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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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- Jakubowska, A, et al.
(författare)
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Association of PHB 1630 C andgt; T and MTHFR 677 C andgt; T polymorphisms with breast and ovarian cancer risk in BRCA1/2 mutation carriers: results from a multicenter study
- 2012
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Ingår i: British Journal of Cancer. - : Cancer Research UK / Nature Publishing Group. - 0007-0920 .- 1532-1827. ; 106:12, s. 2016-2024
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The variable penetrance of breast cancer in BRCA1/2 mutation carriers suggests that other genetic or environmental factors modify breast cancer risk. Two genes of special interest are prohibitin (PHB) and methylene-tetrahydrofolate reductase (MTHFR), both of which are important either directly or indirectly in maintaining genomic integrity. less thanbrgreater than less thanbrgreater thanMETHODS: To evaluate the potential role of genetic variants within PHB and MTHFR in breast and ovarian cancer risk, 4102 BRCA1 and 2093 BRCA2 mutation carriers, and 6211 BRCA1 and 2902 BRCA2 carriers from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) were genotyped for the PHB 1630 Candgt;T (rs6917) polymorphism and the MTHFR 677 Candgt;T (rs1801133) polymorphism, respectively. less thanbrgreater than less thanbrgreater thanRESULTS: There was no evidence of association between the PHB 1630 Candgt;T and MTHFR 677 Candgt;T polymorphisms with either disease for BRCA1 or BRCA2 mutation carriers when breast and ovarian cancer associations were evaluated separately. Analysis that evaluated associations for breast and ovarian cancer simultaneously showed some evidence that BRCA1 mutation carriers who had the rare homozygote genotype (TT) of the PHB 1630 Candgt;T polymorphism were at increased risk of both breast and ovarian cancer (HR 1.50, 95% CI 1.10-2.04 and HR 2.16, 95% CI 1.24-3.76, respectively). However, there was no evidence of association under a multiplicative model for the effect of each minor allele. less thanbrgreater than less thanbrgreater thanCONCLUSION: The PHB 1630TT genotype may modify breast and ovarian cancer risks in BRCA1 mutation carriers. This association need to be evaluated in larger series of BRCA1 mutation carriers.
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- Antoniou, A. C., et al.
(författare)
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Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers : Implications for risk prediction
- 2010
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Ingår i: Cancer Research. - : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 70:23, s. 9742-9754
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Tidskriftsartikel (refereegranskat)abstract
- The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR = 1.10, 95% CI: 1.03-1.18, P = 0.006 and HR = 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P = 7 × 10-11 - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42% to 50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences might be sufficient to influence the clinical management of mutation carriers.
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- Asselbergs, Folkert W., et al.
(författare)
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Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
- 2012
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 91:5, s. 823-838
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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