| 1. |
- Mishra, A., et al.
(författare)
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Stroke genetics informs drug discovery and risk prediction across ancestries
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611, s. 115-123
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Tidskriftsartikel (refereegranskat)abstract
- Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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| 2. |
- Abbott, Benjamin W., et al.
(författare)
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Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire : an expert assessment
- 2016
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%-85% of permafrost carbon release can still be avoided if human emissions are actively reduced.
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| 3. |
- Surendran, Praveen, et al.
(författare)
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Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals
- 2020
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 52:12, s. 1314-1332
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Tidskriftsartikel (refereegranskat)abstract
- Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency <= 0.01) variant BP associations (P < 5 x 10(-8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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| 4. |
- Shungin, Dmitry, et al.
(författare)
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Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions
- 2017
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Ingår i: PLOS Genetics. - : Public Library Science. - 1553-7390 .- 1553-7404. ; 13:6
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Tidskriftsartikel (refereegranskat)abstract
- Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (GxE) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (P-v), GxE interaction effects (with smoking and physical activity), and marginal genetic effects (P-m). Correlations between P-v and P-m were stronger for SNPs with established marginal effects (Spearman's rho = 0.401 for triglycerides, and rho = 0.236 for BMI) compared to all SNPs. When P-v and P-m were compared for all pruned SNPs, only BMI was statistically significant (Spearman's rho = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the P-v distribution (P-binomial < 0.05). SNPs from the top 1% of the P-m distribution for BMI had more significant P-v values (Pmann-Whitney = 1.46x10(-5)), and the odds ratio of SNPs with nominally significant (< 0.05) P-m and P-v was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant GxE interaction P-values (Pint < 0.05) were enriched with nominally significant P-v values (P-binomial = 8.63x10(-9) and 8.52x10(-7) for SNP x smoking and SNP x physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for GxE, and variance-based prioritization can be used to identify them.
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