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- Mullins, N., et al.
(author)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Journal article (peer-reviewed)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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- Jiang, X., et al.
(author)
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Shared heritability and functional enrichment across six solid cancers
- 2019
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Journal article (peer-reviewed)abstract
- Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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- Saevarsdottir, S., et al.
(author)
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Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset
- 2022
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In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 81:8
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Journal article (peer-reviewed)abstract
- Objectives To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. Methods We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and similar to 1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). Results We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1x10(-9)), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3x10(-160)). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6x10(-11)). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10(-9)-10(-27)) and decreased plasma levels of interferon-alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. Conclusion Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.
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- Shungin, Dmitry, et al.
(author)
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New genetic loci link adipose and insulin biology to body fat distribution.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
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Journal article (peer-reviewed)abstract
- Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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- Rothman, Nathaniel, et al.
(author)
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A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci
- 2010
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 978-984
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Journal article (peer-reviewed)abstract
- We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.
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- Sampson, Joshua N., et al.
(author)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Journal article (peer-reviewed)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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