Computationally efficient whole genome regression for quantitative and binary traits

Mbatchou, Joelle; Barnard, Leland; Backman, Joshua; Marcketta, Anthony; Kosmicki, Jack A.; Ziyatdinov, Andrey; Benner, Christian; Ó'Dúshláine, Colm; Barber, Mathew; Boutkov, Boris; Habegger, Lukas; Ferreira, Manuel A. R.; Reid, Jeffrey G.; Abecasis, Gonçalo R.; Maxwell, Evan K.; Marchini, Jonathan

doi:10.1101/2020.06.19.162354

Cited by 72 publications

(85 citation statements)

References 40 publications

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“…A total of 60,800 OA cases and 328,251 controls were included in the primary analysis. For GWAS, we used REGENIE 10 , a ridge regression based method using Firth fallback regression correcting for age, sex, the first 20 genetic principal components, genotyping chip and assessment center. In a sensitivity analysis, we also included 19,846 OA cases which were of self-report only.…”

Section: Methodsmentioning

confidence: 99%

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

Karhunen

Malik

Dichgans

et al. 2021

Osteoarthritis and Cartilage

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Summary Objective To investigate which cardiometabolic factors underlie clustering of osteoarthritis (OA) with cardiovascular disease, and the extent to which these mediate an effect of education. Design Genome-wide association study (GWAS) of OA was performed in UK Biobank (60,800 cases and 328,251 controls) to obtain genetic association estimates for OA risk. Genetic instruments and association estimates for body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), smoking and education were obtained from existing GWAS summary data (sample sizes 188,577–866,834 individuals). Two-sample Mendelian randomization (MR) analyses were performed to investigate the effects of exposure traits on OA risk. MR mediation analyses were undertaken to investigate whether the cardiometabolic traits mediate any effect of education on OA risk. Results MR analyses identified protective effects of higher genetically predicted education (main MR analysis odds ratio (OR) per standard deviation increase 0.59, 95% confidence interval (CI) 0.54–0.64) and LDL-C levels (OR 0.94, 95%CI 0.91–0.98) on OA risk, and unfavourable effects of higher genetically predicted BMI (OR 1.82, 95%CI 1.73–1.92) and smoking (OR 2.23, 95%CI 1.85–2.68). There was no strong evidence of an effect of genetically predicted SBP on OA risk (OR 0.98, 95% CI 0.90–1.06). The proportion of the effect of genetically predicted education mediated through genetically predicted BMI and smoking was 35% (95%CI 13–57%). Conclusions These findings highlight education, obesity and smoking as common mechanisms underlying OA and cardiovascular disease. These risk factors represent clinical and public health targets for reducing multi-morbidity related to the burden these common conditions.

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Section: Methodsmentioning

confidence: 99%

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

Karhunen

Malik

Dichgans

et al. 2021

Osteoarthritis and Cartilage

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“…Association analyses in each study were performed using the genome-wide Firth logistic regression test implemented in REGENIE [59]. In this implementation, Firth’s approach is applied when the p-value from standard logistic regression score test is below 0.05.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease

Horowitz

Kosmicki

Damask

et al. 2020

Preprint

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The need to identify and effectively treat COVID-19 cases at highest risk for severe disease is critical. We identified seven common genetic variants (three novel) that modulate COVID-19 susceptibility and severity, implicating IFNAR2, CCHCR1, TCF19, SLC6A20 and the hyaluronan pathway as potential therapeutic targets. A high genetic burden was strongly associated with increased risk of hospitalization and severe disease among COVID-19 cases, especially among individuals with few known risk factors.

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“…Association analyses in the UK Biobank study were performed using the Firth logistic regression test implemented in REGENIE [31], separately for variants derived from array-based imputation and exome sequencing. In this test, Firth’s approach is applied when the p-value from the standard logistic regression score test is below 0.05.…”

Section: Methodsmentioning

confidence: 99%

A catalog of associations between rare coding variants and COVID-19 outcomes

Kosmicki¹,

Horowitz²,

Banerjee³

et al. 2020

Preprint

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Background. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes Coronavirus disease-19 (COVID-19), a respiratory illness with influenza-like symptoms that can result in hospitalization or death. We investigated human genetic determinants of COVID-19 risk and severity in 455,838 UK Biobank participants, including 2,003 with COVID-19. Methods. We defined eight COVID-19 phenotypes (including risks of infection, hospitalization and severe disease) and tested these for association with imputed and exome sequencing variants. Results. We replicated prior COVID-19 genetic associations with common variants in the 3p21.31 (in LZTFL1) and 9q34.2 (in ABO) loci. The 3p21.31 locus (rs11385942) was associated with disease severity amongst COVID-19 cases (OR=2.2, P=3x10-5), but not risk of SARS-CoV-2 infection without hospitalization (OR=0.89, P=0.25). We identified two loci associated with risk of infection at P<5x10-8, including a missense variant that tags the epsilon 4 haplotype in APOE (rs429358; OR=1.29, P=9x10-9). The association with rs429358 was attenuated after adjusting for cardiovascular disease and Alzheimer′s disease status (OR=1.15, P=0.005). Analyses of rare coding variants identified no significant associations overall, either exome-wide or with (i) 14 genes related to interferon signaling and reported to contain rare deleterious variants in severe COVID-19 patients; (ii) 36 genes located in the 3p21.31 and 9q34.2 GWAS risk loci; and (iii) 31 additional genes of immunologic relevance and/or therapeutic potential. Conclusions. Our analyses corroborate the association with the 3p21.31 locus and highlight that there are no rare protein-coding variant associations with effect sizes detectable at current sample sizes. Our full analysis results are publicly available, providing a substrate for meta-analysis with results from other sequenced COVID-19 cases as they become available. Association results are available at https://rgc-covid19.regeneron.com

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Computationally efficient whole genome regression for quantitative and binary traits

Cited by 72 publications

References 40 publications

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

Cardiometabolic traits mediating the effect of education on osteoarthritis risk: a Mendelian randomization study

Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease

A catalog of associations between rare coding variants and COVID-19 outcomes

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