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- Feitosa, Mary F., et al.
(author)
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Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries
- 2018
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In: PLOS ONE. - : Public library science. - 1932-6203. ; 13:6
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Journal article (peer-reviewed)abstract
- Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in approximate to 131 K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P <1.0 x 10(-5)). In Stage 2, these SNVs were tested for independent external replication in individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10(-8)). For African ancestry samples, we detected 18 potentially novel BP loci (P< 5.0 x 10(-8)) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2 have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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| 2. |
- Haljas, Kadri, et al.
(author)
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Bivariate genome-wide association study of depressive symptoms with type 2 diabetes and quantitative glycemic traits
- 2018
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In: Psychosomatic Medicine. - 0033-3174. ; 80:3, s. 242-251
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Journal article (peer-reviewed)abstract
- Objective: Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. Methods: We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 10−8). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. Results: The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes). Conclusions: We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.
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