Application of body composition zones in boys with nonalcoholic fatty liver disease.

PURPOSE: Screening nonalcoholic fatty liver disease (NAFLD) by body mass index (BMI) as a single surrogate measure for obesity has limitations. We suggest considering body composition zones by drawing a body composition chart composed of body composition indices, including BMI and percent body fat (PBF), to visualize the risk of NAFLD in obese children and adolescents. METHODS: Thirty-eight boys diagnosed with NAFLD were selected retrospectively from patients who visited Konkuk University Medical Center from 2006 to 2015. They had gone through body composition analysis by bioelectrical impedance analysis (BIA), and biochemical analyses, including a liver function test (LFT) and lipid panel, were performed. Fat-free mass index (FFMI) and fat mass index (FMI) were calculated from body composition analysis and height. We plotted FFMI and FMI of patients on a body composition chart and classified the patients into zones A to D. In addition, we analyzed the correlations between LFT, lipid panel, and body composition indices. RESULTS: Thirty-three of 38 boys (86.8%) were located in zone C, corresponding to high BMI and PBF. Four boys (10.5%) were located in zone D, which correlates with sarcopenic obesity. One boy located in zone B was a muscular adolescent. Alanine aminotransferase level was positively correlated with PBF, FMI, and BMI z-score. CONCLUSION: Body composition zones on a body composition chart might be useful in risk assessment in obesity-related diseases such as NAFLD. Zones on a body composition chart could have practical applications, especially in sarcopenic obese children and adolescents.

Cervical small cell neuroendocrine tumor mutation profiles via whole exome sequencing.

Cervical small cell neuroendocrine tumors (CSCNETs) are rare, aggressive neuroendocrine tumors (NETs). Reliable diagnostic and prognostic CSCNET markers are lacking, making diagnosis and prognosis prediction difficult, and treatment strategies limited. Here we provide mutation profiles for five tumor-normal paired CSCNETs using whole exome sequencing (WES). We expanded our assessment of frequently mutated genes to include publicly available data from 55 small intestine neuroendocrine tumors, 10 pancreatic neuroendocrine tumors, 42 small cell lung cancers, six NET cell lines, and 188 cervical cancers, along with our five CSCNETs. We identified 1,968 somatic mutations, including 1,710 missense, 106 nonsense, 144 splice site, 4 lncRNA, 3 nonstop, and 1 start codon mutation. We assigned functions to the 114 most frequently mutated genes based on gene ontology. ATRX, ERBB4, and genes in the Akt/mTOR pathway were most frequently mutated. Positive cytoplasmic ERBB4 immunohistochemical staining was detected in all CSCNET tumors tested, but not in adjacent normal tissues. To our knowledge, this study is the first to utilize WES in matched CSCNET and normal tissues to identify somatic mutations. Further studies will improve our understanding of how ATRX and ERBB4 mutations and AKT/mTOR signaling promote CSCNET tumorigenesis, and may be leveraged in novel anti-cancer treatment strategies.