Validation of Metabolic and Immunologic Biomarkers TNF-a, IGF, IL-6, CRP and Hair Cortisol in the Common Marmoset

The common marmoset is a good model for research because they are easy to house and have complex social relationships (French et al., 2019). Marmosets are sensitive to social isolation, and when introduced to a stressor, the HPA axis is activated (Saltzman & Abbott, 2011). The purpose of this experiment is to validate marmosets as a translational model for stress due to social relationships in humans. This is done by validating biomarker concentration levels at baseline, then comparing the concentration when introduced to a stressor. The biomarkers IL-6, CRP, IGF-1 and TNF-a were tested using a serum assay, then running the well plate under a plate reader to determine the concentration. No antibodies were detected in the marmoset samples for the biomarkers IL-6, CRP, IGF-1 and TNF-a. Chronic cortisol concentration was determined using marmoset hair samples. The high stress group for hair cortisol concentration was significantly greater than the control group, providing evidence that hair cortisol is a reliable biomarker for long-term chronic stress. Marmosets can be used as a translational animal model to further understand and study both acute and chronic stress due to social relationships and isolation

Association of Chronic Hepatitis C Infection With T-Cell Phenotypes in HIV-Negative and HIV-Positive Women

Background: Hepatitis C virus (HCV) viremia is thought to have broad systemic effects on the cellular immune system that go beyond its impact on just those T cells that are HCV specific. However, previous studies of chronic HCV and circulating T-cell subsets (activation and differentiation phenotypes) in HIV negatives used general population controls, rather than a risk-appropriate comparison group. Studies in HIV positives did not address overall immune status (total CD4 + count). Methods: We used fresh blood from HIV-positive and at-risk HIVnegative women, with and without chronic HCV, to measure percentages of activated CD4 + and CD8 + T cells, Tregs, and T-cell differentiation phenotypes (naive, central memory, effector memory (EM), and terminally differentiated effector). This included 158 HIV negatives and 464 HIV positives, of whom 18 and 63, respectively, were HCV viremic. Results: In multivariate models of HIV negatives, HCV viremia was associated with 25% fewer naive CD4 + (P = 0.03), 33% more EM CD4 + (P = 0.0002), and 37% fewer central memory CD8 + (P = 0.02) T cells. Among HIV positives, we observed only 1 of these 3 relationships: higher percentage of EM CD4 + among HCV viremic women. Furthermore, the association with EM CD4 + among HIV positives was limited to individuals with diminished immune status (total CD4 + count #500 cells/mL), as were associations of HCV viremia with higher percentages of activated CD4 + and Tregs. Among HIV positives with high CD4 + count, no significant associations were observed. Conclusions: These data suggest that HCV viremia in HIV negatives is associated with accelerated T-cell differentiation, but among HIV positives, the impact of HCV viremia is less straightforward and varies by total CD4 + count

Demographic and Metabolic Risk Factors Associated with Development of Diabetic Macular Edema among Persons with Diabetes Mellitus

Purpose: Diabetic macular edema (DME), a leading cause of visual impairment, can occur regardless of diabetic retinopathy (DR) stage. Poor metabolic control is hypothesized to contribute to DME development, although large-scale studies have yet to identify such an association. This study aims to determine whether measurable markers of dysmetabolism are associated with DME development in persons with diabetes. Design: Retrospective cohort study. Participants: Using data from the Sight Outcomes Research Collaborative (SOURCE) repository, patients with diabetes mellitus and no preexisting DME were identified and followed over time to see what factors associated with DME development. Methods: Cox proportional hazard modeling was used to assess the relationship between demographic variables, diabetes type, smoking history, baseline DR status, blood pressure (BP), lipid profile, body mass index (BMI), hemoglobin A1C (HbA1C), and new onset of DME. Main Outcome Measures: Adjusted hazard ratio (HR) of developing DME with 95% confidence intervals (CIs). Results: Of 47 509 eligible patients from 10 SOURCE sites (mean age 63 ± 12 years, 58% female sex, 48% White race), 3633 (7.6%) developed DME in the study period. The mean ± standard deviation time to DME was 875 ± 684 days (∼2.4 years) with those with baseline nonproliferative DR (HR 3.67, 95% CI: 3.41–3.95) and proliferative DR (HR 5.19, 95% CI: 4.61–5.85) more likely to develop DME. There was no difference in DME risk between type 1 and type 2 patients; however, Black race was associated with a 40% increase in DME risk (HR 1.40, 95% CI: 1.30–1.51). Every 1 unit increase in HbA1C had a 15% increased risk of DME (HR 1.15, 95% CI: 1.13–1.17), and each 10 mmHg increase in systolic BP was associated with a 6% increased DME risk (HR 1.06, 95% CI: 1.02–1.09). No association was identified between DME development and BMI, triglyceride levels, or high-density lipoprotein levels. Conclusions: These findings suggest that in patients with diabetes modifiable risk factors such as elevated HbA1C and BP confer a higher risk of DME development; however, other modifiable systemic markers of dysmetabolism such as obesity and dyslipidemia did not. Further work is needed to identify the underlying contributions of race in DME. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article