Summary
The colonization of the gut with microbes in early life is critical to the developing newborn immune system, metabolic function and potentially future health. Maternal microbes are ...transmitted to offspring during childbirth, representing a key step in the colonization of the infant gut. Studies of infant meconium suggest that bacteria are present in the foetal gut prior to birth, meaning that colonization could occur prenatally. Animal studies have shown that prenatal transmission of microbes to the foetus is possible, and physiological changes observed in pregnant mothers indicate that in utero transfer is likely in humans as well. However, direct evidence of in utero transfer of bacteria in humans is lacking. Understanding the timing and mechanisms involved in the first colonization of the human gut is critical to a comprehensive understanding of the early life gut microbiome. This review will discuss the evidence supporting in utero transmission of microbes from mother to infants. We also review sources of transferred bacteria, physiological mechanisms of transfer and modifiers of maternal microbiomes and their potential role in early life infant health. Well‐designed longitudinal birth studies that account for established modifiers of the gut microbiome are challenging, but will be necessary to confirm in utero transfer and further our knowledge of the prenatal microbiome.
Muller et al. 1 have provided a strong critique of the Genome-Wide Association Studies (GWAS) of body-mass index (BMI), arguing that the GWAS approach for the study of BMI is flawed, and has provided ...us with few biological insights. They suggest that what is needed instead is a new start, involving GWAS for more complex energy balance related traits. In this invited counter-point, we highlight the substantial advances that have occurred in the obesity field, directly stimulated by the GWAS of BMI. We agree that GWAS for BMI is not perfect, but consider that the best route forward for additional discoveries will likely be to expand the search for common and rare variants linked to BMI and other easily obtained measures of obesity, rather than attempting to perform new, much smaller GWAS for energy balance traits that are complex and expensive to measure. For GWAS in general, we emphasise that the power from increasing the sample size of a crude but easily measured phenotype outweighs the benefits of better phenotyping.
Genome-wide association, the latest gene-finding strategy, has led to the first major success in the field of obesity genetics with the discovery of FTO (fat mass and obesity associated gene) as an ...obesity-susceptibility gene. A cluster of variants in the first intron of FTO showed a strong and highly significant association with obesity-related traits in three independent genome-wide association studies, a finding that has been replicated in several other studies including adults and children of European descent. Homozygotes for the risk allele weigh on average 3-4 kg more and have a 1.67-fold increased risk of obesity compared with those who did not inherit a risk allele. We are still at an early stage in our understanding of the pathways through which FTO confers to increased obesity risk. Studies in humans and rodents have suggested a central role for FTO through regulation of food intake, whereas others have proposed a peripheral role through an effect on lipolytic activity in adipose tissue. There is no doubt that many more obesity-susceptibility loci remain to be discovered. Progress on this front will therefore require major collaborative efforts and pooling of compatible datasets. We stand to learn a lot about the genetic architecture of human obesity in the coming years. The expectations are high but many challenges remain. Among the latter, translating new advances into useful guidelines for prevention and treatment of obesity will be the most demanding.
Obesity prevalence continues to rise worldwide, posing a substantial burden on people's health. However, up to 45% of obese individuals do not suffer from cardiometabolic complications, also called ...the metabolically healthy obese (MHO). Concurrently, up to 30% of normal‐weight individuals demonstrate cardiometabolic risk factors that are generally observed in obese individuals, the metabolically obese normal weight (MONW). Besides lifestyle, environmental factors and demographic factors, innate biological mechanisms are known to contribute to the aetiology of the MHO and MONW phenotypes, as well. Experimental studies in animal models have shown that adipose tissue expandability, fat distribution, adipogenesis, adipose tissue vascularization, inflammation and fibrosis, and mitochondrial function are the main mechanisms that uncouple adiposity from its cardiometabolic comorbidities. We reviewed current genetic association studies to expand insights into the biology of MHO/MONW phenotypes. At least four genetic loci were identified through genome‐wide association studies for body fat percentage (BF%) of which the BF%‐increasing allele was associated with a protective effect on glycemic and lipid outcomes. For some, this association was mediated through favourable effects on body fat distribution. Other studies that characterized the genetic susceptibility of insulin resistance found that a higher susceptibility was associated with lower overall adiposity due to less fat accumulation at hips and legs, suggesting that an impaired capacity to store fat subcutaneously or a preferential storage in the intra‐abdominal cavity may be metabolically harmful. Clearly, more work remains to be done in this field, first through gene discovery and subsequently through functional follow‐up of identified genes.
Content List – 14th Key Symposium ‐ “Metabolic Complications of Obesity”.
Globally, the rapid increase of obesity is reaching alarming proportions. A new approach to reduce obesity and its comorbidities involves tackling the built environment. Environmental influences seem ...to play an important role, but the environmental influences in early life on adult body composition have not been thoroughly investigated. This study seeks to fill the research gap by examining early-life exposure to residential green spaces and traffic exposure in association with body composition among a population of young adult twins.
As part of the East Flanders Prospective Twin Survey (EFPTS) cohort, this study included 332 twins. Residential addresses of the mothers at time of birth of the twins were geocoded to determine residential green spaces and traffic exposure. To capture body composition, body mass index, waist-to-hip ratio (WHR), waist circumference, skinfold thickness, leptin levels, and fat percentage were measured at adult age. Linear mixed modelling analyses were conducted to investigate early-life environmental exposures in association with body composition, while accounting for potential confounders. In addition, moderator effects of zygosity/chorionicity, sex and socio-economic status were tested.
Each interquartile range (IQR) increase in distance to highway was found associated with an increase of 1.2% in WHR (95%CI 0.2-2.2%). For landcover of green spaces, each IQR increase was associated with 0.8% increase in WHR (95%CI 0.4-1.3%), 1.4% increase in waist circumference (95%CI 0.5-2.2%), and 2.3% increase in body fat (95%CI 0.2-4.4%). Stratified analyses by zygosity/chorionicity type indicated that in monozygotic monochorionic twins, each IQR increase in land cover of green spaces was associated with 1.3% increase in WHR (95%CI 0.5-2.1%). In monozygotic dichorionic twins, each IQR increase in land cover of green spaces was associated with 1.4% increase in waist-circumference (95%CI 0.6-2.2%).
The built environment in which mothers reside during pregnancy might play a role on body composition among young adult twins. Our study revealed that based on zygosity/chorionicity type differential effects of prenatal exposure to green spaces on body composition at adult age might exist.
Aims/hypothesis Obesity is a major risk factor for type 2 diabetes. Recent genome-wide association (GWA) studies have identified multiple loci robustly associated with BMI and risk of obesity. ...However, information on their associations with type 2 diabetes is limited. Such information could help increase our understanding of the link between obesity and type 2 diabetes. We examined the associations of 12 obesity susceptibility loci, individually and in combination, with risk of type 2 diabetes in the population-based European Prospective Investigation of Cancer (EPIC) Norfolk cohort. Methods We genotyped 12 SNPs, identified by GWA studies of BMI, in 20,428 individuals (aged 39-79 years at baseline) with an average follow-up of 12.9 years, during which 729 individuals developed type 2 diabetes. A genetic predisposition score was calculated by adding the BMI-increasing alleles across the 12 SNPs. Associations with incidence of type 2 diabetes were examined by logistic regression models. Results Of the 12 SNPs, eight showed a trend with increased risk of type 2 diabetes, consistent with their BMI-increasing effects. Each additional BMI-increasing allele in the genetic predisposition score was associated with a 4% increased odds of developing type 2 diabetes (OR 1.041, 95% CI 1.005-1.078; p = 0.02). Adjustment for BMI completely abolished the association with incident type 2 diabetes (OR 1.003, 95% CI 0.967-1.039; p = 0.89). Conclusions/interpretation The genetic predisposition to obesity leads to increased risk of developing type 2 diabetes, which is completely mediated by its obesity-predisposing effect.
Aims/hypothesis We investigated whether variation in MTNR1B, which was recently identified as a common genetic determinant of fasting glucose levels in healthy, diabetes-free individuals, is ...associated with measures of beta cell function and whole-body insulin sensitivity. Methods We studied 1,276 healthy individuals of European ancestry at 19 centres of the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study. Whole-body insulin sensitivity was assessed by euglycaemic-hyperinsulinaemic clamp and indices of beta cell function were derived from a 75 g oral glucose tolerance test (including 30 min insulin response and glucose sensitivity). We studied rs10830963 in MTNR1B using additive genetic models, adjusting for age, sex and recruitment centre. Results The minor (G) allele of rs10830963 in MTNR1B (frequency 0.30 in HapMap Centre d'Etude du Polymorphisme Utah residents with northern and western European ancestry CEU; 0.29 in RISC participants) was associated with higher levels of fasting plasma glucose (standardised beta 95% CI 0.17 0.085, 0.25 per G allele, p = 5.8 x 10⁻⁵), consistent with recent observations. In addition, the G-allele was significantly associated with lower early insulin response (-0.19 -0.28, -0.10, p = 1.7 x 10⁻⁵), as well as with decreased beta cell glucose sensitivity (-0.11 -0.20, -0.027, p = 0.010). No associations were observed with clamp-assessed insulin sensitivity (p = 0.15) or different measures of body size (p > 0.7 for all). Conclusions/interpretation Genetic variation in MTNR1B is associated with defective early insulin response and decreased beta cell glucose sensitivity, which may contribute to the higher glucose levels of non-diabetic individuals carrying the minor G allele of rs10830963 in MTNR1B.
Obesity – is it a genetic disorder? Loos, R. J. F.; Bouchard, C.
Journal of internal medicine,
November 2003, Letnik:
254, Številka:
5
Journal Article
Recenzirano
Odprti dostop
. Loos RJF, Bouchard C (Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA). Obesity – is it a genetic disorder? (Review). J Intern Med 2003; 254: 401–425.
...Obesity is one of the most pressing problems in the industrialized world. Twin, adoption and family studies have shown that genetic factors play a significant role in the pathogenesis of obesity. Rare mutations in humans and model organisms have provided insights into the pathways involved in body weight regulation. Studies of candidate genes indicate that some of the genes involved in pathways regulating energy expenditure and food intake may play a role in the predisposition to obesity. Amongst these genes, sequence variations in the adrenergic receptors, uncoupling proteins, peroxisome proliferator‐activated receptor, and the leptin receptor genes are of particular relevance. Results that have been replicated in at least three genome‐wide scans suggest that key genes are located on chromosomes 2p, 3q, 5p, 6p, 7q, 10p, 11q, 17p and 20q. We conclude that the currently available evidence suggests four levels of genetic determination of obesity: genetic obesity, strong genetic predisposition, slight genetic predisposition, and genetically resistant. This growing body of research may help in the development of anti‐obesity agents and perhaps genetic tests to predict the risk for obesity.
Aims/hypothesis
Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ...ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies.
Methods
We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR.
Results
We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (
RBJ
also known as
DNAJC27
,
QPTCL
: effect sizes −0.068 and −0.107 SD, respectively), HDL-cholesterol (
SLC39A8
: −0.065 SD,
MTCH2
: −0.039 SD), and diastolic BP (
SLC39A8
: −0.069 SD), and higher and lower levels of LDL- and total cholesterol (
QPTCL
: 0.041 and 0.042 SDs, respectively,
FLJ35779
also known as
POC5
: −0.042 and −0.041 SDs, respectively) (all
p
< 2.4 × 10
−4
), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (
GRB14
: 0.069 SD) and lower fasting glucose levels (
CPEB4
: −0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (−0.005 SD), diastolic BP (−0.006 SD) and 2 h glucose (−0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (−0.015 SD) and higher triacylglycerol levels (0.014 SD) (all
p
< 2.9 × 10
−3
), independent of BMI and/or WHR.
Conclusions/interpretation
These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.
Aims/hypothesis We determined the genetic contribution of 18 anthropometric and metabolic risk factors of type 2 diabetes using a young healthy twin population. Methods Traits were measured in 240 ...monozygotic (MZ) and 138 dizygotic (DZ) twin pairs aged 18 to 34 years. Twins were recruited from the Belgian population-based East Flanders Prospective Twin Survey, which is characterised by its accurate zygosity determination and extensive collection of perinatal and placental data, including information on chorionicity. Heritability was estimated using structural equation modelling implemented in the Mx software package. Results Intra-pair correlations of the anthropometric and metabolic characteristics did not differ between MZ monochorionic and MZ dichorionic pairs; consequently heritabilities were estimated using the classical twin approach. For body mass, BMI and fat mass, quantitative sex differences were observed; genetic variance explained 84, 85 and 81% of the total variation in men and 74, 75 and 70% in women, respectively. Heritability estimates of the waist-to-hip ratio, sum of four skinfold thicknesses and lean body mass were 70, 74 and 81%, respectively. The heritability estimates of fasting glucose, fasting insulin, homeostasis model assessment of insulin resistance and beta cell function, as well as insulin-like growth factor binding protein-1 levels were 67, 49, 48, 62 and 47%, in that order. Finally, for total cholesterol, LDL-cholesterol, HDL-cholesterol, total cholesterol:HDL-cholesterol ratio, triacylglycerol, NEFA and leptin levels, genetic factors explained 75, 78, 76, 79, 58, 37 and 53% of the total variation, respectively. Conclusions/interpretation Genetic factors explain the greater part of the variation in traits related to obesity, glucose intolerance/insulin resistance and dyslipidaemia.
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