Abstract P229: Genetic Risk Scores are Associated with Chronic Venous Disease Prevalence and Severity in a Multi-Ethnic Cohort: The San Diego Population Study (SDPS)

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Christina L Wassel ◽  
Laura J Rasmussen-Torvik ◽  
Peter W Callas ◽  
Julie O Denenberg ◽  
Peter Durda ◽  
...  
Keyword(s):  
Ethnic Group ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Disease Prevalence ◽  
Chronic Venous Disease ◽  
Risk Scores ◽  
Venous Disease ◽  
European Descent ◽  
The Difference

Background: Chronic venous disease is common, affecting up to 40% of the population, although estimates vary quite widely due to differing evaluation methods and definitions. Chronic venous disease shares some risk factors with venous thromboembolism (VTE). Several genetic loci have been recently discovered and replicated for VTE, mostly in populations of European descent. We tested associations of these loci, as well as a genetic risk score including these variants, with chronic venous disease prevalence and severity in a multi-ethnic cohort. Methods: The San Diego Population Study (SDPS) is a prospective cohort study that evaluated 2404 ethnically diverse men and women aged 29-91 for venous disease using duplex ultrasound. The current study includes 1229 participants from the baseline exam who were genotyped for 35 variants in 23 loci. Venous disease was defined as moderate or severe, as well as severe only. Logistic regression was used to examine the association of each variant with venous disease, stratified by ethnic group. A weighted genetic risk score, using the top 20% of variants and weighting by the beta coefficients, was generated for each ethnic group. Associations of this risk score with venous disease were examined stratified by ethnic group. Results: The mean ± standard deviation (SD) age was 60±11, with 64% female, and 62% White, 14% Hispanic, 11% African-American, and 12% Asian. The prevalence of moderate and severe venous disease was 41%, and severe venous disease alone was 25%. While some loci overlapped in the ethnic-specific genetic risk scores, others were exclusive to an ethnic group. In models adjusting for known venous disease risk factors, in Whites, Hispanics, African-Americans and Asians, respectively, each SD higher genetic risk score was associated with a 1.42-fold higher odds (95% CI (1.21, 1.66)), 2.06-fold higher odds (95% CI (1.44, 2.95)), a 2.25-fold higher odds (95% CI (1.38, 3.66)), and 2.45-fold higher odds (95% CI (1.57, 3.82)) for moderate or severe disease. The difference in c-statistics was statistically significant between the known venous risk factor model and this model adding the genetic risk factor for Hispanics, African-Americans, and Asians, with 0.67 vs. 0.75 (p=0.03), 0.69 vs. 0.77 (p=0.02), 0.63 vs. 0.74 (p=0.01), respectively. The difference was not significant for Whites, 0.64 vs. 0.66 (p=0.12). All results were similar for severe venous disease only. Conclusions: This ethnic-specific genetic risk score is strongly associated with chronic venous disease, and may be of greater importance for venous disease in those of non-European descent. Future work should focus on examining racial/ethnic group genetic architecture in relation to venous disease.

scholarly journals A genetic risk score comprising known venous thromboembolism loci is associated with chronic venous disease in a multi-ethnic cohort

2015 ◽  
Vol 136 (5) ◽  
pp. 966-973 ◽  
Author(s):  
Christina L. Wassel ◽  
Laura J. Rasmussen-Torvik ◽  
Peter W. Callas ◽  
Julie O. Denenberg ◽  
J. Peter Durda ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Chronic Venous Disease ◽  
Venous Disease

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

scholarly journals Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study

2018 ◽  
Vol 56 (9) ◽  
pp. 602-605 ◽  
Author(s):  
Andreas Beyerlein ◽  
Ezio Bonifacio ◽  
Kendra Vehik ◽  
Markus Hippich ◽  
Christiane Winkler ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Islet Autoimmunity ◽  
Islet Autoantibody ◽  
Clinical Type

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.ResultsIslet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).ConclusionsGenetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

scholarly journals Burden of genetic risk variants in multiple sclerosis families in the Netherlands

2016 ◽  
Vol 2 ◽  
pp. 205521731664872 ◽  
Author(s):  
Julia Y Mescheriakova ◽  
Linda Broer ◽  
Simin Wahedi ◽  
André G Uitterlinden ◽  
Cornelia M van Duijn ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Weighted Genetic Risk Score ◽  
Sporadic Cases ◽  
Multiplex Families ◽  
The Difference ◽  
Multiple Sclerosis Patients ◽  
Genetic Burden

Background Approximately 20% of multiple sclerosis patients have a family history of multiple sclerosis. Studies of multiple sclerosis aggregation in families are inconclusive. Objective To investigate the genetic burden based on currently discovered genetic variants for multiple sclerosis risk in patients from Dutch multiple sclerosis multiplex families versus sporadic multiple sclerosis cases, and to study its influence on clinical phenotype and disease prediction. Methods Our study population consisted of 283 sporadic multiple sclerosis cases, 169 probands from multiplex families and 2028 controls. A weighted genetic risk score based on 102 non-human leukocyte antigen loci and HLA-DRB1*1501 was calculated. Results The weighted genetic risk score based on all loci was significantly higher in familial than in sporadic cases. The HLA-DRB1*1501 contributed significantly to the difference in genetic burden between the groups. A high weighted genetic risk score was significantly associated with a low age of disease onset in all multiple sclerosis patients, but not in the familial cases separately. The genetic risk score was significantly but modestly better in discriminating familial versus sporadic multiple sclerosis from controls. Conclusion Familial multiple sclerosis patients are more loaded with the common genetic variants than sporadic cases. The difference is mainly driven by HLA-DRB1*1501. The predictive capacity of genetic loci is poor and unlikely to be useful in clinical settings.

scholarly journals Sexual Differences in Genetic Predisposition of Coronary Artery Disease

2020 ◽  
Author(s):  
Yunfeng Huang ◽  
Qin Hui ◽  
Marta Gwinn ◽  
Yi-Juan Hu ◽  
Arshed A. Quyyumi ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Men And Women ◽  
High Genetic Risk ◽  
Genome Wide ◽  
Artery Disease

Background - The genomic structure that contributes to the risk of coronary artery disease (CAD) can be evaluated as a risk score of multiple variants. However, sex differences have not been fully examined in applications of genetic risk score of CAD. Methods - Using data from the UK Biobank, we constructed a CAD genetic risk score based on all known loci, three mediating trait-based (blood pressure, lipids, body mass index) sub-scores, and a genome-wide polygenic risk score based on 1.1 million variants. The differences in genetic associations with prevalent and incident CAD between men and women were investigated among 317,509 unrelated individuals of European ancestry. We also assessed interactions with sex for 161 individual loci included in the comprehensive genetic risk score. Results - For both prevalent and incident CAD, the associations of comprehensive and genome-wide genetic risk scores were stronger among men than women. Using a score of 161 loci, we observed a 2.4 times higher risk for incident CAD comparing men with high genetic risk to men with low genetic risk, but an 80 percent greater risk comparing women with high genetic risk to women with low genetic risk. (interaction p=0.002). Of the three sub-scores, the blood pressure-associated sub-score exhibited sex differences (interaction p=0.0004 per SD increase in sub-score). Analysis of individual variants identified a novel gene-sex interaction at locus 21q22.11 . Conclusions - Sexual differences in genetic predisposition should be considered in future studies of coronary artery disease, and genetic risk scores should not be assumed to perform equally well in men and women.

scholarly journals Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk

2019 ◽  
Vol 14 (1) ◽  
pp. 42-53
Author(s):  
Zhong Guan ◽  
Janhavi R. Raut ◽  
Korbinian Weigl ◽  
Ben Schöttker ◽  
Bernd Holleczek ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Score ◽  
Environmental Risk ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Joint Performance

scholarly journals ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years

2016 ◽  
Author(s):  
Shea J. Andrews ◽  
Ranmalee Eramudugolla ◽  
Jorge I. Velez ◽  
Nicolas Cherbuin ◽  
Simon Easteal ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Demographic Factors ◽  
Population Level ◽  
Risk Scores ◽  
Cognitive States ◽  
State Models

AbstractINTRODUCTIONWe evaluated a risk score comprising lifestyle, medical and demographic factors (ANU-ADRI), and a genetic risk score (GRS) as predictors of Mild Cognitive Impairment (MCI).METHODSANU-ADRI risk scores were computed for the baseline assessment of 2,078 participants from the PATH project. Participants were assessed for clinically diagnosed MCI/Dementia and psychometric test-based MCI (MCI-TB) at 12 years of follow-up. Multi-state models estimated the odds of transitioning from cognitively normal (CN) to MCI/Dementia and MCI-TB over 12 years according to baseline ANU-ADRI and GRS.RESULTSHigher ANU-ADRI score predicted transitioning from CN to either MCI/Dementia and MCI-TB (Hazard ratio [HR] = 1.06, 95% CI:1.04-1.09; HR = 1.06, 95% CI: 1.03-1.09), and a reduced likelihood of cognitive recovery from MCITB to CN (HR = 0.69, 95% CI: 0.49-0.98). GRS was not associated with transition to MCI/Dementia, or MCI-TB.DISCUSSIONThe ANU-ADRI may be used for population-level risk assessment and screening.Research in ContextSystematic ReviewThe authors reviewed the literature using online databases e.g. (PubMed). We consulted mild cognitive impairment (MCI) and Alzheimer’s disease (AD) research detailing the use of risk factors for predicting progression from MCI and AD; and the appropriate statistical models for modelling transitions between cognitive states. These publications are appropriately cited.InterpretationIn the general population, the ANU-ADRI comprising lifestyle, medical and demographic factors is predictive of progression from normal cognition to MCI/Dementia whereas a Genetic Risk Score comprising the main Alzheimer’s risk genes is not predictive.Future DirectionsFurther evaluation of the ANU-ADRI as a predictor of specific MCI and dementia subtypes is required. The ANU-ADRI may be used to identify individuals indicated for risk reduction intervention and to assist clinical management and cognitive health promotion. Genetic risk scores contribute to understanding dementia etiology but apart from APOE are unlikely to be useful in screening or prevention trials.

scholarly journals Pharmacogenomics Factors Influencing the Effect of Risperidone on Prolactin Levels in Thai Pediatric Patients With Autism Spectrum Disorder

2021 ◽  
Vol 12 ◽  
Author(s):  
Yaowaluck Hongkaew ◽  
Andrea Gaedigk ◽  
Bob Wilffert ◽  
Roger Gaedigk ◽  
Wiranpat Kittitharaphan ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Risk Score ◽  
Genetic Risk ◽  
Dopamine D2 Receptor ◽  
Genetic Risk Score ◽  
D2 Receptor ◽  
Kinase Domain ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Risk Scores

We investigated the association between genetic variations in pharmacodynamic genes and risperidone-induced increased prolactin levels in children and adolescents with autism spectrum disorder (ASD). In a retrospective study, variants of pharmacodynamic genes were analyzed in 124 ASD patients treated with a risperidone regimen for at least 3 months. To simplify genotype interpretation, we created an algorithm to calculate the dopamine D2 receptor (DRD2) gene genetic risk score. There was no relationship between prolactin levels and single SNPs. However, the H1/H3 diplotype (A2/A2-Cin/Cin-A/G) of DRD2/ankyrin repeat and kinase domain containing 1 (ANKK1) Taq1A, DRD2 -141C indel, and DRD2 -141A&gt;G, which had a genetic risk score of 5.5, was associated with the highest median prolactin levels (23 ng/ml). As the dose-corrected plasma levels of risperidone, 9-OH-risperidone, and the active moiety increased, prolactin levels in patients carrying the H1/H3 diplotype were significantly higher than those of the other diplotypes. DRD2 diplotypes showed significantly high prolactin levels as plasma risperidone levels increased. Lower levels of prolactin were detected in patients who responded to risperidone. This is the first system for describing DRD2 haplotypes using genetic risk scores based on their protein expression. Clinicians should consider using pharmacogenetic-based decision-making in clinical practice to prevent prolactin increase.

Using a Systems-Based Risk Score Approach to Examine Genetic Predisposition to Novelty Seeking

2017 ◽  
Vol 38 (3) ◽  
pp. 163-174
Author(s):  
Bradley T. Conner ◽  
Gerhard S. Hellemann ◽  
Abigail C. Demianczyk ◽  
Terry Ritchie ◽  
Ernest P. Noble
Keyword(s):  
Mental Illness ◽  
Risk Score ◽  
Genetic Predisposition ◽  
Genetic Risk ◽  
Genetic Information ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Novelty Seeking ◽  
Psychological Constructs ◽  
Dopamine Genes

Abstract. Previous research is mixed regarding the relation between dopamine and Novelty Seeking. The goals of the current study were to support the hypotheses that Novelty Seeking is associated with dopamine genes and that modeling genetic risk score increases the utility of genetic information in hypothesis-driven research. The results showed that higher hypodopaminergic genetic risk score positively predicted higher Novelty Seeking score, F(1, 115) = 5.76, p < .01, R2 = 0.06. The findings support study hypotheses and, in combination with previous studies, show the utility of empirically validated system-based risk scores as a means of modeling genetic predisposition in neurobiological systems. This approach provides a mechanism for incorporating genetic predisposition into theory-driven multivariate etiological models of psychological constructs such as personality and mental illness.

scholarly journals Genetic risk score for ovarian cancer based on chromosomal-scale length variation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Christopher Toh ◽  
James P. Brody
Keyword(s):  
Ovarian Cancer ◽  
Confidence Interval ◽  
Risk Score ◽  
Genetic Risk ◽  
Germ Line ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Length Variation ◽  
Genetic Risk Scores ◽  
Scale Length

Abstract Introduction Twin studies indicate that a substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce ovarian cancer death rates. However, current ovarian cancer genetic risk scores do not work that well. We developed a genetic risk score based on variations in the length of chromosomes. Methods We evaluated this genetic risk score using data collected by The Cancer Genome Atlas. We synthesized a dataset of 414 women who had ovarian serous carcinoma and 4225 women who had no form of ovarian cancer. We characterized each woman by 22 numbers, representing the length of each chromosome in their germ line DNA. We used a gradient boosting machine to build a classifier that can predict whether a woman had been diagnosed with ovarian cancer. Results The genetic risk score based on chromosomal-scale length variation could stratify women such that the highest 20% had a 160x risk (95% confidence interval 50x-450x) compared to the lowest 20%. The genetic risk score we developed had an area under the curve of the receiver operating characteristic curve of 0.88 (95% confidence interval 0.86–0.91). Conclusion A genetic risk score based on chromosomal-scale length variation of germ line DNA provides an effective means of predicting whether or not a woman will develop ovarian cancer.

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