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 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 Cancer PRSweb – an Online Repository with Polygenic Risk Scores (PRS) for Major Cancer Traits and Their Phenome-wide Exploration in Two Independent Biobanks

2020 ◽  
Author(s):  
Lars G. Fritsche ◽  
Snehal Patil ◽  
Lauren J. Beesley ◽  
Peter VandeHaar ◽  
Maxwell Salvatore ◽  
...  
Keyword(s):  
Association Studies ◽  
Predictive Performance ◽  
Risk Scores ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Study Results

AbstractTo facilitate scientific collaboration on polygenic risk scores (PRS) research, we created an extensive PRS online repository for 49 common cancer traits integrating freely available genome-wide association studies (GWAS) summary statistics from three sources: published GWAS, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWAS. Our framework condenses these summary statistics into PRS using various approaches such as linkage disequilibrium pruning / p-value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRS in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance, calibration, and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRS. We expect this integrated platform to accelerate PRS-related cancer research.

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 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 Genome-wide association study of liking of physical activity in the UK Biobank

2021 ◽  
Author(s):  
Yann C. Klimentidis ◽  
Michelle Newell ◽  
Matthijs D. van der Zee ◽  
Victoria L. Bland ◽  
Sebastian May-Wilson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Wide Range ◽  
The Uk

A lack of physical activity (PA) is one of the most pressing health issues facing society today. Our individual propensity for PA is partly influenced by genetic factors. Stated liking of various PA behaviors may capture additional dimensions of PA behavior that are not captured by other measures, and contribute to our understanding of the genetics of PA behavior. Here, in over 157,000 individuals from the UK Biobank, we sought to complement and extend previous findings on the genetics of PA behavior by performing genome-wide association studies of self-reported liking of several PA-related behaviors plus an additional derived trait of overall PA-liking. We identified a total of 19 unique genome-wide significant loci across all traits, only four of which overlap with loci previously identified for PA behavior. The PA-liking traits were genetically correlated with self-reported (rg: 0.38 to 0.80) and accelerometry-derived (rg: 0.26 to 0.49) PA measures, and with a wide range of health-related traits and dietary behaviors. Replication in the Netherlands Twin Register (NTR; n>7,300) and the TwinsUK (n>1,300) study revealed directionally consistent associations. Polygenic risk scores (PRS) were then trained in UKB for each PA-liking trait and for self-reported PA behavior. The PA-liking PRS significantly predicted the same liking trait in NTR. The PRS for liking of going to the gym predicted PA behavior in NTR (r2 = 0.40%) nearly as well as the one constructed based on self-reported PA behavior (r2 = 0.42%). Combining the two PRS into a single model increased the r2 to 0.59%, suggesting that although these PRS correlate with each other, they are also capturing distinct dimensions of PA behavior. In conclusion, we have identified the first loci associated with PA-liking, and extended and refined our understanding of the genetic basis of PA behavior.

scholarly journals S173. GENOME-WIDE ASSOCIATION STUDIES OF SCHIZOPHRENIA AND BIPOLAR DISORDER IN A DIVERSE COHORT OF US VETERANS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S103-S103
Author(s):  
Tim Bigdeli ◽  
Ayman Fanous ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
Yuli Li ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Us Veterans

Abstract Background Schizophrenia and bipolar disorder are debilitating neuropsychiatric illnesses collectively affecting 2% of the world’s population, and which cause tremendous human suffering that impacts patients, their families and their communities. Recognizing the major impact of these disorders on the psychosocial function of more than 200,000 US Veterans, the Department of Veterans Affairs (VA) recently genotyping of nearly 9,000 veterans with schizophrenia or bipolar I disorder in Cooperative Studies Program (CSP) #572: “Genetics of Functional Disability in Schizophrenia and Bipolar Illness”, all of whom were extensively assessed for neurocognitive function and disability, and genotyped using a custom Affymetrix Axiom Biobank array. Methods Primary genome-wide association studies (GWAS) of schizophrenia and bipolar disorder were performed across and within ancestry goups, with attempted replication in matched subjects from the PGC and Genomic Psychiatry Cohort (GPC). We combined results for CSP#572 with available summary statistics from the PGC, Indonesia Schizophrenia Consortium and Genetic REsearch on schizophreniA neTwork-China and Netherland (GREAT-CN) study, and multi-ethnic GPC cohorts, achieving among the largest and most diverse studies of these disorders to date. Results Polygenic risk scores based on published PGC summary statistics for schizophrenia or bipolar disorder were significantly associated with case status among EA (P<10–30) and AA (P<0.0005) participants in CSP#572. Our primary analyses of schizophrenia yielded a single genome-wide significant association with variants in CHD7 at 8q12.2 for European-American (EA) participants, which remained significant in a joint analysis of EA and African-American (AA) subjects (P=4.62e-08). While no genome-wide significant associations were detected by our within-ancestry analyses of bipolar disorder, a cross-ancestry meta-analysis of CSP#572 participants yielded a significant finding at 10q25 with variants in SORCS3 (P=2.62e-08). Among loci attaining P<0.0001 in our within-ancestry analyses, 4 and 8 subsequently achieved genome-wide significance, respectively, when jointly analyzed with matched subjects from the PGC and GPC. Combining our results with published summary statistics, we performed a cross-ancestry GWAS meta-analysis of 69,280 schizophrenia cases and 138,379 controls, identifying 200 genome-wide significant loci of which 76 are newly reported here. Cross-ancestry analysis of 28,326 bipolar cases and 90,570 controls identified 24 genome-wide significant loci, including novel associations with common variants in PAX5, DOCK2, MACROD2, BRE, KCNG1, and LINC01378. Discussion We newly describe genome-wide analyses in a diverse cohort of US Veterans with schizophrenia or bipolar disorder, benchmarking the predictive value of polygenic risk scores based on published GWAS findings. Leveraging available summary statistics from studies of global populations, we add to burgeoning lists of genomic loci implicated in the etiologies of these disorders.

scholarly journals Could personalised risk prediction for type 2 diabetes using polygenic risk scores direct prevention, enhance diagnostics, or improve treatment?

2020 ◽  
Vol 5 ◽  
pp. 206
Author(s):  
Mathilde Boecker ◽  
Alvina G. Lai
Keyword(s):  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Large Scale ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

Over the past three decades, the number of people globally with diabetes mellitus has more than doubled. It is estimated that by 2030, 439 million people will be suffering from the disease, 90-95% of whom will have type 2 diabetes (T2D). In 2017, 5 million deaths globally were attributable to T2D, placing it in the top 10 global causes of death. Because T2D is a result of both genetic and environmental factors, identification of individuals with high genetic risk can help direct early interventions to prevent progression to more serious complications. Genome-wide association studies have identified ~400 variants associated with T2D that can be used to calculate polygenic risk scores (PRS). Although PRSs are not currently more accurate than clinical predictors and do not yet predict risk with equal accuracy across all ethnic populations, they have several potential clinical uses. Here, we discuss potential usages of PRS for predicting T2D and for informing and optimising interventions. We also touch on possible health inequality risks of PRS and the feasibility of large-scale implementation of PRS in clinical practice. Before PRSs can be used as a therapeutic tool, it is important that further polygenic risk models are derived using non-European genome-wide association studies to ensure that risk prediction is accurate for all ethnic groups. Furthermore, it is essential that the ethical, social and legal implications of PRS are considered before their implementation in any context.

scholarly journals Comparison of Two Genome-Wide Association Studies for Heart Rate Response to Exercise from the UK Biobank

2021 ◽  
Author(s):  
Abhinav Thakral ◽  
Andrew D Paterson
Keyword(s):  
Heart Rate ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Post Exercise ◽  
Genome Wide ◽  
The Difference ◽  
The Uk

The short-term changes in heart rate (HR) during and after exercise are important physiologic traits mediated via the autonomic nervous system. Variations in these traits are associated with mortality from cardiovascular causes. We conducted a systematic review of genome-wide association studies for these traits (with >10,000 participants) with the aim of comparing Polygenic Risk Scores (PRS) from different studies. Additionally, we applied the STrengthening of Reporting of Genetic Association Studies (STREGA) statement for assessing the completeness of reporting of evidence. Our systematic search yielded two studies (Verweij et al. and Ramirez et al.) that met our inclusion criteria. Both were conducted on the UK Biobank. Both defined their exercise traits as the difference between resting HR and the maximum HR during exercise. Their recovery traits were defined differently. Verweij et al. defined 5 recovery traits as the differences between the peak HR during exercise and the HRs at 10-50 sec post exercise cessation. Ramirez et al. defined their recovery trait as the difference between peak HR during exercise and the minimum HR during the minute post exercise cessation. While Ramirez et al. divided their sample into discovery and replication subsets, Verweij et al. analyzed the whole sample together. In terms of results, there were several common SNPs identified between studies and traits. There was evidence for the phenomenon of winners curse operating for a SNP from the Ramirez studys HR recovery analysis. Many of the SNPs were mutually exclusive between the studies. However, there was a good agreement of PRS from the studies. The differences in the results could be attributed to the different exclusion criteria, analytic approaches, and definitions of traits used. Both studies had an under-representation of individuals of non-European ancestry compared to those of European ancestry. Further studies with proportionate representation of individuals of all ancestries would help address this gap.

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