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Hindy, G.* ; Dornbos, P.* ; Chaffin, M.D.* ; Liu, D.J.* ; Wang, M.* ; Selvaraj, M.S.* ; Zhang, D.* ; Park, J.* ; Aguilar-Salinas, C.A.* ; Antonacci-Fulton, L.L.* ; Ardissino, D.* ; Arnett, D.K.* ; Aslibekyan, S.* ; Atzmon, G.* ; Ballantyne, C.M.* ; Barajas-Olmos, F.* ; Barzilai, N.* ; Becker, L.C.* ; Bielak, L.F.* ; Bis, J.C.* ; Blangero, J.* ; Boerwinkle, E.* ; Bonnycastle, L.L.* ; Bottinger, E.B.* ; Bowden, D.W.* ; Bown, M.J.* ; Brody, J.A.* ; Broome, J.G.* ; Burtt, N.P.* ; Cade, B.E.* ; Centeno-Cruz, F.* ; Chan, E.* ; Chang, Y.C.* ; Chen, Y.I.* ; Cheng, C.Y.* ; Choi, W.J.* ; Chowdhury, R.* ; Contreras-Cubas, C.* ; Córdova, E.J.* ; Correa, A.* ; Cupples, L.A.* ; Curran, J.E.* ; Danesh, J.* ; de Vries, P.S.* ; DeFronzo, R.A.* ; Doddapaneni, H.V.* ; Duggirala, R.* ; Dutcher, S.K.* ; Ellinor, P.T.* ; Emery, L.S.* ; Florez, J.C.* ; Fornage, M.* ; Freedman, B.I.* ; Fuster, V.* ; Garay-Sevilla, M.E.* ; García-Ortiz, H.* ; Germer, S.* ; Gibbs, R.A.* ; Gieger, C. ; Glaser, B.* ; Gonzalez, C.* ; Gonzalez-Villalpando, M.E.* ; Graff, M.* ; Graham, S.E.* ; Grarup, N.* ; Groop, L.C.* ; Guo, X.* ; Gupta, N.* ; Han, S.* ; Hanis, C.L.* ; Hansen, T.* ; He, J.* ; Heard-Costa, N.L.* ; Hung, Y.J.* ; Hwang, M.Y.* ; Irvin, M.R.* ; Islas-Andrade, S.* ; Jarvik, G.P.* ; Kang, H.M.* ; Kardia, S.L.R.* ; Kelly, T.N.* ; Kenny, E.E.* ; Khan, A.T.* ; Kim, B.J.* ; Kim, R.W.* ; Kim, Y.J.* ; Koistinen, H.A.* ; Kooperberg, C.* ; Kuusisto, J.* ; Kwak, S.H.* ; Laakso, M.* ; Lange, L.A.* ; Lee, J.* ; Lee, S.* ; Lehman, D.M.* ; Lemaitre, R.N.* ; Linneberg, A.* ; Liu, J.* ; Loos, R.J.F.* ; Lubitz, S.A.* ; Lyssenko, V.* ; Ma, R.C.W.* ; Martin, L.W.* ; Martínez-Hernández, A.* ; Mathias, R.A.* ; McGarvey, S.T.* ; McPherson, R.* ; Meigs, J.B.* ; Meitinger, T.* ; Melander, O.* ; Mendoza-Caamal, E.* ; Metcalf, G.A.* ; Mi, X.* ; Mohlke, K.L.* ; Montasser, M.E.* ; Moon, J.Y.* ; Moreno-Macias, H.* ; Morrison, A.C.* ; Muzny, D.M.* ; Nelson, S.C.* ; Nilsson, P.M.* ; O'Connell, J.R.* ; Orho-Melander, M.* ; Orozco, L.* ; Palmer, C.N.A.* ; Palmer, N.D.* ; Park, C.J.* ; Park, K.S.* ; Pedersen, O.* ; Peralta, J.M.* ; Peyser, P.A.* ; Post, W.S.* ; Preuss, M.* ; Psaty, B.M.* ; Qi, Q.* ; Rao, D.C.* ; Redline, S.* ; Reiner, A.P.* ; Revilla-Monsalve, C.* ; Rich, S.S.* ; Samani, N.* ; Schunkert, H.* ; Schurmann, C.* ; Seo, D.* ; Seo, J.S.* ; Sim, X.* ; Sladek, R.* ; Small, K.S.* ; So, W.Y.* ; Stilp, A.M.* ; Tai, E.S.* ; Tam, C.H.T.* ; Taylor, K.D.* ; Teo, Y.Y.* ; Thameem, F.* ; Tomlinson, B.* ; Tsai, M.Y.* ; Tuomi, T.* ; Tuomilehto, J.* ; Tusié-Luna, T.* ; Udler, M.S.* ; van Dam, R.M.* ; Vasan, R.S.* ; Viaud Martinez, K.A.* ; Wang, F.F.* ; Wang, X.* ; Watkins, H.* ; Weeks, D.E.* ; Wilson, J.G.* ; Witte, D.R.* ; Wong, T.Y.* ; Yanek, L.R.* ; Kathiresan, S.* ; Rader, D.J.* ; Rotter, J.I.* ; Boehnke, M.* ; McCarthy, M.I.* ; Willer, C.J.* ; Natarajan, P.* ; Flannick, J.A.* ; Khera, A.V.* ; Peloso, G.M.*

Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.

Am. J. Hum. Genet. 109, 81-96 (2022)
DOI
Free by publisher: Publ. Version/Full Text online available 08/2022
Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Association ; Cholesterol ; Exome Sequencing ; Gene-based Association ; Lipid; Sinusoidal Endothelial-cells; Of-function Mutations; Sequence Variants; Risk; Apoc3; Identification; Triglycerides; Perilipin; Angptl3; Binding
ISSN (print) / ISBN 0002-9297
e-ISSN 1537-6605
Quellenangaben Volume: 109, Issue: 1, Pages: 81-96 Article Number: , Supplement: ,
Publisher Elsevier
Publishing Place New York, NY
Reviewing status Peer reviewed
Grants National Heart, Lung, and Blood Institute (NHLBI)
Swedish Research Council