Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: A meta-analysis within diverse populations

Chen, Fei; Darst, Burcu F.; Madduri, Ravi; Rodríguez, Alex A.; Sheng, Xin; Rentsch, Christopher T; Andrews, Caroline; Tang, Wei; Kibel, Adam S.; Plym, Anna; Cho, Kelly; Jalloh, Mohamed; Gueye, Serigne; Niang, Lamine; Ogunbiyi, Olufemi J.; Popoola, Olufemi; Adebiyi, Akindele Olupelumi; Aisuodionoe-Shadrach, Oseremen I.; Ajibola, Hafees O.; Jamda, Mustapha A; Oluwole, Olabode P.; Nwegbu, Maxwell M.; Adusei, Ben; Mante, Sunny; Abrahams, Afua O.D.; Mensah, James E.; Adjei, Andrew A.; Diop, Halimatou; Lachance, Joseph; Rebbeck, Timothy R.; Ambs, Stefan; Gaziano, J. Michael; Justice, Amy C.; Conti, David V.; Haiman, Christopher A.

doi:10.7554/elife.78304

Cited by 25 publications

(18 citation statements)

References 25 publications

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“…It is worth noting that several trans‐ancestry PRSs have been developed to help account for variation outside of European populations 53,54 . However, even in these efforts that the largest contributor to these scores are European individuals, portability remains an issue.…”

Section: Polygenic Risk Scorementioning

confidence: 99%

“…It is worth noting that several trans-ancestry PRSs have been developed to help account for variation outside of European populations. 53,54 However, even in these efforts that the largest contributor to these scores are European individuals, portability remains an issue. Approaches such as incorporation of function annotation REVIEW to the score has been proposed to increase the portability across populations 55 as well as Bayesian approaches in creating transancestry scores.…”

Section: Polygenic Risk Scorementioning

confidence: 99%

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Multi‐Omics Studies in Historically Excluded Populations: The Road to Equity

Yang

Mishra

Perera

2023

Clin Pharma and Therapeutics

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Over the past few decades, genomewide association studies (GWASs) have identified the specific genetics variants contributing to many complex diseases by testing millions of genetic variations across the human genome against a variety of phenotypes. However, GWASs are limited in their ability to uncover mechanistic insight given that most significant associations are found in non‐coding region of the genome. Furthermore, the lack of diversity in studies has stymied the advance of precision medicine for many historically excluded populations. In this review, we summarize most popular multi‐omics approaches (genomics, transcriptomics, proteomics, and metabolomics) related to precision medicine and highlight if diverse populations have been included and how their findings have advance biological understanding of disease and drug response. New methods that incorporate local ancestry have been to improve the power of GWASs for admixed populations (such as African Americans and Latinx). Because most signals from GWAS are in the non‐coding region, other machine learning and omics approaches have been developed to identify the potential causative single‐nucleotide polymorphisms and genes that explain these phenotypes. These include polygenic risk scores, expression quantitative trait locus mapping, and transcriptome‐wide association studies. Analogous protein methods, such as proteins quantitative trait locus mapping, proteome‐wide association studies, and metabolomic approaches provide insight into the consequences of genetic variation on protein abundance. Whereas, integrated multi‐omics studies have improved our understanding of the mechanisms for genetic association, we still lack the datasets and cohorts for historically excluded populations to provide equity in precision medicine and pharmacogenomics.

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Section: Polygenic Risk Scorementioning

confidence: 99%

Section: Polygenic Risk Scorementioning

confidence: 99%

Multi‐Omics Studies in Historically Excluded Populations: The Road to Equity

Yang

Mishra

Perera

2023

Clin Pharma and Therapeutics

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“…Previous studies indicate a higher prevalence of alleles associated with PCa in the androgen receptors and the cytochrome P450 3A4 (CYP3A4) pathway [39,40].…”

Section: Genomic Researchmentioning

confidence: 99%

“…Recent data have indicated a good performance of polygenic risk score for PCa in multi-ancestry studies. A meta-analysis by Chen et al [40] included a sample of African men of whom 8794 were cases and 55 567 were controls. In that study, when comparing men in the top decile (90-100% of the polygenic risk score [PRS]) to the average 40-60% PRS category, the odds ratio of PCa was 2.8-fold in African ancestry men (95% CI 2.59-3.03).…”

Section: Genomic Researchmentioning

confidence: 99%

“…In that study, when comparing men in the top decile (90-100% of the polygenic risk score [PRS]) to the average 40-60% PRS category, the odds ratio of PCa was 2.8-fold in African ancestry men (95% CI 2.59-3.03). While progress have been made using PRS to predict PCa risk, there remain limits as to the possibilities in predicting aggressive vs indolent PCa in SSA populations [40,41].…”

Section: Genomic Researchmentioning

confidence: 99%

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Global viewpoints: updates on prostate cancer in Sub‐Saharan Africa

Jalloh,

Cassell,

Niang

et al. 2023

BJU International

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Prostate cancer (PCa) is a major health concern in Sub‐Saharan Africa (SSA), with high incidence and mortality rates. However, the widely used prostate‐specific antigen (PSA) screening is not readily available or affordable in SSA. Alternative screening strategies, such as risk stratification approaches and cost‐effective PSA tests, are being explored to target high‐risk individuals and improve access to screening. Diagnosis of PCa in SSA is challenging due to the lack of access to diagnostic tools and limited healthcare resources. Clinical evaluation and digital rectal examination are commonly used, but PSA testing, magnetic resonance imaging, and biopsy are often limited. As a result, many men in SSA are diagnosed at advanced stages of the disease. Treatment options for PCa in SSA are often limited by a lack of resources and trained healthcare providers. Surgery, radiation therapy, and androgen‐deprivation therapy are available but may be inaccessible to many patients. Cultural beliefs and stigma surrounding PCa further impact treatment decisions. Improved patient and community awareness, electronic medical records, and communication between patients and healthcare professionals can enhance evidence‐based decision‐making and advocate for policy changes. Understanding the genetic determinants and implementing comprehensive strategies can lead to improved outcomes and better control of PCa in SSA.

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Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk

Plym,

Zhang,

Stopsack

et al. 2024

JAMA Netw Open

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ImportanceProstate cancer, a leading cause of cancer death among men, urgently requires new prevention strategies, which may involve targeting men with an underlying genetic susceptibility.ObjectiveTo explore differences in risk of early prostate cancer death among men with higher vs lower genetic risk to inform prevention efforts.Design, Setting, and ParticipantsThis cohort study used a combined analysis of genotyped men without prostate cancer at inclusion and with lifestyle data in 2 prospective cohort studies in Sweden and the US, the Malmö Diet and Cancer Study (MDCS) and the Health Professionals Follow-Up Study (HPFS), followed up from 1991 to 2019. Data were analyzed between April 2023 and April 2024.ExposuresMen were categorized according to modifiable lifestyle behaviors and genetic risk. A polygenic risk score above the median or a family history of cancer defined men at higher genetic risk (67% of the study population); the remaining men were categorized as being at lower genetic risk.Main Outcomes and MeasuresProstate cancer death analyzed using time-to-event analysis estimating hazard ratios (HR), absolute risks, and preventable deaths by age.ResultsAmong the 19 607 men included for analysis, the median (IQR) age at inclusion was 59.0 (53.0-64.7) years (MDCS) and 65.1 (58.0-71.8) years (HPFS). During follow-up, 107 early (by age 75 years) and 337 late (after age 75 years) prostate cancer deaths were observed. Compared with men at lower genetic risk, men at higher genetic risk had increased rates of both early (HR, 3.26; 95% CI, 1.82-5.84) and late (HR, 2.26; 95% CI, 1.70-3.01) prostate cancer death, and higher lifetime risks of prostate cancer death (3.1% vs 1.3% [MDCS] and 2.3% vs 0.6% [HPFS]). Men at higher genetic risk accounted for 94 of 107 early prostate cancer deaths (88%), of which 36% (95% CI, 12%-60%) were estimated to be preventable through adherence to behaviors associated with a healthy lifestyle (not smoking, healthy weight, high physical activity, and a healthy diet).Conclusions and RelevanceIn this 20-year follow-up study, men with a genetic predisposition accounted for the vast majority of early prostate cancer deaths, of which one-third were estimated to be preventable. This suggests that men at increased genetic risk should be targeted in prostate cancer prevention strategies.

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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

Cited by 25 publications

References 25 publications

Multi‐Omics Studies in Historically Excluded Populations: The Road to Equity

Multi‐Omics Studies in Historically Excluded Populations: The Road to Equity

Global viewpoints: updates on prostate cancer in Sub‐Saharan Africa

Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk

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