Literature DB >> 30935434

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

Binghui Du1, Chengda Zhang2, Limin Yue1, Bingnan Ren1, Qinglin Zhao1, Dankang Li1, Yuanhong He3, Weidong Zhang1.   

Abstract

No 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.

Entities:  

Keywords:  Efficacy; Folic acid; Genetic risk score; Hyperhomocysteinaemia; Risk prediction

Year:  2019        PMID: 30935434     DOI: 10.1017/S0007114519000783

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  1 in total

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

Authors:  Xiaorui Chen; Xiaowen Huang; Diao Jie; Caifang Zheng; Xiliang Wang; Bowen Zhang; Weihao Shao; Gaili Wang; Weidong Zhang
Journal:  Sci Rep       Date:  2021-11-02       Impact factor: 4.379

  1 in total

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