scholarly journals PCA-based GRS analysis enhances the effectiveness for genetic correlation detection

2018 ◽  
Vol 20 (6) ◽  
pp. 2291-2298
Author(s):  
Yan Zhao ◽  
Yujie Ning ◽  
Feng Zhang ◽  
Miao Ding ◽  
Yan Wen ◽  
...  
Keyword(s):  
Risk Score ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Genetic Risk Score ◽  
Complex Diseases ◽  
Principal Component ◽  
Analysis Approach ◽  
Polygenic Risk Score ◽  
Multiple Testing Correction ◽  
Improved Performance

Abstract Genetic risk score (GRS, also known as polygenic risk score) analysis is an increasingly popular method for exploring genetic architectures and relationships of complex diseases. However, complex diseases are usually measured by multiple correlated phenotypes. Analyzing each disease phenotype individually is likely to reduce statistical power due to multiple testing correction. In order to conquer the disadvantage, we proposed a principal component analysis (PCA)–based GRS analysis approach. Extensive simulation studies were conducted to compare the performance of PCA-based GRS analysis and traditional GRS analysis approach. Simulation results observed significantly improved performance of PCA-based GRS analysis compared to traditional GRS analysis under various scenarios. For the sake of verification, we also applied both PCA-based GRS analysis and traditional GRS analysis to a real Caucasian genome-wide association study (GWAS) data of bone geometry. Real data analysis results further confirmed the improved performance of PCA-based GRS analysis. Given that GWAS have flourished in the past decades, our approach may help researchers to explore the genetic architectures and relationships of complex diseases or traits.

scholarly journals P820 An easy and rapid targeted next generation sequencing-based genotyping assay for the validated IBD risk loci

2020 ◽  
Vol 14 (Supplement_1) ◽  
pp. S637-S638
Author(s):  
S Verstockt ◽  
L Hannes ◽  
S Deman ◽  
W J Wollants ◽  
E Souche ◽  
...  
Keyword(s):  
Risk Score ◽  
Performance Metrics ◽  
Genetic Risk Score ◽  
Cost Effective ◽  
Polygenic Risk Score ◽  
Call Rate ◽  
Susceptibility Loci ◽  
Polygenic Risk ◽  
Genotyping Assay ◽  
Genotyping Call Rate

Abstract Background Inflammatory bowel diseases (IBD) are complex genetic diseases for which 242 susceptibility loci have been identified thus far. For translational or functional follow-up studies it can be of interest to know the genotype of specific variants. For other studies a composite genetic risk score–the polygenic risk score–is of value. There currently is a gap in technology to genotype a few hundred variants in a flexible and cost-effective way. We therefore developed a genotyping assay for the 242 validated IBD susceptibility loci. Methods Using MIPgen v.1.1, we designed molecular inversion probes (MIPs) covering 269 independent variants from the 242 IBD loci. MIP libraries were prepared according to Neveling et al. (Clin Chem. 2017), followed by paired-end sequencing using a MiSeq® System (Illumina). In the pilot studies, 16 IBD patients were genotyped, and results were compared with available immunochip (ichip) data. Genotypes for the covered variants were obtained using an in-house developed pipeline, and performance metrics were assessed (incl. genotyping call rate, percentage off-target reads and concordance with ichip-based genotypes). After optimisation, we genotyped 279 individuals (168 IBD patients and 111 non-IBD controls). We also calculated a weighted IBD polygenic risk score (PRSice 2.0) for these. Results Despite a genotyping call rate of 94.3%, the first pilot run suffered from a high rate of off-target reads (52.5%). After redesigning poorly-performing MIPs, off-target reads dropped to 9.4%, and the genotyping call rate increased to 97.5%. Concordance with genotypes previously obtained from ichip was 99.3%. When applying the optimised design on a larger scale (i.e. on the 279 individuals), we obtained similar performance metrics, with 8.0% off-target reads and a genotyping call rate of 97.3%. Moreover, upscaling resulted in a turnaround time of 2.5 working days/96 samples and a cost of €14/sample. The calculated IBD polygenic risk scores showed higher scores in patients as compared with controls (5.5E−03 vs. 4.0E−03, p = 8.80E−10; R² IBD polygenic risk score = 0.15, p = 1.28E−07), however with a large overlap between both groups. Quartile analysis showed that individuals within the highest quartile had an 8.1-fold (95% CI: 3.7–17.5) increase in risk towards IBD compared with individuals in the first quartile. Conclusion We developed a cost-effective genotyping assay for currently known IBD risk loci, with an integrated bioinformatics pipeline from raw sequencing data to individual genotypes and calculation of a polygenic risk score. Furthermore, this assay enables genotyping of individuals on a large scale while remaining flexible to implement newly identified genetic variants.

scholarly journals Migraine polygenic risk score associates with efficacy of migraine-specific drugs

2019 ◽  
Vol 5 (6) ◽  
pp. e364 ◽  
Author(s):  
Lisette J.A. Kogelman ◽  
Ann-Louise Esserlind ◽  
Anne Francke Christensen ◽  
Swapnil Awasthi ◽  
Stephan Ripke ◽  
...  
Keyword(s):  
Treatment Response ◽  
Risk Score ◽  
Acute Treatment ◽  
Genome Wide Association Study ◽  
Positive Response ◽  
Migraine Treatment ◽  
Polygenic Risk Score ◽  
Semistructured Interview ◽  
Polygenic Risk ◽  
Twofold Increase

ObjectiveTo assess whether the polygenic risk score (PRS) for migraine is associated with acute and/or prophylactic migraine treatment response.MethodsWe interviewed 2,219 unrelated patients at the Danish Headache Center using a semistructured interview to diagnose migraine and assess acute and prophylactic drug response. All patients were genotyped. A PRS was calculated with the linkage disequilibrium pred algorithm using summary statistics from the most recent migraine genome-wide association study comprising ∼375,000 cases and controls. The PRS was scaled to a unit corresponding to a twofold increase in migraine risk, using 929 unrelated Danish controls as reference. The association of the PRS with treatment response was assessed by logistic regression, and the predictive power of the model by area under the curve using a case-control design with treatment response as outcome.ResultsA twofold increase in migraine risk associates with positive response to migraine-specific acute treatment (odds ratio [OR] = 1.25 [95% confidence interval (CI) = 1.05–1.49]). The association between migraine risk and migraine-specific acute treatment was replicated in an independent cohort consisting of 5,616 triptan users with prescription history (OR = 3.20 [95% CI = 1.26–8.14]). No association was found for acute treatment with non–migraine-specific weak analgesics and prophylactic treatment response.ConclusionsThe migraine PRS can significantly identify subgroups of patients with a higher-than-average likelihood of a positive response to triptans, which provides a first step toward genetics-based precision medicine in migraine.

Genome-wide association study (GWAS) of chemotherapy-induced Raynaud's phenomenon (RP) to reveal shared pathways with cardiovascular disease (CVD).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18162-e18162
Author(s):  
Omar El Charif ◽  
Heather E. Wheeler ◽  
Matthew Trendowski ◽  
Eric R Gamazon ◽  
Shirin Ardeshirrouhanifard ◽  
...  
Keyword(s):  
Risk Score ◽  
Cellular Response ◽  
Genome Wide Association Study ◽  
Significant Snps ◽  
Case Control ◽  
Gene Set Enrichment Analysis ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Patient Reported

e18162 Background: RP is an adverse drug reaction characterized by reduced blood flow to the extremities causing pain and sensations of cold. Few studies have examined the genetic basis for RP, although family studies suggest a heritable component to primary RP. Methods: Eligible testicular cancer survivors (TCS) were < 55 y at diagnosis, treated with first line cisplatin-based chemotherapy, and completed questionnaires. Genotyping with standard quality control and imputation were performed. A case-control RP phenotype was derived from patient-reported outcomes and associations were computed by logistic regression. GWAS used cumulative bleomycin dose and 10 genetic principal components as covariates. Gene set enrichment analysis (GSEA) utilized genes ranked by the most significant GWAS SNP in/within 20 kilobases. A polygenic risk score for CVD derived from four prior independent GWAS (Khera et al. NEJM 2016) was assessed for association with RP. Results: Of 749 patients (median age 38 y, median time since chemotherapy 5 y), 38% reported RP. Bleomycin dose was the most significant predictor of RP (OR100 mg/m2 = 1.25, p < 0.0001). Number of years smoking also correlated with RP (ORyear = 1.05, p = 0.002). Age and hypertension showed no significant correlation with RP. GSEA revealed several significant pathways (FDR q < 0.1), including “ cellular response to VEGF stimulus” (q = 0.05) and “ cardiac muscle cell action potential” (q = 0.09). We hypothesized that RP may share genetic architecture with CVD. Deriving a polygenic risk score from genome-wide significant SNPs in prior CVD GWAS (n = 4260-22,389), we showed nearly significant case-control differences in CVD polygenic risk score (two-tailed t-test, p = 0.053). RP frequency significantly increased with polygenic risk score quartile (OR = 1.19, p = 0.008). Conclusions: Over one third of TCS report RP, with greater frequency among bleomycin-treated patients and smokers. Implicated genetic pathways include ones established in CVD. Although shared genetic risk between chemotherapy-induced RP and CVD may be possible, further investigation is required. Primary RP has been inconsistently linked with CVD.

scholarly journals Liver-specific polygenic risk score is more strongly associated than genome-wide score with Alzheimer’s disease diagnosis in a case-control analysis

2021 ◽  
Author(s):  
Daniel J. Panyard ◽  
Yuetiva K. Deming ◽  
Burcu F. Darst ◽  
Carol A. Van Hulle ◽  
Kaj Blennow ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Score ◽  
Functional Annotation ◽  
Disease Diagnosis ◽  
Genomic Research ◽  
Polygenic Risk Score ◽  
Control Analysis ◽  
Multiple Testing Correction ◽  
Polygenic Risk

AbstractAlthough our understanding of Alzheimer’s disease (AD) has greatly improved in recent years, the root cause remains unclear, making it difficult to find effective diagnosis and treatment options. Our understanding of the pathophysiology underlying AD has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. In many aspects of genomic research the use of functional annotation has been able to improve the power of genomic models. Here, we leveraged genomic functional annotations to build tissue-specific PRS models for 13 tissues and applied the scores to two longitudinal cohort studies of AD. The PRS model that was most predictive of AD diagnosis relative to cognitively unimpaired participants was the liver tissue score: n = 1,116; odds ratio (OR) (95% confidence interval [CI]) = 2.19 (1.70-2.82) per standard deviation (SD) increase in PRS; P = 1.46 × 10−9. After removing the APOE locus from the PRS models, the liver score was the only PRS to remain statistically significantly associated with AD diagnosis after multiple testing correction, although the effect was weaker: OR (95% CI) = 1.55 (1.19-2.02) per SD increase in PRS; P = 0.0012. In follow-up analysis, the liver PRS was statistically significantly associated with levels of amyloid (P = 3.53 × 10−6) and tau (P = 1.45 × 10−5) in the cerebrospinal fluid (CSF) (when the APOE locus was included) and nominally associated with CSF soluble TREM2 levels (P = 0.042) (when the APOE locus was excluded). These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research.

scholarly journals Polygenic Risk Score is a Predictor of Adenomatous Polyps at Screening Colonoscopy

2020 ◽  
Author(s):  
Michael Northcutt ◽  
Zhuqing Shi ◽  
Michael Zijlstra ◽  
Ayush Shah ◽  
Siqun Zheng ◽  
...  
Keyword(s):  
Family History ◽  
Risk Score ◽  
Genetic Risk Score ◽  
Positive Family History ◽  
Snp Array ◽  
Adenomatous Polyps ◽  
Screening Colonoscopy ◽  
Polygenic Risk Score ◽  
Average Risk ◽  
Polygenic Risk

Abstract Background: Single nucleotide polymorphism (SNP)-based polygenic risk scoring is predictive of colorectal cancer (CRC) risk. However, few studies have investigated the association of genetic risk score (GRS) with detection of adenomatous polyps at screening colonoscopy. Methods: We randomly selected 1,769 Caucasian subjects who underwent screening colonoscopy from the Genomic Health Initiative (GHI), a biobank of NorthShore University HealthSystem. Outcomes from initial screening colonoscopy were recorded. Twenty-two CRC risk-associated SNPs were obtained from the Affymetrix™ SNP array and used to calculate an odds ratio (OR)-weighted and population-standardized GRS. Subjects with GRS of <0.5, 0.5-1.5, and >1.5 were categorized as low, average and elevated risk.Results: Among 1,769 subjects, 520 (29%) had 1 or more adenomatous polyps. GRS was significantly higher in subjects with adenomatous polyps than those without; mean (95% confidence interval) was 1.02 (1.00-1.05) and 0.97 (0.95-0.99), respectively, p<0.001. The association remained significant after adjusting for age, gender, body mass index, and family history, p<0.001. The detection rate of adenomatous polyps was 10.8%, 29.0% and 39.7% in subjects with low, average and elevated GRS, respectively, p-trend <0.001. Higher GRS was also associated with early age diagnosis of adenomatous polyps, p<0.001. In contrast, positive family history was not associated with risk and age of adenomatous polyps.Conclusions: GRS was significantly associated with adenomatous polyps in subjects undergoing screening colonoscopy. This result may help in stratifying average risk patients and facilitating personalized colonoscopy screening strategies.

scholarly journals Genetic Risk Score to Identify Risk of Venous Thromboembolism in Patients With Cardiometabolic Disease

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Nicholas A. Marston ◽  
Giorgio E.M. Melloni ◽  
Yared Gurmu ◽  
Marc P. Bonaca ◽  
Frederick K. Kamanu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Groups ◽  
Clinical Risk Factors ◽  
Cardiometabolic Disease ◽  
Polygenic Risk Score ◽  
Clinical Risk ◽  
History Of

Background: Venous thromboembolism (VTE) is a major cause of cardiovascular morbidity and mortality and has a known genetic contribution. We tested the performance of a genetic risk score for its ability to predict VTE in 3 cohorts of patients with cardiometabolic disease. Methods: We included patients from the FOURIER (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Patients With Elevated Risk), PEGASUS-TIMI 54 (Prevention of Cardiovascular Events in Patients With Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin), and SAVOR-TIMI 53 (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus) trials (history of a major atherosclerotic cardiovascular event, myocardial infarction, and diabetes, respectively) who consented for genetic testing and were not on baseline anticoagulation. We calculated a VTE genetic risk score based on 297 single nucleotide polymorphisms with established genome-wide significance. Patients were divided into tertiles of genetic risk. Cox proportional hazards models were used to calculate hazard ratios for VTE across genetic risk groups. The polygenic risk score was compared with available clinical risk factors (age, obesity, smoking, history of heart failure, and diabetes) and common monogenic mutations. Results: A total of 29 663 patients were included in the analysis with a median follow-up of 2.4 years, of whom 174 had a VTE event. There was a significantly increased gradient of risk across VTE genetic risk tertiles ( P -trend <0.0001). After adjustment for clinical risk factors, patients in the intermediate and high genetic risk groups had a 1.88-fold (95% CI, 1.23–2.89; P =0.004) and 2.70-fold (95% CI, 1.81–4.06; P <0.0001) higher risk of VTE compared with patients with low genetic risk. In a continuous model adjusted for clinical risk factors, each standard deviation increase in the genetic risk score was associated with a 47% (95% CI, 29–68) increased risk of VTE ( P <0.0001). Conclusions: In a broad spectrum of patients with cardiometabolic disease, a polygenic risk score is a strong, independent predictor of VTE after accounting for available clinical risk factors, identifying 1/3 of patients who have a risk of VTE comparable to that seen with established monogenic thrombophilia.

scholarly journals Examining Gene–Environment Interactions Using Aggregate Scores in a First-Episode Psychosis Cohort

2020 ◽  
Vol 46 (4) ◽  
pp. 1019-1025
Author(s):  
Sergi Mas ◽  
Daniel Boloc ◽  
Natalia Rodríguez ◽  
Gisela Mezquida ◽  
Silvia Amoretti ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk Score ◽  
Dose Dependence ◽  
First Episode ◽  
Polygenic Risk Score ◽  
Additive Interaction ◽  
Gene Environment ◽  
Common Genetic Variants ◽  
Large Populations ◽  
Spectrum Disorders

Abstract Gene–environment (GxE) interactions have been related to psychosis spectrum disorders, involving multiple common genetic variants in multiple genes with very small effect sizes, and several environmental factors that constitute a dense network of exposures named the exposome. Here, we aimed to analyze GxE in a cohort of 310 first-episode psychotic (FEP) and 236 healthy controls, by using aggregate scores estimated in large populations such as the polygenic risk score for schizophrenia and (PRS-SCZ) and the Maudsley environmental risk score (ERS). In contrast to previous findings, in our study, the PRS-SCZ did not discriminate cases from controls, but the ERS score explained a similar percentage of the variance as in other studies using similar approaches. Our study supports a positive additive interaction, indicating synergy between genetic susceptibility to schizophrenia (PRS-SCZ dichotomized according to the highest quartile distribution of the control population) and the exposome (ERS &gt; 75% of the controls). This additive interaction showed genetic and environmental dose dependence. Our study shows that the use of aggregate scores derived from large and powered studies instead of statistics derived from specific sample characteristics is a powerful tool for the study of the effects of GxE on the risk of psychotic spectrum disorders. In conclusion, by using a genetic risk score and an ERS we have provided further evidence for the role of GxE in psychosis.

Sign in / Sign up

Export Citation Format

Share Document