%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 Am J Hum Genet %D 2014 %T Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. %A Lange, Leslie A %A Hu, Youna %A Zhang, He %A Xue, Chenyi %A Schmidt, Ellen M %A Tang, Zheng-Zheng %A Bizon, Chris %A Lange, Ethan M %A Smith, Joshua D %A Turner, Emily H %A Jun, Goo %A Kang, Hyun Min %A Peloso, Gina %A Auer, Paul %A Li, Kuo-Ping %A Flannick, Jason %A Zhang, Ji %A Fuchsberger, Christian %A Gaulton, Kyle %A Lindgren, Cecilia %A Locke, Adam %A Manning, Alisa %A Sim, Xueling %A Rivas, Manuel A %A Holmen, Oddgeir L %A Gottesman, Omri %A Lu, Yingchang %A Ruderfer, Douglas %A Stahl, Eli A %A Duan, Qing %A Li, Yun %A Durda, Peter %A Jiao, Shuo %A Isaacs, Aaron %A Hofman, Albert %A Bis, Joshua C %A Correa, Adolfo %A Griswold, Michael E %A Jakobsdottir, Johanna %A Smith, Albert V %A Schreiner, Pamela J %A Feitosa, Mary F %A Zhang, Qunyuan %A Huffman, Jennifer E %A Crosby, Jacy %A Wassel, Christina L %A Do, Ron %A Franceschini, Nora %A Martin, Lisa W %A Robinson, Jennifer G %A Assimes, Themistocles L %A Crosslin, David R %A Rosenthal, Elisabeth A %A Tsai, Michael %A Rieder, Mark J %A Farlow, Deborah N %A Folsom, Aaron R %A Lumley, Thomas %A Fox, Ervin R %A Carlson, Christopher S %A Peters, Ulrike %A Jackson, Rebecca D %A van Duijn, Cornelia M %A Uitterlinden, André G %A Levy, Daniel %A Rotter, Jerome I %A Taylor, Herman A %A Gudnason, Vilmundur %A Siscovick, David S %A Fornage, Myriam %A Borecki, Ingrid B %A Hayward, Caroline %A Rudan, Igor %A Chen, Y Eugene %A Bottinger, Erwin P %A Loos, Ruth J F %A Sætrom, Pål %A Hveem, Kristian %A Boehnke, Michael %A Groop, Leif %A McCarthy, Mark %A Meitinger, Thomas %A Ballantyne, Christie M %A Gabriel, Stacey B %A O'Donnell, Christopher J %A Post, Wendy S %A North, Kari E %A Reiner, Alexander P %A Boerwinkle, Eric %A Psaty, Bruce M %A Altshuler, David %A Kathiresan, Sekar %A Lin, Dan-Yu %A Jarvik, Gail P %A Cupples, L Adrienne %A Kooperberg, Charles %A Wilson, James G %A Nickerson, Deborah A %A Abecasis, Goncalo R %A Rich, Stephen S %A Tracy, Russell P %A Willer, Cristen J %K Adult %K Aged %K Apolipoproteins E %K Cholesterol, LDL %K Cohort Studies %K Dyslipidemias %K Exome %K Female %K Follow-Up Studies %K Gene Frequency %K Genetic Code %K Genome-Wide Association Study %K Genotype %K Humans %K Lipase %K Male %K Middle Aged %K Phenotype %K Polymorphism, Single Nucleotide %K Proprotein Convertase 9 %K Proprotein Convertases %K Receptors, LDL %K Sequence Analysis, DNA %K Serine Endopeptidases %X

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

%B Am J Hum Genet %V 94 %P 233-45 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507775?dopt=Abstract %R 10.1016/j.ajhg.2014.01.010 %0 Journal Article %J Am J Hum Genet %D 2016 %T Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits. %A Chami, Nathalie %A Chen, Ming-Huei %A Slater, Andrew J %A Eicher, John D %A Evangelou, Evangelos %A Tajuddin, Salman M %A Love-Gregory, Latisha %A Kacprowski, Tim %A Schick, Ursula M %A Nomura, Akihiro %A Giri, Ayush %A Lessard, Samuel %A Brody, Jennifer A %A Schurmann, Claudia %A Pankratz, Nathan %A Yanek, Lisa R %A Manichaikul, Ani %A Pazoki, Raha %A Mihailov, Evelin %A Hill, W David %A Raffield, Laura M %A Burt, Amber %A Bartz, Traci M %A Becker, Diane M %A Becker, Lewis C %A Boerwinkle, Eric %A Bork-Jensen, Jette %A Bottinger, Erwin P %A O'Donoghue, Michelle L %A Crosslin, David R %A de Denus, Simon %A Dubé, Marie-Pierre %A Elliott, Paul %A Engström, Gunnar %A Evans, Michele K %A Floyd, James S %A Fornage, Myriam %A Gao, He %A Greinacher, Andreas %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hernesniemi, Jussi %A Highland, Heather M %A Hirschhorn, Joel N %A Hofman, Albert %A Irvin, Marguerite R %A Kähönen, Mika %A Lange, Ethan %A Launer, Lenore J %A Lehtimäki, Terho %A Li, Jin %A Liewald, David C M %A Linneberg, Allan %A Liu, Yongmei %A Lu, Yingchang %A Lyytikäinen, Leo-Pekka %A Mägi, Reedik %A Mathias, Rasika A %A Melander, Olle %A Metspalu, Andres %A Mononen, Nina %A Nalls, Mike A %A Nickerson, Deborah A %A Nikus, Kjell %A O'Donnell, Chris J %A Orho-Melander, Marju %A Pedersen, Oluf %A Petersmann, Astrid %A Polfus, Linda %A Psaty, Bruce M %A Raitakari, Olli T %A Raitoharju, Emma %A Richard, Melissa %A Rice, Kenneth M %A Rivadeneira, Fernando %A Rotter, Jerome I %A Schmidt, Frank %A Smith, Albert Vernon %A Starr, John M %A Taylor, Kent D %A Teumer, Alexander %A Thuesen, Betina H %A Torstenson, Eric S %A Tracy, Russell P %A Tzoulaki, Ioanna %A Zakai, Neil A %A Vacchi-Suzzi, Caterina %A van Duijn, Cornelia M %A van Rooij, Frank J A %A Cushman, Mary %A Deary, Ian J %A Velez Edwards, Digna R %A Vergnaud, Anne-Claire %A Wallentin, Lars %A Waterworth, Dawn M %A White, Harvey D %A Wilson, James G %A Zonderman, Alan B %A Kathiresan, Sekar %A Grarup, Niels %A Esko, Tõnu %A Loos, Ruth J F %A Lange, Leslie A %A Faraday, Nauder %A Abumrad, Nada A %A Edwards, Todd L %A Ganesh, Santhi K %A Auer, Paul L %A Johnson, Andrew D %A Reiner, Alexander P %A Lettre, Guillaume %X

Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.

%B Am J Hum Genet %V 99 %P 8-21 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27346685?dopt=Abstract %R 10.1016/j.ajhg.2016.05.007 %0 Journal Article %J Am J Hum Genet %D 2016 %T Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases. %A Tajuddin, Salman M %A Schick, Ursula M %A Eicher, John D %A Chami, Nathalie %A Giri, Ayush %A Brody, Jennifer A %A Hill, W David %A Kacprowski, Tim %A Li, Jin %A Lyytikäinen, Leo-Pekka %A Manichaikul, Ani %A Mihailov, Evelin %A O'Donoghue, Michelle L %A Pankratz, Nathan %A Pazoki, Raha %A Polfus, Linda M %A Smith, Albert Vernon %A Schurmann, Claudia %A Vacchi-Suzzi, Caterina %A Waterworth, Dawn M %A Evangelou, Evangelos %A Yanek, Lisa R %A Burt, Amber %A Chen, Ming-Huei %A van Rooij, Frank J A %A Floyd, James S %A Greinacher, Andreas %A Harris, Tamara B %A Highland, Heather M %A Lange, Leslie A %A Liu, Yongmei %A Mägi, Reedik %A Nalls, Mike A %A Mathias, Rasika A %A Nickerson, Deborah A %A Nikus, Kjell %A Starr, John M %A Tardif, Jean-Claude %A Tzoulaki, Ioanna %A Velez Edwards, Digna R %A Wallentin, Lars %A Bartz, Traci M %A Becker, Lewis C %A Denny, Joshua C %A Raffield, Laura M %A Rioux, John D %A Friedrich, Nele %A Fornage, Myriam %A Gao, He %A Hirschhorn, Joel N %A Liewald, David C M %A Rich, Stephen S %A Uitterlinden, Andre %A Bastarache, Lisa %A Becker, Diane M %A Boerwinkle, Eric %A de Denus, Simon %A Bottinger, Erwin P %A Hayward, Caroline %A Hofman, Albert %A Homuth, Georg %A Lange, Ethan %A Launer, Lenore J %A Lehtimäki, Terho %A Lu, Yingchang %A Metspalu, Andres %A O'Donnell, Chris J %A Quarells, Rakale C %A Richard, Melissa %A Torstenson, Eric S %A Taylor, Kent D %A Vergnaud, Anne-Claire %A Zonderman, Alan B %A Crosslin, David R %A Deary, Ian J %A Dörr, Marcus %A Elliott, Paul %A Evans, Michele K %A Gudnason, Vilmundur %A Kähönen, Mika %A Psaty, Bruce M %A Rotter, Jerome I %A Slater, Andrew J %A Dehghan, Abbas %A White, Harvey D %A Ganesh, Santhi K %A Loos, Ruth J F %A Esko, Tõnu %A Faraday, Nauder %A Wilson, James G %A Cushman, Mary %A Johnson, Andrew D %A Edwards, Todd L %A Zakai, Neil A %A Lettre, Guillaume %A Reiner, Alex P %A Auer, Paul L %X

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.

%B Am J Hum Genet %V 99 %P 22-39 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27346689?dopt=Abstract %R 10.1016/j.ajhg.2016.05.003 %0 Journal Article %J Am J Hum Genet %D 2016 %T Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals. %A Eicher, John D %A Chami, Nathalie %A Kacprowski, Tim %A Nomura, Akihiro %A Chen, Ming-Huei %A Yanek, Lisa R %A Tajuddin, Salman M %A Schick, Ursula M %A Slater, Andrew J %A Pankratz, Nathan %A Polfus, Linda %A Schurmann, Claudia %A Giri, Ayush %A Brody, Jennifer A %A Lange, Leslie A %A Manichaikul, Ani %A Hill, W David %A Pazoki, Raha %A Elliot, Paul %A Evangelou, Evangelos %A Tzoulaki, Ioanna %A Gao, He %A Vergnaud, Anne-Claire %A Mathias, Rasika A %A Becker, Diane M %A Becker, Lewis C %A Burt, Amber %A Crosslin, David R %A Lyytikäinen, Leo-Pekka %A Nikus, Kjell %A Hernesniemi, Jussi %A Kähönen, Mika %A Raitoharju, Emma %A Mononen, Nina %A Raitakari, Olli T %A Lehtimäki, Terho %A Cushman, Mary %A Zakai, Neil A %A Nickerson, Deborah A %A Raffield, Laura M %A Quarells, Rakale %A Willer, Cristen J %A Peloso, Gina M %A Abecasis, Goncalo R %A Liu, Dajiang J %A Deloukas, Panos %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Fornage, Myriam %A Richard, Melissa %A Tardif, Jean-Claude %A Rioux, John D %A Dubé, Marie-Pierre %A de Denus, Simon %A Lu, Yingchang %A Bottinger, Erwin P %A Loos, Ruth J F %A Smith, Albert Vernon %A Harris, Tamara B %A Launer, Lenore J %A Gudnason, Vilmundur %A Velez Edwards, Digna R %A Torstenson, Eric S %A Liu, Yongmei %A Tracy, Russell P %A Rotter, Jerome I %A Rich, Stephen S %A Highland, Heather M %A Boerwinkle, Eric %A Li, Jin %A Lange, Ethan %A Wilson, James G %A Mihailov, Evelin %A Mägi, Reedik %A Hirschhorn, Joel %A Metspalu, Andres %A Esko, Tõnu %A Vacchi-Suzzi, Caterina %A Nalls, Mike A %A Zonderman, Alan B %A Evans, Michele K %A Engström, Gunnar %A Orho-Melander, Marju %A Melander, Olle %A O'Donoghue, Michelle L %A Waterworth, Dawn M %A Wallentin, Lars %A White, Harvey D %A Floyd, James S %A Bartz, Traci M %A Rice, Kenneth M %A Psaty, Bruce M %A Starr, J M %A Liewald, David C M %A Hayward, Caroline %A Deary, Ian J %A Greinacher, Andreas %A Völker, Uwe %A Thiele, Thomas %A Völzke, Henry %A van Rooij, Frank J A %A Uitterlinden, André G %A Franco, Oscar H %A Dehghan, Abbas %A Edwards, Todd L %A Ganesh, Santhi K %A Kathiresan, Sekar %A Faraday, Nauder %A Auer, Paul L %A Reiner, Alex P %A Lettre, Guillaume %A Johnson, Andrew D %X

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

%B Am J Hum Genet %V 99 %P 40-55 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27346686?dopt=Abstract %R 10.1016/j.ajhg.2016.05.005 %0 Journal Article %J BioData Min %D 2017 %T Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. %A Holzinger, Emily R %A Verma, Shefali S %A Moore, Carrie B %A Hall, Molly %A De, Rishika %A Gilbert-Diamond, Diane %A Lanktree, Matthew B %A Pankratz, Nathan %A Amuzu, Antoinette %A Burt, Amber %A Dale, Caroline %A Dudek, Scott %A Furlong, Clement E %A Gaunt, Tom R %A Kim, Daniel Seung %A Riess, Helene %A Sivapalaratnam, Suthesh %A Tragante, Vinicius %A van Iperen, Erik P A %A Brautbar, Ariel %A Carrell, David S %A Crosslin, David R %A Jarvik, Gail P %A Kuivaniemi, Helena %A Kullo, Iftikhar J %A Larson, Eric B %A Rasmussen-Torvik, Laura J %A Tromp, Gerard %A Baumert, Jens %A Cruickshanks, Karen J %A Farrall, Martin %A Hingorani, Aroon D %A Hovingh, G K %A Kleber, Marcus E %A Klein, Barbara E %A Klein, Ronald %A Koenig, Wolfgang %A Lange, Leslie A %A Mӓrz, Winfried %A North, Kari E %A Charlotte Onland-Moret, N %A Reiner, Alex P %A Talmud, Philippa J %A van der Schouw, Yvonne T %A Wilson, James G %A Kivimaki, Mika %A Kumari, Meena %A Moore, Jason H %A Drenos, Fotios %A Asselbergs, Folkert W %A Keating, Brendan J %A Ritchie, Marylyn D %X

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).

RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n = 12,853 to n = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.

CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.

%B BioData Min %V 10 %P 25 %8 2017 %G eng %R 10.1186/s13040-017-0145-5