1. |
- Wang, Anqi, et al.
(author)
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Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
- 2023
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 55:12, s. 2065-2074
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Journal article (peer-reviewed)abstract
- The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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2. |
- 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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3. |
- Seldin, Michael F., et al.
(author)
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Argentine population genetic structure : large variance in Amerindian contribution
- 2007
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In: American Journal of Physical Anthropology. - : Wiley. - 0002-9483 .- 1096-8644. ; 132:3, s. 455-462
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Journal article (peer-reviewed)abstract
- Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies.
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4. |
- Lazaridis, Iosif, et al.
(author)
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Ancient human genomes suggest three ancestral populations for present-day Europeans
- 2014
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 513:7518, s. 409-
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Journal article (peer-reviewed)abstract
- We sequenced the genomes of a similar to 7,000-year-old farmer from Germany and eight similar to 8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes(1-4) with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians(3), who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had similar to 44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.
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5. |
- Kosoy, Roman, et al.
(author)
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Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America
- 2009
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In: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 30:1, s. 69-78
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Journal article (peer-reviewed)abstract
- To provide a resource for assessing continental ancestry in a wide variety of genetic studies, we identified, validated, and characterized a set of 128 ancestry informative markers (AIMs). The markers were chosen for informativeness, genome-wide distribution, and genotype reproducibility on two platforms (TaqMan assays and Illumina arrays). We analyzed genotyping data from 825 subjects with diverse ancestry, including European, East Asian, Amerindian, African, South Asian, Mexican, and Puerto Rican. A comprehensive set of 128 AIMs and subsets as small as 24 AIMs are shown to be useful tools for ascertaining the origin of subjects from particular continents, and to correct for population stratification in admixed population sample sets. Our findings provide general guidelines for the application of specific AIM subsets as a resource for wide application. We conclude that investigators can use TaqMan assays for the selected AIMs as a simple and cost efficient tool to control for differences in continental ancestry when conducting association studies in ethnically diverse populations.
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6. |
- Nassir, Rami, et al.
(author)
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An ancestry informative marker set for determining continental origin : validation and extension using human genome diversity panels
- 2009
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In: BMC Genetics. - : Springer Science and Business Media LLC. - 1471-2156. ; 10, s. 39-
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Journal article (peer-reviewed)abstract
- Background: Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia. Results: In this study, genotypes from Human Genome Diversity Panel populations were used to further evaluate a 93 SNP AIM panel, a subset of the 128 AIMS set, for distinguishing continental origins. Using both model-based and relatively model-independent methods, we here confirm the ability of this AIM set to distinguish diverse population groups that were not previously evaluated. This study included multiple population groups from Oceana, South Asia, East Asia, Sub-Saharan Africa, North and South America, and Europe. In addition, the 93 AIM set provides population substructure information that can, for example, distinguish Arab and Ashkenazi from Northern European population groups and Pygmy from other Sub-Saharan African population groups. Conclusion: These data provide additional support for using the 93 AIM set to efficiently identify continental subject groups for genetic studies, to identify study population outliers, and to control for admixture in association studies.
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