Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Huckins, Laura; Dobbyn, Amanda; Ruderfer, Douglas M.; Hoffman, Gabriel E.; Wang, Weiqing; Pardiñas, Antonio F.; Rajagopal, Veera; Als, Thomas Damm; Nguyen, Hoang; Girdhar, Kiran; Boocock, James; Roussos, Panos; Fromer, Menachem; Kramer, Robin; Domenici, Enrico; Gamazon, Eric R.; Purcell, Shaun; Demontis, Ditte; Børglum, Anders D.; Walters, James; O’Donovan, Michael; Sullivan, Patrick F.; Devlin, Bernie; Sieberts, Solveig K.; Cox, Nancy J.; Im, Hae Kyung; Sklar, Pamela; Stahl, Eli A.

doi:10.1038/s41588-019-0364-4

Cited by 166 publications

(155 citation statements)

References 86 publications

Supporting

Mentioning

148

Contrasting

Order By: Relevance

“…whether or not SNPs are eQTLs) [17][18][19][20] . Application of these methods to eQTL and GWAS data has shown that many genes have eQTLs that colocalize with GWAS loci [6][7][8][9][10] and/or exhibit significant cis-genetic correlations between their expression and trait [11][12][13][14][15][16][21][22][23][24][25][26][27][28] , while also showing that eQTLs as a whole are significantly enriched for disease heritability [17][18][19][20] .…”

Section: Introductionmentioning

confidence: 99%

Quantifying genetic effects on disease mediated by assayed gene expression levels

Yao

O’Connor

Price

et al. 2019

Preprint

View full text Add to dashboard Cite

Disease variants identified by genome-wide association studies (GWAS) tend to overlap with expression quantitative trait loci (eQTLs). However, it remains unclear whether this overlap is driven by mediation of genetic effects on disease by expression levels, or whether it primarily reflects pleiotropic relationships instead. Here we introduce a new method, mediated expression score regression (MESC), to estimate disease heritability mediated by the cis-genetic component of assayed steady-state gene expression levels, using summary association statistics from GWAS and eQTL studies. We show that MESC produces robust estimates of expression-mediated heritability across a wide range of simulations. We applied MESC to GWAS summary statistics for 42 diseases and complex traits (average N = 323K) and cis-eQTL data across 48 tissues from the GTEx consortium. We determined that a statistically significant but low proportion of disease heritability (mean estimate 11% with S.E. 2%) is mediated by the cis-genetic component of assayed gene expression levels, with substantial variation across diseases (point estimates from 0% to 38%). We further partitioned expression-mediated heritability across various gene sets. We observed an inverse relationship between cis-heritability of expression and disease heritability mediated by expression, suggesting that genes with weaker eQTLs have larger causal effects on disease. Moreover, we observed broad patterns of expression-mediated heritability enrichment across functional gene sets that implicate specific gene sets in disease, including loss-of-function intolerant genes and FDA-approved drug targets. Our results demonstrate that eQTLs estimated from steady-state expression levels in bulk tissues are informative of regulatory disease mechanisms, but that such eQTLs are insufficient to explain the majority of disease heritability. Instead, additional assays are necessary to more fully capture the regulatory effects of GWAS variants.

show abstract

Section: Introductionmentioning

confidence: 99%

Quantifying genetic effects on disease mediated by assayed gene expression levels

Yao

O’Connor

Price

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Both structural changes using MRI approaches and methodologies to explore either visual or auditory pathways are available in mice. Furthermore, Huckins et al [10] used transcriptomic imputation approaches that combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. They demonstrated that genes encoding proteins involved in metabolic pathways are indeed associated with schizophrenia.…”

Section: Contents Lists Available At Sciencedirectmentioning

confidence: 99%

Translational research identifies a metabolism pathway involved in first-episode of schizophrenia: Towards precision medicine

Simonneau

2019

eBioMedicine

View full text Add to dashboard Cite

“…In order to test this, we use large-scale RNA-seq datasets from the post mortem human brains from the CommonMind Consortium (57) and whole blood from Depression Genes and Networks (58) where eQTL analysis had already been performed. Transcriptome imputation was performed by training an elastic net predictor for each gene expression trait using only cis variants (51,52). For each gene, the fraction of expression variation explainable by cis regulatory variants was termed 'eQTL R 2 '.…”

Section: False Positives Driven By Genetic Regulationmentioning

confidence: 99%

dream: Powerful differential expression analysis for repeated measures designs

Hoffman

Roussos

2018

Preprint

Self Cite

View full text Add to dashboard Cite

Large-scale transcriptome studies with multiple samples per individual are widely used to study disease biology. Yet current methods for differential expression are inadequate for cross-individual testing for these repeated measures designs. Most problematic, we observe across multiple datasets that current methods can give reproducible false positive findings that are driven by genetic regulation of gene expression, yet are unrelated to the trait of interest. Here we introduce a statistical software package, dream, that increases power, controls the false positive rate, enables multiple types of hypothesis tests, and integrates with standard workflows. In 12 analyses in 6 independent datasets, dream yields biological insight not found with existing software while addressing the issue of reproducible false positive findings. Dream is available within the variancePartition Bioconductor package (http://bioconductor.org/packages/ variancePartition).

show abstract

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Cited by 166 publications

References 86 publications

Quantifying genetic effects on disease mediated by assayed gene expression levels

Quantifying genetic effects on disease mediated by assayed gene expression levels

Translational research identifies a metabolism pathway involved in first-episode of schizophrenia: Towards precision medicine

dream: Powerful differential expression analysis for repeated measures designs

Contact Info

Product

Resources

About