scholarly journals Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank

2021 ◽  
Author(s):  
Louise Wang ◽  
Heena Desai ◽  
Shefali S. Verma ◽  
Anh Le ◽  
Ryan Hausler ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Genetic Factors ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Discriminatory Ability ◽  
Polygenic Risk ◽  
Genome Wide ◽  
European Populations

Purpose: Genome-wide association studies (GWAS) have identified hundreds of single nucleotide polymorphisms (SNPs) significantly associated with several cancers, but the predictive ability of polygenic risk scores (PRS) derived from multiple variants is unclear for many cancers, especially among non-European populations. Methods: Genome wide genotype data was available for 20,079 individuals enrolled in an academic biobank. PRS were derived from significant DNA variants for 15 cancers. Logistic regression was used to determine the discriminatory accuracy of each cancer-specific PRS in patients of genetically determined African and European ancestry separately. Results: Among European individuals, four PRS were significantly associated with their respective cancers (breast, colon, melanoma, and prostate), with an OR ranging from 1.25-1.47. Among African individuals, PRS for breast, colon, and prostate were significantly associated with their respective cancers. The discriminatory ability of a model comprised of age, sex, and principal components was 0.617–0.709, and the AUC increased by 1-4% with the addition of the PRS in Europeans. AUC was overall higher in the full model including PRS (AUC 0.742-0.818) in African individuals, but the PRS increased the AUC by less than 1% in the majority of cancers in African individuals. Conclusion: PRS constructed from SNPs moderately increased discriminatory ability for cancer status over age, sex, and nonspecific genetic factors in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors for cancer risk in non-European populations to incorporate PRS into cancer risk assessment.

scholarly journals Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  
...  
Keyword(s):  
Association Studies ◽  
Poor Performance ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Transcript Levels ◽  
Polygenic Risk ◽  
Genome Wide

Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

scholarly journals Evaluating the Utility of Polygenic Risk Scores in Identifying High-Risk Individuals for Eight Common Cancers

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Guochong Jia ◽  
Yingchang Lu ◽  
Wanqing Wen ◽  
Jirong Long ◽  
Ying Liu ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Association Studies ◽  
Elevated Risk ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cancer Case ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Genome Wide

Abstract Background Genome-wide association studies have identified common genetic risk variants in many loci associated with multiple cancers. We sought to systematically evaluate the utility of these risk variants in identifying high-risk individuals for eight common cancers. Methods We constructed polygenic risk scores (PRS) using genome-wide association studies–identified risk variants for each cancer. Using data from 400 812 participants of European descent in a population-based cohort study, UK Biobank, we estimated hazard ratios associated with PRS using Cox proportional hazard models and evaluated the performance of the PRS in cancer risk prediction and their ability to identify individuals at more than a twofold elevated risk, a risk level comparable to a moderate-penetrance mutation in known cancer predisposition genes. Results During a median follow-up of 5.8 years, 14 584 incident case patients of cancers were identified (ranging from 358 epithelial ovarian cancer case patients to 4430 prostate cancer case patients). Compared with those at an average risk, individuals among the highest 5% of the PRS had a two- to threefold elevated risk for cancer of the prostate, breast, pancreas, colorectal, or ovary, and an approximately 1.5-fold elevated risk of cancer of the lung, bladder, or kidney. The areas under the curve ranged from 0.567 to 0.662. Using PRS, 40.4% of the study participants can be classified as having more than a twofold elevated risk for at least one site-specific cancer. Conclusions A large proportion of the general population can be identified at an elevated cancer risk by PRS, supporting the potential clinical utility of PRS for personalized cancer risk prediction.

scholarly journals Polygenic transcriptome risk scores improve portability of polygenic risk scores across ancestries

2020 ◽  
Author(s):  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Prediction Models ◽  
Association Studies ◽  
Transcript Abundance ◽  
Effect Sizes ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Populations

AbstractPolygenic risk scores (PRS) are on course to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry, meaning that the utility of PRS for non-European populations is limited because SNP effects and LD patterns may not be conserved across populations. We hypothesized that cross population prediction at the level of genes rather than SNPs would be more effective, since the effect of genes on traits is likely to be more highly conserved. Therefore, we developed a framework to convert effect sizes at SNPs into effect sizes for genetically predicted transcript abundance, which we used for prediction in non-European populations. We compared this approach, which we call polygenic transcriptome risk scores (PTRS), to PRS, using data from 17 quantitative traits that were measured in multiple ancestries (European, African, East Asian, and South Asian) by UK Biobank. On average, PTRS using whole blood predicted transcriptome had lower absolute prediction accuracy than PRS, as we expected since not all regulatory processes were captured by a single tissue. However, as hypothesized, we found that in the African target set, the portability (prediction accuracy relative to the European reference set) was significantly higher for PTRS than PRS (p=0.03) with additional gain when transcriptomic prediction models ancestry matched the target population (p=0.021). Taken together, our results suggest that using PTRS can improve prediction in underrepresented populations and that increasing the diversity of transcriptomic data may be an effective way to improve portability of GWAS results between populations and help reduce health disparities.

scholarly journals Identification of Recessively Inherited Genetic Variants Potentially Linked to Pancreatic Cancer Risk

2021 ◽  
Vol 11 ◽  
Author(s):  
Ye Lu ◽  
Manuel Gentiluomo ◽  
Angelica Macauda ◽  
Domenica Gioffreda ◽  
Maria Gazouli ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Risk ◽  
Genetic Model ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
Cancer Case ◽  
Genome Wide Association Studies ◽  
Pancreatic Cancer Risk ◽  
Genome Wide

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p<10−5) compared with the additive effects (p>10−3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10−8). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores.

scholarly journals Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

scholarly journals Increasing Sample Diversity in Psychiatric Genetics – Introducing a new Cohort of Patients with Schizophrenia and Controls from Vietnam – Results from a Pilot Study

2021 ◽  
Author(s):  
VT Nguyen ◽  
A Braun ◽  
J Kraft ◽  
TMT Ta ◽  
GM Panagiotaropoulou ◽  
...  
Keyword(s):  
Pilot Study ◽  
Data Collection ◽  
Predictive Power ◽  
Association Studies ◽  
East Asian ◽  
Genetic Research ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractObjectivesGenome-Wide Association Studies (GWAS) of Schizophrenia (SCZ) have provided new biological insights; however, most cohorts are of European ancestry. As a result, derived polygenic risk scores (PRS) show decreased predictive power when applied to populations of different ancestries. We aimed to assess the feasibility of a large-scale data collection in Hanoi, Vietnam, contribute to international efforts to diversify ancestry in SCZ genetic research and examine the transferability of SCZ-PRS to individuals of Vietnamese Kinh ancestry.MethodsIn a pilot study, 368 individuals (including 190 SCZ cases) were recruited at the Hanoi Medical University’s associated psychiatric hospitals and outpatient facilities. Data collection included sociodemographic data, baseline clinical data, clinical interviews assessing symptom severity and genome-wide SNP genotyping. SCZ-PRS were generated using different training data sets: i) European, ii) East-Asian and iii) trans-ancestry GWAS summary statistics from the latest SCZ GWAS meta-analysis.ResultsSCZ-PRS significantly predicted case status in Vietnamese individuals using mixed-ancestry (R2 liability=4.9%, p=6.83*10−8), East-Asian (R2 liability=4.5%, p=2.73*10−7) and European (R2 liability=3.8%, p = 1.79*10−6) discovery samples.DiscussionOur results corroborate previous findings of reduced PRS predictive power across populations, highlighting the importance of ancestral diversity in GWA studies.

scholarly journals Perspective: The Clinical Use of Polygenic Risk Scores: Race, Ethnicity, and Health Disparities

2019 ◽  
Vol 29 (3) ◽  
pp. 513-516 ◽  
Author(s):  
Megan C. Roberts ◽  
Muin J. Khoury ◽  
George A. Mensah
Keyword(s):  
Precision Medicine ◽  
Association Studies ◽  
Clinical Care ◽  
Genomic Research ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Adverse Health Outcomes ◽  
Genome Wide ◽  
Disease Risks

Polygenic risk scores (PRS) are an emerging precision medicine tool based on multiple gene variants that, taken alone, have weak associations with disease risks, but collec­tively may enhance disease predictive value in the population. However, the benefit of PRS may not be equal among non-European populations, as they are under-represented in genome-wide association studies (GWAS) that serve as the basis for PRS develop­ment. In this perspective, we discuss a path forward, which includes: 1) inclusion of underrepresented populations in PRS research; 2) global efforts to build capacity for genomic research; 3) equitable imple­mentation of these tools in clinical practice; and 4) traditional public health approaches to reduce risk of adverse health outcomes as an important component to precision health. As precision medicine is imple­mented in clinical care, researchers must ensure that advances from PRS research will benefit all.Ethn Dis.2019;29(3):513-516; doi:10.18865/ed.29.3.513.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

Sign in / Sign up

Export Citation Format

Share Document