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Altshuler, David

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Altshuler, David
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    Analysis of protein-coding genetic variation in 60,706 humans
    (2016) Lek, Monkol; Karczewski, Konrad; Minikel, Eric; Samocha, Kaitlin E.; Banks, Eric; Fennell, Timothy; O'Donnell-Luria, Anne H; Ware, James S; Hill, Andrew J; Cummings, Beryl; Tukiainen, Taru; Birnbaum, Daniel P; Kosmicki, Jack; Duncan, Laramie E; Estrada, Karol; Zhao, Fengmei; Zou, James; Pierce-Hoffman, Emma; Berghout, Joanne; Cooper, David N; Deflaux, Nicole; DePristo, Mark; Do, Ron; Flannick, Jason; Fromer, Menachem; Gauthier, Laura; Goldstein, Jackie; Gupta, Namrata; Howrigan, Daniel; Kiezun, Adam; Kurki, Mitja; Moonshine, Ami Levy; Natarajan, Pradeep; Orozco, Lorena; Peloso, Gina M; Poplin, Ryan; Rivas, Manuel A; Ruano-Rubio, Valentin; Rose, Samuel A; Ruderfer, Douglas M; Shakir, Khalid; Stenson, Peter D; Stevens, Christine; Thomas, Brett P; Tiao, Grace; Tusie-Luna, Maria T; Weisburd, Ben; Won, Hong-Hee; Yu, Dongmei; Altshuler, David; Ardissino, Diego; Boehnke, Michael; Danesh, John; Donnelly, Stacey; Elosua, Roberto; Florez, Jose; Gabriel, Stacey B; Getz, Gad; Glatt, Stephen J; Hultman, Christina M; Kathiresan, Sekar; Laakso, Markku; McCarroll, Steven; McCarthy, Mark I; McGovern, Dermot; McPherson, Ruth; Neale, Benjamin; Palotie, Aarno; Purcell, Shaun M; Saleheen, Danish; Scharf, Jeremiah; Sklar, Pamela; Sullivan, Patrick F; Tuomilehto, Jaakko; Tsuang, Ming T; Watkins, Hugh C; Wilson, James G; Daly, Mark; MacArthur, Daniel
    Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.
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    Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes
    (Nature Publishing Group UK, 2018) Gusarova, Viktoria; O’Dushlaine, Colm; Teslovich, Tanya M.; Benotti, Peter N.; Mirshahi, Tooraj; Gottesman, Omri; Van Hout, Cristopher V.; Murray, Michael F.; Mahajan, Anubha; Nielsen, Jonas B.; Fritsche, Lars; Wulff, Anders Berg; Gudbjartsson, Daniel F.; Sjögren, Marketa; Emdin, Connor A.; Scott, Robert A.; Lee, Wen-Jane; Small, Aeron; Kwee, Lydia C.; Dwivedi, Om Prakash; Prasad, Rashmi B.; Bruse, Shannon; Lopez, Alexander E.; Penn, John; Marcketta, Anthony; Leader, Joseph B.; Still, Christopher D.; Kirchner, H. Lester; Mirshahi, Uyenlinh L.; Wardeh, Amr H.; Hartle, Cassandra M.; Habegger, Lukas; Fetterolf, Samantha N.; Tusie-Luna, Teresa; Morris, Andrew P.; Holm, Hilma; Steinthorsdottir, Valgerdur; Sulem, Patrick; Thorsteinsdottir, Unnur; Rotter, Jerome I.; Chuang, Lee-Ming; Damrauer, Scott; Birtwell, David; Brummett, Chad M.; Khera, Amit; Natarajan, Pradeep; Orho-Melander, Marju; Flannick, Jason; Lotta, Luca A.; Willer, Cristen J.; Holmen, Oddgeir L.; Ritchie, Marylyn D.; Ledbetter, David H.; Murphy, Andrew J.; Borecki, Ingrid B.; Reid, Jeffrey G.; Overton, John D.; Hansson, Ola; Groop, Leif; Shah, Svati H.; Kraus, William E.; Rader, Daniel J.; Chen, Yii-Der I.; Hveem, Kristian; Wareham, Nicholas J.; Kathiresan, Sekar; Melander, Olle; Stefansson, Kari; Nordestgaard, Børge G.; Tybjærg-Hansen, Anne; Abecasis, Goncalo R.; Altshuler, David; Florez, Jose; Boehnke, Michael; McCarthy, Mark I.; Yancopoulos, George D.; Carey, David J.; Shuldiner, Alan R.; Baras, Aris; Dewey, Frederick E.; Gromada, Jesper
    Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85–0.92, p = 6.3 × 10−10), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49–0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D.
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    Common variants associated with plasma triglycerides and risk for coronary artery disease
    (2013) Do, Ron; Willer, Cristen J.; Schmidt, Ellen M.; Sengupta, Sebanti; Gao, Chi; Peloso, Gina M; Gustafsson, Stefan; Kanoni, Stavroula; Ganna, Andrea; Chen, Jin; Buchkovich, Martin L.; Mora, Samia; Beckmann, Jacques S.; Bragg-Gresham, Jennifer L.; Chang, Hsing-Yi; Demirkan, Ayşe; Den Hertog, Heleen M.; Donnelly, Louise A.; Ehret, Georg B.; Esko, Tõnu; Feitosa, Mary F.; Ferreira, Teresa; Fischer, Krista; Fontanillas, Pierre; Fraser, Ross M.; Freitag, Daniel F.; Gurdasani, Deepti; Heikkilä, Kauko; Hyppönen, Elina; Isaacs, Aaron; Jackson, Anne U.; Johansson, Åsa; Johnson, Toby; Kaakinen, Marika; Kettunen, Johannes; Kleber, Marcus E.; Li, Xiaohui; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Magnusson, Patrik K.E.; Mangino, Massimo; Mihailov, Evelin; Montasser, May E.; Müller-Nurasyid, Martina; Nolte, Ilja M.; O'Connell, Jeffrey R.; Palmer, Cameron D.; Perola, Markus; Petersen, Ann-Kristin; Sanna, Serena; Saxena, Richa; Service, Susan K.; Shah, Sonia; Shungin, Dmitry; Sidore, Carlo; Song, Ci; Strawbridge, Rona J.; Surakka, Ida; Tanaka, Toshiko; Teslovich, Tanya M.; Thorleifsson, Gudmar; Van den Herik, Evita G.; Voight, Benjamin F.; Volcik, Kelly A.; Waite, Lindsay L.; Wong, Andrew; Wu, Ying; Zhang, Weihua; Absher, Devin; Asiki, Gershim; Barroso, Inês; Been, Latonya F.; Bolton, Jennifer L.; Bonnycastle, Lori L; Brambilla, Paolo; Burnett, Mary S.; Cesana, Giancarlo; Dimitriou, Maria; Doney, Alex S.F.; Döring, Angela; Elliott, Paul; Epstein, Stephen E.; Eyjolfsson, Gudmundur Ingi; Gigante, Bruna; Goodarzi, Mark O.; Grallert, Harald; Gravito, Martha L.; Groves, Christopher J.; Hallmans, Göran; Hartikainen, Anna-Liisa; Hayward, Caroline; Hernandez, Dena; Hicks, Andrew A.; Holm, Hilma; Hung, Yi-Jen; Illig, Thomas; Jones, Michelle R.; Kaleebu, Pontiano; Kastelein, John J.P.; Khaw, Kay-Tee; Kim, Eric; Klopp, Norman; Komulainen, Pirjo; Kumari, Meena; Langenberg, Claudia; Lehtimäki, Terho; Lin, Shih-Yi; Lindström, Jaana; Loos, Ruth J.F.; Mach, François; McArdle, Wendy L; Meisinger, Christa; Mitchell, Braxton D.; Müller, Gabrielle; Nagaraja, Ramaiah; Narisu, Narisu; Nieminen, Tuomo V.M.; Nsubuga, Rebecca N.; Olafsson, Isleifur; Ong, Ken K.; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Rader, Daniel J.; Reilly, Muredach P.; Ridker, Paul; Rivadeneira, Fernando; Rudan, Igor; Ruokonen, Aimo; Samani, Nilesh; Scharnagl, Hubert; Seeley, Janet; Silander, Kaisa; Stančáková, Alena; Stirrups, Kathleen; Swift, Amy J.; Tiret, Laurence; Uitterlinden, Andre G.; van Pelt, L. Joost; Vedantam, Sailaja; Wainwright, Nicholas; Wijmenga, Cisca; Wild, Sarah H.; Willemsen, Gonneke; Wilsgaard, Tom; Wilson, James F.; Young, Elizabeth H.; Zhao, Jing Hua; Adair, Linda S.; Arveiler, Dominique; Assimes, Themistocles L.; Bandinelli, Stefania; Bennett, Franklyn; Bochud, Murielle; Boehm, Bernhard O.; Boomsma, Dorret I.; Borecki, Ingrid B.; Bornstein, Stefan R.; Bovet, Pascal; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chambers, John C.; Chen, Yii-Der Ida; Collins, Francis S.; Cooper, Richard S.; Danesh, John; Dedoussis, George; de Faire, Ulf; Feranil, Alan B.; Ferrières, Jean; Ferrucci, Luigi; Freimer, Nelson B.; Gieger, Christian; Groop, Leif C.; Gudnason, Vilmundur; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hingorani, Aroon; Hirschhorn, Joel N.; Hofman, Albert; Hovingh, G. Kees; Hsiung, Chao Agnes; Humphries, Steve E.; Hunt, Steven C.; Hveem, Kristian; Iribarren, Carlos; Järvelin, Marjo-Riitta; Jula, Antti; Kähönen, Mika; Kaprio, Jaakko; Kesäniemi, Antero; Kivimaki, Mika; Kooner, Jaspal S.; Koudstaal, Peter J.; Krauss, Ronald M.; Kuh, Diana; Kuusisto, Johanna; Kyvik, Kirsten O.; Laakso, Markku; Lakka, Timo A.; Lind, Lars; Lindgren, Cecilia M.; Martin, Nicholas G.; März, Winfried; McCarthy, Mark I.; McKenzie, Colin A.; Meneton, Pierre; Metspalu, Andres; Moilanen, Leena; Morris, Andrew D.; Munroe, Patricia B.; Njølstad, Inger; Pedersen, Nancy L.; Power, Chris; Pramstaller, Peter P.; Price, Jackie F.; Psaty, Bruce M.; Quertermous, Thomas; Rauramaa, Rainer; Saleheen, Danish; Salomaa, Veikko; Sanghera, Dharambir K.; Saramies, Jouko; Schwarz, Peter E.H.; Sheu, Wayne H-H; Shuldiner, Alan R.; Siegbahn, Agneta; Spector, Tim D.; Stefansson, Kari; Strachan, David P.; Tayo, Bamidele O.; Tremoli, Elena; Tuomilehto, Jaakko; Uusitupa, Matti; van Duijn, Cornelia M.; Vollenweider, Peter; Wallentin, Lars; Wareham, Nicholas J.; Whitfield, John B.; Wolffenbuttel, Bruce H.R.; Altshuler, David; Ordovas, Jose M.; Boerwinkle, Eric; Palmer, Colin N.A.; Thorsteinsdottir, Unnur; Chasman, Daniel; Rotter, Jerome I.; Franks, Paul W.; Ripatti, Samuli; Cupples, L. Adrienne; Sandhu, Manjinder S.; Rich, Stephen S.; Boehnke, Michael; Deloukas, Panos; Mohlke, Karen L.; Ingelsson, Erik; Abecasis, Goncalo R.; Daly, Mark; Neale, Benjamin; Kathiresan, Sekar
    Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
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    Analysis of 6,515 exomes reveals a recent origin of most human protein-coding variants
    (2012) Fu, Wenqing; O'Connor, Timothy D.; Jun, Goo; Kang, Hyun Min; Abecasis, Goncalo; Leal, Suzanne M.; Gabriel, Stacey; Altshuler, David; Shendure, Jay; Nickerson, Deborah A.; Bamshad, Michael J.; GO, Broad; GO, Seattle; Akey, Joshua M.
    Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history1,2 and will help facilitate the development of new approaches for disease gene discovery3. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth4-6, notable for an excess of rare genetic variants, qualitatively suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European (n=4,298) and African (n=2,217) American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that ~73% of all protein-coding SNVs and ~86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs compared to other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, illustrate the profound effect recent human history has had on the burden of deleterious SNVs segregating in contemporary populations, and provides important practical information that can be used to prioritize variants in disease gene discovery.
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    Multiple rare alleles at LDLR and APOA5 confer risk for early-onset myocardial infarction
    (2014) Do, Ron; Stitziel, Nathan O.; Won, Hong-Hee; Jørgensen, Anders Berg; Duga, Stefano; Merlini, Pier Angelica; Kiezun, Adam; Farrall, Martin; Goel, Anuj; Zuk, Or; Guella, Illaria; Asselta, Rosanna; Lange, Leslie A.; Peloso, Gina M; Auer, Paul L.; Girelli, Domenico; Martinelli, Nicola; Farlow, Deborah N.; DePristo, Mark A.; Roberts, Robert; Stewart, Alexander F.R.; Saleheen, Danish; Danesh, John; Epstein, Stephen E.; Sivapalaratnam, Suthesh; Hovingh, G. Kees; Kastelein, John J.; Samani, Nilesh J.; Schunkert, Heribert; Erdmann, Jeanette; Shah, Svati H.; Kraus, William E.; Davies, Robert; Nikpay, Majid; Johansen, Christopher T.; Wang, Jian; Hegele, Robert A.; Hechter, Eliana; Marz, Winfried; Kleber, Marcus E.; Huang, Jie; Johnson, Andrew D.; Li, Mingyao; Burke, Greg L.; Gross, Myron; Liu, Yongmei; Assimes, Themistocles L.; Heiss, Gerardo; Lange, Ethan M.; Folsom, Aaron R.; Taylor, Herman A.; Olivieri, Oliviero; Hamsten, Anders; Clarke, Robert; Reilly, Dermot F.; Yin, Wu; Rivas, Manuel A.; Donnelly, Peter; Rossouw, Jacques E.; Psaty, Bruce M.; Herrington, David M.; Wilson, James G.; Rich, Stephen S.; Bamshad, Michael J.; Tracy, Russell P.; Cupples, L. Adrienne; Rader, Daniel J.; Reilly, Muredach P.; Spertus, John A.; Cresci, Sharon; Hartiala, Jaana; Tang, W.H. Wilson; Hazen, Stanley L.; Allayee, Hooman; Reiner, Alex P.; Carlson, Christopher S.; Kooperberg, Charles; Jackson, Rebecca D.; Boerwinkle, Eric; Lander, Eric S.; Schwartz, Stephen M.; Siscovick, David S.; McPherson, Ruth; Tybjaerg-Hansen, Anne; Abecasis, Goncalo R.; Watkins, Hugh; Nickerson, Deborah A.; Ardissino, Diego; Sunyaev, Shamil; O’Donnell, Christopher J.; Altshuler, David; Gabriel, Stacey; Kathiresan, Sekar
    Summary Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance1,2. When MI occurs early in life, the role of inheritance is substantially greater1. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families3–8 whereas common variants at more than 45 loci have been associated with MI risk in the population9–15. Here, we evaluate the contribution of rare mutations to MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes where rare coding-sequence mutations were more frequent in cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare, damaging mutations (3.1% of cases versus 1.3% of controls) were at 2.4-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). This sequence-based estimate of the proportion of early MI cases due to LDLR mutations is remarkably similar to an estimate made more than 40 years ago using total cholesterol16. At apolipoprotein A-V (APOA5), carriers of rare nonsynonymous mutations (1.4% of cases versus 0.6% of controls) were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase15,17 and apolipoprotein C318,19. When combined, these observations suggest that, beyond LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
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    Genome-wide meta-analysis in alopecia areata resolves HLA associations and reveals two new susceptibility loci
    (2015) Betz, Regina C.; Petukhova, Lynn; Ripke, Stephan; Huang, Hailiang; Menelaou, Androniki; Redler, Silke; Becker, Tim; Heilmann, Stefanie; Yamany, Tarek; Duvic, Madeliene; Hordinsky, Maria; Norris, David; Price, Vera H.; Mackay-Wiggan, Julian; de Jong, Annemieke; DeStefano, Gina M.; Moebus, Susanne; Böhm, Markus; Blume-Peytavi, Ulrike; Wolff, Hans; Lutz, Gerhard; Kruse, Roland; Bian, Li; Amos, Christopher I.; Lee, Annette; Gregersen, Peter K.; Blaumeiser, Bettina; Altshuler, David; Clynes, Raphael; de Bakker, Paul I. W.; Nöthen, Markus M.; Daly, Mark; Christiano, Angela M.
    Alopecia areata (AA) is a prevalent autoimmune disease with ten known susceptibility loci. Here we perform the first meta-analysis in AA by combining data from two genome-wide association studies (GWAS), and replication with supplemented ImmunoChip data for a total of 3,253 cases and 7,543 controls. The strongest region of association is the MHC, where we fine-map 4 independent effects, all implicating HLA-DR as a key etiologic driver. Outside the MHC, we identify two novel loci that exceed statistical significance, containing ACOXL/BCL2L11(BIM) (2q13); GARP (LRRC32) (11q13.5), as well as a third nominally significant region SH2B3(LNK)/ATXN2 (12q24.12). Candidate susceptibility gene expression analysis in these regions demonstrates expression in relevant immune cells and the hair follicle. We integrate our results with data from seven other autoimmune diseases and provide insight into the alignment of AA within these disorders. Our findings uncover new molecular pathways disrupted in AA, including autophagy/apoptosis, TGFß/Tregs and JAK kinase signaling, and support the causal role of aberrant immune processes in AA.
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    Prospective functional classification of all possible missense variants in PPARG
    (2016) Majithia, Amit R.; Tsuda, Ben; Agostini, Maura; Gnanapradeepan, Keerthana; Rice, Robert; Peloso, Gina; Patel, Kashyap A.; Zhang, Xiaolan; Broekema, Marjoleine F.; Patterson, Nick; Duby, Marc; Sharpe, Ted; Kalkhoven, Eric; Rosen, Evan; Barroso, Inês; Ellard, Sian; Kathiresan, Sekar; O’Rahilly, Stephen; Chatterjee, Krishna; Florez, Jose; Mikkelsen, Tarjei; Savage, David B.; Altshuler, David
    Abstract Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. While approximately one in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning (http://miter.broadinstitute.org). When applied to 55 novel missense variants identified in population-based and clinical sequencing, the classifier annotated six as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.
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    Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population
    (Public Library of Science, 2014) 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; Lindgren, Cecilia M.; Hirschhorn, Joel N.; Metspalu, Andres; Freimer, Nelson B.; Zeller, Tanja; Jalkanen, Sirpa; Koskinen, Seppo; Raitakari, Olli; Durbin, Richard; MacArthur, Daniel; Salomaa, Veikko; Ripatti, Samuli; Daly, Mark; Palotie, Aarno
    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.
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    The Power of Gene-Based Rare Variant Methods to Detect Disease-Associated Variation and Test Hypotheses About Complex Disease
    (Public Library of Science, 2015) Moutsianas, Loukas; Agarwala, Vineeta; Fuchsberger, Christian; Flannick, Jason; Rivas, Manuel A.; Gaulton, Kyle J.; Albers, Patrick K.; McVean, Gil; Boehnke, Michael; Altshuler, David; McCarthy, Mark I.
    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.
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    Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus
    (Public Library of Science, 2015) 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; Morris, Andrew P.; Altshuler, David; Meigs, James; Boehnke, Michael; McCarthy, Mark I.; Lindgren, Cecilia M.; Gloyn, Anna L.
    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.