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- 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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- Botvinik-Nezer, Rotem, et al.
(författare)
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Variability in the analysis of a single neuroimaging dataset by many teams
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 582, s. 84-88
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Tidskriftsartikel (refereegranskat)abstract
- Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.
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- Jansweijer, Joeri A., et al.
(författare)
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Heritability in genetic heart disease : the role of genetic background
- 2019
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Ingår i: Open heart. - : BMJ Publishing Group Ltd. - 2053-3624. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mutations in genes encoding ion channels or sarcomeric proteins are an important cause of hereditary cardiac disease. However, the severity of the resultant disease varies considerably even among those with an identical mutation. Such clinical variation is often thought to be explained largely by differences in genetic background or ‘modifier genes’. We aimed to test the prediction that identical genetic backgrounds result in largely similar clinical expression of a cardiac disease causing mutation, by studying the clinical expression of mutations causing cardiac disease in monozygotic twins.Methods: We compared first available clinical information on 46 monozygotic twin pairs and 59 control pairs that had either a hereditary cardiomyopathy or channelopathy.Results: Despite limited power of this study, we found significant heritability for corrected QT interval (QTc) in long QT syndrome (LQTS). We could not detect significant heritability for structural traits, but found a significant environmental effect on thickness of the interventricular septum in hypertrophic cardiomyopathy.Conclusions: Our study confirms previously found robust heritability for electrical traits like QTc in LQTS, and adds information on low or lacking heritability for structural traits in heritable cardiomyopathies. This may steer the search for genetic modifiers in heritable cardiac disease.
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