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

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 > 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.

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

Journal of Crohn s and Colitis ◽

10.1093/ecco-jcc/jjz203.948 ◽

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.

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POLYGENIC RISK SCORE ANALYSES OF SYMPTOMS AND TREATMENT RESPONSE IN A FIRST EPISODE SCHIZOPHRENIA COHORT

European Neuropsychopharmacology ◽

10.1016/j.euroneuro.2017.08.159 ◽

2019 ◽

Vol 29 ◽

pp. S869

Author(s):

Marcos Santoro ◽

Vanessa Ota ◽

Simone de Jong ◽

Cristiano Noto ◽

Fernanda Talarico ◽

...

Keyword(s):

Treatment Response ◽

Risk Score ◽

First Episode ◽

Polygenic Risk Score ◽

Polygenic Risk ◽

First Episode Schizophrenia

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Polygenic Risk Score Associated With Treatment-Resistance in a Naturalistic Sample of Patients With Schizophrenia Spectrum Disorders

Biological Psychiatry ◽

10.1016/j.biopsych.2020.02.826 ◽

2020 ◽

Vol 87 (9) ◽

pp. S321-S322

Author(s):

Maren Caroline Frogner Werner ◽

Katrine Verena Wirgenes ◽

Marit Haram ◽

Francesco Bettella ◽

Synve Hoffart Lunding ◽

...

Keyword(s):

Risk Score ◽

Treatment Resistance ◽

Polygenic Risk Score ◽

Schizophrenia Spectrum Disorders ◽

Polygenic Risk ◽

Schizophrenia Spectrum ◽

Spectrum Disorders

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Correlations between immune and metabolic serum markers and schizophrenia/bipolar disorder polygenic risk score in first‐episode psychosis

Early Intervention in Psychiatry ◽

10.1111/eip.12906 ◽

2019 ◽

Vol 14 (4) ◽

pp. 507-511 ◽

Cited By ~ 2

Author(s):

Carlo Maj ◽

Sarah Tosato ◽

Roberta Zanardini ◽

Antonio Lasalvia ◽

Angela Favaro ◽

...

Keyword(s):

Bipolar Disorder ◽

Risk Score ◽

First Episode Psychosis ◽

Serum Markers ◽

First Episode ◽

Polygenic Risk Score ◽

Polygenic Risk ◽

Episode Psychosis

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

Briefings in Bioinformatics ◽

10.1093/bib/bby075 ◽

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.

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

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.1528 ◽

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]

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

10.21203/rs.3.rs-62371/v2 ◽

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.

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

Circulation Genomic and Precision Medicine ◽

10.1161/circgen.120.003006 ◽

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.

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