ResearchPad - advances-in-pediatric-obesity-and-cancer Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[OR22-04 Relationship of TSH Levels with the Components of Metabolic Syndrome in a Nationally Representative Population of Youth in the United States]]> Introduction: Subclinical hypothyroidism (SH) is defined as elevated TSH with normal thyroid levels, and is often associated with obesity. SH has been linked to cardiometabolic risk factors such as abnormal lipids, elevated blood pressure, atherosclerosis and fatty liver. This study sought to elucidate the association of TSH level with the components of metabolic syndrome independent of BMI in children from the National Health and Nutrition Examination Survey (NHANES).

Methods: NHANES surveys 1999-01 and 2007-12 that measured thyroid function tests were included in the study. Youth aged 2-18 years with TSH levels < 10 uU/mL and normal Total T4 (TT4) levels were included in the analysis. The components of metabolic syndrome were defined as abdominal obesity (waist circumference > 95th %tile), hypertriglyceridemia (TG >=100 for 0-9 years and >=130 mg/dL for > 10 years), low HDL cholesterol < 40 mg/dL), elevated blood pressure (> 95th %tile for age/sex/height) and hyperglycemia (FBG > 100 mg/dL, or diagnosis of diabetes). The association of these components with quartiles of TSH were examined by logistic and linear regression controlling for age, sex, race/ethnicity and BMI. All analyses were performed in R v3.5.1.

Results: After excluding youth with TSH >10 uU/mL and TT4 levels < 12.4 mcg/dL, 2377 subjects (50% female) were included in the study. The mean age of the cohort was 15 ± 1.7 years; 28.2 % were non-hispanic whites and 38.5 % hispanic/latino. Obesity (BMI >95 %tile) was seen in 21.7% individuals. There were 44 subjects with TSH levels >4.5 uU/mL that was not different by BMI (2.5% in BMI >95%tile and 1.7% BMI < 95%tile, p = 0.29). Based on the distribution in the population, TSH levels were divided into 4 quartiles: Q1= 0.01-0.97, Q2= 0.98-1.42, Q3=1.43-2.0, Q4 = > 2.01 uU/mL. A statistically significant association of the Q4 TSH was seen with abdominal obesity, OR 2.44 (1.38-4.39), p=0.002 and elevated BP, OR 1.6 (1.06-2.44), p = 0.02 but not with high TG, OR 1.58 (0.93-2.75), p=0.09, low HDL, OR 0.84 (0.6-1.17), p = 0.31 or those with hyperglycemia and/or diabetes, OR = 1.25 (0.78-2.05), p = 0.36. Linear regression models showed statistically significant association of abdominal obesity, hypertriglyceridemia, elevated BP and hyperglycemia (and/or diabetes) with increase in TSH level.

Conclusions: In children from a representative US population, the prevalence of SH defined as TSH level >4.5 uU/mL is low, even with BMI >95th %tile. The association of measures of metabolic syndrome with linear increase in TSH suggests that the current reference range may require modification.

<![CDATA[OR22-07 Novel Variants in Protein Kinase a Signaling-Related Genes Identified in Obese Children with and Without NAFLD]]> Context: Nonalcoholic fatty liver disease (NAFLD) is estimated to affect nearly 10% of Americans age 2-19 and about 38% of those affected are obesei. NAFLD is characterized by triglyceride accumulation in hepatocytes and can progress to nonalcoholic steatohepatitis, end stage liver disease and hepatocellular carcinoma. The underlying causes of NAFLD in youth are unclear although obesity, insulin resistance, type 2 diabetes mellitus and metabolic syndrome are risk factors. Genome-wide association studies and candidate gene studies have found several single nucleotide polymorphisms that affect susceptibility to and progression of NAFLD, but clinical translation for some of these genetics is lackingii.

Study design: Because mouse models of dysregulated PKA signaling demonstrate the centrality of this pathway in hepatic lipid metabolism and glucose homeostasis, we hypothesized that defects in hepatic PKA signaling genes could affect susceptibility to or severity of NAFLD in children. We asked whether identified variants might be associated with differences in clinical markers in a cohort of obese pediatric patients (non-NAFLD, n=295; NAFLD, n=165) followed at Yale Medical School, where clinical data and genomic DNA were collected. Exon sequencing of 54 PKA-related candidate genes included those coding for PKA subunits, PDEs and other proteins integral to the hepatic PKA system. Variants were ranked by allele frequency and potential pathogenicity. Ongoing analyses aim to identify associations between single variants and potential additive effects with clinical parameters (anthropometric, liver function, glucose metabolism, plasma lipids).

Results: Gene variants were identified in ABCA1, ADCY4, ADCY5, AKAP7, CREB3L1, CREB3L4, CREM, CYP27A1, DHCR7, ERN1, GYS2, IL6, IL10RB, MC2R, PDE1B, PDE2A, PDE3B, PDE4A, PDE7B, PDE10A, PDE11A, PPARGC1B, PRKAR2A, and PRKAR1B. Reported variants met criteria of high to moderate impact based on 9 in silico scores that predict pathogenicity. Allele frequency ranged from 2.5 to over 50 times higher in our cohort than the general population. One or more variant was identified in 34.9% of non-NAFLD and 19.4% of NAFLD patients (p=.0004).

Conclusion: We report PKA-related gene variants among a cohort of pediatric obese patients that might serve as useful predictors of risk of NAFLD or obesity. Further analyses will help determine whether any of these variants may play a functional role in NAFLD.


i Schwimmer JB, Deutsch R, Kahen T, Lavine JE, Stanley C, Behling C. Pediatrics. 2006;118(4):1388.

ii Vespasiani-Gentilucci U, Gallo P, Dell’Unto C et al. World J Gastroenterol. 2018;24(43):4835-4845.

<![CDATA[OR22-01 NF-κB Pathway Is Implicated in Thyroid Embryogenesis]]> <![CDATA[OR22-06 Bone Outcomes Following Sleeve Gastrectomy in Adolescents and Young Adults with Obesity Versus Non-Surgical Controls]]> <![CDATA[OR22-02 PTEN Hamartoma Tumor Syndrome in Pediatrics: Triggers for Evaluation and the Value of Surveillance]]> <![CDATA[OR22-05 Rare Biallelic Variants in Obesity-Related Genes in the Madrid Pediatric Obesity Cohort]]> +3DS. Participants were sequenced for 35 obesity-related genes, including 23 genes related to Bardet-Biedl (BBS) and Alström syndromes, plus an additional 12 genes associated with non-syndromic, monogenic causes of obesity, to identify individuals with rare (<1% frequency in gnomAD) potentially biallelic (homozygous and compound heterozygous) non-synonymous variants in protein-coding regions. Results: Of the 1019 Spanish patients with obesity, 493 (48.4%) were female and the mean age and BMI were 10.41 ± 3.38 years and 4.38 ± 1.76 SDS (79.8% above +3 SDS), respectively. We identified 26 rare potentially biallelic variants in 25 unique individuals, including 2 individuals with homozygous variants in POMC, 3 individuals with two variants in SRC1, one individual with two variants in ADCY3, and one individual with a homozygous mutation in LEP. In addition, we identified 18 individuals with biallelic mutations in one of 23 BBS or ALMS1 genes, including two individuals with known pathogenic variants and clinically confirmed BBS. Conclusions: Rare and potentially biallelic sequence variants were identified in 25 individuals with childhood obesity. These results support the use of genetic testing for individuals with severe obesity who may be candidates for specific clinical interventions or additional targeted therapies. ]]>