| 1. |
- Coviello, Andrea D, et al.
(författare)
-
A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple Loci implicated in sex steroid hormone regulation.
- 2012
-
Ingår i: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404 .- 1553-7390. ; 8:7
-
Tidskriftsartikel (refereegranskat)abstract
- Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p=1.8×10(-106)), PRMT6 (rs17496332, 1p13.3, p=1.4×10(-11)), GCKR (rs780093, 2p23.3, p=2.2×10(-16)), ZBTB10 (rs440837, 8q21.13, p=3.4×10(-09)), JMJD1C (rs7910927, 10q21.3, p=6.1×10(-35)), SLCO1B1 (rs4149056, 12p12.1, p=1.9×10(-08)), NR2F2 (rs8023580, 15q26.2, p=8.3×10(-12)), ZNF652 (rs2411984, 17q21.32, p=3.5×10(-14)), TDGF3 (rs1573036, Xq22.3, p=4.1×10(-14)), LHCGR (rs10454142, 2p16.3, p=1.3×10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p=2.7×10(-08)), and UGT2B15 (rs293428, 4q13.2, p=5.5×10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p=2.5×10(-08), women p=0.66, heterogeneity p=0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
|
|
| 2. |
- Nikpay, Majid, et al.
(författare)
-
A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease
- 2015
-
Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:10, s. 1121-1121
-
Tidskriftsartikel (refereegranskat)abstract
- Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of similar to 185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
|
|
| 3. |
- Wild, Philipp S., et al.
(författare)
-
A Genome-Wide Association Study Identifies LIPA as a Susceptibility Gene for Coronary Artery Disease
- 2011
-
Ingår i: Circulation: Cardiovascular Genetics. - : American Heart Association/Lippincott, Williams & Wilkins. - 1942-325X .- 1942-3268. ; 4:4, s. 203-403
-
Tidskriftsartikel (refereegranskat)abstract
- Background-eQTL analyses are important to improve the understanding of genetic association results. We performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD). Methods and Results-In a genome-wide association analysis of 2078 CAD cases and 2953 control subjects, we identified 950 single-nucleotide polymorphisms (SNPs) that were associated with CAD at P<10(-3). Subsequent in silico and wet-laboratory replication stages and a final meta-analysis of 21 428 CAD cases and 38 361 control subjects revealed a novel association signal at chromosome 10q23.31 within the LIPA (lysosomal acid lipase A) gene (P=3.7 x 10(-8); odds ratio, 1.1; 95% confidence interval, 1.07 to 1.14). The association of this locus with global gene expression was assessed by genome-wide expression analyses in the monocyte transcriptome of 1494 individuals. The results showed a strong association of this locus with expression of the LIPA transcript (P=1.3 x 10(-96)). An assessment of LIPA SNPs and transcript with cardiovascular phenotypes revealed an association of LIPA transcript levels with impaired endothelial function (P=4.4 x 10(-3)). Conclusions-The use of data on genetic variants and the addition of data on global monocytic gene expression led to the identification of the novel functional CAD susceptibility locus LIPA, located on chromosome 10q23.31. The respective eSNPs associated with CAD strongly affect LIPA gene expression level, which was related to endothelial dysfunction, a precursor of CAD. (Circ Cardiovasc Genet. 2011;4:403-412.)
|
|
| 4. |
- Speliotes, Elizabeth K, et al.
(författare)
-
Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.
- 2011
-
Ingår i: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 7:3
-
Tidskriftsartikel (refereegranskat)abstract
- Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n=880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.
|
|
