Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: a meta-analysis within diverse populations
- University of Southern California, United States
- Fred Hutchinson Cancer Research Center, United States
- Argonne National Laboratory, United States
- Yale School of Medicine, United States
- Dana-Farber Cancer Institute, United States
- National Institutes of Health, United States
- Brigham and Women's Hospital, United States
- Harvard TH Chan School of Public Health, United States
- VA Boston Healthcare System, United States
- Hôpital Général Idrissa Pouye, Senegal
- University of Ibadan, Nigeria
- University of Abuja Teaching Hospital, Nigeria
- 37 Military Hospital, Ghana
- Korle-Bu Teaching Hospital, Ghana
- Hôpital Aristide Le Dantec, Senegal
- Georgia Institute of Technology, United States
- VA Connecticut Healthcare System, United States
- University of Southern California, Spain
Abstract
Background: We recently developed a multi-ancestry polygenic risk score (PRS) that effectively stratifies prostate cancer risk across populations. In this study, we validated the performance of the PRS in the multi-ancestry Million Veteran Program (MVP) and additional independent studies.
Methods: Within each ancestry population, the association of PRS with prostate cancer risk was evaluated separately in each case-control study and then combined in a fixed-effects inverse-variance-weighted meta-analysis. We further assessed the effect modification by age and estimated the age-specific absolute risk of prostate cancer for each ancestry population.
Results: The PRS was evaluated in 31,925 cases and 490,507 controls, including men from European (22,049 cases, 414,249 controls), African (8,794 cases, 55,657 controls), and Hispanic (1,082 cases, 20,601 controls) populations. Comparing men in the top decile (90-100% of the PRS) to the average 40-60% PRS category, the prostate cancer odds ratio (OR) was 3.8-fold in European ancestry men (95% CI=3.62-3.96), 2.8-fold in African ancestry men (95% CI=2.59-3.03), and 3.2-fold in Hispanic men (95% CI=2.64-3.92). The PRS did not discriminate risk of aggressive versus non-aggressive prostate cancer. However, the OR diminished with advancing age (European ancestry men in the top decile: ≤55 years, OR=7.11; 55-60 years, OR=4.26; >70 years, OR=2.79). Men in the top PRS decile reached 5% absolute prostate cancer risk ~10 years younger than men in the 40-60% PRS category.
Conclusions: Our findings validate the multi-ancestry PRS as an effective prostate cancer risk stratification tool across populations. A clinical study of PRS is warranted to determine if the PRS could be used for risk-stratified screening and early detection.
Funding: This work was supported by the National Cancer Institute at the National Institutes of Health (grant numbers U19 CA214253 to C.A.H., U01 CA257328 to C.A.H., U19 CA148537 to C.A.H., R01 CA165862 to C.A.H., K99 CA246063 to B.F.D, and T32CA229110 to F.C), the Prostate Cancer Foundation (grants 21YOUN11 to B.F.D. and 20CHAS03 to C.A.H.), the Achievement Rewards for College Scientists Foundation Los Angeles Founder Chapter to B.F.D, and the Million Veteran Program-MVP017. This research has been conducted using the UK Biobank Resource under application number 42195. This research is based on data from the Million Veteran Program, Office of Research and Development, and the Veterans Health Administration. This publication does not represent the views of the Department of Veteran Affairs or the United States Government.
Data availability
This investigation included published results from the following studies under DOI numbers 10.1038/s41588-020-00748-0 and 10.1093/jnci/djab058. For the MVP data, the final data sets underlying this study cannot be shared outside the VA, except as required under the Freedom of Information Act (FOIA), per VA policy. However, upon request through the formal mechanisms in place and pending approval from the VHA Office of Research Oversight (ORO), a de-identified, anonymized dataset underlying this study can be created. Upon request through the formal mechanisms provided by the VHA ORO, we would be able to provide sufficiently detailed variable names and definitions to allow replication of our work. Any requests for data access should be directed to the VHA ORO (OROCROW@va.gov), and should reference the following project and analysis: 'MVP017: A VA-DOE Exemplar Project on Cancer'. Publicly available data described in this manuscript can be found from the following websites: 1000 Genomes Project (https://www.internationalgenome.org/); SEER (https://seer.cancer.gov/); National Center for Health Statistics, and CDC (https://www.cdc.gov/nchs/index.htm).
Article and author information
Author details
Olufemi J Ogunbiyi
Afua Darkwa-Abrahams
Christopher A Haiman
Funding
National Cancer Institute (U19 CA214253)
- Christopher A Haiman
Million Veteran Program (MVP017)
- J Michael Gaziano
- Amy C Justice
National Cancer Institute (U01 CA257328)
- Christopher A Haiman
National Cancer Institute (U19 CA148537)
- Christopher A Haiman
National Cancer Institute (R01 CA165862)
- Christopher A Haiman
National Cancer Institute (K99 CA246063)
- Burcu F Darst
National Cancer Institute (T32CA229110)
- Fei Chen
Prostate Cancer Foundation (20CHAS03)
- Christopher A Haiman
Prostate Cancer Foundation (21YOUN11)
- Burcu F Darst
Achievement Rewards for College Scientists Foundation
- Burcu F Darst
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- C Daniela Robles-Espinoza, International Laboratory for Human Genome Research, Mexico
Ethics
Human subjects: All study protocols were approved by each site's Institutional Review Board, and informedconsent was obtained from all study participants in accordance with the principles outlined in theDeclaration of Helsinki.
Version history
- Received: March 1, 2022
- Preprint posted: May 3, 2022 (view preprint)
- Accepted: July 7, 2022
- Accepted Manuscript published: July 8, 2022 (version 1)
- Version of Record published: July 26, 2022 (version 2)
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: a meta-analysis within diverse populations
eLife 11:e78304.
https://doi.org/10.7554/eLife.78304
Further reading
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- Epidemiology and Global Health
Background:
Circulating omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) have been associated with various chronic diseases and mortality, but results are conflicting. Few studies examined the role of omega-6/omega-3 ratio in mortality.
Methods:
We investigated plasma omega-3 and omega-6 PUFAs and their ratio in relation to all-cause and cause-specific mortality in a large prospective cohort, the UK Biobank. Of 85,425 participants who had complete information on circulating PUFAs, 6461 died during follow-up, including 2794 from cancer and 1668 from cardiovascular disease (CVD). Associations were estimated by multivariable Cox proportional hazards regression with adjustment for relevant risk factors.
Results:
Risk for all three mortality outcomes increased as the ratio of omega-6/omega-3 PUFAs increased (all Ptrend <0.05). Comparing the highest to the lowest quintiles, individuals had 26% (95% CI, 15–38%) higher total mortality, 14% (95% CI, 0–31%) higher cancer mortality, and 31% (95% CI, 10–55%) higher CVD mortality. Moreover, omega-3 and omega-6 PUFAs in plasma were all inversely associated with all-cause, cancer, and CVD mortality, with omega-3 showing stronger effects.
Conclusions:
Using a population-based cohort in UK Biobank, our study revealed a strong association between the ratio of circulating omega-6/omega-3 PUFAs and the risk of all-cause, cancer, and CVD mortality.
Funding:
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institute of Health under the award number R35GM143060 (KY). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.
