Body composition using bio-impedance analysis in pediatric patients with inflammatory bowel disease. Corcordance with dual energy X-ray absorptiometry and comparison with healthy controls

Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. Objectives: To assess the accuracy of bio-impedance analysis (BIA) compared to the gold standard dual energy X-ray absorptiometry (DEXA) in estimating percentage body fat (fat mass; FM) and lean body mass (fat free mass; FFM) in children with inflammatory bowel disease (IBD). To compare FM and FFM levels between patients with IBD and healthy controls. Methods: Twenty-nine healthy controls (12 females; mean age: 12.7 ± 1.9 years) and 21 patients (11 females; 14.3 ± 1.3 years) were recruited from August 2011 to October 2012 at our institution. BIA was performed in all children and DEXA in patients only. Concordance between BIA and DEXA was assessed using Lin's concordance correlation and the Bland-Altman method. Between-group comparisons were made using analysis of variance adjusting for age. Results: BIA-derived FM% showed a good concordance with DEXA-derived values, while BIA-derived FFM% tended to be slightly higher than DEXA-derived values (table). No differences were found between patients and controls regarding body mass index (mean ± SD: 19.3 ± 3.3 vs. 20.1 ± 2.8 kg/m2, respectively; age-adjusted P = 0.08) and FM% (boys: 25.3 ± 10.2 vs. 22.6 ± 7.1%, for patients and controls, respectively; P = 0.20; girls: 28.2 ± 5.7 vs. 26.4 ± 7.7%; P = 0.91). Also, no differences were found regarding FFM% in boys (74.9 ± 10.2 vs. 77.4 ± 7.1%; P = 0.22) and girls (71.8 ± 5.6 vs. 73.5 ± 7.7%; P = 0.85). Conclusion: BIA adequately assesses body composition (FM%) in children with IBD and could advantageously replace DEXA, which is more expensive and less available. No differences in body composition were found between children with IBD and healthy controls.

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index.

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

FTO genotype is associated with phenotypic variability of body mass index.

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

K-r/K-c but not d(N)/d(S) correlates positively with body mass in birds, raising implications for inferring lineage-specific selection

Background: The ratio of the rates of non-synonymous and synonymous substitution (d(N)/d(S)) is commonly used to estimate selection in coding sequences. It is often suggested that, all else being equal, d(N)/d(S) should be lower in populations with large effective size (Ne) due to increased efficacy of purifying selection. As N-e is difficult to measure directly, life history traits such as body mass, which is typically negatively associated with population size, have commonly been used as proxies in empirical tests of this hypothesis. However, evidence of whether the expected positive correlation between body mass and d(N)/d(S) is consistently observed is conflicting. Results: Employing whole genome sequence data from 48 avian species, we assess the relationship between rates of molecular evolution and life history in birds. We find a negative correlation between dN/dS and body mass, contrary to nearly neutral expectation. This raises the question whether the correlation might be a method artefact. We therefore in turn consider non-stationary base composition, divergence time and saturation as possible explanations, but find no clear patterns. However, in striking contrast to d(N)/d(S), the ratio of radical to conservative amino acid substitutions (K-r/K-c) correlates positively with body mass. Conclusions: Our results in principle accord with the notion that non-synonymous substitutions causing radical amino acid changes are more efficiently removed by selection in large populations, consistent with nearly neutral theory. These findings have implications for the use of d(N)/d(S) and suggest that caution is warranted when drawing conclusions about lineage-specific modes of protein evolution using this metric.

Limited agreement between body mass index, waist and body fat in diagnosing obesity in the Swiss population

Objective: to assess the agreement between different anthropometric markers in defining obesity and the effect on the prevalence of obese subjects. Methods: population-based cross-sectional study including 3213 women and 2912 men aged 35-75 years. Body fat percentage (%BF) was assessed using electric bioimpedance. Obesity was defined using established cut-points for body mass index (BMI) and waist, and three population-defined cut-points for %BF. Between-criteria agreement was assessed by the kappa statistic. Results: in men, agreement between the %BF cut-points was significantly higher (kappa values in the range 0.78 - 0.86) than with BMI or waist (0.47 - 0.62), whereas no such differences were found in women (0.41 - 0.69). In both genders, prevalence of obesity varied considerably according to the criteria used: 17% and 24% according to BMI and waist in men, and 14% and 31%, respectively, in women. For %BF, the prevalence varied between 14% and 17% in men and between 19% and 36% in women according to the cut-point used. In the older age groups, a fourfold difference in the prevalence of obesity was found when different criteria were used. Among subjects with at least one criteria for obesity (increased BMI, waist or %BF), only one third fulfilled all three criteria and one quarter two criteria. Less than half of women and 64% of men were jointly classified as obese by the three population-defined cut-points for %BF. Conclusions: the different anthropometric criteria to define obesity show a relatively poor agreement between them, leading to considerable differences in the prevalence of obesity in the general population.

Body composition phenotypes in pathways to obesity and the metabolic syndrome.

Dynamic changes in body weight have long been recognized as important indicators of risk for debilitating diseases. While weight loss or impaired growth can lead to muscle wastage, as well as to susceptibility to infections and organ dysfunctions, the development of excess fat predisposes to type 2 diabetes and cardiovascular diseases, with insulin resistance as a central feature of the disease entities of the metabolic syndrome. Although widely used as the phenotypic expression of adiposity in population and gene-search studies, body mass index (BMI), that is, weight/height(2) (H(2)), which was developed as an operational definition for classifying both obesity and malnutrition, has considerable limitations in delineating fat mass (FM) from fat-free mass (FFM), in particular at the individual level. After an examination of these limitations within the constraints of the BMI-FM% relationship, this paper reviews recent advances in concepts about health risks related to body composition phenotypes, which center upon (i) the partitioning of BMI into an FM index (FM/H(2)) and an FFM index (FFM/H(2)), (ii) the partitioning of FFM into organ mass and skeletal muscle mass, (iii) the anatomical partitioning of FM into hazardous fat and protective fat and (iv) the interplay between adipose tissue expandability and ectopic fat deposition within or around organs/tissues that constitute the lean body mass. These concepts about body composition phenotypes and health risks are reviewed in the light of race/ethnic variability in metabolic susceptibility to obesity and the metabolic syndrome.

Use of hand-to-hand impedancemetry to predict body composition of African women as measured by air displacement plethysmography.

OBJECTIVES: To test the validity of a simple, rapid, field-adapted, portable hand-held impedancemeter (HHI) for the estimation of lean body mass (LBM) and percentage body fat (%BF) in African women, and to develop specific predictive equations. DESIGN: Cross-sectional observational study. SETTINGS: Dakar, the capital city of Senegal, West Africa. SUBJECTS: A total sample of 146 women volunteered. Their mean age was of 31.0 y (s.d. 9.1), weight 60.9 kg (s.d. 13.1) and BMI 22.6 kg/m(2) (s.d. 4.5). METHODS: Body composition values estimated by HHI were compared to those measured by whole body densitometry performed by air displacement plethysmography (ADP). The specific density of LBM in black subjects was taken into account for the calculation of %BF from body density. RESULTS: : Estimations from HHI showed a large bias (mean difference) of 5.6 kg LBM (P<10(-4)) and -8.8 %BF (P<10(-4)) and errors (s.d. of the bias) of 2.6 kg LBM and 3.7 %BF. In order to correct for the bias, specific predictive equations were developed. With the HHI result as a single predictor, error values were of 1.9 kg LBM and 3.7 %BF in the prediction group (n=100), and of 2.2 kg LBM and 3.6 %BF in the cross-validation group (n=46). Addition of anthropometrical predictors was not necessary. CONCLUSIONS: The HHI analyser significantly overestimated LBM and underestimated %BF in African women. After correction for the bias, the body compartments could easily be estimated in African women by using the HHI result in an appropriate prediction equation with a good precision. It remains to be seen whether a combination of arm and leg impedancemetry in order to take into account lower limbs would further improve the prediction of body composition in Africans.

Prepregnancy body mass index and resting metabolic rate during pregnancy.

AIM: The resting metabolic rate (RMR) varies among pregnant women. The factors responsible for this variability are unknown. This study aimed to assess the influence of the prepregnancy body mass index (BMI) on the RMR during late pregnancy. METHODS: RMR, height, weight, and total (TEE) and activity (AEE) energy expenditures were measured in 46 healthy women aged 31 ± 5 years (mean ± SD) with low (<19.8), normal (19.8-26.0), and high (>26.0) prepregnancy BMI at 38.2 ± 1.5 weeks of gestation (t(gest)) and 40 ± 7 weeks postpartum (t(post)) (n = 27). RESULTS: The mean t(gest) RMR for the low-, normal-, and high-BMI groups was 1,373, 1,807, and 2,191 kcal/day, respectively (p = 0.001). The overall mean t(gest) RMR was 316 ± 183 kcal/day (21%), higher than the overall mean t(post) value and this difference was correlated with gestational weight gain (r = 0.78, p < 0.001). The scaled metabolic rate by allometry (RMR/kilograms⁰·⁷³) was similar in the low-, normal-, and high-BMI groups, respectively (p = 0.45). Changes in t(gest) TEE closely paralleled changes in t(gest) RMR (r = 0.84, p < 0.001). AEE was similar among the BMI groups. CONCLUSION: The RMR is significantly increased in the third trimester of pregnancy. The absolute gestational RMR is higher in women with high prepregnancy BMI due to increased body weight. The scaled metabolic rate (RMR/kilograms⁰·⁷³) is similar among the BMI groups of pregnant women.

Covariation between eumelanic pigmentation and body mass only under specific conditions.

Identifying the factors that mediate covariation between an ornament and other phenotypic attributes is important to determine the signaling function of ornaments. Sign and magnitude of a covariation may vary across environments if the expression of the ornament or of its linked genes regulating correlated phenotypes is condition-dependent. I investigated in the barn owl Tyto alba whether sign and magnitude of covariation between body mass and two heritable melanin-based plumage ornaments change with food supply, along the reproductive cycle and from the morning to the evening. Using a dataset of 1,848 measurements of body mass in 336 breeding females, I found that females displaying large black spots were heavier than conspecifics with smaller spots in the afternoon (i.e., a long time after the last feeding) but not in the morning (i.e., a short time after the last feeding). This is consistent with the recently proposed hypothesis that eumelanin-based ornaments are associated with the ability to maintain energy balance between food intake and energy expenditure. Thus, covariation between melanin-based coloration and body mass can be detected only under specific conditions potentially explaining why it has been reported in only ten out of 28 vertebrate species. The proposition that ornamented individuals achieve a higher fitness than drab conspecifics only in specific environments should be tested for other ornaments.

Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Predicting chick body mass by artificial intelligence-based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

Cross-Sectional and Longitudinal Associations between Body Mass Index and Cardiometabolic Risk Factors in Adolescents in a Country of the African Region.

We assessed the association between several cardiometabolic risk factors (CRFs) (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, uric acid, and glucose) in 390 young adults aged 19-20 years in Seychelles (Indian Ocean, Africa) and body mass index (BMI) measured either at the same time (cross-sectional analysis) or at the age of 12-15 years (longitudinal analysis). BMI tracked markedly between age of 12-15 and age of 19-20. BMI was strongly associated with all considered CRFs in both cross-sectional and longitudinal analyses, with some exceptions. Comparing overweight participants with those having a BMI below the age-specific median, the odds ratios for high blood pressure were 5.4/4.7 (male/female) cross-sectionally and 2.5/3.9 longitudinally (P < 0.05). Significant associations were also found for most other CRFs, with some exceptions. In linear regression analysis including both BMI at age of 12-15 and BMI at age of 19-20, only BMI at age of 19-20 remained significantly associated with most CRFs. We conclude that CRFs are predicted strongly by either current or past BMI levels in adolescents and young adults in this population. The observation that only current BMI remained associated with CRFs when including past and current levels together suggests that weight control at a later age may be effective in reducing CRFs in overweight children irrespective of past weight status.