%0 Journal Article %J Science %D 2012 %T Evolution and functional impact of rare coding variation from deep sequencing of human exomes. %A Tennessen, Jacob A %A Bigham, Abigail W %A O'Connor, Timothy D %A Fu, Wenqing %A Kenny, Eimear E %A Gravel, Simon %A McGee, Sean %A Do, Ron %A Liu, Xiaoming %A Jun, Goo %A Kang, Hyun Min %A Jordan, Daniel %A Leal, Suzanne M %A Gabriel, Stacey %A Rieder, Mark J %A Abecasis, Goncalo %A Altshuler, David %A Nickerson, Deborah A %A Boerwinkle, Eric %A Sunyaev, Shamil %A Bustamante, Carlos D %A Bamshad, Michael J %A Akey, Joshua M %K African Americans %K Disease %K European Continental Ancestry Group %K Evolution, Molecular %K Exome %K Female %K Gene Frequency %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genome, Human %K High-Throughput Nucleotide Sequencing %K Humans %K Male %K Polymorphism, Single Nucleotide %K Population Growth %K Selection, Genetic %X

As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

%B Science %V 337 %P 64-9 %8 2012 Jul 06 %G eng %N 6090 %1 http://www.ncbi.nlm.nih.gov/pubmed/22604720?dopt=Abstract %R 10.1126/science.1219240 %0 Journal Article %J PLoS Genet %D 2014 %T Identification of novel genetic Loci associated with thyroid peroxidase antibodies and clinical thyroid disease. %A Medici, Marco %A Porcu, Eleonora %A Pistis, Giorgio %A Teumer, Alexander %A Brown, Suzanne J %A Jensen, Richard A %A Rawal, Rajesh %A Roef, Greet L %A Plantinga, Theo S %A Vermeulen, Sita H %A Lahti, Jari %A Simmonds, Matthew J %A Husemoen, Lise Lotte N %A Freathy, Rachel M %A Shields, Beverley M %A Pietzner, Diana %A Nagy, Rebecca %A Broer, Linda %A Chaker, Layal %A Korevaar, Tim I M %A Plia, Maria Grazia %A Sala, Cinzia %A Völker, Uwe %A Richards, J Brent %A Sweep, Fred C %A Gieger, Christian %A Corre, Tanguy %A Kajantie, Eero %A Thuesen, Betina %A Taes, Youri E %A Visser, W Edward %A Hattersley, Andrew T %A Kratzsch, Jürgen %A Hamilton, Alexander %A Li, Wei %A Homuth, Georg %A Lobina, Monia %A Mariotti, Stefano %A Soranzo, Nicole %A Cocca, Massimiliano %A Nauck, Matthias %A Spielhagen, Christin %A Ross, Alec %A Arnold, Alice %A van de Bunt, Martijn %A Liyanarachchi, Sandya %A Heier, Margit %A Grabe, Hans Jörgen %A Masciullo, Corrado %A Galesloot, Tessel E %A Lim, Ee M %A Reischl, Eva %A Leedman, Peter J %A Lai, Sandra %A Delitala, Alessandro %A Bremner, Alexandra P %A Philips, David I W %A Beilby, John P %A Mulas, Antonella %A Vocale, Matteo %A Abecasis, Goncalo %A Forsen, Tom %A James, Alan %A Widen, Elisabeth %A Hui, Jennie %A Prokisch, Holger %A Rietzschel, Ernst E %A Palotie, Aarno %A Feddema, Peter %A Fletcher, Stephen J %A Schramm, Katharina %A Rotter, Jerome I %A Kluttig, Alexander %A Radke, Dörte %A Traglia, Michela %A Surdulescu, Gabriela L %A He, Huiling %A Franklyn, Jayne A %A Tiller, Daniel %A Vaidya, Bijay %A De Meyer, Tim %A Jørgensen, Torben %A Eriksson, Johan G %A O'Leary, Peter C %A Wichmann, Eric %A Hermus, Ad R %A Psaty, Bruce M %A Ittermann, Till %A Hofman, Albert %A Bosi, Emanuele %A Schlessinger, David %A Wallaschofski, Henri %A Pirastu, Nicola %A Aulchenko, Yurii S %A de la Chapelle, Albert %A Netea-Maier, Romana T %A Gough, Stephen C L %A Meyer Zu Schwabedissen, Henriette %A Frayling, Timothy M %A Kaufman, Jean-Marc %A Linneberg, Allan %A Räikkönen, Katri %A Smit, Johannes W A %A Kiemeney, Lambertus A %A Rivadeneira, Fernando %A Uitterlinden, André G %A Walsh, John P %A Meisinger, Christa %A den Heijer, Martin %A Visser, Theo J %A Spector, Timothy D %A Wilson, Scott G %A Völzke, Henry %A Cappola, Anne %A Toniolo, Daniela %A Sanna, Serena %A Naitza, Silvia %A Peeters, Robin P %K Autoantibodies %K Genetic Loci %K Genome-Wide Association Study %K Graves Disease %K Hashimoto Disease %K Humans %K Iodide Peroxidase %K Risk Factors %K Thyroiditis, Autoimmune %K Thyrotropin %X

Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,990 individuals. Significant associations (P<5×10(-8)) were detected at TPO-rs11675434, ATXN2-rs653178, and BACH2-rs10944479 for TPOAb-positivity, and at TPO-rs11675434, MAGI3-rs1230666, and KALRN-rs2010099 for TPOAb levels. Individual and combined effects (genetic risk scores) of these variants on (subclinical) hypo- and hyperthyroidism, goiter and thyroid cancer were studied. Individuals with a high genetic risk score had, besides an increased risk of TPOAb-positivity (OR: 2.18, 95% CI 1.68-2.81, P = 8.1×10(-8)), a higher risk of increased thyroid-stimulating hormone levels (OR: 1.51, 95% CI 1.26-1.82, P = 2.9×10(-6)), as well as a decreased risk of goiter (OR: 0.77, 95% CI 0.66-0.89, P = 6.5×10(-4)). The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, which was replicated in an independent cohort of patients with Graves' disease (OR: 1.37, 95% CI 1.22-1.54, P = 1.2×10(-7) and OR: 1.25, 95% CI 1.12-1.39, P = 6.2×10(-5)). The MAGI3 variant was also associated with an increased risk of hypothyroidism (OR: 1.57, 95% CI 1.18-2.10, P = 1.9×10(-3)). This first GWAS meta-analysis for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. The results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which TPOAb-positives are particularly at risk of developing clinical thyroid dysfunction.

%B PLoS Genet %V 10 %P e1004123 %8 2014 Feb %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24586183?dopt=Abstract %R 10.1371/journal.pgen.1004123 %0 Journal Article %J N Engl J Med %D 2014 %T Loss-of-function mutations in APOC3, triglycerides, and coronary disease. %A Crosby, Jacy %A Peloso, Gina M %A Auer, Paul L %A Crosslin, David R %A Stitziel, Nathan O %A Lange, Leslie A %A Lu, Yingchang %A Tang, Zheng-Zheng %A Zhang, He %A Hindy, George %A Masca, Nicholas %A Stirrups, Kathleen %A Kanoni, Stavroula %A Do, Ron %A Jun, Goo %A Hu, Youna %A Kang, Hyun Min %A Xue, Chenyi %A Goel, Anuj %A Farrall, Martin %A Duga, Stefano %A Merlini, Pier Angelica %A Asselta, Rosanna %A Girelli, Domenico %A Olivieri, Oliviero %A Martinelli, Nicola %A Yin, Wu %A Reilly, Dermot %A Speliotes, Elizabeth %A Fox, Caroline S %A Hveem, Kristian %A Holmen, Oddgeir L %A Nikpay, Majid %A Farlow, Deborah N %A Assimes, Themistocles L %A Franceschini, Nora %A Robinson, Jennifer %A North, Kari E %A Martin, Lisa W %A DePristo, Mark %A Gupta, Namrata %A Escher, Stefan A %A Jansson, Jan-Håkan %A Van Zuydam, Natalie %A Palmer, Colin N A %A Wareham, Nicholas %A Koch, Werner %A Meitinger, Thomas %A Peters, Annette %A Lieb, Wolfgang %A Erbel, Raimund %A König, Inke R %A Kruppa, Jochen %A Degenhardt, Franziska %A Gottesman, Omri %A Bottinger, Erwin P %A O'Donnell, Christopher J %A Psaty, Bruce M %A Ballantyne, Christie M %A Abecasis, Goncalo %A Ordovas, Jose M %A Melander, Olle %A Watkins, Hugh %A Orho-Melander, Marju %A Ardissino, Diego %A Loos, Ruth J F %A McPherson, Ruth %A Willer, Cristen J %A Erdmann, Jeanette %A Hall, Alistair S %A Samani, Nilesh J %A Deloukas, Panos %A Schunkert, Heribert %A Wilson, James G %A Kooperberg, Charles %A Rich, Stephen S %A Tracy, Russell P %A Lin, Dan-Yu %A Altshuler, David %A Gabriel, Stacey %A Nickerson, Deborah A %A Jarvik, Gail P %A Cupples, L Adrienne %A Reiner, Alex P %A Boerwinkle, Eric %A Kathiresan, Sekar %K African Continental Ancestry Group %K Apolipoprotein C-III %K Coronary Disease %K European Continental Ancestry Group %K Exome %K Genotype %K Heterozygote %K Humans %K Liver %K Mutation %K Risk Factors %K Sequence Analysis, DNA %K Triglycerides %X

BACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.

METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.

RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)).

CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).

%B N Engl J Med %V 371 %P 22-31 %8 2014 Jul 3 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/24941081?dopt=Abstract %R 10.1056/NEJMoa1307095 %0 Journal Article %J Nat Genet %D 2017 %T Exome-wide association study of plasma lipids in >300,000 individuals. %A Liu, Dajiang J %A Peloso, Gina M %A Yu, Haojie %A Butterworth, Adam S %A Wang, Xiao %A Mahajan, Anubha %A Saleheen, Danish %A Emdin, Connor %A Alam, Dewan %A Alves, Alexessander Couto %A Amouyel, Philippe %A Di Angelantonio, Emanuele %A Arveiler, Dominique %A Assimes, Themistocles L %A Auer, Paul L %A Baber, Usman %A Ballantyne, Christie M %A Bang, Lia E %A Benn, Marianne %A Bis, Joshua C %A Boehnke, Michael %A Boerwinkle, Eric %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brandslund, Ivan %A Brown, Morris %A Busonero, Fabio %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Y Eugene %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Connell, John M %A Cucca, Francesco %A Cupples, L Adrienne %A Damrauer, Scott M %A Davies, Gail %A Deary, Ian J %A Dedoussis, George %A Denny, Joshua C %A Dominiczak, Anna %A Dubé, Marie-Pierre %A Ebeling, Tapani %A Eiriksdottir, Gudny %A Esko, Tõnu %A Farmaki, Aliki-Eleni %A Feitosa, Mary F %A Ferrario, Marco %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frayling, Timothy M %A Frikke-Schmidt, Ruth %A Fritsche, Lars G %A Frossard, Philippe %A Fuster, Valentin %A Ganesh, Santhi K %A Gao, Wei %A Garcia, Melissa E %A Gieger, Christian %A Giulianini, Franco %A Goodarzi, Mark O %A Grallert, Harald %A Grarup, Niels %A Groop, Leif %A Grove, Megan L %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hirschhorn, Joel N %A Holmen, Oddgeir L %A Huffman, Jennifer %A Huo, Yong %A Hveem, Kristian %A Jabeen, Sehrish %A Jackson, Anne U %A Jakobsdottir, Johanna %A Jarvelin, Marjo-Riitta %A Jensen, Gorm B %A Jørgensen, Marit E %A Jukema, J Wouter %A Justesen, Johanne M %A Kamstrup, Pia R %A Kanoni, Stavroula %A Karpe, Fredrik %A Kee, Frank %A Khera, Amit V %A Klarin, Derek %A Koistinen, Heikki A %A Kooner, Jaspal S %A Kooperberg, Charles %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo %A Langenberg, Claudia %A Langsted, Anne %A Launer, Lenore J %A Lauritzen, Torsten %A Liewald, David C M %A Lin, Li An %A Linneberg, Allan %A Loos, Ruth J F %A Lu, Yingchang %A Lu, Xiangfeng %A Mägi, Reedik %A Mälarstig, Anders %A Manichaikul, Ani %A Manning, Alisa K %A Mäntyselkä, Pekka %A Marouli, Eirini %A Masca, Nicholas G D %A Maschio, Andrea %A Meigs, James B %A Melander, Olle %A Metspalu, Andres %A Morris, Andrew P %A Morrison, Alanna C %A Mulas, Antonella %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Neville, Matt J %A Nielsen, Jonas B %A Nielsen, Sune F %A Nordestgaard, Børge G %A Ordovas, Jose M %A Mehran, Roxana %A O'Donnell, Christoper J %A Orho-Melander, Marju %A Molony, Cliona M %A Muntendam, Pieter %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasko, Dorota %A Patel, Aniruddh P %A Pedersen, Oluf %A Perola, Markus %A Peters, Annette %A Pisinger, Charlotta %A Pistis, Giorgio %A Polasek, Ozren %A Poulter, Neil %A Psaty, Bruce M %A Rader, Daniel J %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Rich, Stephen S %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil R %A Roden, Dan M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sanna, Serena %A Sattar, Naveed %A Schmidt, Ellen M %A Scott, Robert A %A Sever, Peter %A Sevilla, Raquel S %A Shaffer, Christian M %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert V %A Smith, Blair H %A Somayajula, Sangeetha %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stirrups, Kathleen E %A Stitziel, Nathan %A Strauch, Konstantin %A Stringham, Heather M %A Surendran, Praveen %A Tada, Hayato %A Tall, Alan R %A Tang, Hua %A Tardif, Jean-Claude %A Taylor, Kent D %A Trompet, Stella %A Tsao, Philip S %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A van Zuydam, Natalie R %A Varbo, Anette %A Varga, Tibor V %A Virtamo, Jarmo %A Waldenberger, Melanie %A Wang, Nan %A Wareham, Nick J %A Warren, Helen R %A Weeke, Peter E %A Weinstock, Joshua %A Wessel, Jennifer %A Wilson, James G %A Wilson, Peter W F %A Xu, Ming %A Yaghootkar, Hanieh %A Young, Robin %A Zeggini, Eleftheria %A Zhang, He %A Zheng, Neil S %A Zhang, Weihua %A Zhang, Yan %A Zhou, Wei %A Zhou, Yanhua %A Zoledziewska, Magdalena %A Howson, Joanna M M %A Danesh, John %A McCarthy, Mark I %A Cowan, Chad A %A Abecasis, Goncalo %A Deloukas, Panos %A Musunuru, Kiran %A Willer, Cristen J %A Kathiresan, Sekar %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genotype %K Humans %K Lipids %K Macular Degeneration %K Phenotype %K Risk Factors %X

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

%B Nat Genet %V 49 %P 1758-1766 %8 2017 Dec %G eng %N 12 %R 10.1038/ng.3977 %0 Journal Article %J PLoS Med %D 2017 %T 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. %A Wheeler, Eleanor %A Leong, Aaron %A Liu, Ching-Ti %A Hivert, Marie-France %A Strawbridge, Rona J %A Podmore, Clara %A Li, Man %A Yao, Jie %A Sim, Xueling %A Hong, Jaeyoung %A Chu, Audrey Y %A Zhang, Weihua %A Wang, Xu %A Chen, Peng %A Maruthur, Nisa M %A Porneala, Bianca C %A Sharp, Stephen J %A Jia, Yucheng %A Kabagambe, Edmond K %A Chang, Li-Ching %A Chen, Wei-Min %A Elks, Cathy E %A Evans, Daniel S %A Fan, Qiao %A Giulianini, Franco %A Go, Min Jin %A Hottenga, Jouke-Jan %A Hu, Yao %A Jackson, Anne U %A Kanoni, Stavroula %A Kim, Young Jin %A Kleber, Marcus E %A Ladenvall, Claes %A Lecoeur, Cécile %A Lim, Sing-Hui %A Lu, Yingchang %A Mahajan, Anubha %A Marzi, Carola %A Nalls, Mike A %A Navarro, Pau %A Nolte, Ilja M %A Rose, Lynda M %A Rybin, Denis V %A Sanna, Serena %A Shi, Yuan %A Stram, Daniel O %A Takeuchi, Fumihiko %A Tan, Shu Pei %A van der Most, Peter J %A van Vliet-Ostaptchouk, Jana V %A Wong, Andrew %A Yengo, Loic %A Zhao, Wanting %A Goel, Anuj %A Martinez Larrad, Maria Teresa %A Radke, Dörte %A Salo, Perttu %A Tanaka, Toshiko %A van Iperen, Erik P A %A Abecasis, Goncalo %A Afaq, Saima %A Alizadeh, Behrooz Z %A Bertoni, Alain G %A Bonnefond, Amélie %A Böttcher, Yvonne %A Bottinger, Erwin P %A Campbell, Harry %A Carlson, Olga D %A Chen, Chien-Hsiun %A Cho, Yoon Shin %A Garvey, W Timothy %A Gieger, Christian %A Goodarzi, Mark O %A Grallert, Harald %A Hamsten, Anders %A Hartman, Catharina A %A Herder, Christian %A Hsiung, Chao Agnes %A Huang, Jie %A Igase, Michiya %A Isono, Masato %A Katsuya, Tomohiro %A Khor, Chiea-Chuen %A Kiess, Wieland %A Kohara, Katsuhiko %A Kovacs, Peter %A Lee, Juyoung %A Lee, Wen-Jane %A Lehne, Benjamin %A Li, Huaixing %A Liu, Jianjun %A Lobbens, Stephane %A Luan, Jian'an %A Lyssenko, Valeriya %A Meitinger, Thomas %A Miki, Tetsuro %A Miljkovic, Iva %A Moon, Sanghoon %A Mulas, Antonella %A Müller, Gabriele %A Müller-Nurasyid, Martina %A Nagaraja, Ramaiah %A Nauck, Matthias %A Pankow, James S %A Polasek, Ozren %A Prokopenko, Inga %A Ramos, Paula S %A Rasmussen-Torvik, Laura %A Rathmann, Wolfgang %A Rich, Stephen S %A Robertson, Neil R %A Roden, Michael %A Roussel, Ronan %A Rudan, Igor %A Scott, Robert A %A Scott, William R %A Sennblad, Bengt %A Siscovick, David S %A Strauch, Konstantin %A Sun, Liang %A Swertz, Morris %A Tajuddin, Salman M %A Taylor, Kent D %A Teo, Yik-Ying %A Tham, Yih Chung %A Tönjes, Anke %A Wareham, Nicholas J %A Willemsen, Gonneke %A Wilsgaard, Tom %A Hingorani, Aroon D %A Egan, Josephine %A Ferrucci, Luigi %A Hovingh, G Kees %A Jula, Antti %A Kivimaki, Mika %A Kumari, Meena %A Njølstad, Inger %A Palmer, Colin N A %A Serrano Ríos, Manuel %A Stumvoll, Michael %A Watkins, Hugh %A Aung, Tin %A Blüher, Matthias %A Boehnke, Michael %A Boomsma, Dorret I %A Bornstein, Stefan R %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Chen, Yduan-Tsong %A Cheng, Ching-Yu %A Cucca, Francesco %A de Geus, Eco J C %A Deloukas, Panos %A Evans, Michele K %A Fornage, Myriam %A Friedlander, Yechiel %A Froguel, Philippe %A Groop, Leif %A Gross, Myron D %A Harris, Tamara B %A Hayward, Caroline %A Heng, Chew-Kiat %A Ingelsson, Erik %A Kato, Norihiro %A Kim, Bong-Jo %A Koh, Woon-Puay %A Kooner, Jaspal S %A Körner, Antje %A Kuh, Diana %A Kuusisto, Johanna %A Laakso, Markku %A Lin, Xu %A Liu, Yongmei %A Loos, Ruth J F %A Magnusson, Patrik K E %A März, Winfried %A McCarthy, Mark I %A Oldehinkel, Albertine J %A Ong, Ken K %A Pedersen, Nancy L %A Pereira, Mark A %A Peters, Annette %A Ridker, Paul M %A Sabanayagam, Charumathi %A Sale, Michele %A Saleheen, Danish %A Saltevo, Juha %A Schwarz, Peter Eh %A Sheu, Wayne H H %A Snieder, Harold %A Spector, Timothy D %A Tabara, Yasuharu %A Tuomilehto, Jaakko %A van Dam, Rob M %A Wilson, James G %A Wilson, James F %A Wolffenbuttel, Bruce H R %A Wong, Tien Yin %A Wu, Jer-Yuarn %A Yuan, Jian-Min %A Zonderman, Alan B %A Soranzo, Nicole %A Guo, Xiuqing %A Roberts, David J %A Florez, Jose C %A Sladek, Robert %A Dupuis, Josée %A Morris, Andrew P %A Tai, E-Shyong %A Selvin, Elizabeth %A Rotter, Jerome I %A Langenberg, Claudia %A Barroso, Inês %A Meigs, James B %K Diabetes Mellitus, Type 2 %K Genetic Variation %K Genome-Wide Association Study %K Glycated Hemoglobin A %K Humans %K Phenotype %K Risk %X

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.

%B PLoS Med %V 14 %P e1002383 %8 2017 Sep %G eng %N 9 %R 10.1371/journal.pmed.1002383 %0 Journal Article %J Hypertension %D 2017 %T Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney. %A Wain, Louise V %A Vaez, Ahmad %A Jansen, Rick %A Joehanes, Roby %A van der Most, Peter J %A Erzurumluoglu, A Mesut %A O'Reilly, Paul F %A Cabrera, Claudia P %A Warren, Helen R %A Rose, Lynda M %A Verwoert, Germaine C %A Hottenga, Jouke-Jan %A Strawbridge, Rona J %A Esko, Tõnu %A Arking, Dan E %A Hwang, Shih-Jen %A Guo, Xiuqing %A Kutalik, Zoltán %A Trompet, Stella %A Shrine, Nick %A Teumer, Alexander %A Ried, Janina S %A Bis, Joshua C %A Smith, Albert V %A Amin, Najaf %A Nolte, Ilja M %A Lyytikäinen, Leo-Pekka %A Mahajan, Anubha %A Wareham, Nicholas J %A Hofer, Edith %A Joshi, Peter K %A Kristiansson, Kati %A Traglia, Michela %A Havulinna, Aki S %A Goel, Anuj %A Nalls, Mike A %A Sõber, Siim %A Vuckovic, Dragana %A Luan, Jian'an %A del Greco M, Fabiola %A Ayers, Kristin L %A Marrugat, Jaume %A Ruggiero, Daniela %A Lopez, Lorna M %A Niiranen, Teemu %A Enroth, Stefan %A Jackson, Anne U %A Nelson, Christopher P %A Huffman, Jennifer E %A Zhang, Weihua %A Marten, Jonathan %A Gandin, Ilaria %A Harris, Sarah E %A Zemunik, Tatijana %A Lu, Yingchang %A Evangelou, Evangelos %A Shah, Nabi %A de Borst, Martin H %A Mangino, Massimo %A Prins, Bram P %A Campbell, Archie %A Li-Gao, Ruifang %A Chauhan, Ganesh %A Oldmeadow, Christopher %A Abecasis, Goncalo %A Abedi, Maryam %A Barbieri, Caterina M %A Barnes, Michael R %A Batini, Chiara %A Beilby, John %A Blake, Tineka %A Boehnke, Michael %A Bottinger, Erwin P %A Braund, Peter S %A Brown, Morris %A Brumat, Marco %A Campbell, Harry %A Chambers, John C %A Cocca, Massimiliano %A Collins, Francis %A Connell, John %A Cordell, Heather J %A Damman, Jeffrey J %A Davies, Gail %A de Geus, Eco J %A de Mutsert, Renée %A Deelen, Joris %A Demirkale, Yusuf %A Doney, Alex S F %A Dörr, Marcus %A Farrall, Martin %A Ferreira, Teresa %A Frånberg, Mattias %A Gao, He %A Giedraitis, Vilmantas %A Gieger, Christian %A Giulianini, Franco %A Gow, Alan J %A Hamsten, Anders %A Harris, Tamara B %A Hofman, Albert %A Holliday, Elizabeth G %A Hui, Jennie %A Jarvelin, Marjo-Riitta %A Johansson, Asa %A Johnson, Andrew D %A Jousilahti, Pekka %A Jula, Antti %A Kähönen, Mika %A Kathiresan, Sekar %A Khaw, Kay-Tee %A Kolcic, Ivana %A Koskinen, Seppo %A Langenberg, Claudia %A Larson, Marty %A Launer, Lenore J %A Lehne, Benjamin %A Liewald, David C M %A Lin, Li %A Lind, Lars %A Mach, François %A Mamasoula, Chrysovalanto %A Menni, Cristina %A Mifsud, Borbala %A Milaneschi, Yuri %A Morgan, Anna %A Morris, Andrew D %A Morrison, Alanna C %A Munson, Peter J %A Nandakumar, Priyanka %A Nguyen, Quang Tri %A Nutile, Teresa %A Oldehinkel, Albertine J %A Oostra, Ben A %A Org, Elin %A Padmanabhan, Sandosh %A Palotie, Aarno %A Paré, Guillaume %A Pattie, Alison %A Penninx, Brenda W J H %A Poulter, Neil %A Pramstaller, Peter P %A Raitakari, Olli T %A Ren, Meixia %A Rice, Kenneth %A Ridker, Paul M %A Riese, Harriëtte %A Ripatti, Samuli %A Robino, Antonietta %A Rotter, Jerome I %A Rudan, Igor %A Saba, Yasaman %A Saint Pierre, Aude %A Sala, Cinzia F %A Sarin, Antti-Pekka %A Schmidt, Reinhold %A Scott, Rodney %A Seelen, Marc A %A Shields, Denis C %A Siscovick, David %A Sorice, Rossella %A Stanton, Alice %A Stott, David J %A Sundström, Johan %A Swertz, Morris %A Taylor, Kent D %A Thom, Simon %A Tzoulaki, Ioanna %A Tzourio, Christophe %A Uitterlinden, André G %A Völker, Uwe %A Vollenweider, Peter %A Wild, Sarah %A Willemsen, Gonneke %A Wright, Alan F %A Yao, Jie %A Thériault, Sébastien %A Conen, David %A Attia, John %A Sever, Peter %A Debette, Stephanie %A Mook-Kanamori, Dennis O %A Zeggini, Eleftheria %A Spector, Tim D %A van der Harst, Pim %A Palmer, Colin N A %A Vergnaud, Anne-Claire %A Loos, Ruth J F %A Polasek, Ozren %A Starr, John M %A Girotto, Giorgia %A Hayward, Caroline %A Kooner, Jaspal S %A Lindgren, Cecila M %A Vitart, Veronique %A Samani, Nilesh J %A Tuomilehto, Jaakko %A Gyllensten, Ulf %A Knekt, Paul %A Deary, Ian J %A Ciullo, Marina %A Elosua, Roberto %A Keavney, Bernard D %A Hicks, Andrew A %A Scott, Robert A %A Gasparini, Paolo %A Laan, Maris %A Liu, Yongmei %A Watkins, Hugh %A Hartman, Catharina A %A Salomaa, Veikko %A Toniolo, Daniela %A Perola, Markus %A Wilson, James F %A Schmidt, Helena %A Zhao, Jing Hua %A Lehtimäki, Terho %A van Duijn, Cornelia M %A Gudnason, Vilmundur %A Psaty, Bruce M %A Peters, Annette %A Rettig, Rainer %A James, Alan %A Jukema, J Wouter %A Strachan, David P %A Palmas, Walter %A Metspalu, Andres %A Ingelsson, Erik %A Boomsma, Dorret I %A Franco, Oscar H %A Bochud, Murielle %A Newton-Cheh, Christopher %A Munroe, Patricia B %A Elliott, Paul %A Chasman, Daniel I %A Chakravarti, Aravinda %A Knight, Joanne %A Morris, Andrew P %A Levy, Daniel %A Tobin, Martin D %A Snieder, Harold %A Caulfield, Mark J %A Ehret, Georg B %X

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.

%B Hypertension %8 2017 Jul 24 %G eng %R 10.1161/HYPERTENSIONAHA.117.09438 %0 Journal Article %J Nat Genet %D 2018 %T Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. %A Evangelou, Evangelos %A Warren, Helen R %A Mosen-Ansorena, David %A Mifsud, Borbala %A Pazoki, Raha %A Gao, He %A Ntritsos, Georgios %A Dimou, Niki %A Cabrera, Claudia P %A Karaman, Ibrahim %A Ng, Fu Liang %A Evangelou, Marina %A Witkowska, Katarzyna %A Tzanis, Evan %A Hellwege, Jacklyn N %A Giri, Ayush %A Velez Edwards, Digna R %A Sun, Yan V %A Cho, Kelly %A Gaziano, J Michael %A Wilson, Peter W F %A Tsao, Philip S %A Kovesdy, Csaba P %A Esko, Tõnu %A Mägi, Reedik %A Milani, Lili %A Almgren, Peter %A Boutin, Thibaud %A Debette, Stephanie %A Ding, Jun %A Giulianini, Franco %A Holliday, Elizabeth G %A Jackson, Anne U %A Li-Gao, Ruifang %A Lin, Wei-Yu %A Luan, Jian'an %A Mangino, Massimo %A Oldmeadow, Christopher %A Prins, Bram Peter %A Qian, Yong %A Sargurupremraj, Muralidharan %A Shah, Nabi %A Surendran, Praveen %A Thériault, Sébastien %A Verweij, Niek %A Willems, Sara M %A Zhao, Jing-Hua %A Amouyel, Philippe %A Connell, John %A de Mutsert, Renée %A Doney, Alex S F %A Farrall, Martin %A Menni, Cristina %A Morris, Andrew D %A Noordam, Raymond %A Paré, Guillaume %A Poulter, Neil R %A Shields, Denis C %A Stanton, Alice %A Thom, Simon %A Abecasis, Goncalo %A Amin, Najaf %A Arking, Dan E %A Ayers, Kristin L %A Barbieri, Caterina M %A Batini, Chiara %A Bis, Joshua C %A Blake, Tineka %A Bochud, Murielle %A Boehnke, Michael %A Boerwinkle, Eric %A Boomsma, Dorret I %A Bottinger, Erwin P %A Braund, Peter S %A Brumat, Marco %A Campbell, Archie %A Campbell, Harry %A Chakravarti, Aravinda %A Chambers, John C %A Chauhan, Ganesh %A Ciullo, Marina %A Cocca, Massimiliano %A Collins, Francis %A Cordell, Heather J %A Davies, Gail %A Borst, Martin H de %A Geus, Eco J de %A Deary, Ian J %A Deelen, Joris %A del Greco M, Fabiola %A Demirkale, Cumhur Yusuf %A Dörr, Marcus %A Ehret, Georg B %A Elosua, Roberto %A Enroth, Stefan %A Erzurumluoglu, A Mesut %A Ferreira, Teresa %A Frånberg, Mattias %A Franco, Oscar H %A Gandin, Ilaria %A Gasparini, Paolo %A Giedraitis, Vilmantas %A Gieger, Christian %A Girotto, Giorgia %A Goel, Anuj %A Gow, Alan J %A Gudnason, Vilmundur %A Guo, Xiuqing %A Gyllensten, Ulf %A Hamsten, Anders %A Harris, Tamara B %A Harris, Sarah E %A Hartman, Catharina A %A Havulinna, Aki S %A Hicks, Andrew A %A Hofer, Edith %A Hofman, Albert %A Hottenga, Jouke-Jan %A Huffman, Jennifer E %A Hwang, Shih-Jen %A Ingelsson, Erik %A James, Alan %A Jansen, Rick %A Jarvelin, Marjo-Riitta %A Joehanes, Roby %A Johansson, Asa %A Johnson, Andrew D %A Joshi, Peter K %A Jousilahti, Pekka %A Jukema, J Wouter %A Jula, Antti %A Kähönen, Mika %A Kathiresan, Sekar %A Keavney, Bernard D %A Khaw, Kay-Tee %A Knekt, Paul %A Knight, Joanne %A Kolcic, Ivana %A Kooner, Jaspal S %A Koskinen, Seppo %A Kristiansson, Kati %A Kutalik, Zoltán %A Laan, Maris %A Larson, Marty %A Launer, Lenore J %A Lehne, Benjamin %A Lehtimäki, Terho %A Liewald, David C M %A Lin, Li %A Lind, Lars %A Lindgren, Cecilia M %A Liu, Yongmei %A Loos, Ruth J F %A Lopez, Lorna M %A Lu, Yingchang %A Lyytikäinen, Leo-Pekka %A Mahajan, Anubha %A Mamasoula, Chrysovalanto %A Marrugat, Jaume %A Marten, Jonathan %A Milaneschi, Yuri %A Morgan, Anna %A Morris, Andrew P %A Morrison, Alanna C %A Munson, Peter J %A Nalls, Mike A %A Nandakumar, Priyanka %A Nelson, Christopher P %A Niiranen, Teemu %A Nolte, Ilja M %A Nutile, Teresa %A Oldehinkel, Albertine J %A Oostra, Ben A %A O'Reilly, Paul F %A Org, Elin %A Padmanabhan, Sandosh %A Palmas, Walter %A Palotie, Aarno %A Pattie, Alison %A Penninx, Brenda W J H %A Perola, Markus %A Peters, Annette %A Polasek, Ozren %A Pramstaller, Peter P %A Nguyen, Quang Tri %A Raitakari, Olli T %A Ren, Meixia %A Rettig, Rainer %A Rice, Kenneth %A Ridker, Paul M %A Ried, Janina S %A Riese, Harriëtte %A Ripatti, Samuli %A Robino, Antonietta %A Rose, Lynda M %A Rotter, Jerome I %A Rudan, Igor %A Ruggiero, Daniela %A Saba, Yasaman %A Sala, Cinzia F %A Salomaa, Veikko %A Samani, Nilesh J %A Sarin, Antti-Pekka %A Schmidt, Reinhold %A Schmidt, Helena %A Shrine, Nick %A Siscovick, David %A Smith, Albert V %A Snieder, Harold %A Sõber, Siim %A Sorice, Rossella %A Starr, John M %A Stott, David J %A Strachan, David P %A Strawbridge, Rona J %A Sundström, Johan %A Swertz, Morris A %A Taylor, Kent D %A Teumer, Alexander %A Tobin, Martin D %A Tomaszewski, Maciej %A Toniolo, Daniela %A Traglia, Michela %A Trompet, Stella %A Tuomilehto, Jaakko %A Tzourio, Christophe %A Uitterlinden, André G %A Vaez, Ahmad %A van der Most, Peter J %A van Duijn, Cornelia M %A Vergnaud, Anne-Claire %A Verwoert, Germaine C %A Vitart, Veronique %A Völker, Uwe %A Vollenweider, Peter %A Vuckovic, Dragana %A Watkins, Hugh %A Wild, Sarah H %A Willemsen, Gonneke %A Wilson, James F %A Wright, Alan F %A Yao, Jie %A Zemunik, Tatijana %A Zhang, Weihua %A Attia, John R %A Butterworth, Adam S %A Chasman, Daniel I %A Conen, David %A Cucca, Francesco %A Danesh, John %A Hayward, Caroline %A Howson, Joanna M M %A Laakso, Markku %A Lakatta, Edward G %A Langenberg, Claudia %A Melander, Olle %A Mook-Kanamori, Dennis O %A Palmer, Colin N A %A Risch, Lorenz %A Scott, Robert A %A Scott, Rodney J %A Sever, Peter %A Spector, Tim D %A van der Harst, Pim %A Wareham, Nicholas J %A Zeggini, Eleftheria %A Levy, Daniel %A Munroe, Patricia B %A Newton-Cheh, Christopher %A Brown, Morris J %A Metspalu, Andres %A Hung, Adriana M %A O'Donnell, Christopher J %A Edwards, Todd L %A Psaty, Bruce M %A Tzoulaki, Ioanna %A Barnes, Michael R %A Wain, Louise V %A Elliott, Paul %A Caulfield, Mark J %X

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

%B Nat Genet %V 50 %P 1412-1425 %8 2018 Oct %G eng %N 10 %R 10.1038/s41588-018-0205-x %0 Journal Article %J Nature %D 2020 %T Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Lin, Amy E %A Taub, Margaret A %A Aguet, Francois %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Boerwinkle, Eric %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Goncalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %X

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

%B Nature %V 586 %P 763-768 %8 2020 10 %G eng %N 7831 %R 10.1038/s41586-020-2819-2 %0 Journal Article %J Cell Genom %D 2021 %T Association of mitochondrial DNA copy number with cardiometabolic diseases. %A Liu, Xue %A Longchamps, Ryan J %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Kurniansyah, Nuzulul %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Cupples, L Adrienne %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Sofer, Tamar %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Correa, Adolfo %A Abecasis, Goncalo %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN ( = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN ( = 1.82 × 10) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity ( = 5.6 × 10), hypertension ( = 2.8 × 10), diabetes ( = 3.6 × 10), and hyperlipidemia ( = 6.3 × 10). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

%B Cell Genom %V 1 %8 2021 Oct 13 %G eng %N 1 %R 10.1016/j.xgen.2021.100006 %0 Journal Article %J Nat Commun %D 2021 %T Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. %A Natarajan, Pradeep %A Pampana, Akhil %A Graham, Sarah E %A Ruotsalainen, Sanni E %A Perry, James A %A de Vries, Paul S %A Broome, Jai G %A Pirruccello, James P %A Honigberg, Michael C %A Aragam, Krishna %A Wolford, Brooke %A Brody, Jennifer A %A Antonacci-Fulton, Lucinda %A Arden, Moscati %A Aslibekyan, Stella %A Assimes, Themistocles L %A Ballantyne, Christie M %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Do, Ron %A Doddapaneni, Harsha %A Emery, Leslie S %A Hung, Yi-Jen %A Irvin, Marguerite R %A Khan, Alyna T %A Lange, Leslie %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Metcalf, Ginger %A Montasser, May E %A Moon, Jee-Young %A Muzny, Donna %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peralta, Juan M %A Peyser, Patricia A %A Stilp, Adrienne M %A Tsai, Michael %A Wang, Fei Fei %A Weeks, Daniel E %A Yanek, Lisa R %A Wilson, James G %A Abecasis, Goncalo %A Arnett, Donna K %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Chang, Yi-Cheng %A Chen, Yii-der I %A Choi, Won Jung %A Correa, Adolfo %A Curran, Joanne E %A Daly, Mark J %A Dutcher, Susan K %A Ellinor, Patrick T %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard A %A He, Jiang %A Hveem, Kristian %A Jarvik, Gail P %A Kaplan, Robert C %A Kardia, Sharon L R %A Kenny, Eimear %A Kim, Ryan W %A Kooperberg, Charles %A Laurie, Cathy C %A Lee, Seonwook %A Lloyd-Jones, Don M %A Loos, Ruth J F %A Lubitz, Steven A %A Mathias, Rasika A %A Martinez, Karine A Viaud %A McGarvey, Stephen T %A Mitchell, Braxton D %A Nickerson, Deborah A %A North, Kari E %A Palotie, Aarno %A Park, Cheol Joo %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Seo, Daekwan %A Seo, Jeong-Sun %A Smith, Albert V %A Tracy, Russell P %A Vasan, Ramachandran S %A Kathiresan, Sekar %A Cupples, L Adrienne %A Rotter, Jerome I %A Morrison, Alanna C %A Rich, Stephen S %A Ripatti, Samuli %A Willer, Cristen %A Peloso, Gina M %X

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

%B Nat Commun %V 12 %P 2182 %8 2021 04 12 %G eng %N 1 %R 10.1038/s41467-021-22339-1 %0 Journal Article %J Nat Genet %D 2022 %T Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. %A Mahajan, Anubha %A Spracklen, Cassandra N %A Zhang, Weihua %A Ng, Maggie C Y %A Petty, Lauren E %A Kitajima, Hidetoshi %A Yu, Grace Z %A Rüeger, Sina %A Speidel, Leo %A Kim, Young Jin %A Horikoshi, Momoko %A Mercader, Josep M %A Taliun, Daniel %A Moon, Sanghoon %A Kwak, Soo-Heon %A Robertson, Neil R %A Rayner, Nigel W %A Loh, Marie %A Kim, Bong-Jo %A Chiou, Joshua %A Miguel-Escalada, Irene %A Della Briotta Parolo, Pietro %A Lin, Kuang %A Bragg, Fiona %A Preuss, Michael H %A Takeuchi, Fumihiko %A Nano, Jana %A Guo, Xiuqing %A Lamri, Amel %A Nakatochi, Masahiro %A Scott, Robert A %A Lee, Jung-Jin %A Huerta-Chagoya, Alicia %A Graff, Mariaelisa %A Chai, Jin-Fang %A Parra, Esteban J %A Yao, Jie %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Steinthorsdottir, Valgerdur %A Cook, James P %A Kals, Mart %A Grarup, Niels %A Schmidt, Ellen M %A Pan, Ian %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Ahmad, Meraj %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Lecoeur, Cécile %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Jensen, Richard A %A Tajuddin, Salman %A Kabagambe, Edmond K %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Flanagan, Jack %A Abaitua, Fernando %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Akiyama, Masato %A Anand, Sonia S %A Bertoni, Alain %A Bian, Zheng %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Brummett, Chad M %A Buchanan, Thomas A %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Fuchsberger, Christian %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Goodarzi, Mark O %A Gordon-Larsen, Penny %A Gorkin, David %A Gross, Myron %A Guo, Yu %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Marit E %A Jørgensen, Torben %A Kamatani, Yoichiro %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kohara, Katsuhiko %A Kriebel, Jennifer %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lyssenko, Valeriya %A Mamakou, Vasiliki %A Mani, K Radha %A Meitinger, Thomas %A Metspalu, Andres %A Morris, Andrew D %A Nadkarni, Girish N %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Nongmaithem, Suraj S %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Porneala, Bianca %A Prasad, Gauri %A Preissl, Sebastian %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Kathryn %A Sabanayagam, Charumathi %A Sander, Maike %A Sandow, Kevin %A Sattar, Naveed %A Schönherr, Sebastian %A Schurmann, Claudia %A Shahriar, Mohammad %A Shi, Jinxiu %A Shin, Dong Mun %A Shriner, Daniel %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Stilp, Adrienne M %A Strauch, Konstantin %A Suzuki, Ken %A Takahashi, Atsushi %A Taylor, Kent D %A Thorand, Barbara %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Torres, Jason M %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Vujkovic, Marijana %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Whitsel, Eric A %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamauchi, Toshimasa %A Yengo, Loic %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Hanis, Craig L %A Peyser, Patricia A %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Zeggini, Eleftheria %A Yokota, Mitsuhiro %A Rich, Stephen S %A Kooperberg, Charles %A Pankow, James S %A Engert, James C %A Chen, Yii-Der Ida %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Kardia, Sharon L R %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Groop, Leif %A Mook-Kanamori, Dennis O %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Bottinger, Erwin P %A Dehghan, Abbas %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Palmer, Colin N A %A Liu, Simin %A Abecasis, Goncalo %A Kooner, Jaspal S %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %A Florez, Jose C %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Mägi, Reedik %A Langenberg, Claudia %A Wareham, Nicholas J %A Maeda, Shiro %A Kadowaki, Takashi %A Lee, Juyoung %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Myers, Simon R %A Ferrer, Jorge %A Gaulton, Kyle J %A Meigs, James B %A Mohlke, Karen L %A Gloyn, Anna L %A Bowden, Donald W %A Below, Jennifer E %A Chambers, John C %A Sim, Xueling %A Boehnke, Michael %A Rotter, Jerome I %A McCarthy, Mark I %A Morris, Andrew P %K Diabetes Mellitus, Type 2 %K Ethnicity %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %X

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

%B Nat Genet %V 54 %P 560-572 %8 2022 May %G eng %N 5 %R 10.1038/s41588-022-01058-3 %0 Journal Article %J J Am Heart Assoc %D 2023 %T Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. %A Liu, Xue %A Sun, Xianbang %A Zhang, Yuankai %A Jiang, Wenqing %A Lai, Meng %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Haessler, Jeffrey %A Zheng, Yinan %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Qian, Yong %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Carson, April P %A Abecasis, Goncalo %A Dupuis, Josée %A Reiner, Alexander %A Kooperberg, Charles %A Hou, Lifang %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

%B J Am Heart Assoc %P e029090 %8 2023 Oct 07 %G eng %R 10.1161/JAHA.122.029090 %0 Journal Article %J medRxiv %D 2024 %T Association analysis of mitochondrial DNA heteroplasmic variants: methods and application. %A Sun, Xianbang %A Bulekova, Katia %A Yang, Jian %A Lai, Meng %A Pitsillides, Achilleas N %A Liu, Xue %A Zhang, Yuankai %A Guo, Xiuqing %A Yong, Qian %A Raffield, Laura M %A Rotter, Jerome I %A Rich, Stephen S %A Abecasis, Goncalo %A Carson, April P %A Vasan, Ramachandran S %A Bis, Joshua C %A Psaty, Bruce M %A Boerwinkle, Eric %A Fitzpatrick, Annette L %A Satizabal, Claudia L %A Arking, Dan E %A Ding, Jun %A Levy, Daniel %A Liu, Chunyu %X

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on bothpooled samples and within each ancestry group. Our results suggest that mtDNA-Enco ded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the and genes ( <0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations ( <0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.

%B medRxiv %8 2024 Jan 13 %G eng %R 10.1101/2024.01.12.24301233