Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

doi:10.1038/s41588-018-0081-4

. 2018 Apr;50(4):621-629.

doi: 10.1038/s41588-018-0081-4. Epub 2018 Apr 9.

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

Hilary K Finucane^{1

2

3}, Yakir A Reshef⁴, Verneri Anttila^{5

6}, Kamil Slowikowski^{5

7

8}, Alexander Gusev⁹, Andrea Byrnes^{5

6}, Steven Gazal⁹, Po-Ru Loh⁹, Caleb Lareau^{5

10}, Noam Shoresh⁵, Giulio Genovese⁵, Arpiar Saunders¹¹, Evan Macosko¹¹, Samuela Pollack⁹; Brainstorm Consortium; John R B Perry¹², Jason D Buenrostro^{5

13}, Bradley E Bernstein^{5

14}, Soumya Raychaudhuri^{5

8

15

16

17}, Steven McCarroll^{5

11}, Benjamin M Neale^{5

6}, Alkes L Price^{18

19}

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
² Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA. [email protected].
³ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. [email protected].
⁴ Department of Computer Science, Harvard University, Cambridge, MA, USA.
⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁷ Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA, USA.
⁸ Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁹ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹¹ Department of Genetics, Harvard Medical School, Boston, MA, USA.
¹² Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.
¹³ Harvard Society of Fellows, Harvard University, Cambridge, MA, USA.
¹⁴ Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
¹⁵ Division of Rheumatology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹⁶ Partners Center for Personalized Genetic Medicine, Boston, MA, USA.
¹⁷ Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK.
¹⁸ Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
¹⁹ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. [email protected].

PMID: 29632380
PMCID: PMC5896795
DOI: 10.1038/s41588-018-0081-4

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

Hilary K Finucane et al. Nat Genet. 2018 Apr.

. 2018 Apr;50(4):621-629.

doi: 10.1038/s41588-018-0081-4. Epub 2018 Apr 9.

Authors

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
² Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA. [email protected].
³ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. [email protected].
⁴ Department of Computer Science, Harvard University, Cambridge, MA, USA.
⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁷ Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA, USA.
⁸ Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
⁹ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹¹ Department of Genetics, Harvard Medical School, Boston, MA, USA.
¹² Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.
¹³ Harvard Society of Fellows, Harvard University, Cambridge, MA, USA.
¹⁴ Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
¹⁵ Division of Rheumatology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹⁶ Partners Center for Personalized Genetic Medicine, Boston, MA, USA.
¹⁷ Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK.
¹⁸ Broad Institute of MIT and Harvard, Cambridge, MA, USA. [email protected].
¹⁹ Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. [email protected].

PMID: 29632380
PMCID: PMC5896795
DOI: 10.1038/s41588-018-0081-4

Abstract

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

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Conflict of interest statement

COMPETING FINANCIAL INTERESTS

The authors declare no competing financial interests.

Figures

**Figure 1**
Overview of the approach. For each tissue in our gene expression data set, we compute t-statistics for differential expression for each gene. We then rank genes by t-statistic, take the top 10% of genes, and add a 100kb window to get a genome annotation. We use stratified LD score regression to test whether this annotation is significantly enriched for per-SNP heritability, conditional on the baseline model and the set of all genes.

**Figure 3**
Validation of gene expression results with chromatin data. (A) Examples of validation using chromatin data (bottom) of results from gene expression data (top), for selected traits. Results using chromatin data for all traits are displayed in Figure S5, with numerical results in Table S7. For the chromatin results, each point represents a track of peaks for H3K4me3, H3K4me1, H3K9ac, H3K27ac, H3K36me3, or DHS in a single tissue/cell type. (B) Results using gene expression data (including GTEx), Roadmap, and EN-TEx, for migraine (all subtypes) and migraine without aura. For both subfigures, large points pass the FDR10(P)=2.85 (chromatin) or –log₁₀(P)=2.75 (gene expression). GWAS data is described in Table S4; gene expression data and chromatin data are described in the Online Methods, Tables S2-3, and Table S7; and the statistical method is described in the Overview of Methods and the Online Methods.

**Figure 4**
Results of the brain analysis for selected traits. Numerical results for all traits are reported in Table S8. (A) Results from within-brain analysis of 13 brain regions in GTEx, classified into four groups, for seven of 12 brain-related traits. Large points passed the FDR10(P)=2.34. (B) Results from the data of Cahoy et al. on three brain cell types for seven of 12 brain-related traits. Large points passed the FDR<5% cutoff, –log₁₀(P)=2.22. (C) Results from PyschENCODE data on two neuronal subtypes for three of five neuron-related traits. Large points passed the Bonferroni significance threshold in this analysis, –log₁₀(P)=2.06. GWAS data is described in Table S4, gene expression data is described in the Online Methods and Table S8, and the statistical method is described in the Overview of Methods and the Online Methods.

**Figure 5**
Results of the analysis of ImmGen gene expression data (top) and hematopoiesis ATAC-seq data (bottom) for selected traits. Results for the remaining traits are displayed in Figure S9. Large points passed the FDR10(P)=3.03 (Gene expression) or –log10(P)=2.32 (Chromatin). Numerical results are reported in Table S10. GWAS data is described in Table S4, gene expression and chromatin data is described in the Online Methods and Table S10, and the statistical method is described in the Overview of Methods and the Online Methods.

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Comment in

Linking tissues to disease.
Cloney R. Cloney R. Nat Rev Genet. 2018 Jun;19(6):328. doi: 10.1038/s41576-018-0009-y. Nat Rev Genet. 2018. PMID: 29686399 No abstract available.

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References

1. The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74. - PMC - PubMed
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[1] The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74. - PMC - PubMed

[2] The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74. - PMC - PubMed

[3] Kundaje A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–330. - PMC - PubMed

[4] Kundaje A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–330. - PMC - PubMed

[5] The GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science. 2015;348:648–660. - PMC - PubMed

[6] The GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science. 2015;348:648–660. - PMC - PubMed

[7] Ernst J, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473:43–49. - PMC - PubMed

[8] Ernst J, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473:43–49. - PMC - PubMed

[9] Trynka G, et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat Genet. 2013;45:124–130. - PMC - PubMed

[10] Trynka G, et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat Genet. 2013;45:124–130. - PMC - PubMed

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Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

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Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

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