Citations

Hyperthyroidism causes increased energy intake and expenditure, although anorexia and higher weight loss have been reported in elderly individuals with hyperthyroidism. To determine the effect of age on energy homeostasis in response to experimental hyperthyroidism, we administered 200 μg triiodothyronine (T3) in 7‐ and 27‐mo‐old rats for 14 d. T3 increased energy expenditure (EE) in both the young and the old rats, although the old rats lost more weight (147 g) than the young rats (58 g) because of the discordant effect of T3 on food intake, with a 40% increase in the young rats, but a 40% decrease in the old ones. The increased food intake in the young rats corresponded with a T3‐mediated increase in the appetite‐regulating proteins agouti‐related peptide, neuropeptide Y, and uncoupling protein 2 in the hypothalamus, but no increase occurred in the old rats. Evidence of mitochondrial biogenesis in response to T3 was similar in the soleus muscle and heart of the young and old animals, but less consistent in old plantaris muscle and liver. Despite the comparable increase in EE, T3's effect on mitochondrial function was modulated by age in a tissue‐specific manner. We conclude that older rats lack compensatory mechanisms to increase caloric intake in response to a T3‐induced increase in EE, demonstrating a detrimental effect of age on energy homeostasis.—Walrand, S., Short, K. R., Heemstra, L. A., Novak, C. M., Levine, J. A., Coenen‐Schimke, J. M., Nair, K. S. Altered regulation of energy homeostasis in older rats in response to thyroid hormone administration. FASEB J. 28, 1499–1510 (2014). www.fasebj.org

Abstract A missense single-nucleotide polymorphism (SNP) in the immune modulatory gene IL1A has been associated with ovarian cancer risk (rs17561). Although the exact mechanism through which this SNP alters risk of ovarian cancer is not clearly understood, rs17561 has also been associated with risk of endometriosis, an epidemiologic risk factor for ovarian cancer. Interleukin-1α (IL1A) is both regulated by and able to activate NF-κB, a transcription factor family that induces transcription of many proinflammatory genes and may be an important mediator in carcinogenesis. We therefore tagged SNPs in more than 200 genes in the NF-κB pathway for a total of 2,282 SNPs (including rs17561) for genotype analysis of 15,604 cases of ovarian cancer in patients of European descent, including 6,179 of high-grade serous (HGS), 2,100 endometrioid, 1,591 mucinous, 1,034 clear cell, and 1,016 low-grade serous, including 23,235 control cases spanning 40 studies in the Ovarian Cancer Association Consortium. In this large population, we confirmed the association between rs17561 and clear cell ovarian cancer [OR, 0.84; 95% confidence interval (CI), 0.76–0.93; P = 0.00075], which remained intact even after excluding participants in the prior study (OR, 0.85; 95% CI, 0.75–0.95; P = 0.006). Considering a multiple-testing–corrected significance threshold of P < 2.5 × 10−5, only one other variant, the TNFSF10 SNP rs6785617, was associated significantly with a risk of ovarian cancer (low malignant potential tumors OR, 0.85; 95% CI, 0.79–0.91; P = 0.00002). Our results extend the evidence that borderline tumors may have a distinct genetic etiology. Further investigation of how these SNPs might modify ovarian cancer associations with other inflammation-related risk factors is warranted. Cancer Res; 74(3); 852–61. ©2013 AACR.

Purpose Indications for sentinel lymph node biopsy (SLNB) for thin melanoma are continually evolving. We present a large multi-institutional study to determine factors predictive of sentinel lymph node (SLN) metastasis in thin melanoma. Patients and Methods Retrospective review of the Sentinel Lymph Node Working Group database from 1994 to 2012 identified 1,250 patients who had an SLNB and thin melanomas (≤ 1 mm). Clinicopathologic characteristics were correlated with SLN status and outcome. Results SLN metastases were detected in 65 (5.2%) of 1,250 patients. On univariable analysis, rates of Breslow thickness ≥ 0.75 mm, Clark level ≥ IV, ulceration, and absence of regression differed significantly between positive and negative SLN groups (all P < .05). These four variables and mitotic rate were used in multivariable analysis, which demonstrated that Breslow thickness ≥ 0.75 mm (P = .03), Clark level ≥ IV (P = .05), and ulceration (P = .01) significantly predicted SLN metastasis with 6.3%, 7.0%, and 11.6% of the patients with these respective characteristics having SLN disease. Melanomas < 0.75 mm had positive SLN rates of < 5% regardless of Clark level and ulceration status. Median follow-up was 2.6 years. Melanoma-specific survival was significantly worse for patients with positive versus negative SLNs (P = .001). Conclusion Breslow thickness ≥ 0.75 mm, Clark level ≥ IV, and ulceration significantly predict SLN disease in thin melanoma. Most SLN metastases (86.2%) occur in melanomas ≥ 0.75 mm, with 6.3% of these patients having SLN disease, whereas in melanomas < 0.75 mm, SLN metastasis rates are < 5%. By using a 5% metastasis risk threshold, SLNB is indicated for melanomas ≥ 0.75 mm, but further study is needed to define indications for SLNB in melanomas < 0.75 mm.

Key Points In combination with cyclophosphamide, intravenous busulfan is associated with better leukemia-free and overall survival in AML than TBI.

Significance We describe a genomic disorder that causes obesity, intellectual disability, and seizures. Children with this syndrome carry an unbalanced chromosome translocation that results in the duplication of over 100 genes, including G protein β3 ( GNB3 ). Although GNB3 polymorphisms have been associated with obesity, hypertension, and diabetes, the mechanism of GNB3 pathogenesis is unknown. We created a transgenic mouse model that carries a duplication of GNB3 , weighs significantly more than wild-type mice, and has excess abdominal fat. GNB3 is highly expressed in the brain and may be important for signaling related to satiety and/or metabolism.

Background: In type 1 diabetes mellitus (T1DM), physical activity (PA) lowers the risk of cardiovascular complications but hinders the achievement of optimal glycemic control, transiently boosting insulin action and increasing hypoglycemia risk. Quantitative investigation of relationships between PA-related signals and glucose dynamics, tracked using, for example, continuous glucose monitoring (CGM) sensors, have been barely explored. Subjects and Methods: In the clinic, 20 control and 19 T1DM subjects were studied for 4 consecutive days. They underwent low-intensity PA sessions daily. PA was tracked by the PA monitoring system (PAMS), a system comprising accelerometers and inclinometers. Variations on glucose dynamics were tracked estimating first- and second-order time derivatives of glucose concentration from CGM via Bayesian smoothing. Short-time effects of PA on glucose dynamics were quantified through the partial correlation function in the interval (0, 60 min) after starting PA. Results: Correlation of PA with glucose time derivatives is evident. In T1DM, the negative correlation with the first-order glucose time derivative is maximal (absolute value) after 15 min of PA, whereas the positive correlation is maximal after 40–45 min. The negative correlation between the second-order time derivative and PA is maximal after 5 min, whereas the positive correlation is maximal after 35–40 min. Control subjects provided similar results but with positive and negative correlation peaks anticipated of 5 min. Conclusions: Quantitative information on correlation between mild PA and short-term glucose dynamics was obtained. This represents a preliminary important step toward incorporation of PA information in more realistic physiological models of the glucose–insulin system usable in T1DM simulators, in development of closed-loop artificial pancreas control algorithms, and in CGM-based prediction algorithms for generation of hypoglycemic alerts.

Background: Currently, patients with type 1 diabetes decide on the amount of insulin to administer based on several factors, including current plasma glucose value, expected meal input, and physical activity (PA). One future therapeutic modality for patients with type 1 diabetes is the artificial endocrine pancreas (AEP). Incorporation of PA could enhance the efficacy of AEP significantly. We compared the main technologies used for PA quantitation. Subjects and Methods: Data were collected during inpatient studies involving healthy control subjects and type 1 diabetes. We report PA quantified from accelerometers (acceleration units [AU]) and heart rate (HR) monitors during a standardized activity protocol performed after a dinner meal at 7 p.m. from nine control subjects (four were males, 37.4±12.7 years old, body mass index of 24.8±3.8 kg/m 2 , and fasting plasma glucose of 4.71±0.63 mmol/L) and eight with type 1 diabetes (six were males, 45.2±13.4 years old, body mass index of 25.1±2.9 kg/m 2 , and fasting plasma glucose of 8.44±2.31 mmol/L). Results: The patient-to-patient variability was considerably less when examining AU compared with HR monitors. Furthermore, the exercise bouts and rest periods were more evident from the data streams when AUs were used to quantify activity. Unlike the AU, the HR measurements provided little insight for active and rest stages, and HR data required patient-specific standardizations to discern any meaningful pattern in the data. Conclusions: Our results indicated that AU provides a reliable signal in response to PA, including low-intensity activity. Correlation of this signal with continuous glucose monitoring data would be the next step before exploring inclusion as input for AEP control.

Key Points Serum 2HG analysis by LC-MS can accurately identify patients with AML with and without IDH mutations. Oncometabolite testing of serum 2HG is indicated as a diagnostic, prognostic, and therapeutic monitoring tool in AML.