👤 J B Keogh

Obesity causes dyslipidemia and is a major risk factor for cardiovascular disease. However, the mechanisms coupling weight gain and lipid metabolism are poorly understood. Brain melanocortin 4 receptors (MC4Rs) regulate body weight and lipid metabolism in mice, but the relevance of these findings to humans is unclear. Here we investigated lipid levels in men and women with obesity due to MC4R deficiency. Among 7,719 people from the Genetics of Obesity Study cohort, we identified 316 probands and 144 adult family members with loss-of-function (LoF) MC4R mutations. Adults with MC4R deficiency had lower levels of total and low-density lipoprotein (LDL)-cholesterol and triglycerides than 336,728 controls from the UK Biobank, after adjusting for adiposity. Carriers of LoF MC4R variants within the UK Biobank had lower lipid levels and a lower risk of cardiovascular disease, after accounting for body weight, compared to noncarriers. After a high-fat meal, the postprandial rise in triglyceride-rich lipoproteins and metabolomic markers of fatty acid oxidation were reduced in people with MC4R deficiency compared to controls, changes that favor triglyceride storage in adipose tissue. We concluded that central MC4Rs regulate lipid metabolism and cardiovascular disease risk in humans, highlighting potential therapeutic approaches for cardiovascular risk reduction. Show less

Base editors can correct disease-causing genetic variants. After a neonate had received a diagnosis of severe carbamoyl-phosphate synthetase 1 deficiency, a disease with an estimated 50% mortality in early infancy, we immediately began to develop a customized lipid nanoparticle-delivered base-editing therapy. After regulatory approval had been obtained for the therapy, the patient received two infusions at approximately 7 and 8 months of age. In the 7 weeks after the initial infusion, the patient was able to receive an increased amount of dietary protein and a reduced dose of a nitrogen-scavenger medication to half the starting dose, without unacceptable adverse events and despite viral illnesses. No serious adverse events occurred. Longer follow-up is warranted to assess safety and efficacy. (Funded by the National Institutes of Health and others.). Show less

Provision of feed is a major determinant of overall profitability in beef production systems, accounting for up to 75% of the variable costs. Thus, improving cattle feed efficiency, by way of determining the underlying genomic control and subsequently selecting for feed efficient cattle, provides a method through which feed input costs may be reduced. The objective of this study was to undertake gene co-expression network analysis using RNA-Sequence data generated from Longissimus dorsi and liver tissue samples collected from steers of two contrasting breeds (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI), across two consecutive distinct dietary phases (zero-grazed grass and high-concentrate). Categories including differentially expressed genes (DEGs) based on the contrasts of RFI phenotype, breed and dietary source, as well as key transcription factors and proteins secreted in plasma were utilised as nodes of the gene co-expression network. Of the 2,929 DEGs within the network analysis, 1,604 were reported to have statistically significant correlations (≥ 0.80), resulting in a total of 43,876 significant connections between genes. Pathway analysis of clusters of co-expressed genes revealed enrichment of processes related to lipid metabolism (fatty acid biosynthesis, fatty acid β-oxidation, cholesterol biosynthesis), immune function, (complement cascade, coagulation system, acute phase response signalling), and energy production (oxidative phosphorylation, mitochondrial L-carnitine shuttle pathway) based on genes related to RFI, breed and dietary source contrasts. Although similar biological processes were evident across the three factors examined, no one gene node was evident across RFI, breed and diet contrasts in both liver and muscle tissues. However within the liver tissue, the IRX4, NR1H3, HOXA13 and ZNF648 gene nodes, which all encode transcription factors displayed significant connections across the RFI, diet and breed comparisons, indicating a role for these transcription factors towards the RFI phenotype irrespective of diet and breed. Moreover, the NR1H3 gene encodes a protein secreted into plasma from the hepatocytes of the liver, highlighting the potential for this gene to be explored as a robust biomarker for the RFI trait in beef cattle. Show less

People who are severely obese due to melanocortin-4 receptor (MC4R) deficiency experience hyperphagia and impaired fullness after a meal (satiety). Meal-induced satiety is influenced by hormones, such as peptide-YY (PYY), which are released by enteroendocrine cells upon nutrient delivery to the small intestine. We investigated whether gastric emptying and PYY levels are altered in MC4R deficiency. Gastric emptying was measured with a gastric scintigraphy protocol using technetium-99m ( We found that gastric emptying time was significantly delayed and percentage meal retention increased in individuals with MC4R deficiency compared to obese controls. In addition, fasting and mean PYY secretion throughout the day were decreased in MC4R deficiency, whereas postprandial PYY secretion was unaltered. Delayed gastric emptying and reduced basal PYY secretion may contribute to impaired satiety in people with obesity due to MC4R deficiency. Show less

We performed exome sequencing and targeted resequencing in 2548 children who presented with severe obesity, and we unexpectedly identified 22 Almost all Because pathogenic mutations may manifest with obesity alone, screening of children with severe obesity for Show less

The Melanocortin-4 Receptor (MC4R) plays a pivotal role in energy homeostasis. We used human MC4R mutations associated with an increased or decreased risk of obesity to dissect mechanisms that regulate MC4R function. Most obesity-associated mutations impair trafficking to the plasma membrane (PM), whereas obesity-protecting mutations either accelerate recycling to the PM or decrease internalization, resulting in enhanced signaling. MC4R mutations that do not affect canonical Gα Show less

The variation in weight within a shared environment is largely attributable to genetic factors. Whilst many genes/loci confer susceptibility to obesity, little is known about the genetic architecture of healthy thinness. Here, we characterise the heritability of thinness which we found was comparable to that of severe obesity (h2 = 28.07 vs 32.33% respectively), although with incomplete genetic overlap (r = -0.49, 95% CI [-0.17, -0.82], p = 0.003). In a genome-wide association analysis of thinness (n = 1,471) vs severe obesity (n = 1,456), we identified 10 loci previously associated with obesity, and demonstrate enrichment for established BMI-associated loci (pbinomial = 3.05x10-5). Simulation analyses showed that different association results between the extremes were likely in agreement with additive effects across the BMI distribution, suggesting different effects on thinness and obesity could be due to their different degrees of extremeness. In further analyses, we detected a novel obesity and BMI-associated locus at PKHD1 (rs2784243, obese vs. thin p = 5.99x10-6, obese vs. controls p = 2.13x10-6 pBMI = 2.3x10-13), associations at loci recently discovered with much larger sample sizes (e.g. FAM150B and PRDM6-CEP120), and novel variants driving associations at previously established signals (e.g. rs205262 at the SNRPC/C6orf106 locus and rs112446794 at the PRDM6-CEP120 locus). Our ability to replicate loci found with much larger sample sizes demonstrates the value of clinical extremes and suggest that characterisation of the genetics of thinness may provide a more nuanced understanding of the genetic architecture of body weight regulation and may inform the identification of potential anti-obesity targets. Show less

Animal studies indicate that the composition of gut microbiota may be involved in the progression of insulin resistance to type 2 diabetes. Probiotics and/or prebiotics could be a promising approach to improve insulin sensitivity by favourably modifying the composition of the gut microbial community, reducing intestinal endotoxin concentrations and decreasing energy harvest. The aim of the present review was to investigate the effects of probiotics, prebiotics and synbiotics (a combination of probiotics and prebiotics) on insulin resistance in human clinical trials and to discuss the potential mechanisms whereby probiotics and prebiotics improve glucose metabolism. The anti-diabetic effects of probiotics include reducing pro-inflammatory cytokines via a NF-κB pathway, reduced intestinal permeability, and lowered oxidative stress. SCFA play a key role in glucose homeostasis through multiple potential mechanisms of action. Activation of G-protein-coupled receptors on L-cells by SCFA promotes the release of glucagon-like peptide-1 and peptide YY resulting in increased insulin and decreased glucagon secretion, and suppressed appetite. SCFA can decrease intestinal permeability and decrease circulating endotoxins, lowering inflammation and oxidative stress. SCFA may also have anti-lipolytic activities in adipocytes and improve insulin sensitivity via GLUT4 through the up-regulation of 5'-AMP-activated protein kinase signalling in muscle and liver tissues. Resistant starch and synbiotics appear to have favourable anti-diabetic effects. However, there are few human interventions. Further well-designed human clinical studies are required to develop recommendations for the prevention of type 2 diabetes with pro- and prebiotics. Show less