Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts

Rashkin, Sara R.; Graff, Rebecca E.; Kachuri, Linda; Thai, Khanh K.; Alexeeff, Stacey; Blatchins, Maruta A.; Cavazos, Taylor B.; Corley, Douglas A.; Emami, Nima C.; Hoffman, Joshua; Jorgenson, Eric; Kushi, Lawrence H.; Meyers, Travis J.; Eeden, Stephen K. Van Den; Ziv, Elad; Habel, Laurel A.; Hoffmann, Thomas J.; Sakoda, Lori C.; Witte, John S.

doi:10.1038/s41467-020-18246-6

Cited by 175 publications

(202 citation statements)

References 67 publications

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“…Cancer sites for which the PRS resulted in the largest gains in prediction performance included prostate, testicular, and thyroid cancers, as well as leukemia, and melanoma. This is consistent with high heritability estimates reported for these cancers in twin studies 14 and our analyses in the UK Biobank 15 . Modeling the PRS in addition to established risk factors yielded very modest improvements in risk discrimination for cancers of the lung, endometrium, bladder, oral cavity/pharynx, and kidney.…”

Section: Discussionsupporting

confidence: 92%

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

et al. 2020

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Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.

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Section: Discussionsupporting

confidence: 92%

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

et al. 2020

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“…Overall, the results of our cross-cancer PRS analyses demonstrated unique patterns of pleiotropy relative to studies focused on array-based shared heritability or genetic correlations [28][29][30][31] . In GERA and the UK Biobank, our group previously found suggestive evidence of positive correlations between bladder and breast cancers, melanoma and testicular cancer, and prostate and thyroid cancers and negative correlations between endometrial and testicular cancers, lung cancer and melanoma, and NHL and prostate cancer 31 . These pairs did not surface in our cross-cancer PRS analyses in these same cohorts, except suggestive evidence of bidirectional positive associations between melanoma and testicular cancer.…”

Section: Discussionmentioning

confidence: 66%

“…Genome-wide association studies (GWAS) of individual cancer types have also identified loci associated with multiple cancer types, including 5p15 ( TERT-CLPTM1L) 3 , 6p21 (HLA complex) 4 , 5 , and 8q24 6 . Non-GWAS approaches have yielded further pleiotropic cancer risk variants 7 – 27 , and genetic correlation studies have identified cancer pairs with shared heritability 28 – 31 .…”

Section: Introductionmentioning

confidence: 99%

Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts

et al. 2021

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Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.

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“…We explored pleiotropic associations between lead variants influencing antibody levels and several chronic diseases with known or hypothesized viral risk factors. Associations with selected cancers were obtained from a cancer pleiotropy meta-analysis of the UK Biobank and Genetic Epidemiology Research on Aging cohorts [ 27 ]. Summary statistics for the schizophrenia GWAS of 33,640 cases and 43,456 controls by Lam et al [ 28 ] were downloaded from the Psychiatric Genomics Consortium.…”

Section: Methodsmentioning

confidence: 99%

The landscape of host genetic factors involved in immune response to common viral infections

et al. 2020

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Background Humans and viruses have co-evolved for millennia resulting in a complex host genetic architecture. Understanding the genetic mechanisms of immune response to viral infection provides insight into disease etiology and therapeutic opportunities. Methods We conducted a comprehensive study including genome-wide and transcriptome-wide association analyses to identify genetic loci associated with immunoglobulin G antibody response to 28 antigens for 16 viruses using serological data from 7924 European ancestry participants in the UK Biobank cohort. Results Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. We identified specific amino acid (AA) residues that are associated with seroreactivity, the strongest associations presented in a range of AA positions within DRβ1 at positions 11, 13, 71, and 74 for Epstein-Barr virus (EBV), Varicella zoster virus (VZV), human herpesvirus 7, (HHV7), and Merkel cell polyomavirus (MCV). Genome-wide association analyses discovered 7 novel genetic loci outside the HLA associated with viral antibody response (P < 5.0 × 10−8), including FUT2 (19q13.33) for human polyomavirus BK (BKV), STING1 (5q31.2) for MCV, and CXCR5 (11q23.3) and TBKBP1 (17q21.32) for HHV7. Transcriptome-wide association analyses identified 114 genes associated with response to viral infection, 12 outside of the HLA region, including ECSCR: P = 5.0 × 10−15 (MCV), NTN5: P = 1.1 × 10−9 (BKV), and P2RY13: P = 1.1 × 10−8 EBV nuclear antigen. We also demonstrated pleiotropy between viral response genes and complex diseases, from autoimmune disorders to cancer to neurodegenerative and psychiatric conditions. Conclusions Our study confirms the importance of the HLA region in host response to viral infection and elucidates novel genetic determinants beyond the HLA that contribute to host-virus interaction.

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Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts

Cited by 175 publications

References 67 publications

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts

The landscape of host genetic factors involved in immune response to common viral infections

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