scholarly journals Pathway specific polygenic risk scores identify pathways and patient clusters associated with inflammatory bowel disease risk, severity and treatment response

2021 ◽  
Author(s):  
Corneliu A Bodea ◽  
Michael Macoritto ◽  
Yingchun Liu ◽  
Wenliang Zhang ◽  
Jozsef Karman ◽  
...  
Keyword(s):  
Treatment Response ◽  
Genetic Risk ◽  
Disease Risk ◽  
Clinical Care ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Stratification Method ◽  
Inflammatory Bowel

Crohn's disease (CD) and ulcerative colitis (UC) are inflammatory bowel diseases (IBD) with a strong genetic component. Genome-wide association studies (GWAS) have successfully identified over 240 genetic loci that are statistically associated with risk of developing IBD, and these associations provide valuable insights into disease pathobiology. Building on GWAS findings, conventional polygenic risk scores (cPRS) aim to quantify the aggregated disease risk based on DNA variation, and these scores can identify individuals at high risk. While stratifying individuals based on cPRS has the potential to inform clinical care, the development of novel therapeutics requires deep insight into how aggregated genetic risk leads to disruption of specific biological pathways. Here, we developed a pathway-specific PRS (pPRS) methodology to assess IBD common variant genetic risk burden across 31 manually curated pathways. We first prioritized 206 genes based on comprehensive fine-mapping and eQTL colocalization analyses of genome-wide significant IBD GWAS loci and 58 highly penetrant genes based on their involvement in early onset IBD or autoimmunity-related colitis. These 264 genes were assigned to at least one of the 31 pathways based on Gene Ontology annotations and manual curation. Finally, we integrated these inputs into a novel pPRS model and performed an extensive investigation of IBD disease risk, severity, complications, and anti-TNF treatment response by applying our pPRS approach to three complementary datasets encompassing IBD cases and controls. Our analysis identified multiple promising pathways that can inform drug target discovery and provides a patient stratification method that offers insights into the biology of treatment response.

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.

scholarly journals Impute.me: an open source, non-profit tool for using data from DTC genetic testing to calculate and interpret polygenic risk scores

2019 ◽  
Author(s):  
Lasse Folkersen ◽  
Oliver Pain ◽  
Andres Ingasson ◽  
Thomas Werge ◽  
Cathryn M. Lewis ◽  
...  
Keyword(s):  
Open Source ◽  
Public Perception ◽  
Disease Risk ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Complex Disorders ◽  
Risk Variants ◽  
Genome Wide ◽  
The Impact

AbstractTo date, interpretation of genomic information has focused on single variants conferring disease risk, but most disorders of major public concern have a polygenic architecture. Polygenic risk scores (PRS) give a single measure of disease liability by summarising disease risk across hundreds of thousands of genetic variants. They can be calculated in any genome-wide genotype data-source, using a prediction model based on genome-wide summary statistics from external studies.As genome-wide association studies increase in power, the predictive ability for disease risk will also increase. While PRS are unlikely ever to be fully diagnostic, they may give valuable medical information for risk stratification, prognosis, or treatment response prediction.Public engagement is therefore becoming important on the potential use and acceptability of PRS. However, the current public perception of genetics is that it provides ‘Yes/No’ answers about the presence/absence of a condition, or the potential for developing a condition, which in not the case for common, complex disorders with of polygenic architecture.Meanwhile, unregulated third-party applications are being developed to satisfy consumer demand for information on the impact of lower risk variants on common diseases that are highly polygenic. Often applications report results from single SNPs and disregard effect size, which is highly inappropriate for common, complex disorders where everybody carries risk variants.Tools are therefore needed to communicate our understanding of genetic predisposition as a continuous trait, where a genetic liability confers risk for disease. Impute.me is one such a tool, whose focus is on education and information on common, complex disorders with polygenetic architecture. Its research-focused open-source website allows users to upload consumer genetics data to obtain PRS, with results reported on a population-level normal distribution. Diseases can only be browsed by ICD10-chapter-location or alphabetically, thus prompting the user to consider genetic risk scores in a medical context of relevance to the individual.Here we present an overview of the implementation of the impute.me site, along with analysis of typical usage-patterns, which may advance public perception of genomic risk and precision medicine.

scholarly journals Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring

2021 ◽  
Author(s):  
Sophia Gunn ◽  
Michael Wainberg ◽  
Zeyuan Song ◽  
Stacy Andersen ◽  
Robert Boudreau ◽  
...  
Keyword(s):  
General Population ◽  
Genetic Risk ◽  
Disease Risk ◽  
Association Studies ◽  
Risk Scores ◽  
Human Longevity ◽  
Genome Wide Association Studies ◽  
Predictive Values ◽  
Polygenic Risk ◽  
Polygenic Scores

Background: A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict risk of disease than individual significant variants alone. Methods: We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring and controls and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting ancestral background of the individuals (PCs). In our analyses we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. Results: We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD), coronary artery disease (CAD) and systemic lupus than controls, suggesting genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function. In addition, the PRS for AD was associated with higher risk of dementia among controls but not ELLIs (p = 0.0004, 0.3 in NECS, p = 0.03, 0.93 in LLFS respectively). Interestingly, ELLIs did not have a larger number of homozygous risk genotypes for AD (TNECS = -1.72, TLLFs = 0.83) and CAD (TNECS = -5.08, TLLFs = -0.31) in both cohorts, but did have significantly larger number of homozygous protective genotypes than controls for the two traits (AD: TNECS =3.10, TLLFs = 2.2, CAD: TNECS = 6.57, TLLFs =2.36, respectively). Conclusions: ELLIs have a similar burden of genetic disease risk as the general population for most traits, but have significantly lower genetic risk of AD, CAD, and lupus. The lack of association between AD PRS and dementia among ELLIs suggests that their genetic risk for AD is somehow buffered by protective genetic or environmental factors.

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 Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

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]

scholarly journals Dissociable influences of APOE ε4 and polygenic risk of AD dementia on amyloid and cognition

Neurology ◽  
2018 ◽  
Vol 90 (18) ◽  
pp. e1605-e1612 ◽  
Author(s):  
Tian Ge ◽  
Mert R. Sabuncu ◽  
Jordan W. Smoller ◽  
Reisa A. Sperling ◽  
Elizabeth C. Mormino ◽  
...  
Keyword(s):  
Cognitive Decline ◽  
Genetic Risk ◽  
Large Scale ◽  
Association Studies ◽  
Specific Effect ◽  
Hippocampal Volume ◽  
Risk Scores ◽  
Hippocampal Atrophy ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

ObjectiveTo investigate the effects of genetic risk of Alzheimer disease (AD) dementia in the context of β-amyloid (Aβ) accumulation.MethodsWe analyzed data from 702 participants (221 clinically normal, 367 with mild cognitive impairment, and 114 with AD dementia) with genetic data and florbetapir PET available. A subset of 669 participants additionally had longitudinal MRI scans to assess hippocampal volume. Polygenic risk scores (PRSs) were estimated with summary statistics from previous large-scale genome-wide association studies of AD dementia. We examined relationships between APOE ε4 status and PRS with longitudinal Aβ and cognitive and hippocampal volume measurements.ResultsAPOE ε4 was strongly related to baseline Aβ, whereas only weak associations between PRS and baseline Aβ were present. APOE ε4 was additionally related to greater memory decline and hippocampal atrophy in Aβ+ participants. When APOE ε4 was controlled for, PRS was related to cognitive decline in Aβ+ participants. Finally, PRSs were associated with hippocampal atrophy in Aβ− participants and weakly associated with baseline hippocampal volume in Aβ+ participants.ConclusionsGenetic risk factors of AD dementia demonstrate effects related to Aβ, as well as synergistic interactions with Aβ. The specific effect of faster cognitive decline in Aβ+ individuals with higher genetic risk may explain the large degree of heterogeneity in cognitive trajectories among Aβ+ individuals. Consideration of genetic variants in conjunction with baseline Aβ may improve enrichment strategies for clinical trials targeting Aβ+ individuals most at risk for imminent cognitive decline.

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.

Sign in / Sign up

Export Citation Format

Share Document