Recent studies of animal models reported Nicotinamide N-methyltransferase (NNMT) as a potential therapeutic target for preventing alcohol-associated fatty liver (AFL), yet its efficacy and safety in humans remain unknown. We aim to estimate the effectiveness and safety of inhibiting NNMT in humans. We leveraged Electronic Medical Records (EMRs) data coupled with genetic information to perform a retrospective drug target validation study.
View Article and Find Full Text PDFThis study aims to determine whether CYP2C19 loss-of-function (LoF) variants were associated with long-term ischemic stroke risk in Chinese primary care patients treated with clopidogrel. Patients treated with clopidogrel were ascertained from Chinese electronic medical records linked with a biobank for a retrospective cohort study. Their medical information was examined for the period from January 2018 to December 2021.
View Article and Find Full Text PDFThis study examined intronic gene variants for their association with metformin intolerance in a Chinese population, focusing on the plasma monoamine transporter () cis-protein expression quantitative trait loci (cis-eQTL) variant rs3889348. We recruited Type 2 diabetes patients from two hospitals and identified 111 metformin-intolerant patients using a questionnaire, and selected 206 metformin-tolerant patients from 2180 Type 2 diabetes mellitus patients. Genetic testing revealed an association between adverse gastrointestinal (GI) effects and and .
View Article and Find Full Text PDFPrecis Clin Med
March 2023
Background: Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene-environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection.
View Article and Find Full Text PDFThe R package Continuous Glucose Monitoring Time Series Data Analysis (CGMTSA) was developed to facilitate investigations that examine the continuous glucose monitoring (CGM) data as a time series. Accordingly, novel time series functions were introduced to (1) enable more accurate missing data imputation and outlier identification; (2) calculate recommended CGM metrics as well as key time series parameters; (3) plot interactive and three-dimensional graphs that allow direct visualizations of temporal CGM data and time series model optimization. The software was designed to accommodate all popular CGM devices and support all common data processing steps.
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