Hindy G., Dornbos P., Chaffin MD., Liu DJ., Wang M., Selvaraj MS., Zhang D., Park J., Aguilar-Salinas CA., Antonacci-Fulton L., Ardissino D., Arnett DK., Aslibekyan S., Atzmon G., Ballantyne CM., Barajas-Olmos F., Barzilai N., Becker LC., Bielak LF., Bis JC., Blangero J., Boerwinkle E., Bonnycastle LL., Bottinger E., Bowden DW., Bown MJ., Brody JA., Broome JG., Burtt NP., Cade BE., Centeno-Cruz F., Chan E., Chang Y-C., Chen Y-DI., Cheng C-Y., Choi WJ., Chowdhury R., Contreras-Cubas C., Córdova EJ., Correa A., Cupples LA., Curran JE., Danesh J., de Vries PS., DeFronzo RA., Doddapaneni H., Duggirala R., Dutcher SK., Ellinor PT., Emery LS., Florez JC., Fornage M., Freedman BI., Fuster V., Garay-Sevilla ME., García-Ortiz H., Germer S., Gibbs RA., Gieger C., Glaser B., Gonzalez C., Gonzalez-Villalpando ME., Graff M., Graham SE., Grarup N., Groop LC., Guo X., Gupta N., Han S., Hanis CL., Hansen T., He J., Heard-Costa NL., Hung Y-J., Hwang MY., Irvin MR., Islas-Andrade S., Jarvik GP., Kang HM., Kardia SLR., Kelly T., Kenny EE., Khan AT., Kim B-J., Kim RW., Kim YJ., Koistinen HA., Kooperberg C., Kuusisto J., Kwak SH., Laakso M., Lange LA., Lee J., Lee J., Lee S., Lehman DM., Lemaitre RN., Linneberg A., Liu J., Loos RJF., Lubitz SA., Lyssenko V., Ma RCW., Martin LW., Martínez-Hernández A., Mathias RA., McGarvey ST., McPherson R., Meigs JB., Meitinger T., Melander O., Mendoza-Caamal E., Metcalf GA., Mi X., Mohlke KL., Montasser ME., Moon J-Y., Moreno-Macías H., Morrison AC., Muzny DM., Nelson SC., Nilsson PM., O'Connell JR., Orho-Melander M., Orozco L., Palmer CNA., Palmer ND., Park CJ., Park KS., Pedersen O., Peralta JM., Peyser PA., Post WS., Preuss M., Psaty BM., Qi Q., Rao DC., Redline S., Reiner AP., Revilla-Monsalve C., Rich SS., Samani N., Schunkert H., Schurmann C., Seo D., Seo J-S., Sim X., Sladek R., Small KS., So WY., Stilp AM., Tai ES., Tam CHT., Taylor KD., Teo YY., Thameem F., Tomlinson B., Tsai MY., Tuomi T., Tuomilehto J., Tusié-Luna T., Udler MS., van Dam RM., Vasan RS., Viaud Martinez KA., Wang FF., Wang X., Watkins H., Weeks DE., Wilson JG., Witte DR., Wong T-Y., Yanek LR., AMP-T2D-GENES, Myocardial Infarction Genetics Consortium None., NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium None., NHLBI TOPMed Lipids Working Group None., Kathiresan S., Rader DJ., Rotter JI., Boehnke M., McCarthy MI., Willer CJ., Natarajan P., Flannick JA., Khera AV., Peloso GM.

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.

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

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