BACKGROUND: An increased level of Lp(a) lipoprotein has been identified as a risk factor for coronary artery disease that is highly heritable. The genetic determinants of the Lp(a) lipoprotein level and their relevance for the risk of coronary disease are incompletely understood. METHODS: We used a novel gene chip containing 48,742 single-nucleotide polymorphisms (SNPs) in 2100 candidate genes to test for associations in 3145 case subjects with coronary disease and 3352 control subjects. Replication was tested in three independent populations involving 4846 additional case subjects with coronary disease and 4594 control subjects. RESULTS: Three chromosomal regions (6q26-27, 9p21, and 1p13) were strongly associated with the risk of coronary disease. The LPA locus on 6q26-27 encoding Lp(a) lipoprotein had the strongest association. We identified a common variant (rs10455872) at the LPA locus with an odds ratio for coronary disease of 1.70 (95% confidence interval [CI], 1.49 to 1.95) and another independent variant (rs3798220) with an odds ratio of 1.92 (95% CI, 1.48 to 2.49). Both variants were strongly associated with an increased level of Lp(a) lipoprotein, a reduced copy number in LPA (which determines the number of kringle IV-type 2 repeats), and a small Lp(a) lipoprotein size. Replication studies confirmed the effects of both variants on the Lp(a) lipoprotein level and the risk of coronary disease. A meta-analysis showed that with a genotype score involving both LPA SNPs, the odds ratios for coronary disease were 1.51 (95% CI, 1.38 to 1.66) for one variant and 2.57 (95% CI, 1.80 to 3.67) for two or more variants. After adjustment for the Lp(a) lipoprotein level, the association between the LPA genotype score and the risk of coronary disease was abolished. CONCLUSIONS: We identified two LPA variants that were strongly associated with both an increased level of Lp(a) lipoprotein and an increased risk of coronary disease. Our findings provide support for a causal role of Lp(a) lipoprotein in coronary disease
Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.
We screened DNA sequence variants on an exome-focused genotyping array in >300,000 participants with replication in >280,000 participants and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice revealed lipid changes consistent with the human data. We utilized mapped variants to address four clinically relevant questions and found the following: (1) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease; (2) outside of the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (3) only some mechanisms of lowering LDL-C seemed to increase risk for type 2 diabetes; and (4) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (e.g., TM6SF2, PNPLA3) tracked with higher liver fat, higher risk for type 2 diabetes, and lower risk for coronary artery disease whereas TG-lowering alleles involved in peripheral lipolysis (e.g., LPL, ANGPTL4) had no effect on liver fat but lowered risks for both type 2 diabetes and coronary artery disease.
Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knock-down experiments (ABCA1, TRIB1) and clinical trial results (CCR2, CCR5), with consistent regulation. Finally we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including (gene symbols) EGF, IL16, PAPPA, SPON1, F3, ADM, CASP8, CHI3L1, CXCL16, GDF15, and MMP12. Taken together these findings demonstrate the utility of largescale mapping the genetics of the proteome, and provide a resource for future precision studies of circulating proteins in human health.
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