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 Polygenic risk score is a predictor of adenomatous polyps at screening colonoscopy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Michael J. 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 1769 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 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: 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 Parkinson’s disease determinants, prediction and gene-environment interactions in the UK Biobank

2020 ◽  
Author(s):  
Benjamin M. Jacobs ◽  
Daniel Belete ◽  
Jonathan P Bestwick ◽  
Cornelis Blauwendraat ◽  
Sara Bandres-Ciga ◽  
...  
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Risk Score ◽  
Genetic Risk ◽  
Positive Family History ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Gene Environment ◽  
History Of

AbstractObjectiveTo systematically investigate the association of environmental risk factors and prodromal features with incident Parkinson’s disease (PD) diagnosis and the interaction of genetic risk with these factors. To evaluate existing risk prediction algorithms and the impact of including addition genetic risk on the performance of prediction.MethodsWe identified individuals with incident PD diagnoses (n=1276) and unmatched controls (n=500,406) in UK Biobank. We determined the association of risk factors with incident PD using adjusted logistic regression models. A polygenic risk score (PRS) was constructed and used to examine gene-environment interactions. The PRS was also incorporated into a previously-developed prediction algorithm for finding incident cases.ResultsStrong evidence of association (Pcorr<0.05) was found between PD and a positive family history of PD, a positive family history of dementia, non-smoking, low alcohol consumption, depression, and daytime somnolence, and novel associations with epilepsy and earlier menarche. Individuals with the highest 10% of PRS scores had increased risk of PD (OR=3.30, 95% CI 2.57-4.24) compared to the lowest risk decile. Higher PRS scores were associated with earlier age at PD diagnosis and inclusion of the PRS in the PREDICT-PD algorithm improved model performance (Nagelkerke pseudo-R2 0.0053, p=6.87×10−14). We found evidence of interaction between the PRS and diabetes.InterpretationHere we used UK Biobank data to reproduce several well-known associations with PD, to demonstrate the validity and predictive power of a polygenic risk score, and to demonstrate a novel gene-environment interaction, whereby the effect of diabetes on PD risk appears to depend on prior genetic risk for PD.

scholarly journals Relative contributions of family history and a polygenic risk score on COPD and related outcomes: COPDGene and ECLIPSE studies

2020 ◽  
Vol 7 (1) ◽  
pp. e000755
Author(s):  
Matthew Moll ◽  
Sharon M. Lutz ◽  
Auyon J. Ghosh ◽  
Phuwanat Sakornsakolpat ◽  
Craig P. Hersh ◽  
...  
Keyword(s):  
Family History ◽  
Risk Score ◽  
Characteristic Curve ◽  
Significant Proportion ◽  
Chronic Obstructive ◽  
Polygenic Risk Score ◽  
Positive Interaction ◽  
Polygenic Risk ◽  
Mediation Analyses ◽  
The Impact

IntroductionFamily history is a risk factor for chronic obstructive pulmonary disease (COPD). We previously developed a COPD risk score from genome-wide genetic markers (Polygenic Risk Score, PRS). Whether the PRS and family history provide complementary or redundant information for predicting COPD and related outcomes is unknown.MethodsWe assessed the predictive capacity of family history and PRS on COPD and COPD-related outcomes in non-Hispanic white (NHW) and African American (AA) subjects from COPDGene and ECLIPSE studies. We also performed interaction and mediation analyses.ResultsIn COPDGene, family history and PRS were significantly associated with COPD in a single model (PFamHx <0.0001; PPRS<0.0001). Similar trends were seen in ECLIPSE. The area under the receiver operator characteristic curve for a model containing family history and PRS was significantly higher than a model with PRS (p=0.00035) in NHWs and a model with family history (p<0.0001) alone in NHWs and AAs. Both family history and PRS were significantly associated with measures of quantitative emphysema and airway thickness. There was a weakly positive interaction between family history and the PRS under the additive, but not multiplicative scale in NHWs (relative excess risk due to interaction=0.48, p=0.04). Mediation analyses found that a significant proportion of the effect of family history on COPD was mediated through PRS in NHWs (16.5%, 95% CI 9.4% to 24.3%), but not AAs.ConclusionFamily history and the PRS provide complementary information for predicting COPD and related outcomes. Future studies can address the impact of obtaining both measures in clinical practice.

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 Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia

2015 ◽  
Vol 72 (7) ◽  
pp. 635 ◽  
Author(s):  
Esben Agerbo ◽  
Patrick F. Sullivan ◽  
Bjarni J. Vilhjálmsson ◽  
Carsten B. Pedersen ◽  
Ole Mors ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Family History ◽  
Psychiatric Disorders ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
History Of ◽  
Parental Socioeconomic Status

scholarly journals Capturing additional genetic risk from family history for improved polygenic risk prediction

2022 ◽  
Author(s):  
Tianyuan Lu ◽  
Vincenzo Forgetta ◽  
J Brent Richards ◽  
Celia MT Greenwood
Keyword(s):  
Family History ◽  
Risk Prediction ◽  
Risk Score ◽  
Genetic Risk ◽  
Adult Height ◽  
Prediction Models ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Parental History ◽  
Polygenic Risk

Family history of complex traits may reflect transmitted rare pathogenic variants, intrafamilial shared exposures to environmental and lifestyle factors, as well as a common genetic predisposition. We developed a latent factor model to quantify trait heritability in excess of that captured by a common variant-based polygenic risk score, but inferable from family history. We applied our model to predict adult height for 941 children in the Avon Longitudinal Study of Parents and Children cohort as well as 11 complex diseases for ~400,000 European ancestry participants in the UK Biobank. Parental history brought consistent significant improvements in the predictive power of polygenic risk prediction. For instance, a joint predictor was able to explain ~55% of the total variance in sex-adjusted adult height z-scores, close to the estimated heritability. Our work showcases an innovative paradigm for risk calculation, and supports incorporation of family history into polygenic risk score-based genetic risk prediction models.

826 – Polygenic Risk Score, Family History, and Colorectal Cancer by Molecular Subtypes

2019 ◽  
Vol 156 (6) ◽  
pp. S-178
Author(s):  
Long H. Nguyen ◽  
Kathryn Penney ◽  
Amit D. Joshi ◽  
Yin Cao ◽  
Mingyang Song ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Family History ◽  
Risk Score ◽  
Molecular Subtypes ◽  
Polygenic Risk Score ◽  
Polygenic Risk

scholarly journals Public Health Mode Personalized Medicine: Risk Stratification for Breast Cancer Screening

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 44s-44s
Author(s):  
M. Wolfson
Keyword(s):  
Public Health ◽  
Breast Cancer ◽  
Risk Assessment ◽  
Family History ◽  
Risk Stratification ◽  
Risk Score ◽  
Joint Distribution ◽  
Genetic Mutations ◽  
Polygenic Risk Score ◽  
Polygenic Risk

Background: Breast cancer (BC) screening, primarily age-based, is a major public health program in many wealthy countries. At the same time, there is a dramatic increase in using genetics to support personalized medicine. These two approaches would seem antithetical. However, they can join powerfully with the possibility of using genetic information as the basis for a major shift from age-based to a risk-based BC screening programs. Aim: To assess the prospective cost-effectiveness of such a shift to risk-based BC screening requires representative population data on the relationships among a woman's age when a risk assessment is done, her family history of cancer in the context of pedigree data, and specific features of her genotype - comprising both the presence of rare genetic mutations like BRCA1/2 and recently derived polygenic risk scores. We use our newly developed Genetic Mixing Model (GMM) to estimate this joint distribution as the initial step in assessing the prospective cost-effectiveness of risk stratified BC screening in Canada. Methods: BOADICEA is a BC risk stratification algorithm already in wide use around the world, and in particular in Ontario, for high risk screening. A new version of BOADICEA incorporating a polygenic risk score has recently (will have) been published. We embedded the new core BOADICEA algorithm into the GMM. GMM thus provides the empirical foundation for assessing risk stratification for a representative population by constructing an estimate of the multivariate joint distribution of family history, presence of rare genetic mutations including BRCA1/2, and a polygenic risk score, derived from genome-wide association studies. Results: Using a polygenic risk score (PRS) would be far more useful for stratifying women according to their risk of breast cancer than the two most commonly used indicators at present: family history and rare genetic mutations. We have assessed a variety of combinations of these genetic indicators, in combination with offering universal risk assessment to women in Canada at various ages, and using different thresholds for categorizing women as being at high risk. The optimal age for risk assessment is in the 35 to 40 range. And the PRS is substantially more useful than family history or rare mutations for stratifying women for screening intensity by their risk of BC. Conclusion: Shifting from the current public health approach of primarily age-based screening for breast cancer, to one based on risk stratification, especially making use of recent advances in assessing polygenic risk, offers major potential benefits.

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