👤 Susann Blüher

A single nucleotide polymorphism in the brain derived neurotrophic factor (BDNF)-encoding gene leads to diminished BDNF signaling resulting from Val66Met and has been linked to obesity. Previous imaging studies regarding the impact of BDNF Val66Met on the central serotonin system, which is involved in behavior, cognition and control of satiety, have not focused on body weight or food-intake related behavior. We revisited a cohort of thirty non-depressed individuals with obesity and 15 normal-weight controls. 29 obese and 13 controls underwent [ Show less

Glucose-dependent insulinotropic polypeptide (GIP) was the first incretin identified and plays an essential role in the maintenance of glucose tolerance in healthy humans. Until recently GIP had not been developed as a therapeutic and thus has been overshadowed by the other incretin, glucagon-like peptide 1 (GLP-1), which is the basis for several successful drugs to treat diabetes and obesity. However, there has been a rekindling of interest in GIP biology in recent years, in great part due to pharmacology demonstrating that both GIPR agonism and antagonism may be beneficial in treating obesity and diabetes. This apparent paradox has reinvigorated the field, led to new lines of investigation, and deeper understanding of GIP. In this review, we provide a detailed overview on the multifaceted nature of GIP biology and discuss the therapeutic implications of GIPR signal modification on various diseases. Following its classification as an incretin hormone, GIP has emerged as a pleiotropic hormone with a variety of metabolic effects outside the endocrine pancreas. The numerous beneficial effects of GIPR signal modification render the peptide an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, drug-induced nausea and both bone and neurodegenerative disorders. Show less

White adipose tissue dysfunction has emerged as a critical factor in cardiometabolic disease development, yet the cellular microstructure and genetic architecture of adipocyte morphology remain poorly explored. We introduce Adipocyte U-Net 2.0, an advanced deep learning method for the semantic segmentation of adipose tissue histology, enabling analysis of over 27 million adipocytes from 2,667 individuals. Our approach revealed that adipocyte hypertrophy associates with metabolic dysfunction, including increased fasting glucose, glycated hemoglobin, leptin, and triglycerides, with decreased adiponectin and HDL cholesterol levels. Through the largest genome-wide association study of adipocyte size to date (N Our findings demonstrate the utility of deep learning for adipocyte phenotyping at scale and provide novel insights into the genetic basis of adipocyte morphology and its relationship to metabolic disease. Show less

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity. Show less

The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149). We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits. Show less

The prevalence of obesity and type 2 diabetes is increasing worldwide and threatens to shorten lifespan. Impaired insulin action in peripheral tissues is a major pathogenic factor. Insulin stimulates glucose uptake in adipose tissue through the GLUT4 (also known as SLC2A4) glucose transporter, and alterations in adipose tissue GLUT4 expression or function regulate systemic insulin sensitivity. Downregulation of human and mouse adipose tissue GLUT4 occurs early in diabetes development. Here we report that adipose tissue GLUT4 regulates the expression of carbohydrate-responsive-element-binding protein (ChREBP; also known as MLXIPL), a transcriptional regulator of lipogenic and glycolytic genes. Furthermore, adipose ChREBP is a major determinant of adipose tissue fatty acid synthesis and systemic insulin sensitivity. We find a new mechanism for glucose regulation of ChREBP: glucose-mediated activation of the canonical ChREBP isoform (ChREBP-α) induces expression of a novel, potent isoform (ChREBP-β) that is transcribed from an alternative promoter. ChREBP-β expression in human adipose tissue predicts insulin sensitivity, indicating that it may be an effective target for treating diabetes. Show less

Recent genome-wide association studies identified novel candidate genes for fasting and 2 h blood glucose and insulin levels in adults. We investigated the role of four of these loci (ADCY5, GIPR, GCKR and VPS13C) in early impairment of glucose and insulin metabolism in children. We genotyped four variants (rs2877716; rs1260326; rs10423928; rs17271305) in 638 Caucasian children with detailed metabolic testing including an oGTT and assessed associations with measures of glucose and insulin metabolism (including fasting blood glucose, insulin levels and insulin sensitivity/secretion indices) by linear regression analyses adjusted for age, sex, BMI-SDS and pubertal stage. The major allele (C) of rs2877716 (ADCY5) was nominally associated with decreased fasting plasma insulin (P = 0.008), peak insulin (P = 0.009) and increased QUICKI (P = 0.016) and Matsuda insulin sensitivity index (P = 0.013). rs17271305 (VPS13C) was nominally associated with 2 h blood glucose (P = 0.009), but not with any of the insulin or insulin sensitivity parameters. We found no association of the GIPR and GCKR variants with parameters of glucose and insulin metabolism. None of the variants correlated with anthropometric traits such as height, WHR or BMI-SDS, which excluded potential underlying associations with obesity. Our data on obese children indicate effects of genetic variation within ADCY5 in early impairment of insulin metabolism and VPS13C in early impairment of blood glucose homeostasis. Show less