The impact of low-frequency and rare variants on lipid levels.
Ida SurakkaMomoko HorikoshiReedik MägiAntti-Pekka SarinAnubha MahajanVasiliki LagouLetizia MarulloTeresa FerreiraBenjamin MiraglioSanna TimonenJohannes KettunenMatti PirinenJuha KarjalainenGudmar ThorleifssonSara HäggJouke-Jan HottengaAaron IsaacsClaes LadenvallMarian BeekmanTõnu EskoJanina S RiedChristopher P NelsonChristina WillenborgStefan GustafssonHarm-Jan WestraMatthew BladesAnton J M de CraenEco J C N de GeusJoris DeelenHarald GrallertAnders HamstenAki S HavulinnaChristian HengstenbergJeanine J Houwing-DuistermaatElina HyppönenLennart C KarssenTerho LehtimäkiValeriya LyssenkoPatrik K E MagnussonEvelin MihailovMartina Müller-NurasyidJohn-Patrick MpindiNancy L PedersenBrenda W J H PenninxMarkus PerolaTune H PersAnnette PetersJohan RungJohannes H SmitValgerdur SteinthorsdottirMartin D TobinNatalia TsernikovaElisabeth M van LeeuwenJorma S ViikariSara M WillemsGonneke WillemsenHeribert SchunkertJeanette ErdmannNilesh J SamaniJaakko A KaprioLars LindChristian GiegerAndres MetspaluP Eline SlagboomLeif GroopCornelia M van DuijnJohan G ErikssonAntti JulaVeikko SalomaaDorret I BoomsmaChristine PowerOlli T RaitakariErik IngelssonMarjo-Riitta JärvelinUnnur ThorsteinsdottirLude H FrankeElina IkonenOlli KallioniemiVilja PietiäinenCecilia M LindgrenKari StefanssonAarno PalotieMark I McCarthyAndrew P MorrisInga ProkopenkoSamuli Ripattinull nullPublished in: Nature genetics (2015)
Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.