Next generation sequencing in endocrine practice.

With the completion of the Human Genome Project and advances in genomic sequencing technologies, the use of clinical molecular diagnostics has grown tremendously over the last decade. Next-generation sequencing (NGS) has overcome many of the practical roadblocks that had slowed the adoption of molecular testing for routine clinical diagnosis. In endocrinology, targeted NGS now complements biochemical testing and imaging studies. The goal of this review is to provide clinicians with a guide to the application of NGS to genetic testing for endocrine conditions, by compiling a list of established gene mutations detectable by NGS, and highlighting key phenotypic features of these disorders. As we outline in this review, the clinical utility of NGS-based molecular testing for endocrine disorders is very high. Identifying an exact genetic etiology improves understanding of the disease, provides clear explanation to families about the cause, and guides decisions about screening, prevention and/or treatment. To illustrate this approach, a case of hypophosphatasia with a pathogenic mutation in the ALPL gene detected by NGS is presented.

Relation of Cardiometabolic Risk Factors between Parents and Children.

OBJECTIVES: To explore the relations of parent-child cardiometabolic risk factors and assess the influence of adiposity on these associations. STUDY DESIGN: Associations of adiposity, blood pressure (BP), lipids, fasting insulin and glucose, and a risk factor cluster score (CS) were evaluated in a cross-sectional study of 179 parents and their children (6-18 years, N = 255). Insulin resistance was assessed by euglycemic clamp in parents and children aged 10 years or older. Metabolic syndrome in parents was defined by National Cholesterol Education Program's Adult Treatment Panel III criteria. CSs of the risk factors were created based on age-specific z-scores. Analyses included Pearson correlation and linear regression, adjusted for parent and child age, sex, race, and body mass index (BMI), accounting for within-family correlation. RESULTS: We found positive parent-child correlations for measures of adiposity (BMI, BMI percentile, waist, subcutaneous fat, and visceral fat; r = 0.22-0.34, all P ≤ .003), systolic BP (r = 0.20, P = .002), total cholesterol (r = 0.39, P < .001), low-density lipoprotein cholesterol (r = 0.34, P < .001), high density lipoprotein cholesterol (r = 0.26, P < .001), triglycerides (r = 0.19, P = .01), and insulin sensitivity (r = 0.22, P = .02) as well as CSs (r = 0.15, P = .02). After adjustment for BMI all parent-child correlations, except systolic BP, remained significant. CONCLUSIONS: Although adiposity is strongly correlated between parents and children, many cardiometabolic risk factors correlate independent of parent and child BMI. Adverse parental cardiometabolic profiles may identify at-risk children independent of the child's adiposity status.