Multi-Ancestry Meta-Analysis yields novel genetic discoveries and ancestry-specific associations
Open accessAbstract
We present a new method, Multi-Ancestry Meta-Analysis (MAMA), which combines genome-wide association study (GWAS) summary statistics from multiple populations to produce new summary statistics for each population, identifying novel loci that would not have been discovered in either set of GWAS summary statistics alone. In simulations, MAMA increases power with less bias and generally lower type-1 error rate than other multi-ancestry meta-analysis approaches. We apply MAMA to 23 phenotypes in East-Asian- and European-ancestry populations and find substantial gains in power. In an independent sample, novel genetic discoveries from MAMA replicate strongly.
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MAMA identified 94 independent genome-wide significant SNPs with EAS-specific meta-analysis, 2 of which were previously unreported for EduYears (rs2881903 and rs16930687).
“Using MAMA, we identified 94 independent genome-wide significant SNPs with EAS-specific meta-analysis (Fig. 1c and Supplementary Table 13), 2 of which were previously unreported for EduYears (rs2881903 and rs16930687)”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [30]
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MethodThe impact of stability considerations on genetic fine-mappingPreprint
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“The last sentence in the preceding paragraph suggests there are teleological similarities between the stability-guided approach and meta-analysis approaches ( Turley et al., 2021 ).”
The Impact of Stability Considerations on Genetic Fine-Mapping
Aw, A. J., Jin, L., Ioannidis, N., & Song, Y. S. (2023) · bioRxiv · doi:10.1101/2023.04.11.536456
“…cohorts typically representing multiple population ancestries (M´arquez-Luna et al. 2017), meta-analyses of earlier studies across diverse cohorts (Turley et al. 2021; Han and Eskin 2012; Morris 2011; Willer et al. 2010), or focusing on biological markers that are more likely a priori to play a…”
Background
- Authors
- Turley, P., Martin, A. R., Goldman, G., Li, H., Kanai, M., Walters, R. K., Jala, J. B., Lin, K., Millwood, I. Y., Carey, C. E., Palmer, D. S., Zacher, M., Atkinson, E. G., Chen, Z., Li, L., Akiyama, M., Okada, Y., Kamatani, Y., Walters, R. G., Callier, S., Laibson, D., Meyer, M. N., Cesarini, D., Daly, M., Benjamin, D. J., & Neale, B. M.
- Affiliations
- University of Southern California (US)
- Broad Institute (US)
- National Bureau of Economic Research (US)
- Harvard University (US)
- University of California, Los Angeles (US)
- University of Oxford (GB)
- Brown University (US)
- Peking University (CN)
- Kyushu University (JP)
- The University of Osaka (JP)
- RIKEN Center for Integrative Medical Sciences (JP)
- Geisinger Medical Center (US)
- Corresponding author
- Turley, Patrick
- ORCID
- Turley, Patrick
- Martin, Alicia R.
- Goldman, Grant
- Li, Hui
- Kanai, Masahiro
- Walters, Raymond K.
- Lin, Kuang
- Millwood, Iona Y.
- Carey, Caitlin E.
- Palmer, Duncan S.
- Zacher, Meghan
- Atkinson, Elizabeth G.
- Chen, Zhengming
- Li, Liming
- Akiyama, Masato
- Okada, Yukinori
- Walters, Robin G.
- Callier, Shawneequa
- Laibson, David
- Meyer, Michelle N.
- Cesarini, David
- Daly, Mark
- Benjamin, Daniel J.
- Neale, Benjamin M.
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2021-04-24
- OpenAlex
- W3158903754
- Cited by
- 35
- References
- 41
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 5 · 2023: 11 · 2022: 8 · 2021: 2
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Funders
- Medical Research Council (MC_PC_14135, MC_UU_00017/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- genome-wide association study, statistical power, type I error, East Asian ancestry, European ancestry, novel genetic loci, genetic discovery
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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