(1)H-MRS measured ectopic fat in liver and muscle is associated with the metabolic syndrome in Danish girls but not in boys with overweight and obesity

BACKGROUND: The metabolic syndrome (MetS) is a complication to overweight and obesity, which can be observed already in childhood. Ectopic lipid accumulation in muscle and liver has been shown to associate with the development of insulin resistance and dyslipidemia. Thus, the interaction between MetS and ectopic fat may offer clinical relevance. OBJECTIVES: To investigate the prevalence of MetS, or components hereof, and ectopic fat accumulation in liver and skeletal muscle tissue in children, as well as interactions between these. METHODS: Two‐hundred‐and‐sixteen children and adolescents (95 boys) with overweight/obesity were investigated, as well as 47 controls (22 boys) with normal weight. The assessments included anthropometry, fasting blood biochemistry and blood pressure measurements. Liver and muscle lipid contents were assessed by proton magnetic resonance spectroscopy. RESULTS: We observed an odds ratio in girls with overweight/obesity of 12.2 (95% confidence interval: [3.8; 49.0]) for exhibiting MetS when hepatic steatosis was present, whereas no association was observed in boys with overweight/obesity (odds ratio 0.7 [0.2; 2.7]). The odds ratio of exhibiting MetS in the presence of muscular steatosis was 3.5 [1.4; 9.5] in girls with overweight/obesity and 1.0 [0.2; 5.6] in boys with overweight/obesity. Similar results were seen for girls with overweight/obesity exhibiting concurrent hepatic and muscular steatoses. CONCLUSION: Hepatic and muscular steatoses were associated with MetS among girls, but not among boys with overweight/obesity

Specific gut microbiota features and metabolic markers in postmenopausal women with obesity

BACKGROUND: Gut microbial gene richness and specific bacterial species are associated with metabolic risk markers in humans, but the impact of host physiology and dietary habits on the link between the gut microbiota and metabolic markers remain unclear. The objective of this study was to identify gut metagenomic markers associated with estimates of insulin resistance, lipid metabolism and inflammation in obesity, and to explore whether the associations between metagenomic and metabolic markers persisted after adjustment for body fat, age and habitual dietary intake. METHODS: Faecal DNA from 53 women with obesity was analysed through quantitative metagenomic sequencing and analysis, and a systematic search was performed for bacterial genes associated with estimates of insulin resistance, inflammation and lipid metabolism. Subsequently, the correlations between metagenomic species and metabolic markers were tested by linear regression models, with and without covariate adjustment. RESULTS: One hundred and fourteen metagenomic species correlated with metabolic markers (P<0.001) including Akkermansia muciniphila, Bilophila wadsworthia, Bifidobacterium longum and Faecalibacterium prausnitzii, but also species not previously associated with metabolic markers including Bacteroides faecis and Dorea longicatena. The majority of the identified correlations between bacterial species and metabolic markers persisted after adjustment for differences in body fat, age and dietary macronutrient composition; however, the negative correlation with insulin resistance observed for B. longum and F. prausnitzii appeared to be modified by the intake of dietary fibre and fat, respectively. CONCLUSIONS: This study shows that several gut bacterial species are linked to metabolic risk markers in obesity, also after adjustment for potential confounders, such as long-term diet composition. The study supports the use of gut metagenomic markers for metabolic disease prediction and warrants further investigation of causality

Identification of novel genetic determinants of erythrocyte membrane fatty acid composition among Greenlanders

Fatty acids (FAs) are involved in cellular processes important for normal body function, and perturbation of FA balance has been linked to metabolic disturbances, including type 2 diabetes. An individual's level of FAs is affected by diet, lifestyle, and genetic variation. We aimed to improve the understanding of the mechanisms and pathways involved in regulation of FA tissue levels, by identifying genetic loci associated with inter-individual differences in erythrocyte membrane FA levels. We assessed the levels of 22 FAs in the phospholipid fraction of erythrocyte membranes from 2,626 Greenlanders in relation to single nucleotide polymorphisms genotyped on the MetaboChip or imputed. We identified six independent association signals. Novel loci were identified on chromosomes 5 and 11 showing strongest association with oleic acid (rs76430747 in ACSL6, beta (SE): -0.386% (0.034), p = 1.8x10-28) and docosahexaenoic acid (rs6035106 in DTD1, 0.137% (0.025), p = 6.4x10-8), respectively. For a missense variant (rs80356779) in CPT1A, we identified a number of novel FA associations, the strongest with 11-eicosenoic acid (0.473% (0.035), p = 2.6x10-38), and for variants in FADS2 (rs174570), LPCAT3 (rs2110073), and CERS4 (rs11881630) we replicated known FA associations. Moreover, we observed metabolic implications of the ACSL6 (rs76430747) and CPT1A (rs80356779) variants, which both were associated with altered HbA1c (0.051% (0.013), p = 5.6x10-6 and -0.034% (0.016), p = 3.1x10-4, respectively). The latter variant was also associated with reduced insulin resistance (HOMA-IR, -0.193 (0.050), p = 3.8x10-6), as well as measures of smaller body size, including weight (-2.676 kg (0.523), p = 2.4x10-7), lean mass (-1.200 kg (0.271), p = 1.7x10-6), height (-0.966 cm (0.230), p = 2.0x10-5), and BMI (-0.638 kg/m2 (0.181), p = 2.8x10-4). In conclusion, we have identified novel genetic determinants of FA composition in phospholipids in erythrocyte membranes, and have shown examples of links between genetic variants associated with altered FA membrane levels and changes in metabolic traits

Diabetic cats have decreased gut microbial diversity and a lack of butyrate producing bacteria

none11noneKieler, Ida Nordang*; Osto, Melania; Hugentobler, Leoni; Puetz, Lara; Gilbert, M. Thomas P.; Hansen, Torben; Pedersen, Oluf; Reusch, Claudia E.; Zini, Eric; Lutz, Thomas A.; Bjørnvad, Charlotte ReinhardKieler, Ida Nordang; Osto, Melania; Hugentobler, Leoni; Puetz, Lara; Gilbert, M. Thomas P.; Hansen, Torben; Pedersen, Oluf; Reusch, Claudia E.; Zini, Eric; Lutz, Thomas A.; Bjørnvad, Charlotte Reinhar

Uncovering the genetic history of the present-day greenlandic population

Because of past limitations in samples and genotyping technologies, important questions about the history of the present-day Greenlandic population remain unanswered. In an effort to answer these questions and in general investigate the genetic history of the Greenlandic population, we analyzed ∼200,000 SNPs from more than 10% of the adult Greenlandic population (n = 4,674). We found that recent gene flow from Europe has had a substantial impact on the population: more than 80% of the Greenlanders have some European ancestry (on average ∼25% of their genome). However, we also found that the amount of recent European gene flow varies across Greenland and is far smaller in the more historically isolated areas in the north and east and in the small villages in the south. Furthermore, we found that there is substantial population structure in the Inuit genetic component of the Greenlanders and that individuals from the east, west, and north can be distinguished from each other. Moreover, the genetic differences in the Inuit ancestry are consistent with a single colonization wave of the island from north to west to south to east. Although it has been speculated that there has been historical admixture between the Norse Vikings who lived in Greenland for a limited period ∼600–1,000 years ago and the Inuit, we found no evidence supporting this hypothesis. Similarly, we found no evidence supporting a previously hypothesized admixture event between the Inuit in East Greenland and the Dorset people, who lived in Greenland before the Inuit

Studies of association of AGPAT6 variants with type 2 diabetes and related metabolic phenotypes in 12,068 Danes

BACKGROUND: Type 2 diabetes, obesity and insulin resistance are characterized by hypertriglyceridemia and ectopic accumulation of lipids in liver and skeletal muscle. AGPAT6 encodes a novel glycerol-3 phosphate acyltransferase, GPAT4, which catalyzes the first step in the de novo triglyceride synthesis. AGPAT6-deficient mice show lower weight and resistance to diet- and genetically induced obesity. Here, we examined whether common or low-frequency variants in AGPAT6 associate with type 2 diabetes or related metabolic traits in a Danish population. METHODS: Eleven variants selected by a candidate gene approach capturing the common and low-frequency variation of AGPAT6 were genotyped in 12,068 Danes from four study populations of middle-aged individuals. The case–control study involved 4,638 type 2 diabetic and 5,934 glucose-tolerant individuals, while studies of quantitative metabolic traits were performed in 5,645 non-diabetic participants of the Inter99 Study. RESULTS: None of the eleven AGPAT6 variants were robustly associated with type 2 diabetes in the Danish case–control study. Moreover, none of the AGPAT6 variants showed association with measures of obesity (waist circumference and BMI), serum lipid concentrations, fasting or 2-h post-glucose load levels of plasma glucose and serum insulin, or estimated indices of insulin secretion or insulin sensitivity. CONCLUSIONS: Common and low-frequency variants in AGPAT6 do not significantly associate with type 2 diabetes susceptibility, or influence related phenotypic traits such as obesity, dyslipidemia or indices of insulin sensitivity or insulin secretion in the population studied

Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota

BACKGROUND: Roux-en-Y gastric bypass (RYGB) is an effective means to achieve sustained weight loss for morbidly obese individuals. Besides rapid weight reduction, patients achieve major improvements of insulin sensitivity and glucose homeostasis. Dysbiosis of gut microbiota has been associated with obesity and some of its co-morbidities, like type 2 diabetes, and major changes of gut microbial communities have been hypothesized to mediate part of the beneficial metabolic effects observed after RYGB. Here we describe changes in gut microbial taxonomic composition and functional potential following RYGB. METHODS: We recruited 13 morbidly obese patients who underwent RYGB, carefully phenotyped them, and had their gut microbiomes quantified before (n = 13) and 3 months (n = 12) and 12 months (n = 8) after RYGB. Following shotgun metagenomic sequencing of the fecal microbial DNA purified from stools, we characterized the gut microbial composition at species and gene levels followed by functional annotation. RESULTS: In parallel with the weight loss and metabolic improvements, gut microbial diversity increased within the first 3 months after RYGB and remained high 1 year later. RYGB led to altered relative abundances of 31 species (P < 0.05, q < 0.15) within the first 3 months, including those of Escherichia coli, Klebsiella pneumoniae, Veillonella spp., Streptococcus spp., Alistipes spp., and Akkermansia muciniphila. Sixteen of these species maintained their altered relative abundances during the following 9 months. Interestingly, Faecalibacterium prausnitzii was the only species that decreased in relative abundance. Fifty-three microbial functional modules increased their relative abundance between baseline and 3 months (P < 0.05, q < 0.17). These functional changes included increased potential (i) to assimilate multiple energy sources using transporters and phosphotransferase systems, (ii) to use aerobic respiration, (iii) to shift from protein degradation to putrefaction, and (iv) to use amino acids and fatty acids as energy sources. CONCLUSIONS: Within 3 months after morbidly obese individuals had undergone RYGB, their gut microbiota featured an increased diversity, an altered composition, an increased potential for oxygen tolerance, and an increased potential for microbial utilization of macro- and micro-nutrients. These changes were maintained for the first year post-RYGB. TRIAL REGISTRATION: Current controlled trials (ID NCT00810823, NCT01579981, and NCT01993511). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0312-1) contains supplementary material, which is available to authorized users

Variation in CHI3LI in Relation to Type 2 Diabetes and Related Quantitative Traits

CHI3LI encoding the inflammatory glycoprotein YKL-40 is located on chromosome 1q32.1. YKL-40 is involved in inflammatory processes and patients with Type 2 Diabetes (T2D) have elevated circulating YKL-40 levels which correlate with their level of insulin resistance. Interestingly, it has been reported that rs10399931 (-329 G/A) of CHI3LI contributes to the inter-individual plasma YKL-40 levels in patients with sarcoidosis, and that rs4950928 (-131 C/G) is a susceptibility polymorphism for asthma and a decline in lung function. We hypothesized that single nucleotide polymorphisms (SNPs) or haplotypes thereof the CHI3LI locus might influence risk of T2D. The aim of the present study was to investigate the putative association between SNPs and haplotype blocks of CHI3LI and T2D and T2D related quantitative traits.Eleven SNPs of CHI3LI were genotyped in 6514 individuals from the Inter99 cohort and 2924 individuals from the outpatient clinic at Steno Diabetes Center. In cas-control studies a total of 2345 T2D patients and 5302 individuals with a normal glucose tolerance test were examined. We found no association between rs10399931 (OR, 0.98 (CI, 0.88-1.10), p = 0.76), rs4950928 (0.98 (0.87-1.10), p = 0.68) or any of the other SNPs with T2D. Similarly, we found no significant association between any of the 11 tgSNPs and T2D related quantitative traits, all p>0.14. None of the identified haplotype blocks of CHI3LI showed any association with T2D, all p>0.16.None of the examined SNPs or haplotype blocks of CHI3LI showed any association with T2D or T2D related quantitative traits. Estimates of insulin resistance and dysregulated glucose homeostasis in T2D do not seem to be accounted for by the examined variations of CHI3LI