Interaction of MC4R rs17782313 variants and dietary carbohydrate quantity and quality on basal metabolic rate and general and central obesity in overweight/obese women: a cross-sectional study

Melanocortin-4 receptor and proopiomelanocortin: Candidate genes for obesity in domestic shorthair cats

Obesity is an escalating global health problem affecting both humans and companion animals. In cats it is associated with increased mortality and multiple diseases, including diabetes mellitus. Two genes coding for proteins known to play a critical role in energy homeostasis across species are the proopiomelanocortin (POMC) gene and the melanocortin-4 receptor (MC4R) gene. A missense variant in the coding sequence of the feline MC4R (MC4R:c.92C>T) has been reported to be associated with diabetes and overweight in domestic shorthair cats, and while variants in the POMC gene are known to cause obesity in humans and dogs, variants in POMC and their association with feline obesity and diabetes mellitus have not been investigated to date. The current study aimed to assess the association between the previously described MC4R variant and body condition score (BCS), as well as body fat content (%BF) in 89 non-diabetic domestic shorthair cats. Furthermore, we investigated the feline POMC gene as a potential candidate gene for obesity. Our results indicate that the MC4R:c.92C>T polymorphism is not associated with BCS or %BF in non-diabetic domestic shorthair cats. The mutation analysis of all POMC exons identified two missense variants, with a variant in exon 1 (c.28G>C; p.G10R) predicted to be damaging. The variant was subsequently assessed in all 89 cats, and cats heterozygous for the variant had a significantly increased body condition score (p = 0.03) compared with cats homozygous for the wild-type allele. Results from our study provide additional evidence that the previously described variant in MC4R is not associated with obesity in domestic shorthair cats. More importantly, we have identified a novel variant in the POMC gene, which might play a role in increased body condition score and body fat content in domestic shorthair cats.

The rs17782313 polymorphism near MC4R gene confers a high risk of obesity and hyperglycemia, while PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder: a systematic review and meta-analysis

Background

The relationships of the rs17782313 polymorphism near melanocortin 4 receptor gene (MC4R) and the rs8192678 polymorphism in peroxisome proliferator-activated receptor gamma coactivator 1 alpha gene (PGC1α) with metabolic abnormalities have been explored in many populations around the world, but the findings were not all consistent and sometimes even a bit contradictory.

Methods

Electronic databases including Medline, Scopus, Embase, Web of Science, CNKI and Google Scholar were checked for studies that met the inclusion criteria. Data were carefully extracted from eligible studies. Standardized mean differences (SMDs) were calculated by using a random-effects model to examine the differences in the indexes of obesity, glucometabolic disorder and dyslipidemia between the genotypes of the rs17782313 and rs8192678 polymorphisms. Cochran's Q-statistic test and Begg's test were employed to identify heterogeneity among studies and publication bias, respectively.

Results

Fifty studies (58,716 subjects) and 51 studies (18,660 subjects) were respectively included in the pooled meta-analyses for the rs17782313 and rs8192678 polymorphisms. The C-allele carriers of the rs17782313 polymorphism had a higher average level of body mass index (SMD = 0.21 kg/m2, 95% confidence interval [95% CI] = 0.12 to 0.29 kg/m2, p < 0.001), waist circumference (SMD = 0.14 cm, 95% CI = 0.06 to 0.23 cm, p < 0.001) and blood glucose (SMD = 0.09 mg/dL, 95% CI = 0.02 to 0.16 mg/dL, p = 0.01) than the TT homozygotes. Regarding the rs8192678 polymorphism, no significant associations with the indexes of obesity, glucometabolic disorder and dyslipidemia were detected. However, significant correlations between the rs8192678 polymorphism and multiple glucometabolic indexes were observed in subgroup analyses stratified by sex, age, ethnicity and health status.

Conclusion

The meta-analysis demonstrates that the C allele of the MC4R rs17782313 polymorphism confers a higher risk of obesity and hyperglycemia, and the PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder. These findings may partly explain the relationships between these variants and diabetes as well as cardiovascular disease.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42022373543.

Association of the rs17782313, rs17773430 and rs34114122 Polymorphisms of/near MC4R Gene with Obesity-Related Biomarkers in a Spanish Pediatric Cohort

Obesity is a multifactorial disease whose onset and development are shaped by the individual genetic background. The melanocortin 4 receptor gene (MC4R) is involved in the regulation of food intake and energy expenditure. Some of the single nucleotide polymorphisms (SNPs) of this gene are related to obesity and metabolic risk factors. The present study was undertaken to assess the relationship between three polymorphism SNPs, namely, rs17782313, rs17773430 and rs34114122, and obesity and metabolic risk factors. One hundred seventy-eight children with obesity aged between 7 and 16 years were studied to determine anthropometric variables and biochemical and inflammatory parameters. Our results highlight that metabolic risk factors, especially alterations in carbohydrate metabolism, were related to rs17782313. The presence of the minor C allele in the three variants (C-C-C) was significantly associated with anthropometric measures indicative of obesity, such as the body mass and fat mass indexes, and increased the values of insulinemia to 21.91 µIU/mL with respect to the wild type values. Our study suggests that the C-C-C haplotype of the SNPs rs17782313, rs17773430 and rs34114122 of the MC4R gene potentiates metabolic risk factors at early ages in children with obesity.

Precision Nutrition: Recent Advances in Obesity

"Precision nutrition" is an emerging area of nutrition research that focuses on understanding metabolic variability within and between individuals and helps develop customized dietary plans and interventions to maintain optimal individual health. It encompasses nutritional genomic (gene-nutrient interactions), epigenetic, microbiome, and environmental factors. Obesity is a complex disease that is affected by genetic and environmental factors and thus a relevant target of precision nutrition-based approaches. Recent studies have shown significant associations between obesity phenotypes (body weight, body mass index, waist circumference, and central and regional adiposity) and genetic variants, epigenetic factors (DNA methylation and noncoding RNA), microbial species, and environment (sociodemographics and physical activity). Additionally, studies have also shown that the interactions between genetic variants, microbial metabolites, and epigenetic factors affect energy balance and adiposity. These include variants in FTO, MC4R, PPAR, APOA, and FADS genes, DNA methylation in CpG island regions, and specific miRNAs and microbial species such as Firmicutes, Bacteriodes, Clostridiales, etc. Similarly, studies have shown that microbial metabolites, folate, B-vitamins, and short-chain fatty acids interact with miRNAs to influence obesity phenotypes. With the advent of next-generation sequencing and analytical approaches, the advances in precision nutrition have the potential to lead to new paradigms, which can further lead to interventions or customized treatments specific to individuals or susceptible groups of individuals. This review highlights the recent advances in precision nutrition as applied to obesity and projects the importance of precision nutrition in obesity and weight management.

Interaction between ultra-processed food intake and genetic risk score on mental health and sleep quality

PURPOSE

Mental health and sleep quality are associated with genetics and nutrient and energy intake. The present study examined the association between ultra-processed food (UPF) intake and genetic risk score (GRS) and their interactions on mental health and sleep quality in Iranian women.

METHODS

A cross-sectional study was conducted on 278 overweight and obese females aged between 18 and 56 years. According to the NOVA classification system, 37 food groups and beverages were collected using a 147-item semi-quantitative food frequency questionnaire (FFQ). The blood parameters of all participants were assessed. Mini-column kit (type G; Genall; Exgene) and the PCR-RFLP method were used to extract DNA and determine gene polymorphism, respectively. Three single nucleotide polymorphisms (SNPs), including Caveolin_1 (Cav_1), Melanocortin4 receptor (MC4R), and cryptochrome circadian regulator 1 (CRY1), were used to calculate GRS. The individual risk allele (0, 1, 2) for each SNP was calculated using the incremental genetic model.

RESULTS

After controlling for confounders, a significant interaction was found for depression (β = 0.026, 95% CI 0.003, 0.049, P = 0.028) and depression anxiety stress scales (DASS) score (β = 0.059, 95% CI 0.001, 0.117, P = 0.046) on the NOVA classification system and GRS.

CONCLUSIONS

The findings of this study showed a significant interaction between GRS and the NOVA classification system on mental disorders, including depression, DASS score and stress. There was also a significant relationship between the NOVA classification system and anxiety, DASS score, sleep quality and depression. Furthermore, a partially significant association was observed between GRS and stress.

LEVEL OF EVIDENCE

Level V, cross-sectional descriptive study.

Meat consumption and the risk of general and central obesity: the Shahedieh study

Objective

This study aimed to investigate the relations of total meat intake and its subtypes, including red and processed meat, white meat, poultry, fish, and organ meat to the risk of general/central obesity.

Methods

This cross-sectional study included a total of 7312 Iranian adults with the age range of 35–70 years from the Shahedieh cohort study, Yazd, Iran. Dietary intake of subjects was evaluated using a validated 120-item Food Frequency Questionnaire. General obesity was defined as body mass index ≥ 30 kg/m2 and central obesity as waist circumference ≥ 102 cm in men and ≥ 88 cm in women.

Results

After controlling for potential covariates including energy intake, age, marital status, gender, physical activity, supplement use, house possession, education, family size, current smoking, night shift working, history of thyroid disease and depression, and intakes of vegetables, legumes, nuts, fruits, whole grains, and dairy, a significant direct association was found between the higher consumption of white meat (OR = 1.31; 95% CI: 1.06–1.61) and poultry (OR = 1.23; 95% CI: 1.04–1.45) with odds of general obesity. Processed meat was a significant predictor for central obesity in the fully adjusted model, so that individuals in the fourth quartile of processed meat intake, compared with those in the first quartile, had a 22% (OR = 1.22; 95% CI: 1.04–1.43) increased risk to be centrally obese.

Conclusion

This study reveals that higher intakes of white meat and poultry are associated with increased risk of general obesity, while, processed meat consumption was associated with central obesity.

Predictive Roles of Basal Metabolic Rate and Body Water Distribution in Sarcopenia and Sarcopenic Obesity: The link to Carbohydrates

Sarcopenic obesity is a new category of obesity and is a specific condition of sarcopenia. This study aimed to find the relationship of the basal metabolic rate (BMR) and body water distribution with muscle health and their prospective roles in screening for sarcopenic obesity and sarcopenia. The role of nutrients such as carbohydrates in the relationship was further detected. A total of 402 elderly subjects were recruited. Body composition was estimated by bioelectrical impedance analysis. Sarcopenia was defined by the Asian Working Group for Sarcopenia 2019. The cutoff values were determined by the receiver operating characteristic curve. Mediation analyses were performed using SPSS PROCESS. Higher BMR and BMR/body surface area (BSA) were protective factors against sarcopenic obesity (OR = 0.047, p = 0.004; OR = 0.035, p = 0.002) and sarcopenia (OR = 0.085, p = 0.001; OR = 0.100, p = 0.003) in elderly people. Low extracellular water (ECW)/intracellular water (ICW) and ECW/total body water (TBW) were negatively correlated with the skeletal muscle index (SMI). The intake of dietary carbohydrates in people with sarcopenic obesity was the lowest, but in subjects with obesity, it was the highest (p = 0.023). The results of the moderated mediation model showed that BMR fully mediated the positive relationship between carbohydrates and SMI, which was more obvious in the population with an abnormal body water distribution. BMR or BMR/BSA had the potential role of predicting a higher risk of sarcopenic obesity and sarcopenia. Higher BMR and lower ECW/ICW and ECW/TBW may benefit muscle health. The overconsumption of carbohydrates (especially > AMDR) might be a risk factor for obesity. Moderate dietary carbohydrate intake might promote SMI by regulating BMR and body water distribution in the elderly.

Association and interaction of the MC4R rs17782313 polymorphism with plasma ghrelin, GLP-1, cortisol, food intake and eating behaviors in overweight/obese Iranian adults

BACKGROUND

Recent studies have shown that obesity is largely influenced by heredity and created by the interactions between several genes and environmental and behavioral factors. This study aimed to examine association between variant rs17782313 near melanocortin-4 receptor (MC4R) gene and behavioral and hormonal factors then evaluated interactions between variant MC4R rs17782313 with behavioral and hormonal factors on obesity.

METHODS

This cross-sectional study included 403 subjects, overweight and/or obesity, aged 20-50 years from Iran. The MC4R rs17782313 data were measured by the PCR-RFLP method. Dietary intake, physical activity, stress, anxiety, depression, appetite and emotional eating were assessed by using validated questionnaires. Ghrelin, glucagon-like peptide-1 and cortisol were measured by radioimmunoassay in plasma samples. Participants were also divided into three groups based on rs17782313 genotype and BMI.

RESULTS

After adjustment for age, gender, energy intake and PA, significant associations were observed between food intake, appetite, emotional eating, stress and physical activity with MC4R rs17782313 (p ˂0.05). Also, significant interactions were observed between fat intake (p-interaction = 0.002), protein intake (p-interaction = 0.01), energy intake (p-interaction = 0.01), emotional eating (p-interaction = 0.02), appetite (p-interaction = 0.04), stress (p-interaction = 0.04), ghrelin (p-interaction = 0.03), cortisol (p-interaction = 0.04) and physical activity (p-interaction = 0.04) and MC4R rs17782313 in terms of BMI.

CONCLUSION

Interactions between the CC genotype and high intakes of fat and energy, emotional eating, high appetite, and too much stress with high levels of cortisol and ghrelin probably can have an effect on BMI in overweight/obese subjects.

The interaction between Alternative Healthy Eating Index and MC4R rs17782313 gene variants on central and general obesity indices in women: a cross-sectional study

BACKGROUND

Previous studies have shown that the C allele of melanocortin 4 receptor (MC4R) rs17782313 and Alternative Healthy Eating Index (AHEI) are separately associated with obesity. However, no study has assessed the aim of this study which is to investigate the interaction between MC4R rs17782313 variants and AHEI and their association with central and general obesity indices.

METHODS

A total of 291 women with BMI ≥25 and aged 18-48 years enrolled in this cross-sectional study. All participants were assessed for body composition, anthropometric measures, dietary intake, and blood parameters. After obtaining data of dietary intake from the 147-item food frequency questionnaire (FFQ) the AHEI was calculated. MC4R rs17782313 SNPs were assessed using the restriction fragment length polymorphism (PCR-RFLP) method.

RESULTS

After adjustment for age, energy intake, physical activity, marital and economic status, the interaction between MC4R rs17782313 and AHEI was associated with hip circumference (HC) (β=-0.41, 95%CI: -0.77 to -0.05, P=0.02), body mass index (BMI) (β=-0.15, 95%CI: -0.29 to -0.02, P=0.02), fat mass (kg) (β=-0.28, 95%CI: -0.56 to -0.01, P=0.03), Visceral fat area (VFA) (β=-5.68, 95%CI: -9.55 to -1.80, P=0.004). The other measures that seem to be suggestively related to this interaction (0.05< P <0.07) are waist circumference (WC), waist-to-height ratio (WHtR), trunk fat (TF) (%), TF (kg), fat mass (%), and fat mass index (FMI).

CONCLUSION

Interaction between MC4R rs17782313 and AHEI can be related to some central and general obesity indices in overweight/obese women. This article is protected by copyright. All rights reserved.