Citations

SummaryWeight loss is an effective intervention for diminishing disease burden in obese older adults. Pharmacological interventions that reduce food intake and thereby promote weight loss may offer effective strategies to reduce age‐related disease. We previously reported that 17α‐estradiol (17α‐E2) administration elicits beneficial effects on metabolism and inflammation in old male mice. These observations were associated with reduced calorie intake. Here, we demonstrate that 17α‐E2 acts through pro‐opiomelanocortin (Pomc) expression in the arcuate nucleus (ARC) to reduce food intake and body mass in mouse models of obesity. These results confirm that 17α‐E2 modulates appetite through selective interactions within hypothalamic anorexigenic pathways. Interestingly, some peripheral markers of metabolic homeostasis were also improved in animals with near complete loss of ARC Pomc transcription. This suggests that 17α‐E2 might have central and peripheral actions that can beneficially affect metabolism cooperatively or independently.

ObjectiveTo determine whether machine learning can accurately classify human papillomavirus (HPV) status of oropharyngeal squamous cell carcinoma (OPSCC) using computed tomography (CT)-based texture analysis.MethodsTexture analyses were retrospectively applied to regions of interest from OPSCC primary tumors on contrast-enhanced neck CT, and machine learning was used to create a model that classified HPV status with the highest accuracy. Results were compared against the blinded review of 2 neuroradiologists.ResultsThe HPV-positive (n = 92) and -negative (n = 15) cohorts were well matched clinically. Neuroradiologist classification accuracies for HPV status (44.9%, 55.1%) were not significantly different (P= 0.13), and there was a lack of agreement between the 2 neuroradiologists (κ = −0.145). The best machine learning model had an accuracy of 75.7%, which was greater than either neuroradiologist (P< 0.001,P= 0.002).ConclusionsUseful diagnostic information regarding HPV infection can be extracted from the CT appearance of OPSCC beyond what is apparent to the trained human eye.

Abstract Purpose: DNA topoisomerase inhibitors are commonly used for treating small-cell lung cancer (SCLC). Tyrosyl-DNA phosphodiesterase (TDP1) repairs DNA damage caused by this class of drugs and may therefore influence treatment outcome. In this study, we investigated whether common TDP1 single-nucleotide polymorphisms (SNP) are associated with overall survival among SCLC patients. Experimental Design: Two TDP1 SNPs (rs942190 and rs2401863) were analyzed in 890 patients from 10 studies in the International Lung Cancer Consortium (ILCCO). The Kaplan–Meier method and Cox regression analyses were used to evaluate genotype associations with overall mortality at 36 months postdiagnosis, adjusting for age, sex, race, and tumor stage. Results: Patients homozygous for the minor allele (GG) of rs942190 had poorer survival compared with those carrying AA alleles, with a HR of 1.36 [95% confidence interval (CI): 1.08–1.72, P = 0.01), but no association with survival was observed for patients carrying the AG genotype (HR = 1.04, 95% CI, 0.84–1.29, P = 0.72). For rs2401863, patients homozygous for the minor allele (CC) tended to have better survival than patients carrying AA alleles (HR = 0.79; 95% CI, 0.61–1.02, P = 0.07). Results from the Genotype Tissue Expression (GTEx) Project, the Encyclopedia of DNA Elements (ENCODE), and the ePOSSUM web application support the potential function of rs942190. Conclusions: We found the rs942190 GG genotype to be associated with relatively poor survival among SCLC patients. Further investigation is needed to confirm the result and to determine whether this genotype may be a predictive marker for treatment efficacy of DNA topoisomerase inhibitors. Clin Cancer Res; 23(24); 7550–7. ©2017 AACR.

Abstract Introduction: DNA topoisomerase inhibitors (e.g. etoposide, irinotecan, teniposide, topotecan) are commonly used for treating small cell lung cancer (SCLC). Tyrosyl-DNA phosphodiesterase (TDP1) plays a role in repairing DNA damage caused by DNA topoisomerase inhibitors and it is believed to be responsible for resistance to this class of drugs. The purpose of this study was to determine whether common TDP1 polymorphisms are associated with overall survival among SCLC patients. Method: Two common TDP1 SNPs (rs942190 and rs2401863, r2(European)=0.63 and r2(East Asian)=0.26) were analyzed in 898 patients from 10 studies in the International Lung Cancer Consortium, conducted in the U.S., Canada, Japan, Italy, Spain and the United Kingdom. Genotype data were obtained from either the OncoArray Consortium or other existing genome-wide association studies. Cox proportional hazard regression models with robust standard error were used to evaluate genotype associations for overall survival at 36 months post-diagnosis, adjusting for age, sex, race and tumor stage. Results: Patients homozygous for the minor allele (GG) of TDP1 SNP rs942190 were associated with poorer survival compared to those carrying both major alleles (AA), with a hazard ratio (HR) of 1.36 (95% confidence interval (CI): 1.07-1.72, p-value=0.01), but there was no association with survival for patients with the heterozygous genotype (HR=1.02, 95% CI: 0.83-1.27, p-value=0.83). For rs2401863, patients carrying both minor alleles (CC) tended to have better survival than patients carrying AA alleles, but this was within the limits of chance given no significant association (HR=0.79, 95% CI: 0.61-1.02, p-value=0.07). In addition, multi-tissue expression quantitative trait loci (eQTL) analyses from the Genotype-Tissue Expression Project indicated a potential effect of rs942190 on lung tissue, with higher TDP1 gene expression for the GG than AG or AA genotypes. Conclusion: We found that among SCLC patients the TDP1 rs942190 GG genotype was associated with poor overall survival. Further study could determine if this genotype can serve as a predictive marker for the treatment efficacy of DNA topoisomerase inhibitors in SCLC. Citation Format: Pawadee Lohavanichbutr, Lori C. Sakoda, Christopher I. Amos, Susanne M. Arnold, David C. Christiani, Michael P. Davies, John K. Field, Eric B. Haura, Rayjean J. Hung, Takashi Kohno, Maria Teresa Landi, Geoffrey Liu, Yi Liu, Michael W. Marcus, Grainne M. O'Kane, Matthew B. Schabath, Kouya Shiraishi, Stacey A. Slone, Adonina Tardón, Ping Yang, Kazushi Yoshida, Ruyang Zhang, Xuchen Zong, Noel S. Weiss, Chu Chen. Common TDP1 polymorphisms in relation to survival among small cell lung cancer patients in a multicenter study from the International Lung Cancer Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2248. doi:10.1158/1538-7445.AM2017-2248

Abstract Introduction Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. Methods Serial T1‐weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed‐effects models estimated the change‐points when atrophy rates deviate from normal and the rates of change before and after this point. Results Atrophy increased after the change‐point, which occurred 1–1.5 years (assuming a single step change in atrophy rate) or 3–8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change‐point. Discussion Atrophy rates are pathologically increased up to seven years before “expected onset”. During this period, atrophy rates may be useful for inclusion and tracking of disease progression.

This study builds on previous research that identified fears and concerns heard by procurement coordinators during the donation discussion and that classified those concerns according to the ease with which they can be addressed. In this study, 53 coordinators working for 4 procurement agencies provided data on 323 donation discussions, including fears and concerns expressed by families. The fears and concerns were analyzed by outcome (consent or refusal), race and ethnicity of the family, frequency of reports, and difficulty in addressing. This research confirms many of the findings of the earlier study. The results also indicate that the types of concerns expressed by donor and non–donor families vary somewhat by the family's race and ethnicity. The results can be used to provide training targeted at raising consent rates and to train minority requestors.

Background The current subclassification of migraine is according to headache frequency and aura status. The variability in migraine symptoms, disease course, and response to treatment suggest the presence of additional heterogeneity or subclasses within migraine. Objective The study objective was to subclassify migraine via a data‐driven approach, identifying latent factors by jointly exploiting multiple sets of brain structural features obtained via magnetic resonance imaging (MRI). Methods Migraineurs ( n = 66) and healthy controls ( n = 54) had brain MRI measurements of cortical thickness, cortical surface area, and volumes for 68 regions. A multimodality factor mixture model was used to subclassify MRIs and to determine the brain structural factors that most contributed to the subclassification. Clinical characteristics of subjects in each subgroup were compared. Results Automated MRI classification divided the subjects into two subgroups. Migraineurs in subgroup #1 had more severe allodynia symptoms during migraines (6.1 ± 5.3 vs. 3.6 ± 3.2, P = .03), more years with migraine (19.2 ± 11.3 years vs 13 ± 8.3 years, P = .01), and higher Migraine Disability Assessment (MIDAS) scores (25 ± 22.9 vs 15.7 ± 12.2, P = .04). There were not differences in headache frequency or migraine aura status between the two subgroups. Conclusions Data‐driven subclassification of brain MRIs based upon structural measurements identified two subgroups. Amongst migraineurs, the subgroups differed in allodynia symptom severity, years with migraine, and migraine‐related disability. Since allodynia is associated with this imaging‐based subclassification of migraine and prior publications suggest that allodynia impacts migraine treatment response and disease prognosis, future migraine diagnostic criteria could consider allodynia when defining migraine subgroups.

Impaired brain clearance of amyloid-beta peptides (Aβ) 40 and 42 across the blood–brain barrier (BBB) is believed to be one of the pathways responsible for Alzheimer’s disease (AD) pathogenesis. Hyperinsulinemia prevalent in type II diabetes was shown to damage cerebral vasculature and increase Aβ accumulation in AD brain. However, there is no clarity on how aberrations in peripheral insulin levels affect Aβ accumulation in the brain. This study describes, for the first time, an intricate relation between plasma insulin and Aβ transport at the BBB. Upon peripheral insulin administration in wild-type mice: the plasma clearance of Aβ40 increased, but Aβ42 clearance reduced; the plasma-to-brain influx of Aβ40 increased, and that of Aβ42 reduced; and the clearance of intracerebrally injected Aβ40 decreased, whereas Aβ42 clearance increased. In hCMEC/D3 monolayers (in vitro BBB model) exposed to insulin, the luminal uptake and luminal-to-abluminal permeability of Aβ40 increased and that of Aβ42 reduced; the abluminal-to-luminal permeability of Aβ40 decreased, whereas Aβ42 permeability increased. Moreover, Aβ cellular trafficking machinery was altered. In summary, Aβ40 and Aβ42 demonstrated distinct distribution kinetics in plasma and brain compartments, and insulin differentially modulated their distribution. Cerebrovascular disease and metabolic disorders may disrupt this intricate homeostasis and aggravate AD pathology.