Identification and Evolutionary Analysis of Potential Candidate Genes in a Human Eating Disorder

Risk factors for eating disorders: findings from a rapid review

BACKGROUND

Risk factors represent a range of complex variables associated with the onset, development, and course of eating disorders. Understanding these risk factors is vital for the refinement of aetiological models, which may inform the development of targeted, evidence-based prevention, early intervention, and treatment programs. This Rapid Review aimed to identify and summarise research studies conducted within the last 12 years, focusing on risk factors associated with eating disorders.

METHODS

The current review forms part of a series of Rapid Reviews to be published in a special issue in the Journal of Eating Disorders, funded by the Australian Government to inform the development of the National Eating Disorder Research and Translation Strategy 2021-2031. Three databases were searched for studies published between 2009 and 2021, published in English, and comprising high-level evidence studies (meta-analyses, systematic reviews, moderately sized randomised controlled studies, moderately sized controlled-cohort studies, or population studies). Data pertaining to risk factors for eating disorders were synthesised and outlined in the current paper.

RESULTS

A total of 284 studies were included. The findings were divided into nine main categories: (1) genetics, (2) gastrointestinal microbiota and autoimmune reactions, (3) childhood and early adolescent exposures, (4) personality traits and comorbid mental health conditions, (5) gender, (6) socio-economic status, (7) ethnic minority, (8) body image and social influence, and (9) elite sports. A substantial amount of research exists supporting the role of inherited genetic risk in the development of eating disorders, with biological risk factors, such as the role of gut microbiota in dysregulation of appetite, an area of emerging evidence. Abuse, trauma and childhood obesity are strongly linked to eating disorders, however less conclusive evidence exists regarding developmental factors such as role of in-utero exposure to hormones. Comorbidities between eating disorders and mental health disorders, including personality and mood disorders, have been found to increase the severity of eating disorder symptomatology. Higher education attainment, body image-related factors, and use of appearance-focused social media are also associated with increased risk of eating disorder symptoms.

CONCLUSION

Eating disorders are associated with multiple risk factors. An extensive amount of research has been conducted in the field; however, further studies are required to assess the causal nature of the risk factors identified in the current review. This will assist in understanding the sequelae of eating disorder development and in turn allow for enhancement of existing interventions and ultimately improved outcomes for individuals.

A holistic miRNA-mRNA module discovery

The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. In this paper we will focus on miRNA-mRNA modules, where regulation jointly occurs in miRNA-mRNA pairs. Namely, we propose a holistic procedure to identify miRNA-mRNA modules within a population of candidate pairs. Since current methods still leave open issues, we adopt the strategy of postponing any decision on the value of the module ingredients exactly at the end, i.e. at the moment of biologically exploiting the results. This diverts chains of statistical tests into sequences of specially-devised-evolving metrics on the possible solutions. This strategy is rather expensive under a computational perspective, so needing implementations on HPC. The reward stands in the discovery of new modules, possibly hosting non differentially expressed miRNAs and mRNAs and pairs containing genes that currently are considered not targeted. In the paper we implement the procedure on a Multiple Myeloma dataset publicly available on GEO platform, as a template of a cancer instance analysis, and hazard some biological issues. These results, jointly with the normal manageability of the computations, suggest that the discovery procedure may be profitably extended to a wide spectrum of diseases where miRNA-mRNA interactions play a relevant role.

Changes in VGF and C3aR1 gene expression in human adipose tissue in obesity

The VGF gene, which has been shown to be metabolically associated with energy balance, glucose homeostasis, insulin secretion process, and biological processes related to overeating, is prominent in relation to obesity. TLQP-21 neuropeptide, derived from the VGF, is considered to promote lipolysis by the beta-adrenergic pathway through targeting the C3aR1 receptor located in the adipocyte membrane. In this study, we aimed to measure the expression levels of the VGF and C3aR1 genes in the adipose tissue of obese subjects and individuals with normal weight determined based on body mass index (BMI), and to reveal the correlation of these levels with obesity. VGF and C3aR1 gene expression levels were measured using Real Time Polymerase Chain Reaction (RT PCR) in the visceral adipose tissue (VAT) samples of 52 obese patients (BMI ≥ 35 kg/m²) and 21 non-obese controls (BMI = 18.5-24.9 kg/m²). The results were statistically analyzed. The VGF expression was lower and the C3aR1 gene expression was higher in obese patients compared to the non-obese control group (p < 0.05). In obese patients, there was a statistically significant positive correlation of 85.6% between VGF and C3aR1, in which when one level increased, the other also increased (p < 0.05, r = 0.856). The findings show that the VGF may be significantly associated with obesity and is very important since it is the first to measure the level of VGF gene expression in human adipose tissue. This research provides new evidence of a link between obesity and VGF/C3aR1 and in the future may help design strategies to combat obesity.

Survey of allele specific expression in bovine muscle

Allelic imbalance is a common phenomenon in mammals that plays an important role in gene regulation. An Allele Specific Expression (ASE) approach can be used to detect variants with a cis-regulatory effect on gene expression. In cattle, this type of study has only been done once in Holstein. In our study we performed a genome-wide analysis of ASE in 19 Limousine muscle samples. We identified 5,658 ASE SNPs (Single Nucleotide Polymorphisms showing allele specific expression) in 13% of genes with detectable expression in the Longissimus thoraci muscle. Interestingly we found allelic imbalance in AOX1, PALLD and CAST genes. We also found 2,107 ASE SNPs located within genomic regions associated with meat or carcass traits. In order to identify causative cis-regulatory variants explaining ASE we searched for SNPs altering binding sites of transcription factors or microRNAs. We identified one SNP in the 3’UTR region of PRNP that could be a causal regulatory variant modifying binding sites of several miRNAs. We showed that ASE is frequent within our muscle samples. Our data could be used to elucidate the molecular mechanisms underlying gene expression imbalance.

A region-resolved mucosa proteome of the human stomach

The human gastric mucosa is the most active layer of the stomach wall, involved in food digestion, metabolic processes and gastric carcinogenesis. Anatomically, the human stomach is divided into seven regions, but the protein basis for cellular specialization is not well understood. Here we present a global analysis of protein profiles of 82 apparently normal mucosa samples obtained from living individuals by endoscopic stomach biopsy. We identify 6,258 high-confidence proteins and estimate the ranges of protein expression in the seven stomach regions, presenting a region-resolved proteome reference map of the near normal, human stomach. Furthermore, we measure mucosa protein profiles of tumor and tumor nearby tissues (TNT) from 58 gastric cancer patients, enabling comparisons between tumor, TNT, and normal tissue. These datasets provide a rich resource for the gastrointestinal tract research community to investigate the molecular basis for region-specific functions in mucosa physiology and pathology including gastric cancer.

The human stomach is divided into seven anatomically distinct regions but their protein composition is largely unknown. Here, the authors present a region-resolved map of the healthy human stomach mucosa as well as mucosa proteomes of tumor and tumor nearby tissue from gastric cancer patients.