Pediatric Obesity Algorithm: A Practical Approach to Obesity Diagnosis and Management

Childhood obesity is a growing global health problem. Despite the highest rates of childhood obesity in the United States and other developed countries over the last 30 years, there is still no clear treatment strategy. Practitioners often do not know where to turn to find guidance on managing the nearly one third of their population who present for medical care either with obesity that coexists with other medical problems or because of obesity. The Pediatric Obesity Algorithm is an evidence based roadmap for the diagnosis and management of children with obesity. In this article, we summarize topics from the Pediatric Obesity Algorithm pertaining to pediatric obesity diagnosis, evaluation, and management including assessment, differential diagnosis, review of systems, diagnostic work up, physical exam, age specific management, comorbidities, use of medications and surgery, and medication associated weight gain. Identifying and treating children with obesity as early as possible is important, as is identifying comorbid conditions. Earlier and more comprehensive management through resources such as the Pediatric Obesity Algorithm serve to help guide health care practitioners with a practical and evidence based approach to the diagnosis and management of children with obesity, and provide families with the tools needed for a healthy future

Elevated blood pressure in youth in pediatric weight management programs in the Pediatric Obesity Weight Evaluation Registry (POWER)

Abstract Blood pressure (BP) assessment and management are important aspects of care for youth with obesity. This study evaluates data of youth with obesity seeking care at 35 pediatric weight management (PWM) programs enrolled in the Pediatric Obesity Weight Evaluation Registry (POWER). Data obtained at a first clinical visit for youth aged 3–17 years were evaluated to: (1) assess prevalence of BP above the normal range (high BP); and (2) identify characteristics associated with having high BP status. Weight status was evaluated using percentage of the 95th percentile for body mass index (%BMIp95); %BMIp95 was used to group youth by obesity class (class 1, 100% to < 120% %BMIp95; class 2, 120% to < 140% %BMIp95; class 3, ≥140% %BMIp95; class 2 and class 3 are considered severe obesity). Logistic regression evaluated associations with high BP. Data of 7943 patients were analyzed. Patients were: mean 11.7 (SD 3.3) years; 54% female; 19% Black non‐Hispanic, 32% Hispanic, 39% White non‐Hispanic; mean %BMIp95 137% (SD 25). Overall, 48.9% had high BP at the baseline visit, including 60.0% of youth with class 3 obesity, 45.9% with class 2 obesity, and 37.7% with class 1 obesity. Having high BP was positively associated with severe obesity, older age (15–17 years), and being male. Nearly half of treatment‐seeking youth with obesity presented for PWM care with high BP making assessment and management of BP a key area of focus for PWM programs

A Cyclic Peptide Inhibitor of HIF‑1 Heterodimerization That Inhibits Hypoxia Signaling in Cancer Cells

Hypoxia inducible factor-1 (HIF-1) is a heterodimeric transcription factor that acts as the master regulator of cellular response to reduced oxygen levels, thus playing a key role in the adaptation, survival, and progression of tumors. Here we report <i>cyclo-</i>CLLFVY, identified from a library of 3.2 million cyclic hexapeptides using a genetically encoded high-throughput screening platform, as an inhibitor of the HIF-1α/HIF-1β protein–protein interaction in vitro and in cells. The identified compound inhibits HIF-1 dimerization and transcription activity by binding to the PAS-B domain of HIF-1α, reducing HIF-1-mediated hypoxia response signaling in a variety of cell lines, without affecting the function of the closely related HIF-2 isoform. The reported cyclic peptide demonstrates the utility of our high-throughput screening platform for the identification of protein–protein interaction inhibitors, and forms the starting point for the development of HIF-1 targeted cancer therapeutics

Multidimensional, quantitative assessment of PD-1/PD-L1 expression in patients with Merkel cell carcinoma and association with response to pembrolizumab

Abstract Background We recently reported a 56% objective response rate in patients with advanced Merkel cell carcinoma (MCC) receiving pembrolizumab. However, a biomarker predicting clinical response was not identified. Methods Pretreatment FFPE tumor specimens (n = 26) were stained for CD8, PD-L1, and PD-1 by immunohistochemistry/immunofluorescence (IHC/IF), and the density and distribution of positive cells was quantified to determine the associations with anti-PD-1 response. Multiplex IF was used to test a separate cohort of MCC archival specimens (n = 16), to identify cell types expressing PD-1. Results Tumors from patients who responded to anti-PD-1 showed higher densities of PD-1+ and PD-L1+ cells when compared to non-responders (median cells/mm2, 70.7 vs. 6.7, p = 0.03; and 855.4 vs. 245.0, p = 0.02, respectively). There was no significant association of CD8+ cell density with clinical response. Quantification of PD-1+ cells located within 20 μm of a PD-L1+ cell showed that PD-1/PD-L1 proximity was associated with clinical response (p = 0.03), but CD8/PD-L1 proximity was not. CD4+ and CD8+ cells in the TME expressed similar amounts of PD-1. Conclusions While the binomial presence or absence of PD-L1 expression in the TME was not sufficient to predict response to anti-PD-1 in patients with MCC, we show that quantitative assessments of PD-1+ and PD-L1+ cell densities as well as the geographic interactions between these two cell populations correlate with clinical response. Cell types expressing PD-1 in the TME include CD8+ T-cells, CD4+ T-cells, Tregs, and CD20+ B-cells, supporting the notion that multiple cell types may potentiate tumor regression following PD-1 blockade