Implication of phosphatidylethanolamine N-methyltransferase in adipocyte differentiation

Xiao

et al. 2022

IJMS

Concern about rising rates of obesity has prompted searches for obesity-related single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS). Identifying plausible regulatory SNPs is very difficult partially because of linkage disequilibrium. We used an unusual epigenomic and transcriptomic analysis of obesity GWAS-derived SNPs in adipose versus heterologous tissues. From 50 GWAS and 121,064 expanded SNPs, we prioritized 47 potential causal regulatory SNPs (Tier-1 SNPs) for 14 gene loci. A detailed examination of seven loci revealed that four (CABLES1, PC, PEMT, and FAM13A) had Tier-1 SNPs positioned so that they could regulate use of alternative transcription start sites, resulting in different polypeptides being generated or different amounts of an intronic microRNA gene being expressed. HOXA11 and long noncoding RNA gene RP11-392O17.1 had Tier-1 SNPs in their 3′ or promoter region, respectively, and strong preferences for expression in subcutaneous versus visceral adipose tissue. ZBED3-AS1 had two intragenic Tier-1 SNPs, each of which could contribute to mediating obesity risk through modulating long-distance chromatin interactions. Our approach not only revealed especially credible novel regulatory SNPs, but also helped evaluate previously highlighted obesity GWAS SNPs that were candidates for transcription regulation.

Section: Discussionmentioning

confidence: 95%

Epigenomic and Transcriptomic Prioritization of Candidate Obesity-Risk Regulatory GWAS SNPs

Xiao

et al. 2022

IJMS

“…Padmavathi et al found that smoking could upregulate the levels of phosphatidylethanolamine and downregulate phosphatidylcholine in men(43). Although no association, to our knowledge, between phosphatidylethanolamine and body weight has been reported in previous studies, several investigations have found that the deficiency of phosphatidylethanolamine N-methyltransferase a small integral membrane protein that converts PE to phosphatidylcholine, decreases the risk of high-fat diet-induced obesity and insulin resistance by inhibiting the differentiation of preadipocytes into mature adipose cells(44,45). The role of PE (18:0/20:4[5Z,8Z,11Z,14Z]) in body weight regulation warrants further investigation.Through comparing the serum metabolome between current smokers and never smokers, we identified both external and endogenous metabolites associated with current smoking.…”

mentioning

confidence: 77%

Examination of serum metabolome altered by cigarette smoking identifies novel metabolites mediating smoking‐BMI association

Sun

Huang

et al. 2022

Obesity

Objective The authors hypothesize that an untargeted metabolomics study will identify novel mechanisms underlying smoking‐associated weight loss. Methods This study performed cross‐sectional analyses among 1,252 participants in the Bogalusa Heart Study and assessed 1,202 plasma metabolites for mediation effects on smoking‐BMI associations. Significant metabolites were tested for associations with smoking genetic risk scores among a subset of participants (n = 654) with available genomic data, followed by direction dependence analysis to investigate causal relationships between the metabolites and smoking and BMI. All analyses controlled for age, sex, race, education, alcohol drinking, and physical activity. Results Compared with never smokers, current and former smokers had a 3.31‐kg/m2 and 1.77‐kg/m2 lower BMI after adjusting for all covariables, respectively. A total of 22 xenobiotics and 94 endogenous metabolites were significantly associated with current smoking. Eight xenobiotics were also associated with former smoking. Forty metabolites mediated the smoking‐BMI associations, and five showed causal relationships with both smoking and BMI. These metabolites, including 1‐oleoyl‐GPE (18:1), 1‐linoleoyl‐GPE (18:2), 1‐stearoyl‐2‐arachidonoyl‐GPE (18:0/20:4), α‐ketobutyrate, and 1‐palmitoyl‐GPE (16:0), mediated 26.0% of the association between current smoking and BMI. Conclusions This study cataloged plasma metabolites altered by cigarette smoking and identified five metabolites that partially mediated the association between current smoking and BMI.

“…PEMT is a tiny integral membrane protein that transforms phosphatidylethanolamine (PE) to phosphatidylcholine (PC). PEMT knockdown prevented lipid droplet formation, lowered triacylglycerol concentration, and decreased leptin release from adipocytes ( 24 – 26 ). Fat migration into the periphery of the vast lateral, gastrocnemius, as well as soleus muscles, was seen in all ADSSL1 myopathy patients, as were increased lipid droplets ( 27 ).…”

Section: Discussionmentioning

confidence: 98%

Construction and Analysis of a Joint Diagnosis Model of Random Forest and Artificial Neural Network for Obesity

Xie

et al. 2022

Front. Med.

Obesity is a significant global health concern since it is connected to a higher risk of several chronic diseases. As a consequence, obesity may be described as a condition that reduces human life expectancy and significantly impacts life quality. Because traditional obesity diagnosis procedures have several flaws, it is vital to design new diagnostic models to enhance current methods. More obesity-related markers have been discovered in recent years as a result of improvements and enhancements in gene sequencing technology. Using current gene expression profiles from the Gene Expression Omnibus (GEO) collection, we identified differentially expressed genes (DEGs) associated with obesity and found 12 important genes (CRLS1, ANG, ALPK3, ADSSL1, ABCC1, HLF, AZGP1, TSC22D3, F2R, FXN, PEMT, and SPTAN1) using a random forest classifier. ALPK3, HLF, FXN, and SPTAN1 are the only genes that have never been linked to obesity. We also used an artificial neural network to build a novel obesity diagnosis model and tested its diagnostic effectiveness using public datasets.