Dataset Information

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

ABSTRACT: There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

SUBMITTER: Jiang Y

PROVIDER: S-EPMC7288273 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

Jiang Yu Y Chen Sai S Wang Xingyan X Liu Mengzhen M Iacono William G WG Hewitt John K JK Hokanson John E JE Krauter Kenneth K Laakso Markku M Li Kevin W KW Lutz Sharon M SM McGue Matthew M Pandit Anita A Zajac Gregory J M GJM Boehnke Michael M Abecasis Goncalo R GR Vrieze Scott I SI Jiang Bibo B Zhan Xiaowei X Liu Dajiang J DJ

Genes 20200525 5

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misl ...[more]

PMID: 32466134

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Project description:ContextMutations in the low-density lipoprotein receptor-related protein 5 (LRP5) gene cause rare syndromes characterized by altered bone mineral density (BMD). More common LRP5 variants may affect osteoporosis risk in the general population.ObjectiveTo generate large-scale evidence on whether 2 common variants of LRP5 (Val667Met, Ala1330Val) and 1 variant of LRP6 (Ile1062Val) are associated with BMD and fracture risk.Design and settingProspective, multicenter, collaborative study of individual-level data on 37,534 individuals from 18 participating teams in Europe and North America. Data were collected between September 2004 and January 2007; analysis of the collected data was performed between February and May 2007. Bone mineral density was assessed by dual-energy x-ray absorptiometry. Fractures were identified via questionnaire, medical records, or radiographic documentation; incident fracture data were available for some cohorts, ascertained via routine surveillance methods, including radiographic examination for vertebral fractures.Main outcome measuresBone mineral density of the lumbar spine and femoral neck; prevalence of all fractures and vertebral fractures.ResultsThe Met667 allele of LRP5 was associated with reduced lumbar spine BMD (n = 25,052 [number of participants with available data]; 20-mg/cm2 lower BMD per Met667 allele copy; P = 3.3 x 10(-8)), as was the Val1330 allele (n = 24,812; 14-mg/cm2 lower BMD per Val1330 copy; P = 2.6 x 10(-9)). Similar effects were observed for femoral neck BMD, with a decrease of 11 mg/cm2 (P = 3.8 x 10(-5)) and 8 mg/cm2 (P = 5.0 x 10(-6)) for the Met667 and Val1330 alleles, respectively (n = 25 193). Findings were consistent across studies for both LRP5 alleles. Both alleles were associated with vertebral fractures (odds ratio [OR], 1.26; 95% confidence interval [CI], 1.08-1.47 for Met667 [2001 fractures among 20 488 individuals] and OR, 1.12; 95% CI, 1.01-1.24 for Val1330 [1988 fractures among 20,096 individuals]). Risk of all fractures was also increased with Met667 (OR, 1.14; 95% CI, 1.05-1.24 per allele [7876 fractures among 31,435 individuals)]) and Val1330 (OR, 1.06; 95% CI, 1.01-1.12 per allele [7802 fractures among 31 199 individuals]). Effects were similar when adjustments were made for age, weight, height, menopausal status, and use of hormone therapy. Fracture risks were partly attenuated by adjustment for BMD. Haplotype analysis indicated that Met667 and Val1330 variants both independently affected BMD. The LRP6 Ile1062Val polymorphism was not associated with any osteoporosis phenotype. All aforementioned associations except that between Val1330 and all fractures and vertebral fractures remained significant after multiple-comparison adjustments.ConclusionsCommon LRP5 variants are consistently associated with BMD and fracture risk across different white populations. The magnitude of the effect is modest. LRP5 may be the first gene to reach a genome-wide significance level (a conservative level of significance [herein, unadjusted P < 10(-7)] that accounts for the many possible comparisons in the human genome) for a phenotype related to osteoporosis.

Dataset Information

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

Publications

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

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