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  1. Csato V, Kadir SZSA, Khavandi K, Bennett H, Sugden S, Gurney AM, et al.
    Physiol Rep, 2019 Nov;7(22):e14260.
    PMID: 31782255 DOI: 10.14814/phy2.14260
    We investigated the biomechanical relationship between intraluminal pressure within small mesenteric resistance arteries, oxidant activation of PKG, Ca2+ sparks, and BK channel vasoregulation. Mesenteric resistance arteries from wild type (WT) and genetically modified mice with PKG resistance to oxidative activation were studied using wire and pressure myography. Ca2+ sparks and Ca2+ transients within vascular smooth muscle cells of intact arteries were characterized using high-speed confocal microscopy of intact arteries. Arteries were studied under conditions of varying intraluminal pressure and oxidation. Intraluminal pressure specifically, rather than the generic stretch of the artery, was necessary to activate the oxidative pathway. We demonstrated a graded step activation profile for the generation of Ca2+ sparks and also a functional "ceiling" for this pressure --sensitive oxidative pathway. During steady state pressure - induced constriction, any additional Ca2+ sensitive-K+ channel functional availability was independent of oxidant activated PKG. There was an increase in the amplitude, but not the Area under the Curve (AUC) of the caffeine-induced Ca2+ transient in pressurized arteries from mice with oxidant-resistant PKG compared with wild type. Overall, we surmise that intraluminal pressure within resistance arteries controls Ca2+ spark vasoregulation through a tightly controlled pathway with a graded onset switch. The pathway, underpinned by oxidant activation of PKG, cannot be further boosted by additional pressure or oxidation once active. We propose that these restrictive characteristics of pressure-induced Ca2+ spark vasoregulation confer stability for the artery in order to provide a constant flow independent of additional pressure fluctuations or exogenous oxidants.
  2. Karunamuni RA, Huynh-Le MP, Fan CC, Thompson W, Eeles RA, Kote-Jarai Z, et al.
    Prostate Cancer Prostatic Dis, 2021 Jun;24(2):532-541.
    PMID: 33420416 DOI: 10.1038/s41391-020-00311-2
    BACKGROUND: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

    MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

    RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

    CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

  3. Jalil AA, Triwahyono S, Adam SH, Rahim ND, Aziz MA, Hairom NH, et al.
    J Hazard Mater, 2010 Sep 15;181(1-3):755-62.
    PMID: 20538408 DOI: 10.1016/j.jhazmat.2010.05.078
    In this study, calcined Lapindo volcanic mud (LVM) was used as an adsorbent to remove an anionic dye, methyl orange (MO), from an aqueous solution by the batch adsorption technique. Various conditions were evaluated, including initial dye concentration, adsorbent dosage, contact time, solution pH, and temperature. The adsorption kinetics and equilibrium isotherms of the LVM were studied using pseudo-first-order and -second-order kinetic equations, as well as the Freundlich and Langmuir models. The experimental data obtained with LVM fits best to the Langmuir isotherm model and exhibited a maximum adsorption capacity (q(max)) of 333.3 mg g(-1); the data followed the second-order equation. The intraparticle diffusion studies revealed that the adsorption rates were not controlled only by the diffusion step. The thermodynamic parameters, such as the changes in enthalpy, entropy, and Gibbs free energy, showed that the adsorption is endothermic, random and spontaneous at high temperature. The results indicate that LVM adsorbs MO efficiently and could be utilized as a low-cost alternative adsorbent for the removal of anionic dyes in wastewater treatment.
  4. Loh KH, Lim KC, Then AY, Adam S, Leung AJ, Hu W, et al.
    Animals (Basel), 2023 Mar 09;13(6).
    PMID: 36978544 DOI: 10.3390/ani13061002
    The data provided in this article are partial fragments of the Cytochrome c oxidase subunit 1 mitochondrial gene (CO1) sequences of 175 tissues sampled from sharks and batoids collected from Malaysian waters, from June 2015 to June 2022. The barcoding was done randomly for six specimens from each species, so as to authenticate the code. We generated barcodes for 67 different species in 20 families and 11 orders. DNA was extracted from the tissue samples following the Chelex protocols and amplified by polymerase chain reaction (PCR) using the barcoding universal primers FishF2 and FishR2. A total of 654 base pairs (bp) of barcode CO1 gene from 175 samples were sequenced and analysed. The genetic sequences were blasted into the NCBI GenBank and Barcode of Life Data System (BOLD). A review of the blast search confirmed that there were 68 valid species of sharks and batoids that occurred in Malaysian waters. We provided the data of the COI gene mid-point rooting phylogenetic relation trees and analysed the genetic distances among infra-class and order, intra-species, inter-specific, inter-genus, inter-familiar, and inter-order. We confirmed the addition of Squalus edmundsi, Carcharhinus amboinensis, Alopias superciliosus, and Myliobatis hamlyni as new records for Malaysia. The establishment of a comprehensive CO1 database for sharks and batoids will help facilitate the rapid monitoring and assessment of elasmobranch fisheries using environmental DNA methods.
  5. Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2018 07;50(7):928-936.
    PMID: 29892016 DOI: 10.1038/s41588-018-0142-8
    Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.
  6. Schumacher FR, Olama AAA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al.
    Nat Genet, 2019 02;51(2):363.
    PMID: 30622367 DOI: 10.1038/s41588-018-0330-6
    In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
  7. Matejcic M, Saunders EJ, Dadaev T, Brook MN, Wang K, Sheng X, et al.
    Nat Commun, 2019 01 17;10(1):382.
    PMID: 30655571 DOI: 10.1038/s41467-019-08293-z
    The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.
  8. Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.
    Nat Genet, 2023 Dec;55(12):2065-2074.
    PMID: 37945903 DOI: 10.1038/s41588-023-01534-4
    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.
  9. Adams CD, Richmond R, Ferreira DLS, Spiller W, Tan V, Zheng J, et al.
    Cancer Epidemiol Biomarkers Prev, 2019 Jan;28(1):208-216.
    PMID: 30352818 DOI: 10.1158/1055-9965.EPI-18-0079
    BACKGROUND: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).

    METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

    RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

    CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

    IMPACT: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

  10. Darst BF, Shen J, Madduri RK, Rodriguez AA, Xiao Y, Sheng X, et al.
    medRxiv, 2023 May 15.
    PMID: 37292833 DOI: 10.1101/2023.05.12.23289860
    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.
  11. Darst BF, Shen J, Madduri RK, Rodriguez AA, Xiao Y, Sheng X, et al.
    Am J Hum Genet, 2023 Jul 06;110(7):1200-1206.
    PMID: 37311464 DOI: 10.1016/j.ajhg.2023.05.010
    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.
  12. Howson JMM, Zhao W, Barnes DR, Ho WK, Young R, Paul DS, et al.
    Nat Genet, 2017 Jul;49(7):1113-1119.
    PMID: 28530674 DOI: 10.1038/ng.3874
    Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.
  13. Dadaev T, Saunders EJ, Newcombe PJ, Anokian E, Leongamornlert DA, Brook MN, et al.
    Nat Commun, 2018 06 11;9(1):2256.
    PMID: 29892050 DOI: 10.1038/s41467-018-04109-8
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
  14. Yam MF, Loh YC, Tan CS, Khadijah Adam S, Abdul Manan N, Basir R
    Int J Mol Sci, 2018 Jul 24;19(8).
    PMID: 30042373 DOI: 10.3390/ijms19082164
    Pain has been considered as a concept of sensation that we feel as a reaction to the stimulus of our surrounding, putting us in harm's way and acting as a form of defense mechanism that our body has permanently installed into its system. However, pain leads to a huge chunk of finances within the healthcare system with continuous rehabilitation of patients with adverse pain sensations, which might reduce not only their quality of life but also their productivity at work setting back the pace of our economy. It may not look like a huge deal but factor in pain as an issue for majority of us, it becomes an economical burden. Although pain has been researched into and understood by numerous researches, from its definition, mechanism of action to its inhibition in hopes of finding an absolute solution for victims of pain, the pathways of pain sensation, neurotransmitters involved in producing such a sensation are not comprehensively reviewed. Therefore, this review article aims to put in place a thorough understanding of major pain conditions that we experience-nociceptive, inflammatory and physiologically dysfunction, such as neuropathic pain and its modulation and feedback systems. Moreover, the complete mechanism of conduction is compiled within this article, elucidating understandings from various researches and breakthroughs.
  15. Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al.
    Cancer Discov, 2016 Sep;6(9):1052-67.
    PMID: 27432226 DOI: 10.1158/2159-8290.CD-15-1227
    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.

    SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

  16. Szulkin R, Karlsson R, Whitington T, Aly M, Gronberg H, Eeles RA, et al.
    Cancer Epidemiol Biomarkers Prev, 2015 Nov;24(11):1796-800.
    PMID: 26307654 DOI: 10.1158/1055-9965.EPI-15-0543
    BACKGROUND: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical.

    METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).

    RESULTS: We observed no significant association between genetic variants and prostate cancer survival.

    CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study.

    IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.

  17. Matejcic M, Saunders EJ, Dadaev T, Brook MN, Wang K, Sheng X, et al.
    Nat Commun, 2018 Nov 05;9(1):4616.
    PMID: 30397198 DOI: 10.1038/s41467-018-06863-1
    Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p 
  18. Chowdhury R, Noh MFM, Ismail SR, van Daalen KR, Kamaruddin PSNM, Zulkiply SH, et al.
    JMIR Res Protoc, 2022 Feb 10;11(2):e31885.
    PMID: 35142634 DOI: 10.2196/31885
    BACKGROUND: Although the burden of premature myocardial infarction (MI) is high in Malaysia, direct evidence on the determinants of MI in this multi-ethnic population remains sparse.

    OBJECTIVE: The Malaysian Acute Vascular Events Risk (MAVERIK) study is a retrospective case-control study established to investigate the genomic, lipid-related, and other determinants of acute MI in Malaysia. In this paper, we report the study protocol and early results.

    METHODS: By June 2019, we had enrolled approximately 2500 patients with their first MI and 2500 controls without cardiovascular disease, who were frequency-matched by age, sex, and ethnicity, from 17 hospitals in Malaysia. For each participant, serum and whole blood have been collected and stored. Clinical, demographic, and behavioral information has been obtained using a 200-item questionnaire.

    RESULTS: Tobacco consumption, a history of diabetes, hypertension, markers of visceral adiposity, indicators of lower socioeconomic status, and a family history of coronary disease were more prevalent in cases than in controls. Adjusted (age and sex) logistic regression models for traditional risk factors indicated that current smoking (odds ratio [OR] 4.11, 95% CI 3.56-4.75; P30 kg/m2; OR 1.19, 95% CI 1.05-1.34; P=.009) were associated with MI in age- and sex-adjusted models.

    CONCLUSIONS: The MAVERIK study can serve as a useful platform to investigate genetic and other risk factors for MI in an understudied Southeast Asian population. It should help to hasten the discovery of disease-causing pathways and inform regionally appropriate strategies that optimize public health action.

    INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/31885.

  19. Huynh-Le MP, Fan CC, Karunamuni R, Thompson WK, Martinez ME, Eeles RA, et al.
    Nat Commun, 2021 02 23;12(1):1236.
    PMID: 33623038 DOI: 10.1038/s41467-021-21287-0
    Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p 
  20. Huynh-Le MP, Karunamuni R, Fan CC, Asona L, Thompson WK, Martinez ME, et al.
    Prostate Cancer Prostatic Dis, 2022 Apr;25(4):755-761.
    PMID: 35152271 DOI: 10.1038/s41391-022-00497-7
    BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.

    METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.

    RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.

    CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

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