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- 2019
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Journal article (peer-reviewed)
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- Mahajan, Anubha, et al.
(author)
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
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Journal article (peer-reviewed)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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- Antoniou, Antonis C., et al.
(author)
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Common alleles at 6q25.1 and 1p11.2 are associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers
- 2011
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 20:16, s. 3304-3321
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Journal article (peer-reviewed)abstract
- Two single nucleotide polymorphisms (SNPs) at 6q25.1, near the ESR1 gene, have been implicated in the susceptibility to breast cancer for Asian (rs2046210) and European women (rs9397435). A genome-wide association study in Europeans identified two further breast cancer susceptibility variants: rs11249433 at 1p11.2 and rs999737 in RAD51L1 at 14q24.1. Although previously identified breast cancer susceptibility variants have been shown to be associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers, the involvement of these SNPs to breast cancer susceptibility in mutation carriers is currently unknown. To address this, we genotyped these SNPs in BRCA1 and BRCA2 mutation carriers from 42 studies from the Consortium of Investigators of Modifiers of BRCA1/2. In the analysis of 14 123 BRCA1 and 8053 BRCA2 mutation carriers of European ancestry, the 6q25.1 SNPs (r(2) = 0.14) were independently associated with the risk of breast cancer for BRCA1 mutation carriers [ hazard ratio (HR) = 1.17, 95% confidence interval (CI): 1.11-1.23, P-trend = 4.5 x 10(-9) for rs2046210; HR = 1.28, 95% CI: 1.18-1.40, P-trend = 1.3 x 10(-8) for rs9397435], but only rs9397435 was associated with the risk for BRCA2 carriers (HR = 1.14, 95% CI: 1.01-1.28, P-trend = 0.031). SNP rs11249433 (1p11.2) was associated with the risk of breast cancer for BRCA2 mutation carriers (HR = 1.09, 95% CI: 1.02-1.17, P-trend = 0.015), but was not associated with breast cancer risk for BRCA1 mutation carriers (HR = 0.97, 95% CI: 0.92-1.02, P-trend = 0.20). SNP rs999737 (RAD51L1) was not associated with breast cancer risk for either BRCA1 or BRCA2 mutation carriers (P-trend = 0.27 and 0.30, respectively). The identification of SNPs at 6q25.1 associated with breast cancer risk for BRCA1 mutation carriers will lead to a better understanding of the biology of tumour development in these women.
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- Conti, David, V, et al.
(author)
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
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Journal article (peer-reviewed)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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- Hamdi, Yosr, et al.
(author)
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Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression : identification of a modifier of breast cancer risk at locus 11q22.3
- 2017
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In: Breast Cancer Research and Treatment. - : Springer Science and Business Media LLC. - 0167-6806 .- 1573-7217. ; 161:1, s. 117-134
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Journal article (peer-reviewed)abstract
- Purpose: Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways. Methods: Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2. Results: We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10−6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance. Conclusion: We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.
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- Mahajan, Anubha, et al.
(author)
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
- 2018
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
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Journal article (peer-reviewed)abstract
- We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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- Tobias, Deirdre K, et al.
(author)
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Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
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In: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
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Research review (peer-reviewed)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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- Vigorito, Elena, et al.
(author)
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Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers
- 2016
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:7
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Journal article (peer-reviewed)abstract
- Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95% CI: 0.68 to 0.79, p-value 2x 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95% CI: 0.59 to 0.80, p-value 1.0 x 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
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