Prediction model for the efficacy of folic acid therapy on hyperhomocysteinaemia based on genetic risk score methods

2019 ◽  
Vol 122 (1) ◽  
pp. 39-46
Author(s):  
Binghui Du ◽  
Chengda Zhang ◽  
Limin Yue ◽  
Bingnan Ren ◽  
Qinglin Zhao ◽  
...  
Keyword(s):  
Folic Acid ◽  
Prediction Model ◽  
Risk Score ◽  
Genetic Risk ◽  
Acid Treatment ◽  
Genetic Risk Score ◽  
Assessment Tools ◽  
Acid Therapy ◽  
Gene Environment ◽  
History Of

AbstractNo risk assessment tools for the efficacy of folic acid treatment for hyperhomocysteinaemia (HHcy) have been developed. We aimed to use two common genetic risk score (GRS) methods to construct prediction models for the efficacy of folic acid therapy on HHcy, and the best gene–environment prediction model was screened out. A prospective cohort study enrolling 638 HHcy patients was performed. We used a logistic regression model to estimate the associations of two GRS methods with the efficacy. Performances were compared using area under the receiver operating characteristic curve (AUC). The simple count genetic risk score (SC-GRS) and weighted genetic risk score (wGRS) were found to be independently associated with the efficacy of folic acid treatment for HHcy. Using the SC-GRS, per risk allele increased with a 1·46-fold increased failure risk (P < 0·001) after adjustment for traditional risk factors, including age, sex, BMI, smoking, alcohol consumption, history of diabetes, history of hypertension, history of hyperlipidaemia, history of stroke and history of CHD. When used the wGRS, the association was strengthened (OR = 2·08, P < 0·001). Addition of the SC-GRS and wGRS to the traditional risk model significantly improved the predictive ability by AUC (0·859). A precise gene–environment predictive model with good performance was developed for predicting the treatment failure rate of folic acid therapy for HHcy.

scholarly journals Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaorui Chen ◽  
Xiaowen Huang ◽  
Diao Jie ◽  
Caifang Zheng ◽  
Xiliang Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Folic Acid ◽  
Environmental Factors ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Ann Model ◽  
Acid Therapy ◽  
Youden’S Index

AbstractArtificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its application in medicine. However, none has applied ANN to predict the efficacy of folic acid treatment to Hyperhomocysteinemia (HHcy). The efficacy has been proved to associate with both genetic and environmental factors while previous studies just focused on the latter one. The explained variance genetic risk score (EV-GRS) had better power and could represent the effect of genetic architectures. Our aim was to add EV-GRS into environmental factors to establish ANN to predict the efficacy of folic acid therapy to HHcy. We performed the prospective cohort research enrolling 638 HHcy patients. The multilayer perception algorithm was applied to construct ANN. To evaluate the effect of ANN, we also established logistic regression (LR) model to compare with ANN. According to our results, EV-GRS was statistically associated with the efficacy no matter analyzed as a continuous variable (OR = 3.301, 95%CI 1.954–5.576, P < 0.001) or category variable (OR = 3.870, 95%CI 2.092–7.159, P < 0.001). In our ANN model, the accuracy was 84.78%, the Youden’s index was 0.7073 and the AUC was 0.938. These indexes above indicated higher power. When compared with LR, the AUC, accuracy, and Youden’s index of the ANN model (84.78%, 0.938, 0.7073) were all slightly higher than the LR model (83.33% 0.910, 0.6687). Therefore, clinical application of the ANN model may be able to better predict the folic acid efficacy to HHcy than the traditional LR model. When testing two models in the validation set, we got the same conclusion. This study appears to be the first one to establish the ANN model which added EV-GRS into environmental factors to predict the efficacy of folic acid to HHcy. This model would be able to offer clinicians a new method to make decisions and individual therapeutic plans.

Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score

Diabetologia ◽  
2013 ◽  
Vol 56 (12) ◽  
pp. 2556-2563 ◽  
Author(s):  
Soo Heon Kwak ◽  
Sung Hee Choi ◽  
Kyunga Kim ◽  
Hye Seung Jung ◽  
Young Min Cho ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
History Of

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 Genetic polymorphisms of key enzymes in folate metabolism affect the efficacy of folate therapy in patients with hyperhomocysteinaemia

2018 ◽  
Vol 119 (8) ◽  
pp. 887-895 ◽  
Author(s):  
Binghui Du ◽  
Huizi Tian ◽  
Dandan Tian ◽  
Chengda Zhang ◽  
Wenhua Wang ◽  
...  
Keyword(s):  
Folic Acid ◽  
Interaction Model ◽  
Folate Metabolism ◽  
Efficacy Rate ◽  
Environment Interaction ◽  
Optimal Model ◽  
Acid Therapy ◽  
Gene Environment ◽  
History Of ◽  
Factor Interaction

AbstractThe aim of this study is to analyse the efficacy rate of folate for the treatment of hyperhomocysteinaemia (HHcy) and to explore how folate metabolism-related gene polymorphisms change its efficacy. This study also explored the effects of gene–gene and gene–environment interactions on the efficacy of folate. A prospective cohort study enrolling HHcy patients was performed. The subjects were treated with oral folate (5 mg/d) for 90 d. We analysed the efficacy rate of folate for the treatment of HHcy by measuring homocysteine (Hcy) levels after treatment. Unconditioned logistic regression was conducted to analyse the association between SNP and the efficacy of folic acid therapy for HHcy. The efficacy rate of folate therapy for HHcy was 56·41 %. The MTHFR rs1801133 CT genotype, TT genotype and T allele; the MTHFR rs1801131 AC genotype, CC genotype and C allele; the MTRR rs1801394 GA genotype, GG genotype and G allele; and the MTRR rs162036 AG genotype and AG+GG genotypes were associated with the efficacy of folic acid therapy for HHcy (P<0·05). No association was seen between other SNP and the efficacy of folic acid. The optimal model of gene–gene interactions was a two-factor interaction model including rs1801133 and rs1801394. The optimal model of gene–environment interaction was a three-factor interaction model including history of hypertension, history of CHD and rs1801133. Folate supplementation can effectively decrease Hcy level. However, almost half of HHcy patients failed to reach the normal range. The efficacy of folate therapy may be genetically regulated.

scholarly journals Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance

2017 ◽  
Vol 10 (9) ◽  
pp. 535-541 ◽  
Author(s):  
Motoki Iwasaki ◽  
Sachiko Tanaka-Mizuno ◽  
Aya Kuchiba ◽  
Taiki Yamaji ◽  
Norie Sawada ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Prediction Model ◽  
Japanese Men

Identifying gene-environment interactions on the efficacy of folic acid therapy for hyperhomocysteinemia based on prediction model

2020 ◽  
Vol 77 ◽  
pp. 54-61
Author(s):  
Qinglin Zhao ◽  
Dankang Li ◽  
Xiaowen Huang ◽  
Bingnan Ren ◽  
Limin Yue ◽  
...  
Keyword(s):  
Folic Acid ◽  
Prediction Model ◽  
Acid Therapy ◽  
Gene Environment

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.

Abstract P414: Omega-3 Fatty Acids Modify the Genetic Risk of Early Onset Acute Coronary Syndrome

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Sylvie S Leung Yinko ◽  
James C Engert ◽  
George Thanassoulis` ◽  
Ken D Stark ◽  
Meytal Avgil Tsadok ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Fatty Acid Intake ◽  
Omega 3 ◽  
Omega 3 Fatty Acid ◽  
Coronary Syndrome ◽  
Acid Intake ◽  
Gene Environment

Background: Recent gene-environment interaction studies suggest that diet may influence an individual’s genetic predisposition to cardiovascular risk. We tested the hypothesis that omega-3 fatty acid intake may influence the risk for acute coronary syndrome (ACS) conferred by genetic polymorphisms among patients with premature ACS. Methods: Our study population consisted of 706 patients of white European descent enrolled in GENESIS PRAXY, a multicentre prospective cohort study of patients aged 18 to 55 years hospitalized with ACS. We used a case-only design to investigate gene-environment interactions between the omega-3 index (a validated biomarker of omega-3 fatty acid intake) and 30 single nucleotide polymorphisms (SNPs) that have been robustly associated with ACS. We used logistic regression to study the associations between each SNP and the omega-3 index. Interaction was also assessed between the omega-3 index and a genetic risk score generated from the 30 SNPs as a simple unweighted count of the risk alleles for each SNP. All the SNPs used in the genetic risk score were uncorrelated (r2 <0.3). We further adjusted all models for age and sex. Results: The median age of our population was 49 years and 72.1% were male. Median omega-3 index was 3.35% (interquartile range 2.81-4.07%). None of the SNPs deviated from Hardy-Weinberg equilibrium. A synergistic multiplicative interaction for increased ACS risk was found between carriers of chromosome 9p21 variant rs4977574 and low omega-3 index (OR 1.57, 95% CI 1.07-2.32, p=0.02), but did not reach significance after correction for multiple testing. Similar results were obtained in the adjusted model (OR 1.55, 95% CI 1.05-2.29, p=0.03). We did not observe interaction between the genetic risk score and the omega-3 index. Conclusions: In conclusion, our results suggest that omega-3 fatty acid intake may modify the genetic risk conferred by chromosome 9p21 variation among ACS patients but require independent replication in other cohorts. Further validation research is also warranted to examine whether this interaction occurs in other ethnic groups.

Sign in / Sign up

Export Citation Format

Share Document