Cross-cancer genome-wide association study of endometrial cancer and epithelial ovarian cancer identifies genetic risk regions associated with risk of both cancers

AbstractAccumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

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Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women

Gynecologic Oncology ◽

10.1016/j.ygyno.2019.02.023 ◽

2019 ◽

Vol 153 (2) ◽

pp. 343-355 ◽

Cited By ~ 9

Author(s):

Kate Lawrenson ◽

Fengju Song ◽

Dennis J. Hazelett ◽

Siddhartha P. Kar ◽

Jonathan Tyrer ◽

...

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Association Studies ◽

East Asian ◽

Genome Wide Association ◽

Asian Women ◽

Genome Wide Association Studies ◽

Susceptibility Loci ◽

Genome Wide

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Abstract 4579: Variants in long non-coding RNAs are associated with epithelial ovarian cancer risk in a pooled analysis of three genome-wide association studies.

10.1158/1538-7445.am2013-4579 ◽

2013 ◽

Author(s):

Yian Ann Chen ◽

Zhihua Chen ◽

Jennifer Permuth-Wey ◽

Ya-Yu Tsai ◽

Hui-Yi Lin ◽

...

Keyword(s):

Ovarian Cancer ◽

Cancer Risk ◽

Epithelial Ovarian Cancer ◽

Association Studies ◽

Pooled Analysis ◽

Genome Wide Association ◽

Ovarian Cancer Risk ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Non Coding Rnas

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Genome-Wide Association Studies of Endometrial Cancer: Latest Developments and Future Directions

Cancer Epidemiology Biomarkers & Prevention ◽

10.1158/1055-9965.epi-18-1031 ◽

2019 ◽

Vol 28 (7) ◽

pp. 1095-1102 ◽

Cited By ~ 16

Author(s):

Tracy A. O'Mara ◽

Dylan M. Glubb ◽

Pik Fang Kho ◽

Deborah J. Thompson ◽

Amanda B. Spurdle

Keyword(s):

Endometrial Cancer ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Future Directions ◽

Genome Wide

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Challenges and progress in interpretation of non-coding genetic variants associated with human disease

Experimental Biology and Medicine ◽

10.1177/1535370217713750 ◽

2017 ◽

Vol 242 (13) ◽

pp. 1325-1334 ◽

Cited By ~ 19

Author(s):

Yizhou Zhu ◽

Cagdas Tazearslan ◽

Yousin Suh

Keyword(s):

Molecular Mechanisms ◽

Target Genes ◽

Disease Risk ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Functional Interpretation ◽

Genome Wide ◽

Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

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Genome-wide association analysis reveals extensive genetic overlap between mood instability and psychiatric disorders but divergent patterns of genetic effects

10.1101/2021.07.16.21260608 ◽

2021 ◽

Author(s):

Guy Hindley ◽

Kevin S O'Connell ◽

Zillur Rahman ◽

Oleksandr Frei ◽

Shahram Bahrami ◽

...

Keyword(s):

Psychiatric Disorders ◽

Genetic Correlation ◽

Association Studies ◽

Single Gene ◽

Genetic Effects ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genetic Determinants ◽

Mood Instability ◽

Genome Wide

Mood instability (MOOD) is a transdiagnostic phenomenon with a prominent neurobiological basis. Recent genome-wide association studies found significant positive genetic correlation between MOOD and major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. Summary statistics for schizophrenia (SCZ, n=105,318), bipolar disorder (BIP, n=413,466), DEP (n=450,619), attention-deficit hyperactivity disorder (ADHD, n=53,293) and MOOD (n=363,705), were analysed using the bivariate causal mixture model and conjunctional false discovery rate methods to estimate the proportion of shared variants influencing MOOD and each disorder, and identify jointly associated genomic loci. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg=0.10-0.62). Of 10.4K genomic variants influencing MOOD, 4K-9.4K were estimated to influence psychiatric disorders. MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25, with consistent genetic effects in independent samples. Fifty-three jointly associated loci were overlapping across two or more disorders (transdiagnostic), seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, synapse organization. The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions of shared loci suggest divergent effects on corresponding neurobiological mechanisms which may relate to differences in the core clinical features of each disorder.

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Meta-analysis of genome-wide association studies identifies common susceptibility polymorphisms for colorectal and endometrial cancer near SH2B3 and TSHZ1

Scientific Reports ◽

10.1038/srep17369 ◽

2015 ◽

Vol 5 (1) ◽

Cited By ~ 25

Author(s):

Timothy HT Cheng ◽

Deborah Thompson ◽

Jodie Painter ◽

Tracy O’Mara ◽

Maggie Gorman ◽

...

Keyword(s):

Endometrial Cancer ◽

Association Studies ◽

Meta Analysis ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual through variant-to-gene mapping

10.1101/2020.02.17.20024133 ◽

2020 ◽

Cited By ~ 2

Author(s):

Diana L. Cousminer ◽

Yadav Wagley ◽

James A. Pippin ◽

Ahmed Elhakeem ◽

Gregory P. Way ◽

...

Keyword(s):

Gene Mapping ◽

Cell Fate ◽

Target Genes ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Gene Promoters ◽

Skeletal Health ◽

Effector Genes ◽

Genome Wide

Introductory paragraphBone accrual impacts lifelong skeletal health, but genetic discovery has been hampered by cross-sectional study designs and uncertainty about target effector genes. Here, we captured this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans followed by genome-wide association studies (GWAS). We revealed 40 loci (35 novel), half residing in topological associated domains harboring known bone genes. Variant-to-gene mapping identified contacts between GWAS loci and nearby gene promoters, and siRNA knockdown of gene expression clarified the putative effector gene at three specific loci in two osteoblast cell models. The resulting target genes highlight the cell fate decision between osteogenic and adipogenic lineages as important in normal bone accrual.

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