira A, Slagboom PE, Smit JH, Sparsø TH, Stirrups K, Stolk RP, Stringham HM, Swertz MA, Swift AJ, Syvänen AC, Tan ST, Thorand B, Tönjes A, Tremblay A, Tsafantakis E, van der Most PJ, Völker U, Vohl MC, Vonk JM, Waldenberger M, Walker RW, Wennauer R, Widén E, Willemsen G, Wilsgaard T, Wright AF, Zillikens MC, van Dijk SC, van Schoor NM, Asselbergs FW, de Bakker PI, Beckmann JS, Beilby J, Bennett DA, Bergman RN, Bergmann S, Böger CA, Boehm BO, Boerwinkle E, Boomsma DI, Bornstein SR, Bottinger EP, Bouchard C, Chambers JC, Chanock SJ, Chasman DI, Cucca F, Cusi D, Dedoussis G, Erdmann J, Eriksson JG, Evans DA, de Faire U, Farrall M, Ferrucci L, Ford I, Franke L, Franks PW, Froguel P, Gansevoort RT, Gieger C, Grönberg H, Gudnason V, Gyllensten U, Hall P, Hamsten A, van der Harst P, Hayward C, Heliövaara M, Hengstenberg C, Hicks AA, Hingorani A, Hofman A, Hu F, Huikuri HV, Hveem K, James AL, Jordan JM, Jula A, Kähönen M, Kajantie E, Kathiresan S, Kiemeney LA, Kivimaki M, Knekt PB, Koistinen HA, Kooner JS, Koskinen S, Kuusisto J, Maerz W, Martin NG, Laakso M, Lakka TA, Lehtimäki T, Lettre G, Levinson DF, Lind L, Lokki ML, Mäntyselkä P, Melbye M, Metspalu A, Mitchell BD, Moll FL, Murray JC, Musk AW, Nieminen MS, Njølstad I, Ohlsson C, Oldehinkel AJ, Oostra BA, Palmer LJ, Pankow JS, Pasterkamp G, Pedersen NL, Pedersen O, Penninx BW, Perola M, Peters A, Polašek O, Pramstaller PP, Psaty BM, Qi L, Quertermous T, Raitakari OT, Rankinen T, Rauramaa R, Ridker PM, Rioux JD, Rivadeneira F, Rotter JI, Rudan I, den Ruijter HM, Saltevo J, Sattar N, Schunkert H, Schwarz PE, Shuldiner AR, Sinisalo J, Snieder H, Sørensen TI, Spector TD, Staessen JA, Stefania B, Thorsteinsdottir U, Stumvoll M, Tardif JC, Tremoli E, Tuomilehto J, Uitterlinden AG, Uusitupa M, Verbeek AL, Vermeulen SH, Viikari JS, Vitart V, Völzke H, Vollenweider P, Waeber G, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Zeggini E, Chakravarti A, Clegg DJ, Cupples LA, Gordon-Larsen P, Jaquish CE, Rao DC, Abecasis GR, Assimes TL, Barroso I, Berndt SI, Boehnke M, Deloukas P, Fox CS, Groop LC, Hunter DJ, Ingelsson E, Kaplan RC, McCarthy MI, Mohlke KL, O'Connell JR, Schlessinger D, Strachan DP, Stefansson K, van Duijn CM, Hirschhorn JN, Lindgren CM, Heid IM, North KE, Borecki IB, Kutalik Z, and Loos RJ
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1005378.].
Published: 2016
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33. Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci.

Author: Service SK, Teslovich TM, Fuchsberger C, Ramensky V, Yajnik P, Koboldt DC, Larson DE, Zhang Q, Lin L, Welch R, Ding L, McLellan MD, O'Laughlin M, Fronick C, Fulton LL, Magrini V, Swift A, Elliott P, Jarvelin MR, Kaakinen M, McCarthy MI, Peltonen L, Pouta A, Bonnycastle LL, Collins FS, Narisu N, Stringham HM, Tuomilehto J, Ripatti S, Fulton RS, Sabatti C, Wilson RK, Boehnke M, and Freimer NB
Subjects: Cholesterol metabolism, Cholesterol, HDL metabolism, Finland, Genotype, High-Throughput Nucleotide Sequencing, Humans, Linkage Disequilibrium, Phenotype, Population Groups, White People, Cholesterol genetics, Cholesterol, HDL genetics, Genome-Wide Association Study, Quantitative Trait Loci
Abstract: Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20-30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5' and 3' untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.
Published: 2014
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34. Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Author: Wu Y, Waite LL, Jackson AU, Sheu WH, Buyske S, Absher D, Arnett DK, Boerwinkle E, Bonnycastle LL, Carty CL, Cheng I, Cochran B, Croteau-Chonka DC, Dumitrescu L, Eaton CB, Franceschini N, Guo X, Henderson BE, Hindorff LA, Kim E, Kinnunen L, Komulainen P, Lee WJ, Le Marchand L, Lin Y, Lindström J, Lingaas-Holmen O, Mitchell SL, Narisu N, Robinson JG, Schumacher F, Stančáková A, Sundvall J, Sung YJ, Swift AJ, Wang WC, Wilkens L, Wilsgaard T, Young AM, Adair LS, Ballantyne CM, Bůžková P, Chakravarti A, Collins FS, Duggan D, Feranil AB, Ho LT, Hung YJ, Hunt SC, Hveem K, Juang JM, Kesäniemi AY, Kuusisto J, Laakso M, Lakka TA, Lee IT, Leppert MF, Matise TC, Moilanen L, Njølstad I, Peters U, Quertermous T, Rauramaa R, Rotter JI, Saramies J, Tuomilehto J, Uusitupa M, Wang TD, Boehnke M, Haiman CA, Chen YD, Kooperberg C, Assimes TL, Crawford DC, Hsiung CA, North KE, and Mohlke KL
Subjects: Black or African American genetics, Apolipoprotein A-V, Cholesterol, HDL blood, Cholesterol, HDL genetics, Cholesterol, LDL blood, Cholesterol, LDL genetics, Humans, Lipoproteins, HDL blood, Lipoproteins, HDL genetics, Lipoproteins, LDL blood, Lipoproteins, LDL genetics, Proprotein Convertase 9, Triglycerides blood, Triglycerides genetics, White People genetics, Apolipoproteins A genetics, Genome-Wide Association Study, Proprotein Convertases genetics, Serine Endopeptidases genetics
Abstract: Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies., Competing Interests: The authors have declared that no competing interests exist.
Published: 2013
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35. A genome-wide association search for type 2 diabetes genes in African Americans.

Author: Palmer ND, McDonough CW, Hicks PJ, Roh BH, Wing MR, An SS, Hester JM, Cooke JN, Bostrom MA, Rudock ME, Talbert ME, Lewis JP, Ferrara A, Lu L, Ziegler JT, Sale MM, Divers J, Shriner D, Adeyemo A, Rotimi CN, Ng MC, Langefeld CD, Freedman BI, Bowden DW, Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI, Soranzo N, Wheeler E, Glazer NL, Bouatia-Naji N, Mägi R, Randall J, Johnson T, Elliott P, Rybin D, Henneman P, Dehghan A, Hottenga JJ, Song K, Goel A, Egan JM, Lajunen T, Doney A, Kanoni S, Cavalcanti-Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll SA, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben-Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YD, Chines P, Clarke R, Coin LJ, Cooper MN, Crisponi L, Day IN, de Geus EJ, Delplanque J, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hicks AA, Hillman DR, Hingorani AD, Hui J, Hung J, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer JB, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Oostra BA, Orrù M, Pakyz R, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AF, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sijbrands EJ, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Tönjes A, Uitterlinden AG, van Dijk KW, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JC, Yarnell JW, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJ, Meneton P, Magnusson PK, Nathan DM, Williams GH, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Lind L, Palmer LJ, Franks PW, Ebrahim S, Marmot M, Kao WH, Pramstaller PP, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Siscovick DS, Penninx BW, Boomsma DI, Deloukas P, Spector TD, Ferrucci L, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, and Sladek R
Subjects: Adult, Aged, Case-Control Studies, Cohort Studies, Female, Genetic Predisposition to Disease, Genotype, Humans, Male, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide, Validation Studies as Topic, Black or African American genetics, Diabetes Mellitus, Type 2 ethnology, Diabetes Mellitus, Type 2 genetics, Genome-Wide Association Study
Abstract: African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
Published: 2012
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36. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Author: Dastani Z, Hivert MF, Timpson N, Perry JR, Yuan X, Scott RA, Henneman P, Heid IM, Kizer JR, Lyytikäinen LP, Fuchsberger C, Tanaka T, Morris AP, Small K, Isaacs A, Beekman M, Coassin S, Lohman K, Qi L, Kanoni S, Pankow JS, Uh HW, Wu Y, Bidulescu A, Rasmussen-Torvik LJ, Greenwood CM, Ladouceur M, Grimsby J, Manning AK, Liu CT, Kooner J, Mooser VE, Vollenweider P, Kapur KA, Chambers J, Wareham NJ, Langenberg C, Frants R, Willems-Vandijk K, Oostra BA, Willems SM, Lamina C, Winkler TW, Psaty BM, Tracy RP, Brody J, Chen I, Viikari J, Kähönen M, Pramstaller PP, Evans DM, St Pourcain B, Sattar N, Wood AR, Bandinelli S, Carlson OD, Egan JM, Böhringer S, van Heemst D, Kedenko L, Kristiansson K, Nuotio ML, Loo BM, Harris T, Garcia M, Kanaya A, Haun M, Klopp N, Wichmann HE, Deloukas P, Katsareli E, Couper DJ, Duncan BB, Kloppenburg M, Adair LS, Borja JB, Wilson JG, Musani S, Guo X, Johnson T, Semple R, Teslovich TM, Allison MA, Redline S, Buxbaum SG, Mohlke KL, Meulenbelt I, Ballantyne CM, Dedoussis GV, Hu FB, Liu Y, Paulweber B, Spector TD, Slagboom PE, Ferrucci L, Jula A, Perola M, Raitakari O, Florez JC, Salomaa V, Eriksson JG, Frayling TM, Hicks AA, Lehtimäki T, Smith GD, Siscovick DS, Kronenberg F, van Duijn C, Loos RJ, Waterworth DM, Meigs JB, Dupuis J, Richards JB, Voight BF, Scott LJ, Steinthorsdottir V, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Hofmann OM, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Morris AD, Palmer CN, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Pedersen O, Barroso I, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI, Soranzo N, Wheeler E, Glazer NL, Bouatia-Naji N, Mägi R, Randall J, Elliott P, Rybin D, Dehghan A, Hottenga JJ, Song K, Goel A, Lajunen T, Doney A, Cavalcanti-Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll SA, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben-Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YD, Chines P, Clarke R, Coin LJ, Cooper MN, Crisponi L, Day IN, de Geus EJ, Delplanque J, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hillman DR, Hingorani AD, Hui J, Hung J, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Martínez-Larrad MT, McAteer JB, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Orrù M, Pakyz R, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Pfeiffer AF, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sigurðsson G, Sijbrands EJ, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tönjes A, Uitterlinden AG, van Dijk KW, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JC, Yarnell JW, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Meneton P, Magnusson PK, Nathan DM, Williams GH, Silander K, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Serrano-Ríos M, Lind L, Palmer LJ, Hu FB 1st, Franks PW, Ebrahim S, Marmot M, Kao WH, Pramstaller PP, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Penninx BW, Boomsma DI, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Peltonen L, Mooser V, Sladek R, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Chasman DI, Johansen CT, Fouchier SW, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Feitosa MF, Orho-Melander M, Melander O, Li X, Li M, Cho YS, Go MJ, Kim YJ, Lee JY, Park T, Kim K, Sim X, Ong RT, Croteau-Chonka DC, Lange LA, Smith JD, Ziegler A, Zhang W, Zee RY, Whitfield JB, Thompson JR, Surakka I, Spector TD, Smit JH, Sinisalo J, Scott J, Saharinen J, Sabatti C, Rose LM, Roberts R, Rieder M, Parker AN, Pare G, O'Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, McArdle W, Masson D, Martin NG, Marroni F, Lucas G, Luben R, Lokki ML, Lettre G, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, König IR, Khaw KT, Kaplan LM, Johansson Å, Janssens AC, Igl W, Hovingh GK, Hengstenberg C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Groop LC, Gonzalez E, Freimer NB, Erdmann J, Ejebe KG, Döring A, Dominiczak AF, Demissie S, Deloukas P, de Faire U, Crawford G, Chen YD, Caulfield MJ, Boekholdt SM, Assimes TL, Quertermous T, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Taylor HA Jr, Gabriel SB, Holm H, Gudnason V, Krauss RM, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Strachan DP, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, and Kathiresan S
Subjects: Adiponectin genetics, Black or African American, Asian People, Cholesterol, HDL genetics, Female, Gene Expression, Genetic Predisposition to Disease, Glucose Tolerance Test, Humans, Insulin Resistance genetics, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio, White People, Adiponectin blood, Diabetes Mellitus, Type 2 genetics, Genome-Wide Association Study
Abstract: Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance., Competing Interests: DM Waterworth, X Yuan, and VE Mooser are full-time employees of GlaxoSmithKline. P Vollenweider received grant money from GlaxoSmithKline to fund the CoLaus study. The other authors declare no competing financial interests.
Published: 2012
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37. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children.

Author: Kilpeläinen TO, Qi L, Brage S, Sharp SJ, Sonestedt E, Demerath E, Ahmad T, Mora S, Kaakinen M, Sandholt CH, Holzapfel C, Autenrieth CS, Hyppönen E, Cauchi S, He M, Kutalik Z, Kumari M, Stančáková A, Meidtner K, Balkau B, Tan JT, Mangino M, Timpson NJ, Song Y, Zillikens MC, Jablonski KA, Garcia ME, Johansson S, Bragg-Gresham JL, Wu Y, van Vliet-Ostaptchouk JV, Onland-Moret NC, Zimmermann E, Rivera NV, Tanaka T, Stringham HM, Silbernagel G, Kanoni S, Feitosa MF, Snitker S, Ruiz JR, Metter J, Larrad MT, Atalay M, Hakanen M, Amin N, Cavalcanti-Proença C, Grøntved A, Hallmans G, Jansson JO, Kuusisto J, Kähönen M, Lutsey PL, Nolan JJ, Palla L, Pedersen O, Pérusse L, Renström F, Scott RA, Shungin D, Sovio U, Tammelin TH, Rönnemaa T, Lakka TA, Uusitupa M, Rios MS, Ferrucci L, Bouchard C, Meirhaeghe A, Fu M, Walker M, Borecki IB, Dedoussis GV, Fritsche A, Ohlsson C, Boehnke M, Bandinelli S, van Duijn CM, Ebrahim S, Lawlor DA, Gudnason V, Harris TB, Sørensen TI, Mohlke KL, Hofman A, Uitterlinden AG, Tuomilehto J, Lehtimäki T, Raitakari O, Isomaa B, Njølstad PR, Florez JC, Liu S, Ness A, Spector TD, Tai ES, Froguel P, Boeing H, Laakso M, Marmot M, Bergmann S, Power C, Khaw KT, Chasman D, Ridker P, Hansen T, Monda KL, Illig T, Järvelin MR, Wareham NJ, Hu FB, Groop LC, Orho-Melander M, Ekelund U, Franks PW, and Loos RJ
Subjects: Adipose Tissue metabolism, Adolescent, Adult, Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Child, Female, Genotype, Humans, Male, Obesity metabolism, Obesity physiopathology, Risk Factors, Genetic Predisposition to Disease, Motor Activity, Obesity genetics, Polymorphism, Single Nucleotide, Proteins genetics
Abstract: Background: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268)., Methods and Findings: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r(2)>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (p(interaction) = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents., Conclusions: The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity.
Published: 2011
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