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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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| 6. |
- Gandin, V, et al.
(författare)
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nanoCAGE reveals 5' UTR features that define specific modes of translation of functionally related MTOR-sensitive mRNAs
- 2016
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Ingår i: Genome research. - : Cold Spring Harbor Laboratory. - 1549-5469 .- 1088-9051. ; 26:5, s. 636-648
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Tidskriftsartikel (refereegranskat)abstract
- The diversity of MTOR-regulated mRNA translation remains unresolved. Whereas ribosome-profiling suggested that MTOR almost exclusively stimulates translation of the TOP (terminal oligopyrimidine motif) and TOP-like mRNAs, polysome-profiling indicated that MTOR also modulates translation of mRNAs without the 5′ TOP motif (non-TOP mRNAs). We demonstrate that in ribosome-profiling studies, detection of MTOR-dependent changes in non-TOP mRNA translation was obscured by low sensitivity and methodology biases. Transcription start site profiling using nano-cap analysis of gene expression (nanoCAGE) revealed that not only do many MTOR-sensitive mRNAs lack the 5′ TOP motif but that 5′ UTR features distinguish two functionally and translationally distinct subsets of MTOR-sensitive mRNAs: (1) mRNAs with short 5′ UTRs enriched for mitochondrial functions, which require EIF4E but are less EIF4A1-sensitive; and (2) long 5′ UTR mRNAs encoding proliferation- and survival-promoting proteins, which are both EIF4E- and EIF4A1-sensitive. Selective inhibition of translation of mRNAs harboring long 5′ UTRs via EIF4A1 suppression leads to sustained expression of proteins involved in respiration but concomitant loss of those protecting mitochondrial structural integrity, resulting in apoptosis. Conversely, simultaneous suppression of translation of both long and short 5′ UTR mRNAs by MTOR inhibitors results in metabolic dormancy and a predominantly cytostatic effect. Thus, 5′ UTR features define different modes of MTOR-sensitive translation of functionally distinct subsets of mRNAs, which may explain the diverse impact of MTOR and EIF4A inhibitors on neoplastic cells.
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