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1.
Shanghai Journal of Preventive Medicine ; (12): 1044-1048, 2023.
Artigo em Chinês | WPRIM | ID: wpr-1003494

RESUMO

To establish a disease risk prediction model based on genetic susceptibility genes and environmental risk factors, which can target high-risk population as early as possible, and intervene in the environmental risk factors in this population. Moreover, accurate screening of genetically susceptible populations can enhance the efficiency of health system. In recent years, with the maturation and cost reduction of high-throughput gene testing, gene testing has been widely used in individual clinical decision-making and will play a more important role in medical and health decision-making. The correlation between genetic testing and disease risk prediction is increasing, making it a prominent research topic in this field. This review summarizes the approaches for establishing and evaluating risk prediction models and discusses potential future challenges and opportunities.

2.
Neuroscience Bulletin ; (6): 696-704, 2020.
Artigo em Inglês | WPRIM | ID: wpr-826799

RESUMO

To evaluate whether the polygenic profile modifies the development of sporadic Alzheimer's disease (sAD) and pathological biomarkers in cerebrospinal fluid (CSF), 462 sAD patients and 463 age-matched cognitively normal (CN) controls were genotyped for 35 single-nucleotide polymorphisms (SNPs) that are significantly associated with sAD. Then, the alleles found to be associated with sAD were used to build polygenic risk score (PRS) models to represent the genetic risk. Receiver operating characteristic (ROC) analyses and the Cox proportional hazards model were used to evaluate the predictive value of PRS for the sAD risk and age at onset. We measured the CSF levels of Aβ42, Aβ42/Aβ40, total tau (T-tau), and phosphorylated tau (P-tau) in a subgroup (60 sAD and 200 CN participants), and analyzed their relationships with the PRSs. We found that 14 SNPs, including SNPs in the APOE, BIN1, CD33, EPHA1, SORL1, and TOMM40 genes, were associated with sAD risk in our cohort. The PRS models built with these SNPs showed potential for discriminating sAD patients from CN controls, and were able to predict the incidence rate of sAD and age at onset. Furthermore, the PRSs were correlated with the CSF levels of Aβ42, Aβ42/Aβ40, T-tau, and P-tau. Our study suggests that PRS models hold promise for assessing the genetic risk and development of AD. As genetic risk profiles vary among populations, large-scale genome-wide sequencing studies are urgently needed to identify the genetic risk loci of sAD in Chinese populations to build accurate PRS models for clinical practice.

3.
Chinese Journal of Epidemiology ; (12): 1027-1030, 2019.
Artigo em Chinês | WPRIM | ID: wpr-797764

RESUMO

Along with the rapid progress in the field of human genomics, genome-wide association studies have successfully identified numerous risk loci for complex diseases. Polygenic risk scores can predict disease risk by integrating the effects of multiple susceptibility loci, and begin to show good performance for improving risk prediction, screening strategy and precision prevention. This paper briefly reviews the recent progress of polygenic risk scores in disease prevention, and summarizes the opportunities and challenges of its application.

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