03125nas a2200553 4500008004100000022001400041245011100055210006900166260000900235300001200244490000600256520150100262653002101763653001101784653003401795653001101829653000901840653001601849653003601865100003001901700002901931700002001960700002201980700002102002700002202023700002202045700002402067700001202091700002302103700001902126700002202145700001802167700001902185700001902204700002602223700002802249700002102277700002802298700002402326700002002350700002502370700002702395700002002422700001802442700002802460700002402488700002302512856003602535 2014 eng d a1932-620300aThe challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.0 achallenges of genomewide interaction studies lessons to learn fr c2014 ae1092900 v93 a
Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.
10aCholesterol, HDL10aFemale10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide1 avan Leeuwen, Elisabeth, M1 aSmouter, Françoise, A S1 aKam-Thong, Tony1 aKarbalai, Nazanin1 aSmith, Albert, V1 aHarris, Tamara, B1 aLauner, Lenore, J1 aSitlani, Colleen, M1 aLi, Guo1 aBrody, Jennifer, A1 aBis, Joshua, C1 aWhite, Charles, C1 aJaiswal, Alok1 aOostra, Ben, A1 aHofman, Albert1 aRivadeneira, Fernando1 aUitterlinden, André, G1 aBoerwinkle, Eric1 aBallantyne, Christie, M1 aGudnason, Vilmundur1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aJarvelin, Marjo-Riitta1 aRipatti, Samuli1 aIsaacs, Aaron1 aMüller-Myhsok, Bertram1 aKarssen, Lennart, C1 aDuijn, Cornelia, M uhttps://chs-nhlbi.org/node/660704013nas a2201093 4500008004100000022001400041245012400055210006900179260000900248300000900257490000600266520085300272653003801125653001601163653001901179653003201198653001101230653002301241653001601264100003001280700002401310700001801334700001801352700002801370700001801398700002701416700002001443700001801463700001801481700002801499700002501527700002201552700002101574700002001595700002101615700002001636700002001656700002001676700002101696700002301717700002001740700002101760700002701781700002601808700002401834700001901858700002601877700001901903700001901922700002101941700002401962700002001986700002502006700001602031700001902047700002202066700002302088700001902111700002202130700002402152700002302176700001902199700002202218700002602240700002002266700001502286700002102301700002102322700002202343700001902365700002202384700001602406700002002422700002102442700002002463700002302483700002502506700002002531700002202551700001902573700001502592700002302607700002402630700002802654700002202682700002702704700002502731700002002756700002302776700002002799700002302819710004102842856003602883 2015 eng d a2041-172300aGenome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels.0 aGenome of The Netherlands populationspecific imputations identif c2015 a60650 v63 aVariants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of The Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.
10aATP-Binding Cassette Transporters10aCholesterol10aGene Frequency10aGenetic Association Studies10aHumans10aMutation, Missense10aNetherlands1 avan Leeuwen, Elisabeth, M1 aKarssen, Lennart, C1 aDeelen, Joris1 aIsaacs, Aaron1 aMedina-Gómez, Carolina1 aMbarek, Hamdi1 aKanterakis, Alexandros1 aTrompet, Stella1 aPostmus, Iris1 aVerweij, Niek1 avan Enckevort, David, J1 aHuffman, Jennifer, E1 aWhite, Charles, C1 aFeitosa, Mary, F1 aBartz, Traci, M1 aManichaikul, Ani1 aJoshi, Peter, K1 aPeloso, Gina, M1 aDeelen, Patrick1 avan Dijk, Freerk1 aWillemsen, Gonneke1 ade Geus, Eco, J1 aMilaneschi, Yuri1 aPenninx, Brenda, W J H1 aFrancioli, Laurent, C1 aMenelaou, Androniki1 aPulit, Sara, L1 aRivadeneira, Fernando1 aHofman, Albert1 aOostra, Ben, A1 aFranco, Oscar, H1 aLeach, Irene, Mateo1 aBeekman, Marian1 ade Craen, Anton, J M1 aUh, Hae-Won1 aTrochet, Holly1 aHocking, Lynne, J1 aPorteous, David, J1 aSattar, Naveed1 aPackard, Chris, J1 aBuckley, Brendan, M1 aBrody, Jennifer, A1 aBis, Joshua, C1 aRotter, Jerome, I1 aMychaleckyj, Josyf, C1 aCampbell, Harry1 aDuan, Qing1 aLange, Leslie, A1 aWilson, James, F1 aHayward, Caroline1 aPolasek, Ozren1 aVitart, Veronique1 aRudan, Igor1 aWright, Alan, F1 aRich, Stephen, S1 aPsaty, Bruce, M1 aBorecki, Ingrid, B1 aKearney, Patricia, M1 aStott, David, J1 aCupples, Adrienne1 aJukema, Wouter1 aHarst, Pim1 aSijbrands, Eric, J1 aHottenga, Jouke-Jan1 aUitterlinden, André, G1 aSwertz, Morris, A1 avan Ommen, Gert-Jan, B1 ade Bakker, Paul, I W1 aSlagboom, Eline1 aBoomsma, Dorret, I1 aWijmenga, Cisca1 aDuijn, Cornelia, M1 aGenome of the Netherlands Consortium uhttps://chs-nhlbi.org/node/6682