publication . Preprint . 2017

A powerful approach to estimating annotation-stratified genetic covariance using GWAS summary statistics

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L.; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; ...
Open Access
  • Published: 07 Mar 2017
  • Publisher: Cold Spring Harbor Laboratory
Abstract
<jats:title>Abstract</jats:title><jats:p>Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits’ genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses we demonstrate that our method provides accurate...
Subjects
free text keywords: Minor allele frequency, Covariance, Single-nucleotide polymorphism, Genetic association, Inference, Genetics, Bioinformatics, Interpretability, Genome-wide association study, Biology, Genetic architecture
Funded by
NIH| Collaborative GWAS of Dementia, AD and related MRI and Cognitive Endophenotypes
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1R01AG033193-01
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Statistical Methods to Map Genes for Complex Traits
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM059507-08
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| ALZHEIMERS DISEASE DATA COORDINATING CENTER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U01AG016976-03
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| National Cell Repository for Alzheimers Disease
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U24AG021886-09
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| CHARGE consortium: gene discovery for CVD and aging phenotypes
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2R01HL105756-07
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
17 references, page 1 of 2

Yang, J., et al., Common SNPs explain a large proportion of the heritability for human height. Nature genetics, 2010. 42(7): p. 565-569.

Yang, J., et al., GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics, 2011. 88(1): p. 76-82.

Yang, J., et al., Genome partitioning of genetic variation for complex traits using common SNPs. Nature genetics, 2011. 43(6): p. 519-525.

Lee, S.H., et al., Estimation of pleiotropy between complex diseases using singlenucleotide polymorphism-derived genomic relationships and restricted maximum likelihood. Bioinformatics, 2012. 28(19): p. 2540-2542.

Vattikuti, S., J. Guo, and C.C. Chow, Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLoS Genet, 2012. 8(3): p. e1002637.

Lee, H., et al., Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 2013. 45(9): p. 984-94.

Bulik-Sullivan, B., et al., An atlas of genetic correlations across human diseases and traits. Nature genetics, 2015.

Pasaniuc, B. and A.L. Price, Dissecting the genetics of complex traits using summary association statistics. Nature Reviews Genetics, 2016. [OpenAIRE]

Anttila, V., et al., Analysis of shared heritability in common disorders of the brain. bioRxiv, 2016: p. 048991.

Zheng, J., et al., LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics, 2016: p. btw613.

Zhou, X., A Unified Framework for Variance Component Estimation with Summary Statistics in Genome-wide Association Studies. bioRxiv, 2016: p. 042846.

Finucane, H.K., et al., Partitioning heritability by functional annotation using genomewide association summary statistics. Nature Genetics, 2015.

Lu, Q., et al., Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease. bioRxiv, 2016: p. 078865.

Gusev, A., et al., Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. The American Journal of Human Genetics, 2014. 95(5): p.

bioRxiv, 2015.

17 references, page 1 of 2
Abstract
<jats:title>Abstract</jats:title><jats:p>Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits’ genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses we demonstrate that our method provides accurate...
Subjects
free text keywords: Minor allele frequency, Covariance, Single-nucleotide polymorphism, Genetic association, Inference, Genetics, Bioinformatics, Interpretability, Genome-wide association study, Biology, Genetic architecture
Funded by
NIH| Collaborative GWAS of Dementia, AD and related MRI and Cognitive Endophenotypes
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1R01AG033193-01
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Statistical Methods to Map Genes for Complex Traits
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM059507-08
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| ALZHEIMERS DISEASE DATA COORDINATING CENTER
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U01AG016976-03
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| National Cell Repository for Alzheimers Disease
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5U24AG021886-09
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| CHARGE consortium: gene discovery for CVD and aging phenotypes
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2R01HL105756-07
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
17 references, page 1 of 2

Yang, J., et al., Common SNPs explain a large proportion of the heritability for human height. Nature genetics, 2010. 42(7): p. 565-569.

Yang, J., et al., GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics, 2011. 88(1): p. 76-82.

Yang, J., et al., Genome partitioning of genetic variation for complex traits using common SNPs. Nature genetics, 2011. 43(6): p. 519-525.

Lee, S.H., et al., Estimation of pleiotropy between complex diseases using singlenucleotide polymorphism-derived genomic relationships and restricted maximum likelihood. Bioinformatics, 2012. 28(19): p. 2540-2542.

Vattikuti, S., J. Guo, and C.C. Chow, Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits. PLoS Genet, 2012. 8(3): p. e1002637.

Lee, H., et al., Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 2013. 45(9): p. 984-94.

Bulik-Sullivan, B., et al., An atlas of genetic correlations across human diseases and traits. Nature genetics, 2015.

Pasaniuc, B. and A.L. Price, Dissecting the genetics of complex traits using summary association statistics. Nature Reviews Genetics, 2016. [OpenAIRE]

Anttila, V., et al., Analysis of shared heritability in common disorders of the brain. bioRxiv, 2016: p. 048991.

Zheng, J., et al., LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics, 2016: p. btw613.

Zhou, X., A Unified Framework for Variance Component Estimation with Summary Statistics in Genome-wide Association Studies. bioRxiv, 2016: p. 042846.

Finucane, H.K., et al., Partitioning heritability by functional annotation using genomewide association summary statistics. Nature Genetics, 2015.

Lu, Q., et al., Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease. bioRxiv, 2016: p. 078865.

Gusev, A., et al., Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. The American Journal of Human Genetics, 2014. 95(5): p.

bioRxiv, 2015.

17 references, page 1 of 2
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