scholarly journals Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

2019 ◽  
Author(s):  
Yan Zhang ◽  
Amber N. Wilcox ◽  
Haoyu Zhang ◽  
Parichoy Pal Choudhury ◽  
Douglas F. Easton ◽  
...  
Keyword(s):  
Association Studies ◽  
Disease Incidence ◽  
Effect Sizes ◽  
European Ancestry ◽  
Risk Scores ◽  
Average Risk ◽  
Genome Wide Association Studies ◽  
Lymphoid Leukemia ◽  
Polygenic Risk ◽  
Wide Range

AbstractWe analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

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 Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

2020 ◽  
Author(s):  
Evan A. Winiger ◽  
Jarrod M. Ellingson ◽  
Claire L. Morrison ◽  
Robin P. Corley ◽  
Joëlle A. Pasman ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Sleep Duration ◽  
Association Studies ◽  
Genetic Correlations ◽  
Cannabis Use ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Short Sleep Duration ◽  
Polygenic Risk

AbstractStudy ObjectivesEstimate the genetic relationship of cannabis use with sleep deficits and eveningness chronotype.MethodsWe used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk scores (PRSs) and estimated their ability to predict cannabis use behaviors using logistic regression. Summary statistics came from existing genome wide association studies (GWASs) of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family community-based studies (n = 796, male = 66%; mean age = 26.81). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms).ResultsSignificant genetic correlation between lifetime cannabis use and eveningness chronotype (rG = 0.24, p < 0.01), as well as between CUD and both short sleep duration (<7 h) (rG = 0.23, p = 0.02) and insomnia (rG = 0.20, p = 0.02). Insomnia PRS predicted earlier age of first cannabis use (β = −0.09, p = 0.02) and increased lifetime CUD symptom count use (β = 0.07, p = 0.03).ConclusionCannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.

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 On cross-ancestry cancer polygenic risk scores

PLoS Genetics ◽  
2021 ◽  
Vol 17 (9) ◽  
pp. e1009670
Author(s):  
Lars G. Fritsche ◽  
Ying Ma ◽  
Daiwei Zhang ◽  
Maxwell Salvatore ◽  
Seunggeun Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
South Asian ◽  
Disease Risk ◽  
Association Studies ◽  
East Asian ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Target Sample

Polygenic risk scores (PRS) can provide useful information for personalized risk stratification and disease risk assessment, especially when combined with non-genetic risk factors. However, their construction depends on the availability of summary statistics from genome-wide association studies (GWAS) independent from the target sample. For best compatibility, it was reported that GWAS and the target sample should match in terms of ancestries. Yet, GWAS, especially in the field of cancer, often lack diversity and are predominated by European ancestry. This bias is a limiting factor in PRS research. By using electronic health records and genetic data from the UK Biobank, we contrast the utility of breast and prostate cancer PRS derived from external European-ancestry-based GWAS across African, East Asian, European, and South Asian ancestry groups. We highlight differences in the PRS distributions of these groups that are amplified when PRS methods condense hundreds of thousands of variants into a single score. While European-GWAS-derived PRS were not directly transferrable across ancestries on an absolute scale, we establish their predictive potential when considering them separately within each group. For example, the top 10% of the breast cancer PRS distributions within each ancestry group each revealed significant enrichments of breast cancer cases compared to the bottom 90% (odds ratio of 2.81 [95%CI: 2.69,2.93] in European, 2.88 [1.85, 4.48] in African, 2.60 [1.25, 5.40] in East Asian, and 2.33 [1.55, 3.51] in South Asian individuals). Our findings highlight a compromise solution for PRS research to compensate for the lack of diversity in well-powered European GWAS efforts while recruitment of diverse participants in the field catches up.

scholarly journals Polygenic Risk Scores for Psychiatric Disorders Reveal Novel Clues About the Genetics of Disordered Gambling

2019 ◽  
Author(s):  
Thomas M. Piasecki ◽  
Ian R. Gizer ◽  
Wendy S. Slutske
Keyword(s):  
Psychiatric Disorders ◽  
Association Studies ◽  
Common Variant ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Adult Health ◽  
Disordered Gambling ◽  
Polygenic Risk ◽  
Common Genetic Variants

Background and Aims: Twin studies indicate that disordered gambling (DG) is heritable but are silent with respect to specific genes or pathways involved. Genome-wide association studies of other psychiatric disorders permit calculation of polygenic risk scores (PRS) that reflect the aggregated effects of common genetic variants contributing to risk for the target condition. We investigated whether gambling and DG are associated with PRSs for four psychiatric conditions found to be comorbid with DG in epidemiologic surveys. Design and Setting: Data were drawn from the Wave IV assessment of the National Longitudinal Study of Adolescent to Adult Health, a representative sample of adolescents recruited in 1994-5 and followed into young adulthood. Participants: Analyses were limited to unrelated individuals classified as having European ancestry based on analysis of genetic principal components (N = 5,215). Measurements: Participants were surveyed about lifetime gambling and DG. Genotyping data were used to construct PRSs quantifying participants’ common variant genetic risk for major depression (MDD), attention-deficit hyperactivity disorder (ADHD), bipolar disorder (BD), and schizophrenia (SCZ). Findings: Most participants (78.4%) reported ever having gambled, and 1.3% of those reported lifetime DG. Polygenic risk for BD was associated with decreased odds of lifetime gambling, OR = 0.93 [0.87, 0.99], p = .045, pseudo-R2(%) = 0.12. The SCZ PRS was associated with increased odds of DG, OR = 1.54 [1.07, 2.21], p = .020, pseudo-R2 (%) = 0.85. Polygenic risk for MDD and ADHD were not related to either gambling outcome. Conclusions: Common variant risk for SCZ is associated with DG. Investigating features common to both SCZ and DG might generate valuable clues about the genetically-influenced liabilities to DG.

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 Risk Scores for Cardio-renal-metabolic Diseases in the Penn Medicine Biobank

2019 ◽  
Author(s):  
R.L. Kember ◽  
A. Verma ◽  
S. Verma ◽  
A. Lucas ◽  
R. Judy ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Metabolic Diseases ◽  
Association Studies ◽  
African Ancestry ◽  
Treatment Strategies ◽  
European Ancestry ◽  
Risk Scores ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

AbstractCardio-renal-metabolic (CaReMe) conditions are common and the leading cause of mortality around the world. Genome-wide association studies have shown that these diseases are polygenic and share many genetic risk factors. Identifying individuals at high genetic risk will allow us to target prevention and treatment strategies. Polygenic risk scores (PRS) are aggregate weighted counts that can demonstrate an individual’s genetic liability for disease. However, current PRS are often based on European ancestry individuals, limiting the implementation of precision medicine efforts in diverse populations. In this study, we develop PRS for six diseases and traits related to cardio-renal-metabolic disease in the Penn Medicine Biobank. We investigate their performance in both European and African ancestry individuals, and identify genetic and phenotypic overlap within these conditions. We find that genetic risk is associated with the primary phenotype in both ancestries, but this does not translate into a model of predictive value in African ancestry individuals. We conclude that future research should prioritize genetic studies in diverse ancestries in order to address this disparity.

scholarly journals Polygenic risk prediction and SNCA haplotype analysis in a Latino Parkinson's disease cohort

2021 ◽  
Author(s):  
Douglas P. Loesch ◽  
Andrea RVR Horimoto ◽  
Irem Sarihan ◽  
Miguel Inca-Martinez ◽  
Emily Mason ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Risk Prediction ◽  
Association Studies ◽  
Gwas Data ◽  
European Ancestry ◽  
Risk Scores ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

Background: Large-scale Parkinson's disease (PD) genome-wide association studies (GWAS) and meta-analyses have, until recently, only been conducted on subjects with European-ancestry. Consequently, polygenic risk scores (PRS) constructed using PD GWAS data are likely to be less predictive when applied to non-European cohorts. Methods: Using GWAS data from Nalls et al. 2019, we constructed a PD PRS for a Latino PD cohort (LARGE-PD) and tested it for association with PD status. We validated the PRS performance through testing the PD PRS in an independent cohort of Latino PD patients and by repeating the PRS analysis in LARGE-PD with the addition of 440 external Peruvian controls. To explore the global distribution of PD PRS, we utilized 1000 Genomes Project (1KGP) and Peruvian Genome Project (PGP) data to estimate PD risk allele frequencies. We also tested SNCA haplotypes for association with PD risk using logistic regression in LARGE-PD and a European-ancestry PD cohort from the International Parkinson Disease Genomics Consortium (IPDGC). Results: The GWAS-significant PD PRS had an area under the receiver-operator curve (AUC) of 0.668 (95% CI: 0.640-0.695) and explained 2.8% of the phenotypic variance in LARGE-PD as determined via pseudo R2. The inclusion of external Peruvian data as controls mitigated this result, dropping the AUC 0.632 (95% CI: 0.607-0.657). In 1KGP Latinos, we found the PD PRS to exhibit a bias by ancestry. At the SNCA locus, haplotypes differ by ancestry. Ancestry-specific SNCA haplotypes are significantly associated with PD status in both LARGE-PD and the IPDGC cohort (p-value < 0.05). Apart from rs356182, these haplotypes share as little as 14% of their variants. Conclusion: The PD PRS has potential for PD risk prediction in Latinos, but variability caused by admixture patterns and bias in the PD PRS calculated using only European-ancestry data limits its utility. The inclusion of diverse subjects can help elucidate PD risk loci and improve risk prediction in non-European cohorts. In the case of the SNCA locus, by leveraging a Latino cohort, we provide orthogonal evidence for rs356182 causality.

scholarly journals Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bingxin Zhao ◽  
Yue Shan ◽  
Yue Yang ◽  
Zhaolong Yu ◽  
Tengfei Li ◽  
...  
Keyword(s):  
Association Analysis ◽  
Complex Traits ◽  
Association Studies ◽  
Brain Structures ◽  
Imaging Genetics ◽  
Risk Scores ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Wide Range

AbstractStructural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10−8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10−31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.

scholarly journals On Cross-ancestry Cancer Polygenic Risk Scores

2021 ◽  
Author(s):  
Lars G. Fritsche ◽  
Ying Ma ◽  
Daiwei Zhang ◽  
Maxwell Salvatore ◽  
Seunggeun Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
South Asian ◽  
Disease Risk ◽  
Association Studies ◽  
East Asian ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Target Sample

AbstractPolygenic risk scores (PRS) can provide useful information for personalized risk stratification and disease risk assessment, especially when combined with non-genetic risk factors. However, their construction depends on the availability of summary statistics from genome-wide association studies (GWAS) independent from the target sample. For best compatibility, it was reported that GWAS and the target sample should match in terms of ancestries. Yet, GWAS, especially in the field of cancer, often lack diversity and are predominated by European ancestry. This bias is a limiting factor in PRS research. By using electronic health records and genetic data from the UK Biobank, we contrast the utility of breast and prostate cancer PRS derived from external European-ancestry-based GWAS across African, East Asian, European, and South Asian ancestry groups. We highlight differences in the PRS distributions of these groups that are amplified when PRS methods condense hundreds of thousands of variants into a single score. While European-GWAS-derived PRS were not directly transferrable across ancestries on an absolute scale, we establish their predictive potential when considering them separately within each group. For example, the top 10% of the breast cancer PRS distributions within each ancestry group each revealed significant enrichments of breast cancer cases compared to the bottom 90% (odds ratio of 2.81 [95%CI: 2.69,2.93] in European, 2.88 [1.85, 4.48] in African, 2.60 [1.25, 5.40] in East Asian, and 2.33 [1.55, 3.51] in South Asian individuals). Our findings highlight a compromise solution for PRS research to compensate for the lack of diversity in well-powered European GWAS efforts while recruitment of diverse participants in the field catches up.

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