TY - JOUR T1 - Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. JF - Am J Hum Genet Y1 - 2016 A1 - Liu, Ching-Ti A1 - Raghavan, Sridharan A1 - Maruthur, Nisa A1 - Kabagambe, Edmond Kato A1 - Hong, Jaeyoung A1 - Ng, Maggie C Y A1 - Hivert, Marie-France A1 - Lu, Yingchang A1 - An, Ping A1 - Bentley, Amy R A1 - Drolet, Anne M A1 - Gaulton, Kyle J A1 - Guo, Xiuqing A1 - Armstrong, Loren L A1 - Irvin, Marguerite R A1 - Li, Man A1 - Lipovich, Leonard A1 - Rybin, Denis V A1 - Taylor, Kent D A1 - Agyemang, Charles A1 - Palmer, Nicholette D A1 - Cade, Brian E A1 - Chen, Wei-Min A1 - Dauriz, Marco A1 - Delaney, Joseph A C A1 - Edwards, Todd L A1 - Evans, Daniel S A1 - Evans, Michele K A1 - Lange, Leslie A A1 - Leong, Aaron A1 - Liu, Jingmin A1 - Liu, Yongmei A1 - Nayak, Uma A1 - Patel, Sanjay R A1 - Porneala, Bianca C A1 - Rasmussen-Torvik, Laura J A1 - Snijder, Marieke B A1 - Stallings, Sarah C A1 - Tanaka, Toshiko A1 - Yanek, Lisa R A1 - Zhao, Wei A1 - Becker, Diane M A1 - Bielak, Lawrence F A1 - Biggs, Mary L A1 - Bottinger, Erwin P A1 - Bowden, Donald W A1 - Chen, Guanjie A1 - Correa, Adolfo A1 - Couper, David J A1 - Crawford, Dana C A1 - Cushman, Mary A1 - Eicher, John D A1 - Fornage, Myriam A1 - Franceschini, Nora A1 - Fu, Yi-Ping A1 - Goodarzi, Mark O A1 - Gottesman, Omri A1 - Hara, Kazuo A1 - Harris, Tamara B A1 - Jensen, Richard A A1 - Johnson, Andrew D A1 - Jhun, Min A A1 - Karter, Andrew J A1 - Keller, Margaux F A1 - Kho, Abel N A1 - Kizer, Jorge R A1 - Krauss, Ronald M A1 - Langefeld, Carl D A1 - Li, Xiaohui A1 - Liang, Jingling A1 - Liu, Simin A1 - Lowe, William L A1 - Mosley, Thomas H A1 - North, Kari E A1 - Pacheco, Jennifer A A1 - Peyser, Patricia A A1 - Patrick, Alan L A1 - Rice, Kenneth M A1 - Selvin, Elizabeth A1 - Sims, Mario A1 - Smith, Jennifer A A1 - Tajuddin, Salman M A1 - Vaidya, Dhananjay A1 - Wren, Mary P A1 - Yao, Jie A1 - Zhu, Xiaofeng A1 - Ziegler, Julie T A1 - Zmuda, Joseph M A1 - Zonderman, Alan B A1 - Zwinderman, Aeilko H A1 - Adeyemo, Adebowale A1 - Boerwinkle, Eric A1 - Ferrucci, Luigi A1 - Hayes, M Geoffrey A1 - Kardia, Sharon L R A1 - Miljkovic, Iva A1 - Pankow, James S A1 - Rotimi, Charles N A1 - Sale, Michèle M A1 - Wagenknecht, Lynne E A1 - Arnett, Donna K A1 - Chen, Yii-Der Ida A1 - Nalls, Michael A A1 - Province, Michael A A1 - Kao, W H Linda A1 - Siscovick, David S A1 - Psaty, Bruce M A1 - Wilson, James G A1 - Loos, Ruth J F A1 - Dupuis, Josée A1 - Rich, Stephen S A1 - Florez, Jose C A1 - Rotter, Jerome I A1 - Morris, Andrew P A1 - Meigs, James B AB -

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

VL - 99 IS - 1 U1 - http://www.ncbi.nlm.nih.gov/pubmed/27321945?dopt=Abstract ER - TY - JOUR T1 - 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. JF - PLoS Med Y1 - 2017 A1 - Wheeler, Eleanor A1 - Leong, Aaron A1 - Liu, Ching-Ti A1 - Hivert, Marie-France A1 - Strawbridge, Rona J A1 - Podmore, Clara A1 - Li, Man A1 - Yao, Jie A1 - Sim, Xueling A1 - Hong, Jaeyoung A1 - Chu, Audrey Y A1 - Zhang, Weihua A1 - Wang, Xu A1 - Chen, Peng A1 - Maruthur, Nisa M A1 - Porneala, Bianca C A1 - Sharp, Stephen J A1 - Jia, Yucheng A1 - Kabagambe, Edmond K A1 - Chang, Li-Ching A1 - Chen, Wei-Min A1 - Elks, Cathy E A1 - Evans, Daniel S A1 - Fan, Qiao A1 - Giulianini, Franco A1 - Go, Min Jin A1 - Hottenga, Jouke-Jan A1 - Hu, Yao A1 - Jackson, Anne U A1 - Kanoni, Stavroula A1 - Kim, Young Jin A1 - Kleber, Marcus E A1 - Ladenvall, Claes A1 - Lecoeur, Cécile A1 - Lim, Sing-Hui A1 - Lu, Yingchang A1 - Mahajan, Anubha A1 - Marzi, Carola A1 - Nalls, Mike A A1 - Navarro, Pau A1 - Nolte, Ilja M A1 - Rose, Lynda M A1 - Rybin, Denis V A1 - Sanna, Serena A1 - Shi, Yuan A1 - Stram, Daniel O A1 - Takeuchi, Fumihiko A1 - Tan, Shu Pei A1 - van der Most, Peter J A1 - van Vliet-Ostaptchouk, Jana V A1 - Wong, Andrew A1 - Yengo, Loic A1 - Zhao, Wanting A1 - Goel, Anuj A1 - Martinez Larrad, Maria Teresa A1 - Radke, Dörte A1 - Salo, Perttu A1 - Tanaka, Toshiko A1 - van Iperen, Erik P A A1 - Abecasis, Goncalo A1 - Afaq, Saima A1 - Alizadeh, Behrooz Z A1 - Bertoni, Alain G A1 - Bonnefond, Amélie A1 - Böttcher, Yvonne A1 - Bottinger, Erwin P A1 - Campbell, Harry A1 - Carlson, Olga D A1 - Chen, Chien-Hsiun A1 - Cho, Yoon Shin A1 - Garvey, W Timothy A1 - Gieger, Christian A1 - Goodarzi, Mark O A1 - Grallert, Harald A1 - Hamsten, Anders A1 - Hartman, Catharina A A1 - Herder, Christian A1 - Hsiung, Chao Agnes A1 - Huang, Jie A1 - Igase, Michiya A1 - Isono, Masato A1 - Katsuya, Tomohiro A1 - Khor, Chiea-Chuen A1 - Kiess, Wieland A1 - Kohara, Katsuhiko A1 - Kovacs, Peter A1 - Lee, Juyoung A1 - Lee, Wen-Jane A1 - Lehne, Benjamin A1 - Li, Huaixing A1 - Liu, Jianjun A1 - Lobbens, Stephane A1 - Luan, Jian'an A1 - Lyssenko, Valeriya A1 - Meitinger, Thomas A1 - Miki, Tetsuro A1 - Miljkovic, Iva A1 - Moon, Sanghoon A1 - Mulas, Antonella A1 - Müller, Gabriele A1 - Müller-Nurasyid, Martina A1 - Nagaraja, Ramaiah A1 - Nauck, Matthias A1 - Pankow, James S A1 - Polasek, Ozren A1 - Prokopenko, Inga A1 - Ramos, Paula S A1 - Rasmussen-Torvik, Laura A1 - Rathmann, Wolfgang A1 - Rich, Stephen S A1 - Robertson, Neil R A1 - Roden, Michael A1 - Roussel, Ronan A1 - Rudan, Igor A1 - Scott, Robert A A1 - Scott, William R A1 - Sennblad, Bengt A1 - Siscovick, David S A1 - Strauch, Konstantin A1 - Sun, Liang A1 - Swertz, Morris A1 - Tajuddin, Salman M A1 - Taylor, Kent D A1 - Teo, Yik-Ying A1 - Tham, Yih Chung A1 - Tönjes, Anke A1 - Wareham, Nicholas J A1 - Willemsen, Gonneke A1 - Wilsgaard, Tom A1 - Hingorani, Aroon D A1 - Egan, Josephine A1 - Ferrucci, Luigi A1 - Hovingh, G Kees A1 - Jula, Antti A1 - Kivimaki, Mika A1 - Kumari, Meena A1 - Njølstad, Inger A1 - Palmer, Colin N A A1 - Serrano Ríos, Manuel A1 - Stumvoll, Michael A1 - Watkins, Hugh A1 - Aung, Tin A1 - Blüher, Matthias A1 - Boehnke, Michael A1 - Boomsma, Dorret I A1 - Bornstein, Stefan R A1 - Chambers, John C A1 - Chasman, Daniel I A1 - Chen, Yii-Der Ida A1 - Chen, Yduan-Tsong A1 - Cheng, Ching-Yu A1 - Cucca, Francesco A1 - de Geus, Eco J C A1 - Deloukas, Panos A1 - Evans, Michele K A1 - Fornage, Myriam A1 - Friedlander, Yechiel A1 - Froguel, Philippe A1 - Groop, Leif A1 - Gross, Myron D A1 - Harris, Tamara B A1 - Hayward, Caroline A1 - Heng, Chew-Kiat A1 - Ingelsson, Erik A1 - Kato, Norihiro A1 - Kim, Bong-Jo A1 - Koh, Woon-Puay A1 - Kooner, Jaspal S A1 - Körner, Antje A1 - Kuh, Diana A1 - Kuusisto, Johanna A1 - Laakso, Markku A1 - Lin, Xu A1 - Liu, Yongmei A1 - Loos, Ruth J F A1 - Magnusson, Patrik K E A1 - März, Winfried A1 - McCarthy, Mark I A1 - Oldehinkel, Albertine J A1 - Ong, Ken K A1 - Pedersen, Nancy L A1 - Pereira, Mark A A1 - Peters, Annette A1 - Ridker, Paul M A1 - Sabanayagam, Charumathi A1 - Sale, Michele A1 - Saleheen, Danish A1 - Saltevo, Juha A1 - Schwarz, Peter Eh A1 - Sheu, Wayne H H A1 - Snieder, Harold A1 - Spector, Timothy D A1 - Tabara, Yasuharu A1 - Tuomilehto, Jaakko A1 - van Dam, Rob M A1 - Wilson, James G A1 - Wilson, James F A1 - Wolffenbuttel, Bruce H R A1 - Wong, Tien Yin A1 - Wu, Jer-Yuarn A1 - Yuan, Jian-Min A1 - Zonderman, Alan B A1 - Soranzo, Nicole A1 - Guo, Xiuqing A1 - Roberts, David J A1 - Florez, Jose C A1 - Sladek, Robert A1 - Dupuis, Josée A1 - Morris, Andrew P A1 - Tai, E-Shyong A1 - Selvin, Elizabeth A1 - Rotter, Jerome I A1 - Langenberg, Claudia A1 - Barroso, Inês A1 - Meigs, James B KW - Diabetes Mellitus, Type 2 KW - Genetic Variation KW - Genome-Wide Association Study KW - Glycated Hemoglobin A KW - Humans KW - Phenotype KW - Risk AB -

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.

VL - 14 IS - 9 ER - TY - JOUR T1 - Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. JF - Am J Hum Genet Y1 - 2019 A1 - Sarnowski, Chloe A1 - Leong, Aaron A1 - Raffield, Laura M A1 - Wu, Peitao A1 - de Vries, Paul S A1 - DiCorpo, Daniel A1 - Guo, Xiuqing A1 - Xu, Huichun A1 - Liu, Yongmei A1 - Zheng, Xiuwen A1 - Hu, Yao A1 - Brody, Jennifer A A1 - Goodarzi, Mark O A1 - Hidalgo, Bertha A A1 - Highland, Heather M A1 - Jain, Deepti A1 - Liu, Ching-Ti A1 - Naik, Rakhi P A1 - O'Connell, Jeffrey R A1 - Perry, James A A1 - Porneala, Bianca C A1 - Selvin, Elizabeth A1 - Wessel, Jennifer A1 - Psaty, Bruce M A1 - Curran, Joanne E A1 - Peralta, Juan M A1 - Blangero, John A1 - Kooperberg, Charles A1 - Mathias, Rasika A1 - Johnson, Andrew D A1 - Reiner, Alexander P A1 - Mitchell, Braxton D A1 - Cupples, L Adrienne A1 - Vasan, Ramachandran S A1 - Correa, Adolfo A1 - Morrison, Alanna C A1 - Boerwinkle, Eric A1 - Rotter, Jerome I A1 - Rich, Stephen S A1 - Manning, Alisa K A1 - Dupuis, Josée A1 - Meigs, James B AB -

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

VL - 105 IS - 4 ER - TY - JOUR T1 - A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies. JF - J Endocr Soc Y1 - 2023 A1 - Srinivasan, Shylaja A1 - Wu, Peitao A1 - Mercader, Josep M A1 - Udler, Miriam S A1 - Porneala, Bianca C A1 - Bartz, Traci M A1 - Floyd, James S A1 - Sitlani, Colleen A1 - Guo, Xiquing A1 - Haessler, Jeffrey A1 - Kooperberg, Charles A1 - Liu, Jun A1 - Ahmad, Shahzad A1 - van Duijn, Cornelia A1 - Liu, Ching-Ti A1 - Goodarzi, Mark O A1 - Florez, Jose C A1 - Meigs, James B A1 - Rotter, Jerome I A1 - Rich, Stephen S A1 - Dupuis, Josée A1 - Leong, Aaron AB -

CONTEXT: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.

OBJECTIVE: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

METHODS: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.

RESULTS: The T1D PS was not associated with T2D both in CHARGE ( = .15) and in the MGB Biobank ( = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, = .03) in CHARGE T2D cases but not with other outcomes.

CONCLUSION: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

VL - 7 IS - 11 ER -