Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Baca, Sylvan C.; Singler, Cassandra; Zacharia, Soumya; Seo, Ji-Heui; Morova, Tunç; Hach, Faraz; Ding, Yi; Schwarz, Tommer; Huang, Chia-Chi Flora; Anderson, Jacob B.; Fay, André P.; Kalita, Cynthia A; Groha, Stefan; Pomerantz, Mark; Wang, Victoria; Linder, Simon; Sweeney, Christopher J.; Zwart, Wilbert; Lack, Nathan A.; Paşaniuc, Bogdan; Takeda, David Y.; Gusev, Alexander; Freedman, Matthew L.

doi:10.1038/s41588-022-01168-y

Cited by 33 publications

(17 citation statements)

References 107 publications

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“…Having established an association of AR enhancer heterogeneity in PCa with biological consequences on enhancer activity, we next investigated the impact of 764 risk single nucleotide polymorphisms (rSNPs) [26][27][28] and single nucleotide variation (SNV) reported previously in primary PCa (n = 278,209) 10 and in metastatic PCa (mPCa, n = 1,048,576) 11 on primary ranked ARBS as SNVs accumulate during PCa progression. Moreover, we included germline allelic imbalance SNP data (cQTL, n = 4454; q < 0.05) which was called from our primary AR ChIP-seq data in a recent Cistrome-Wide Association Study (CWAS) 29 . Overlap of rSNPs with primary ranked ARBS was limited (52 out of 764 unique rSNPs) without any enrichment on particular ARBS, while germline cQTL SNPs and somatically acquired SNVs in primary and metastatic PCa are enriched in primary SH-ARBS (n = 1201, Fig.…”

Section: Ranked Arbs Have Functional Divergence On Enhancer Activity ...mentioning

confidence: 99%

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

et al. 2022

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Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients’ outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

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Section: Ranked Arbs Have Functional Divergence On Enhancer Activity ...mentioning

confidence: 99%

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

et al. 2022

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“…Cell state or environment 225,227,231,233,[241][242][243][244][245][246][247][248] -The causative eQTL has effects that are undetectable in steadystate expression under normal conditions.…”

Section: Extended Models Of Gene Regulationmentioning

confidence: 99%

The missing link between genetic association and regulatory function

Nazeen

Lee

et al. 2021

Preprint

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The genetic basis of most complex traits is highly polygenic and dominated by non-coding alleles, and it is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite availability of expansive gene expression and epigenomic data sets, few variant-to-gene links have emerged. We identified 139 genes in which protein-coding variants cause severe or familial forms of nine human traits. We then computed the association between common complex forms of the same traits and non-coding variation, revealing that most such traits are also associated with non-coding variation in the vicinity of the same genes. However, we found colocalization evidence--the same variant influencing both the physiological trait and gene expression--for only 7% of genes, and transcriptome-wide association evidence with correct direction of effect for only 4% of genes, despite an abundance of eQTLs in most loci. Fine mapping variants to regulatory elements and assigning these to genes by linear distance similarly failed to implicate most genes in complex traits. These results contradict the hypothesis that most complex trait-associated variants coincide with currently ascertained expression quantitative trait loci. The field must confront this deficit, and pursue the "missing regulation."

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“…chromatin accessibility QTLs. These additional data may explain a larger fraction of heritability missed by eQTLs [48].…”

Section: Resultsmentioning

confidence: 99%

“…Lastly, our method can be applied to other types of molecular QTL data, e.g. chromatin accessibility QTLs, which may explain a large fraction of heritability missed by eQTLs [7].…”

Section: Discussionmentioning

confidence: 99%

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Adjusting for genetic confounders in transcriptome-wide association studies leads to reliable detection of causal genes

Zhao

Crouse

Qian

et al. 2022

Preprint

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Expression QTLs (eQTLs), provide valuable information on the functional effects of variants. Many methods have been developed to leverage eQTLs to nominate candidate genes of complex traits. These methods include colocalization analysis, transcriptome-wide association studies (TWAS) that correlate genetic components of expression with traits, and Mendelian Randomization (MR)-based methods. A fundamental problem of all these methods is that, when assessing the role of one gene in a trait using its eQTLs, nearby variants and nearby genetic components of expression of other genes can be correlated with the eQTLs of the test gene, while affecting the trait directly. These "genetic confounders" may lead to false discoveries. To address this challenge, we introduced a novel statistical framework that generalizes TWAS to adjust all genetic confounders. In our simulations, we found that existing methods based on TWAS, colocalization or MR all suffered from high false positive rates, often greater than 50%. Our method, causal-TWAS (cTWAS), in contrast, showed calibrated false positive rates while maintaining power. Application of cTWAS on several common traits highlighted the weakness of existing methods and discovered novel candidate genes. In conclusion, cTWAS is a robust statistical framework to integrate eQTL and GWAS data for gene discovery, and is extendable to other molecular QTLs.

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Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Cited by 33 publications

References 107 publications

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

The missing link between genetic association and regulatory function

Adjusting for genetic confounders in transcriptome-wide association studies leads to reliable detection of causal genes

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