| 2. |
- Scott, Robert A., et al.
(author)
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Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways
- 2012
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 44:9, s. 991-1005
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Journal article (peer-reviewed)abstract
- Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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| 3. |
- Coviello, Andrea D, et al.
(author)
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A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple Loci implicated in sex steroid hormone regulation.
- 2012
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In: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404 .- 1553-7390. ; 8:7
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Journal article (peer-reviewed)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.
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