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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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| 2. |
- Haan, Elis, et al.
(författare)
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Associations between attention-deficit hyperactivity disorder genetic liability and ICD-10 medical conditions in adults : utilizing electronic health records in a Phenome-Wide Association Study
- 2024
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Ingår i: Psychological Medicine. - : Cambridge University Press. - 0033-2917 .- 1469-8978.
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Attention-deficit hyperactivity disorder (ADHD) is often comorbid with other medical conditions in adult patients. However, ADHD is extremely underdiagnosed in adults and little is known about the medical comorbidities in undiagnosed adult individuals with high ADHD liability. In this study we investigated associations between ADHD genetic liability and electronic health record (EHR)-based ICD-10 diagnoses across all diagnostic categories, in individuals without ADHD diagnosis history.METHODS: We used data from the Estonian Biobank cohort (N = 111 261) and generated polygenic risk scores (PRS) for ADHD (PRSADHD) based on the ADHD genome-wide association study. We performed a phenome-wide association study (PheWAS) to test for associations between standardized PRSADHD and 1515 EHR-based ICD-10 diagnoses in the full and sex-stratified sample. We compared the observed significant ICD-10 associations to associations with (1) ADHD diagnosis and (2) questionnaire-based high ADHD risk analyses.RESULTS: After Bonferroni correction (p = 3.3 × 10-5) we identified 80 medical conditions associated with PRSADHD. The strongest evidence was seen with chronic obstructive pulmonary disease (OR 1.15, CI 1.11-1.18), obesity (OR 1.13, CI 1.11-1.15), and type 2 diabetes (OR 1.11, CI 1.09-1.14). Sex-stratified analysis generally showed similar associations in males and females. Out of all identified associations, 40% and 78% were also observed using ADHD diagnosis or questionnaire-based ADHD, respectively, as the predictor.CONCLUSIONS: Overall our findings indicate that ADHD genetic liability is associated with an increased risk of a substantial number of medical conditions in undiagnosed individuals. These results highlight the need for timely detection and improved management of ADHD symptoms in adults.
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