Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival.

BACKGROUND: Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE: To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS: We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS: We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS: This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY: By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa.

Racial and Ethnic Differences in the Population-Attributable Fractions of Alzheimer Disease and Related Dementias.

BACKGROUND AND OBJECTIVES: Previous studies estimated that modifiable risk factors explain up to 40% of the dementia cases in the United States and that this population-attributable fraction (PAF) differs by race and ethnicity-estimates of future impact based on the risk factor prevalence in contemporary surveys. The aim of this study was to determine the race-specific and ethnicity-specific PAF of late-onset Alzheimer disease and related dementias (ADRDs) based on the risk factor prevalence and associations observed on the same individuals within a prospective cohort. METHODS: Data were from Multiethnic Cohort Study participants (African American, Japanese American, Latino, Native Hawaiian, and White) enrolled in Medicare Fee-for-Service. We estimated the PAF based on the prevalence of risk factors at cohort baseline and their mutually adjusted association with subsequent ADRD incidence. Risk factors included low educational attainment and midlife exposures to low neighborhood socioeconomic status, unmarried status, history of hypertension, stroke, diabetes or heart disease, smoking, physical inactivity, short or long sleep duration, obesity, and low-quality diet, as well as APOE ε4 for a subset. RESULTS: Among 91,881 participants (mean age 59.3 at baseline, 55.0% female participants), 16,507 incident ADRD cases were identified from Medicare claims (1999-2016, mean follow-up 9.3 years). The PAF for nongenetic factors combined was similar in men (24.0% [95% CI 21.3-26.6]) and women (22.8% [20.3-25.2]) but varied across Japanese American (14.2% [11.1-17.2]), White (21.9% [19.0-24.7]), African American (27.8% [22.3-33.0]), Native Hawaiian (29.3% [21.0-36.7]), and Latino (33.3% [27.5-38.5]) groups. The combined PAF was attenuated when accounting for competing risk of death, in both men (10.4%) and women (13.9%) and across racial and ethnic groups (4.7%-25.5%). The combined PAF was also different by age at diagnosis and ADRD subtypes, higher for younger (65-74 years: 43.2%) than older (75-84 years: 32.4%; ≥85 years: 11.3%) diagnoses and higher for vascular or unspecified ADRD than for AD or Lewy body dementia. An additional PAF of 11.8% (9.9-13.6) was associated with APOE ε4, which together with nongenetic risk factors accounted for 30.6% (25.8-35.1) of ADRD. DISCUSSION: Known risk factors explained about a third of the ADRD cases but with unequal distributions across racial and ethnic groups.

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

Polygenic Risk Score Modifies Prostate Cancer Risk of Pathogenic Variants in Men of African Ancestry.

Prostate cancer risk is influenced by rare and common germline variants. We examined the aggregate association of rare germline pathogenic/likely pathogenic/deleterious (P/LP/D) variants in ATM, BRCA2, PALB2, and NBN with a polygenic risk score (PRS) on prostate cancer risk among 1,796 prostate cancer cases (222 metastatic) and 1,424 controls of African ancestry. Relative to P/LP/D non-carriers at average genetic risk (33%-66% of PRS), men with low (0%-33%) and high (66%-100%) PRS had Odds Ratios (ORs) for overall prostate cancer of 2.08 [95% confidence interval (CI) = 0.58-7.49] and 18.06 (95% CI = 4.24-76.84) among P/LP/D carriers and 0.57 (95% CI = 0.46-0.71) and 3.02 (95% CI = 2.53-3.60) among non-carriers, respectively. The OR for metastatic prostate cancer was 2.73 (95% CI = 0.24-30.54) and 28.99 (95% CI = 4.39-191.43) among P/LP/D carriers and 0.54 (95% CI = 0.31-0.95) and 3.22 (95% CI = 2.20-4.73) among non-carriers, for men with low and high PRS, respectively. Lifetime absolute risks of overall prostate cancer increased with PRS (low to high) from 9.8% to 51.5% in P/LP/D carriers and 5.5% to 23.9% in non-carriers. Lifetime absolute risks of metastatic prostate cancer increased with PRS from 1.9% to 18.1% in P/LP/D carriers and 0.3% to 2.2% in non-carriers These findings suggest that assessment of prostate cancer risk for rare variant carriers should include PRS status. SIGNIFICANCE: These findings highlight the importance of considering rare and common variants to comprehensively assess prostate cancer risk in men of African ancestry.

Metabolomic epidemiology offers insights into disease aetiology.

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.

Germline Sequencing Analysis to Inform Clinical Gene Panel Testing for Aggressive Prostate Cancer.

Importance: Germline gene panel testing is recommended for men with advanced prostate cancer (PCa) or a family history of cancer. While evidence is limited for some genes currently included in panel testing, gene panels are also likely to be incomplete and missing genes that influence PCa risk and aggressive disease. Objective: To identify genes associated with aggressive PCa. Design, Setting, and Participants: A 2-stage exome sequencing case-only genetic association study was conducted including men of European ancestry from 18 international studies. Data analysis was performed from January 2021 to March 2023. Participants were 9185 men with aggressive PCa (including 6033 who died of PCa and 2397 with confirmed metastasis) and 8361 men with nonaggressive PCa. Exposure: Sequencing data were evaluated exome-wide and in a focused investigation of 29 DNA repair pathway and cancer susceptibility genes, many of which are included on gene panels. Main Outcomes and Measures: The primary study outcomes were aggressive (category T4 or both T3 and Gleason score ≥8 tumors, metastatic PCa, or PCa death) vs nonaggressive PCa (category T1 or T2 and Gleason score ≤6 tumors without known recurrence), and metastatic vs nonaggressive PCa. Results: A total of 17 546 men of European ancestry were included in the analyses; mean (SD) age at diagnosis was 65.1 (9.2) years in patients with aggressive PCa and 63.7 (8.0) years in those with nonaggressive disease. The strongest evidence of association with aggressive or metastatic PCa was noted for rare deleterious variants in known PCa risk genes BRCA2 and ATM (P ≤ 1.9 × 10-6), followed by NBN (P = 1.7 × 10-4). This study found nominal evidence (P < .05) of association with rare deleterious variants in MSH2, XRCC2, and MRE11A. Five other genes had evidence of greater risk (OR≥2) but carrier frequency differences between aggressive and nonaggressive PCa were not statistically significant: TP53, RAD51D, BARD1, GEN1, and SLX4. Deleterious variants in these 11 candidate genes were carried by 2.3% of patients with nonaggressive, 5.6% with aggressive, and 7.0% with metastatic PCa. Conclusions and Relevance: The findings of this study provide further support for DNA repair and cancer susceptibility genes to better inform disease management in men with PCa and for extending testing to men with nonaggressive disease, as men carrying deleterious alleles in these genes are likely to develop more advanced disease.

An epidemiological introduction to human metabolomic investigations.

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.

BACKGROUND: Genetic factors play an important role in prostate cancer (PCa) susceptibility. OBJECTIVE: To discover common genetic variants contributing to the risk of PCa in men of African ancestry. DESIGN, SETTING, AND PARTICIPANTS: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness. RESULTS AND LIMITATIONS: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4). CONCLUSIONS: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry. PATIENT SUMMARY: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals.

Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (radmix) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis radmix = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies.

Liver-Specific Polygenic Risk Score Is Associated with Alzheimer's Disease Diagnosis.

BACKGROUND: Our understanding of the pathophysiology underlying Alzheimer's disease (AD) has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. The use of functional annotation has been able to improve the power of genomic models. OBJECTIVE: We sought to leverage genomic functional annotations to build tissue-specific AD PRS models and study their relationship with AD and its biomarkers. METHODS: We built 13 tissue-specific AD PRS and studied the scores' relationships with AD diagnosis, cerebrospinal fluid (CSF) amyloid, CSF tau, and other CSF biomarkers in two longitudinal cohort studies of AD. RESULTS: The AD PRS model that was most predictive of AD diagnosis (even without APOE) was the liver AD PRS: n = 1,115; odds ratio = 2.15 (1.67-2.78), p = 3.62×10-9. The liver AD PRS was also statistically significantly associated with cerebrospinal fluid biomarker evidence of amyloid-ß (Aß42:Aß40 ratio, p = 3.53×10-6) and the phosphorylated tau:amyloid-ß ratio (p = 1.45×10-5). CONCLUSION: These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research.

Genetic variants associated with post-traumatic stress symptoms in patients with gynecologic cancer.

OBJECTIVE: Patients with cancer experience symptoms of post-traumatic stress disorder (PTSD) more commonly than the general population. The objective of this study was to identify single nucleotide polymorphisms (SNPs) associated with increased risk of post-traumatic stress disorder (PTSD) in patients with gynecologic cancer. METHODS: A prospective cohort study recruited 181 gynecologic cancer survivors receiving care at the University of Minnesota between 2017 and 2020 who completed PTSD DSM-V surveys to self-report their symptoms of PTSD and provided saliva samples. DNA samples were genotyped for 11 SNPs in 9 genes involved in dopaminergic, serotonergic, and opioidergic systems previously associated with risk of PTSD in populations without cancer. RESULTS: Most participants had either ovarian (42.5%) or endometrial (46.4%) cancer; fewer had cervical (7.7%) or vaginal/vulvar (3.3%) cancer. Two SNPS were identified as statistically significantly associated with higher PTSD scores: rs622337 in HTR2A and rs510769 in OPRM1. CONCLUSIONS: Genetic variation likely plays a role in development of PTSD. HTR2A is involved in the serotonin pathway, and OPRM1 is involved in the opioid receptor pathway. This information can be used by oncologic providers to identify patients at greater risk of developing PTSD and may facilitate referral to appropriate consultants and resources early in their treatment.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa.

BACKGROUND: Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa. RESULTS: Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608-0.707, OR 2.37-5.71) than for African individuals (AUC 0.502-0.585, OR 0.95-2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores. CONCLUSIONS: Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.

Association of Prostate-Specific Antigen Levels with Prostate Cancer Risk in a Multiethnic Population: Stability Over Time and Comparison with Polygenic Risk Score.

BACKGROUND: Studies in men of European ancestry suggest prostate-specific antigen (PSA) as a marker of early prostate cancer development that may help to risk-stratify men earlier in life. METHODS: We examined PSA levels in men measured up to 10+ years before a prostate cancer diagnosis in association with prostate cancer risk in 2,245 cases and 2,203 controls of African American, Latino, Japanese, Native Hawaiian, and White men in the Multiethnic Cohort. We also compared the discriminative ability of PSA to polygenic risk score (PRS) for prostate cancer. RESULTS: Excluding cases diagnosed within 2 and 10 years of blood draw, men with PSA above the median had a prostate cancer OR (95% CIs) of 9.12 (7.66-10.92) and 3.52 (2.50-5.03), respectively, compared with men with PSA below the median. A PSA level above the median identified 90% and 75% of cases diagnosed more than 2 and 10 years after blood draw, respectively. The associations were significantly greater for Gleason ≤7 versus 8+ disease. At 10+ years, the association of prostate cancer with PSA was comparable with that with the PRS [OR per SD increase: 1.88 (1.45-2.46) and 2.12 (1.55-2.93), respectively]. CONCLUSIONS: We found PSA to be an informative marker of prostate cancer risk at least a decade before diagnosis across multiethnic populations. This association was diminished with increasing time, greater for low grade tumors, and comparable with a PRS when measured 10+ years before diagnosis. IMPACT: Our multiethnic investigation suggests broad clinical implications on the utility of PSA and PRS for risk stratification in prostate cancer screening practices.

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

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 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 (8794 cases, 55,657 controls), and Hispanic (1082 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 nonaggressive 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 whether 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.