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Clinically relevant body composition methods for obese pediatric patients.

ABSTRACT: BACKGROUND:There is no gold standard in body composition measurement in pediatric patients with obesity. Therefore, the aim of this study was to investigate if there are any differences between two bioelectrical impedance analysis techniques performed in children and adolescents with obesity. METHODS:Data were collected at the Department of Pediatrics and Adolescent Medicine in Vienna from September 2015 to May 2017. Body composition measurement was performed with TANITA scale and BIA-BIACORPUS. RESULTS:In total, 38 children and adolescents (age: 10-18?years, BMI: 25-54?kg/m2) were included. Boys had significantly increased fat free mass (TANITA p?=?0.019, BIA p?=?0.003), total body water (TANITA p?=?0.020, BIA p?=?0.005), and basal metabolic rate (TANITA p?=?0.002, BIA p?=?0.029). Girls had significantly increased body fat percentage with BIA (BIA p?=?0.001). No significant gender differences of core abdominal area have been determined. TANITA overestimated body fat percentage (p?

SUBMITTER: Kreissl A

PROVIDER: S-EPMC6427859 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Clinically relevant body composition methods for obese pediatric patients.

Kreissl Alexandra A Jorda Anselm A Truschner Katharina K Skacel Gabriele G Greber-Platzer Susanne S

BMC pediatrics 20190321 1

<h4>Background</h4>There is no gold standard in body composition measurement in pediatric patients with obesity. Therefore, the aim of this study was to investigate if there are any differences between two bioelectrical impedance analysis techniques performed in children and adolescents with obesity.<h4>Methods</h4>Data were collected at the Department of Pediatrics and Adolescent Medicine in Vienna from September 2015 to May 2017. Body composition measurement was performed with TANITA scale and ...[more]

PMID: 30898093

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Project description:BackgroundPediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions.ResultsOur Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient's medical record, both known and novel fusions provided medically meaningful information.ConclusionsThe EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Project description:BackgroundObesity is known to be related to the development of type 2 diabetes mellitus (T2D). The most commonly used anthropometric indicator (body mass index [BMI]) presents several limitations such as the lack of possibility to distinguish adipose tissue distribution. Thus, this study examines the suitability of a body shape index (ABSI) for prediction of body composition and sarcopenic obesity in obese or overweight T2D subjects.MethodsCross-sectional study in 199 overweight/obese T2D adults. Anthropometric (BMI, ABSI) and body composition (fat mass [FM], fat-free mass [FFM], fat mass index [FMI] and fat-free mass index, and the ratio FM/FFM as an index of sarcopenic obesity) data was collected, as well as metabolic parameters (glycated haemoglobin [HbA1c], mean blood glucose, fasting plasma glucose [FPG], high-density-lipoprotein cholesterol [HDL], low-density-lipoprotein cholesterol, total cholesterol, and triglycerides [TG] levels; the ratio TG/HDL was also calculated as a surrogate marker for insulin resistance).ResultsABSI was significantly associated with age and waist circumference. It showed a statistically significant correlation with BMI exclusively in women. Regarding body composition, in men, ABSI was associated with FM (%), while in women it was associated with both FM and FFM. Both males and females groups with high ABSI scores were significantly older (men: 59.3 ± 10.8 vs 54.6 ± 10.1, p ≤ 0.05; women: 65.1 ± 9.8 vs 58.1 ± 13.3, p ≤ 0.005) and showed lower FFM values (men: 62.3 ± 9.0 vs 66.2 ± 9.3, p ≤ 0.05; women: 48.7 ± 5.6 vs 54.5 ± 8.9, p ≤ 0.001) compared with low-ABSI groups. Multiple linear regression revealed that ABSI independently predict FMI and the FM/FFM ratio in women. Sarcopenic obesity was identified in 70 (36.5%) individuals according to the FM/FFM ratio. The AUROC of ABSI was 63.1% (95% CI 54.6-71.6%; p = 0.003) and an ABSI value of 0.083 m11/6 kg-2/3 was the optimal threshold in discriminating patients with sarcopenic obesity (sensitivity: 48%, specificity: 73%). Moreover, a significant association between ABSI and FPG was found in men.ConclusionsABSI could be useful to identify visceral and sarcopenic obesity in overweight/obese adults with T2D, adding some relevant clinical information to traditional anthropometric measures.

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Clinically relevant body composition methods for obese pediatric patients.

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Clinically relevant body composition methods for obese pediatric patients.

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