A bidirectional link between metabolic syndrome and elevation in alanine aminotransferase in elderly female: a longitudinal community study.

Pre-obesity, as a significant risk factor for the progression of metabolic syndrome (MS), has become a prevalent public health threat globally. In this three-year longitudinal study of pre-obese women at baseline, the goal was to clarify the female-specific bidirectional relationship between the risk of MS and blood alanine aminotransferase. In this manuscript, the MS score was determined using the following equation: MS score = 2*waist/height + fasting glucose/5.6 + TG/1.7 + SBP/130-HDL/1.02 for men and 1.28 for women, which is highly related to the risk of MS. With 2,338 participants, a hierarchical nonlinear model with random effects was utilized to analyze the temporal trends of serum characteristics from 2017 to 2019. A bivariate cross-lagged panel model (CLPM) was employed to estimate the structural relations of frequently measured variables at three different time points to determine the directionality of the relationship between the risk of MS and serum characteristics. MassARRAY Analyzer 4 platforms were used to evaluate and genotype candidate SNPs. In this study, the MS score only rose with age in females; it was positively correlated with serum alanine aminotransferase (ALT) in females; the CLPM revealed that the MS score in 2017 predicted ALT in 2018 (ß = 0.066, p < 0.001); and ALT in 2018 predicted an MS score in 2019 (ß = 0.037, p < 0.050); both relationships were seen in females. Additionally, the MS score in elderly females with NAFLD was related to the rs295 in the lipoprotein lipase (LPL) gene (p = 0.042). Our work showed that there may be female-specific causal correlations between elevated ALT and risk of MS and that the polymorphism rs295 in LPL may serve as a marker for the prognosis of MS. The genetic roles of rs295 in the LPL gene in the onset of MS and the development of ALT in the elderly Chinese Han population are thus provided by this, offering one potential mechanism.

3D genome-selected microRNAs to improve Alzheimer's disease prediction.

Introduction: Alzheimer's disease (AD) is a type of neurodegenerative disease that has no effective treatment in its late stage, making the early prediction of AD critical. There have been an increase in the number of studies indicating that miRNAs play an important role in neurodegenerative diseases including Alzheimer's disease via epigenetic modifications including DNA methylation. Therefore, miRNAs may serve as excellent biomarkers in early AD prediction. Methods: Considering that the non-coding RNAs' activity may be linked to their corresponding DNA loci in the 3D genome, we collected the existing AD-related miRNAs combined with 3D genomic data in this study. We investigated three machine learning models in this work under leave-one-out cross-validation (LOOCV): support vector classification (SVC), support vector regression (SVR), and knearest neighbors (KNNs). Results: The prediction results of different models demonstrated the effectiveness of incorporating 3D genome information into the AD prediction models. Discussion: With the assistance of the 3D genome, we were able to train more accurate models by selecting fewer but more discriminatory miRNAs, as witnessed by several ML models. These interesting findings indicate that the 3D genome has great potential to play an important role in future AD research.

College students' screening early warning factors in identification of suicide risk.

This study aimed to explore the main influencing factors of suicide risk among Chinese students and establish an early warning model to provide interventions for high-risk students. We conducted surveys of students in their first and third years from a cohort study at Jining Medical College. Logistic regression models were used to screen the early warning factors, and four machine learning models were used to establish early warning models. There were 8 factors related to suicide risk that were eventually obtained through screening, including age, having a rough father, and CES-D, OHQ, ASLEC-4, BFI-Neuroticism, BFI-Openness, and MMC-AF-C scores. A random forest model with SMOTE was adopted, and it verified that these 8 early warning signs, for suicide risk can effectively predict suicide risk within 2 years with an AUC score of 0.947. Among the factors, we constructed a model that indicated that different personality traits affected suicide risk by different paths. Moreover, the factors obtained by screening can be used to identify college students in the same year with a high risk of suicide, with an AUC score that reached 0.953. Based on this study, we suggested some interventions to prevent students going high suicide risk.

The gender-specific bidirectional relations between chronic diseases and total bilirubin/urea in the elderly population: A 3-year longitudinal study.

Aging is accompanied by changes in physiology over time, which remains the largest risk of chronic diseases. The aim of this study was to explore the gender-specific bidirectional relations between the risk of chronic diseases and serum traits in a 3-year longitudinal study. A hierarchical non-linear model with random effects was used to assess the temporal patterns of anthropometric and serum traits from 2017 to 2019 among 2,338 participants. To assess the directional effect between the risk of chronic diseases and serum traits, a bivariate cross-lagged panel model (CLPM) was used to estimate the structural relations of repeatedly measured variables at three different time points. Candidate SNPs were analyzed and genotyped in MassARRAY Analyzer 4 platforms. In this study, metabolic syndrome (MS) score increased with aging in females, whereas the fatty liver disease (FLD) index decreased with aging in males; the MS score was negatively correlated with TB in females, and FLD index was positively related to urea in males; CLPM showed that the MS score predicted total bilirubin (TB) in females, and urea predicted the FLD index in males. Additionally, rs2292354 in G protein-coupled receptor kinase interactor 2 (GIT2) was associated with the MS score and TB in aged females. Our study suggests the potential gender-specific causal associations between development in MS and increase in TB level in females, and rise in urea level and improved FLD index in males. The SNP rs2292354 we investigated might be a biomarker for predicting MS in the elderly Chinese Han population.

The host genetics affects gut microbiome diversity in Chinese depressed patients.

The gut microbiome and host genetics are both associated with major depressive disorder (MDD); however, the molecular mechanisms among the associations are poorly understood, especially in the Asian, Chinese group. Our study applied linear discriminant analysis (LDA) effect size (LEfSe) and genome-wide association analysis in the cohort with both gut sequencing data and genomics data. We reported the different gut microbiota characteristics between MDD and control groups in the Chinese group and further constructed the association between host genetics and the gut microbiome. Actinobacteria and Pseudomonades were found more in the MDD group. We found significant differences in the ACE and Chao indexes of alpha diversity while no discrepancy in beta diversity. We found three associations between host genetics with microbiome features: beta diversity and rs6108 (p = 8.65 × 10-9), Actinobacteria and rs77379751 (p = 8.56 × 10-9), and PWY-5913 and rs1775633082 (p = 4.54 × 10-8). A species of the Romboutsia genus was co-associated with the species of Ruminococcus gnavus in an internetwork through four genes: METTL8, ITGB2, OTULIN, and PROSER3, with a strict threshold (p < 5 × 10-4). Furthermore, our findings suggested that the gut microbiome diversity might affect microRNA expression in the brain and influenced SERPINA5 and other spatially close genes afterward. These findings suggest new linkages between depression and gut microbiome in Asian, Chinese people, which might be mediated by genes and microRNA regulation in space distance.

Effect of exercise and diet intervention in NAFLD and NASH via GAB2 methylation.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a disorder that extends from simple hepatic steatosis to nonalcoholic steatohepatitis (NASH), which is effectively alleviated by lifestyle intervention. Nevertheless, DNA methylation mechanism underling the effect of environmental factors on NAFLD and NASH is still obscure. The aim of this study was to investigate the effect of exercise and diet intervention in NAFLD and NASH via DNA methylation of GAB2. METHODS: Methylation of genomic DNA in human NAFLD was quantified using Infinium Methylation EPIC BeadChip assay after exercise (Ex), low carbohydrate diet (LCD) and exercise plus low carbohydrate diet (ELCD) intervention. The output Idat files were processed using ChAMP package. False discovery rate on genome-wide analysis of DNA methylation (q < 0.05), and cytosine-guanine dinucleotides (CpGs) which are located in promoters were used for subsequent analysis (|Δß|≥ 0.1). K-means clustering was used to cluster differentially methylated genes according to 3D genome information from Human embryonic stem cell. To quantify DNA methylation and mRNA expression of GRB2 associated binding protein 2 (GAB2) in NASH mice after Ex, low fat diet (LFD) and exercise plus low fat diet (ELFD), MassARRAY EpiTYPER and quantitative reverse transcription polymerase chain reaction were used. RESULTS: Both LCD and ELCD intervention on human NAFLD can induce same DNA methylation alterations at critical genes in blood, e.g., GAB2, which was also validated in liver and adipose of NASH mice after LFD and ELFD intervention. Moreover, methylation of CpG units (i.e., CpG_10.11.12) inversely correlated with mRNA expression GAB2 in adipose tissue of NASH mice after ELFD intervention. CONCLUSIONS: We highlighted the susceptibility of DNA methylation in GAB2 to ELFD intervention, through which exercise and diet can protect against the progression of NAFLD and NASH on the genome level, and demonstrated that the DNA methylation variation in blood could mirror epigenetic signatures in target tissues of important biological function, i.e., liver and adipose tissue. Trial registration International Standard Randomized Controlled Trial Number Register (ISRCTN 42622771).

No Association Between SLC6A4 Gene Polymorphisms With Treatment Remission to Venlafaxine in Han Chinese Depressive Patients.

OBJECTIVE: Major depressive disorder (MDD) is a heterogeneous psychiatric disorder and considered to be one of the most common mental diseases worldwide. The antidepressant venlafaxine, as a serotonin noradrenaline reuptake inhibitor, is applied to MDD relief. Solute carrier family 6 member 4 (SLC6A4) has been reported to promote the reuptake of serotonin and to be closely correlated to depression. The present study examined whether rs6354 and rs1487971 in SLC6A4 are associated with remission after venlafaxine treatment in MDD patients. METHODS: This study consisted of 195 Han Chinese patients with MDD, who accepted a 6-week treatment with venlafaxine. Two SLC6A4 single-nucleotide polymorphisms (SNPs) were selected from database of SNP and genotyped by matrix-assisted laser desorption/ionization time of flight mass spectrometer in MassARRAY Analyzer 4 platforms. The 17-item Hamilton Depression Scale was used to access the severity of major depression. Allele and genotype frequencies between patients in remission and nonremission were calculated with online software SHEsis. RESULTS: No significant differences in allele or genotype frequencies were observed in rs6354 and rs1487971. There were no significant associations between 2 SNPs and venlafaxine treatment outcome. CONCLUSIONS: It suggested that rs6354 or rs1487971 within SLC6A4 appears not to be involved in the venlafaxine treatment outcome in Han Chinese patients with MDD.