Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.
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ABSTRACT:
SUBMITTER: Huynh-Le MP
PROVIDER: S-EPMC7902617 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
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Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.
Huynh-Le Minh-Phuong MP Fan Chun Chieh CC Karunamuni Roshan R Thompson Wesley K WK Martinez Maria Elena ME Eeles Rosalind A RA Kote-Jarai Zsofia Z Muir Kenneth K Schleutker Johanna J Pashayan Nora N Batra Jyotsna J Grönberg Henrik H Neal David E DE Donovan Jenny L JL Hamdy Freddie C FC Martin Richard M RM Nielsen Sune F SF Nordestgaard Børge G BG Wiklund Fredrik F Tangen Catherine M CM Giles Graham G GG Wolk Alicja A Albanes Demetrius D Travis Ruth C RC Blot William J WJ Zheng Wei W Sanderson Maureen M Stanford Janet L JL Mucci Lorelei A LA West Catharine M L CML Kibel Adam S AS Cussenot Olivier O Berndt Sonja I SI Koutros Stella S Sørensen Karina Dalsgaard KD Cybulski Cezary C Grindedal Eli Marie EM Menegaux Florence F Khaw Kay-Tee KT Park Jong Y JY Ingles Sue A SA Maier Christiane C Hamilton Robert J RJ Thibodeau Stephen N SN Rosenstein Barry S BS Lu Yong-Jie YJ Watya Stephen S Vega Ana A Kogevinas Manolis M Penney Kathryn L KL Huff Chad C Teixeira Manuel R MR Multigner Luc L Leach Robin J RJ Cannon-Albright Lisa L Brenner Hermann H John Esther M EM Kaneva Radka R Logothetis Christopher J CJ Neuhausen Susan L SL De Ruyck Kim K Pandha Hardev H Razack Azad A Newcomb Lisa F LF Fowke Jay H JH Gamulin Marija M Usmani Nawaid N Claessens Frank F Gago-Dominguez Manuela M Townsend Paul A PA Bush William S WS Roobol Monique J MJ Parent Marie-Élise MÉ Hu Jennifer J JJ Mills Ian G IG Andreassen Ole A OA Dale Anders M AM Seibert Tyler M TM
Nature communications 20210223 1
Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS<sub>1</sub>) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS<sub>2</sub> (PHS<sub>1</sub>, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS<sub>2</sub> is associated with age at diagnosis of any and aggr ...[more]
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Project description:Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.
| S-EPMC8135907 | biostudies-literature
Project description:ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
| S-EPMC5759091 | biostudies-literature
Project description:BackgroundLate-onset Alzheimer's disease (AD) is a polygenic neurodegenerative disease. Identifying the neuroimaging phenotypes behind the genetic predisposition of AD is critical to the understanding of AD pathogenesis. Two major questions which previous studies have led to are: (1) should the general "polygenic hazard score" (PHS) be a good choice to identify the individual genetic risk for AD; and (2) should researchers also include inter-modality relationships in the analyses considering these may provide complementary information about the AD etiology.MethodsWe collected 88 healthy controls, 77 patients with mild cognitive impairment (MCI), and 22 AD patients to simulate the AD continuum included from the ADNI database. PHS-guided multimodal fusion was used to investigate the impact of PHS on multimodal brain networks in AD-continuum by maximizing both inter-modality association and reference-modality correlation. Fractional amplitude of low frequency fluctuations, gray matter (GM) volume, and amyloid standard uptake value ratios were included as neuroimaging features. Eventually, the changes in neuroimaging features along AD continuum were investigated, and relationships between cognitive performance and identified PHS associated multimodal components were established.ResultsWe found that PHS was associated with multimodal brain networks, which showed different functional and structural impairments under increased amyloid deposits. Notably, along with AD progression, functional impairment occurred before GM atrophy, amyloid deposition started from the MCI stage and progressively increased throughout the disease continuum.ConclusionPHS is associated with multi-facets of brain impairments along the AD continuum, including cognitive dysfunction, pathological deposition, which might underpin the AD pathogenesis.
| S-EPMC8446666 | biostudies-literature
Project description:BackgroundWe 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.MethodsWithin 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.ResultsThe 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.ConclusionsOur 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.FundingThis 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.
| S-EPMC9322982 | biostudies-literature
Project description:Mounting evidence indicates that the polygenic basis of late-onset Alzheimer's disease can be harnessed to identify individuals at greatest risk for cognitive decline. We have previously developed and validated a polygenic hazard score comprising of 31 single nucleotide polymorphisms for predicting Alzheimer's disease dementia age of onset. In this study, we examined whether polygenic hazard scores are associated with: (i) regional tracer uptake using amyloid PET; (ii) regional volume loss using longitudinal MRI; (iii) post-mortem regional amyloid-β protein and tau associated neurofibrillary tangles; and (iv) four common non-Alzheimer's pathologies. Even after accounting for APOE, we found a strong association between polygenic hazard scores and amyloid PET standard uptake volume ratio with the largest effects within frontal cortical regions in 980 older individuals across the disease spectrum, and longitudinal MRI volume loss within the entorhinal cortex in 607 older individuals across the disease spectrum. We also found that higher polygenic hazard scores were associated with greater rates of cognitive and clinical decline in 632 non-demented older individuals, even after controlling for APOE status, frontal amyloid PET and entorhinal cortex volume. In addition, the combined model that included polygenic hazard scores, frontal amyloid PET and entorhinal cortex volume resulted in a better fit compared to a model with only imaging markers. Neuropathologically, we found that polygenic hazard scores were associated with regional post-mortem amyloid load and neuronal neurofibrillary tangles, even after accounting for APOE, validating our imaging findings. Lastly, polygenic hazard scores were associated with Lewy body and cerebrovascular pathology. Beyond APOE, we show that in living subjects, polygenic hazard scores were associated with amyloid deposition and neurodegeneration in susceptible brain regions. Polygenic hazard scores may also be useful for the identification of individuals at the highest risk for developing multi-aetiological dementia.
| S-EPMC6351776 | biostudies-literature
Project description:There is an urgent need for identifying nondemented individuals at the highest risk of progressing to Alzheimer's disease (AD) dementia. Here, we evaluated whether a recently validated polygenic hazard score (PHS) can be integrated with known in vivo cerebrospinal fluid (CSF) or positron emission tomography (PET) biomarkers of amyloid, and CSF tau pathology to prospectively predict cognitive and clinical decline in 347 cognitive normal (CN; baseline age range = 59.7-90.1, 98.85% white) and 599 mild cognitively impaired (MCI; baseline age range = 54.4-91.4, 98.83% white) individuals from the Alzheimer's Disease Neuroimaging Initiative 1, GO, and 2. We further investigated the association of PHS with post-mortem amyloid load and neurofibrillary tangles in the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 485, age at death range = 71.3-108.3). In CN and MCI individuals, we found that amyloid and total tau positivity systematically varies as a function of PHS. For individuals in greater than the 50th percentile PHS, the positive predictive value for amyloid approached 100%; for individuals in less than the 25th percentile PHS, the negative predictive value for total tau approached 85%. High PHS individuals with amyloid and tau pathology showed the steepest longitudinal cognitive and clinical decline, even among APOE ε4 noncarriers. Among the CN subgroup, we similarly found that PHS was strongly associated with amyloid positivity and the combination of PHS and biomarker status significantly predicted longitudinal clinical progression. In the ROSMAP cohort, higher PHS was associated with higher post-mortem amyloid load and neurofibrillary tangles, even in APOE ε4 noncarriers. Together, our results show that even after accounting for APOE ε4 effects, PHS may be useful in MCI and preclinical AD therapeutic trials to enrich for biomarker-positive individuals at highest risk for short-term clinical progression.
| S-EPMC5758038 | biostudies-literature
Project description:IntroductionSuperAgers are individuals over age 80 with superior episodic memory, at a level consistent with individuals 20 to 30 years their junior and who seem to show resistance to age-related neurofibrillary degeneration. Here we examine whether low genetic risk for Alzheimer's disease (AD) contributes to SuperAgers' unusually high episodic memory performance in advanced age.MethodsThe AD polygenic hazard score (PHS) was calculated for each SuperAger and cognitively normal participant and compared between groups.ResultsA total of 37 SuperAgers (73% female, mean [standard deviation] 82.7 [2.8] years old) and 35 controls (54% female, 83.7 [4.3] years old) were included. There was no significant difference in the AD PHS between SuperAgers and cognitively normal controls.DiscussionUnusually successful cognitive aging cannot be simply explained by low polygenic risk for AD as assessed by common genetic variants. However, rare variants and common protective genetic factors may contribute to resistance or resilience.HighlightsSuperAging cannot be simply explained by low polygenic risk for Alzheimer's disease.Rare variants and common protective genetic factors may contribute to SuperAging.A protective factors polygenic score may uncover mechanisms for SuperAging.
| S-EPMC9345399 | biostudies-literature
Project description:BackgroundGenome-wide association studies have identified over 100 single-nucleotide polymorphisms (SNPs) associated with prostate cancer (PrCa), and polygenic risk scores (PRS) based on their combined genotypes have been developed for risk stratification. We aimed to assess the contribution of PRS to PrCa risk in a large multisite study.MethodsThe sample included 1972 PrCa cases and 1919 unaffected controls. Next-generation sequencing was used to assess pathogenic variants in 14 PrCa-susceptibility genes and 72 validated PrCa-associated SNPs. We constructed a population-standardized PRS and tested its association with PrCa using logistic regression adjusted for age and family history of PrCa.ResultsThe mean age of PrCa cases at diagnosis and age of controls at testing/last clinic visit was 59.5 ± 7.2 and 57.2 ± 13.0 years, respectively. Among 1740 cases with pathology data, 57.4% had Gleason score ≤ 6, while 42.6% had Gleason score ≥ 8. In addition, 39.6% cases and 20.1% controls had a family history of PrCa. The PRS was significantly higher in cases than controls (mean ± SD: 1.42 ± 1.11 vs 1.02 ± 0.76; P < .0001). Compared with men in the 1st quartile of age-adjusted PRS, those in the 2nd, 3rd, and 4th quartile were 1.58 (95% confidence interval [CI]: 1.31-1.90), 2.36 (95% CI: 1.96-2.84), and 3.98 (95% CI: 3.29-4.82) times as likely to have PrCa (all P < .0001). Adjustment for family history yielded similar results. PRS predictive performance was consistent with prior literature (area under the receiver operating curve = 0.64; 95% CI: 0.62-0.66).ConclusionsThese data suggest that a 72-SNP PRS is predictive of PrCa, supporting its potential use in clinical risk assessment.
| S-EPMC7590110 | biostudies-literature
Project description:Decreasing costs of genetic testing and interest in disease inheritance has changed the landscape of cancer prediction in prostate cancer (PCa), and guidelines now include genetic testing for high-risk groups. Familial and hereditary PCa comprises approximately 20% and 5% of all PCa, respectively. Multifaceted disorders like PCa are caused by a combinatory effect of rare genes of high penetrance and smaller genetic variants of relatively lower effect size. Polygenic risk score (PRS) is a novel tool utilizing PCa-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association study (GWAS) to generate an additive estimate of an individual's lifetime genetic risk for cancer. However, most PRS are developed based on GWAS collected from mainly European populations and do not address ethnic differences in PCa genetics. This review highlights the attempts to generate a PRS tailored to Asian males including data from Korea, China, and Japan, and discuss the clinical implications for prediction of early onset and aggressive PCa.
| S-EPMC8100017 | biostudies-literature
Project description:We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.
| S-EPMC7608255 | biostudies-literature