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Meigs, James

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Meigs

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Meigs, James

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  • Publication

    Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

    (Public Library of Science, 2012) 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; Scott, Laura J.; Hu, Frank; Meigs, James

    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.

  • Publication

    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

    (Public Library of Science, 2017) 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; 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; 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; Sladek, Robert; Dupuis, Josée; Morris, Andrew P.; Tai, E-Shyong; Selvin, Elizabeth; Rotter, Jerome I.; Langenberg, Claudia; Barroso, Inês; Meigs, James

    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 × 10−29); 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.