Preservation of renal function by thyroid hormone replacement therapy in chronic kidney disease patients with subclinical hypothyroidism

Context: Subclinical hypothyroidism is not a rare condition, but the use of thyroid hormone to treat subclinical hypothyroidism is an issue of debate. Objective: This study was undertaken to investigate the impact of thyroid hormone therapy on the changes in estimated glomerular filtration rate (eGFR) in subclinical hypothyroidism patients with stage 2-4 chronic kidney disease. Patients: A total of 309 patients were included in the final analysis. Main Outcome Measure: The changes in eGFR over time were compared between patients with and without thyroid hormone replacement therapy using a linear mixed model. Kaplan-Meier curves were constructed to determine the effect of thyroid hormone on renal outcome, a reduction of eGFR by 50%, or end-stage renal disease. The independent prognostic value of subclinical hypothyroidism treatment for renal outcome was ascertained by multivariate Cox regression analysis. Results: Among the 309 patients, 180 (58.3%) took thyroid hormone (treatment group), whereas 129 (41.7%) did not (nontreatment group). During the mean follow-up duration of 34.8 ± 24.3 months, the overall rate of decline in eGFR was significantly greater in the nontreatment group compared to the treatment group (-5.93 ± 1.65 vs. -2.11 ± 1.12 ml/min/yr/1.73 m(2); P = 0.04). Moreover, a linear mixed model revealed that there was a significant difference in the rates of eGFR decline over time between the two groups (P < 0.01). Kaplan-Meier analysis also showed that renal event-free survival was significantly lower in the nontreatment group (P < 0.01). In multivariate Cox regression analysis, thyroid hormone replacement therapy was found to be an independent predictor of renal outcome (hazard ratio, 0.28; 95% CI, 0.12-0.68; P = 0.01). Conclusion: Thyroid hormone therapy not only preserved renal function better, but was also an independent predictor of renal outcome in chronic kidney disease patients with subclinical hypothyroidism.     

Serum ferritin levels predict incident non-alcoholic fatty liver disease in healthy Korean men

Little research has been done to examine the temporal relationship between serum ferritin and the development of nonalcoholic fatty liver disease. The aim of this study was to examine whether serum ferritin levels predict incident fatty liver in non-diabetic men. The study cohort comprised 2410 healthy Korean male who were aged 30 to 59years old with no evidence of ultrasonographically detectable fatty liver (USFL) at baseline. Alcohol intake was assessed with a self-reported questionnaire. At each visit, biochemical and anthropometric measurements and abdominal ultrasonography were done. Cox proportional hazard models were used to calculate the adjusted hazard ratios in separate models for USFL. During 7545.9 person-years of follow-up, 586 participants developed USFL. The hazard ratio (95% confidence interval) for incident USFL comparing the highest quartile of serum ferritin level to the lowest quartile was 1.54 (1.21-1.94) after adjusting for age, body mass index, smoking, alcohol intake, and exercise. That association remained significant after further adjustment for cardiovascular risk factors and in time-dependent models. The association between serum ferritin and incident USFL was still significant in the non-overweight group or the no current smoker group. Serum ferritin level was an independent risk factor of incident fatty liver detected by ultrasonography even in non-obese, healthy Korean men. Increased serum ferritin levels appear to be an early predictor for incident fatty liver.     

Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells

We describe a microchip designed to quantify the levels of a dozen cytoplasmic and membrane proteins from single cells. We use the platform to assess protein–protein interactions associated with the EGF-receptor-mediated PI3K signaling pathway. Single-cell sensitivity is achieved by isolating a defined number of cells (n = 0–5) in 2 nL volume chambers, each of which is patterned with two copies of a miniature antibody array. The cells are lysed on-chip, and the levels of released proteins are assayed using the antibody arrays. We investigate three isogenic cell lines representing the cancer glioblastoma multiforme, at the basal level, under EGF stimulation, and under erlotinib inhibition plus EGF stimulation. The measured protein abundances are consistent with previous work, and single-cell analysis uniquely reveals single-cell heterogeneity, and different types and strengths of protein–protein interactions. This platform helps provide a comprehensive picture of altered signal transduction networks in tumor cells and provides insight into the effect of targeted therapies on protein signaling networks.Although signal transduction inhibitors occasionally offer clinical benefit for cancer patients (1), signal flux emanating from oncogenes is often distributed through multiple pathways (2), potentially underlying the failure of most such inhibitors (3). Measuring signal flux through multiple pathways, in response to signal transduction inhibitors, may help uncover network interactions that contribute to therapeutic resistance and that are not predicted by analyzing pathways in isolation (4). The cellular and molecular complexity of a solid tumor microenvironment (5) suggests the need to study signaling in individual cancer cells.Protein–protein interactions within signaling pathways are often elucidated by assessing the levels of relevant pathway proteins in model and tumor-derived cell lines and with various genetic and molecular perturbations. Such interactions, and the implied signaling networks, may also be elucidated via quantitative measurements of multiple pathway-related proteins within single cells (6). At the single-cell level, inhibitory and activating protein–protein relationships, as well as stochastic (single-cell) fluctuations, are revealed. However, most techniques for profiling signaling pathways (7, 8) require large numbers of cells. Single-cell immunostaining (9) is promising, and some flow cytometry (6) techniques are relevant, as discussed below.We describe quantitative, multiplex assays of intracellular signaling proteins from single cancer cells using a platform called the single-cell barcode chip (SCBC). The SCBC is simple in concept: A single or defined number of cells is isolated within an approximately 2 nL volume microchamber that contains an antibody array (10) for the capture and detection of a panel of proteins. The SCBC design (11) permits lysis of each individual trapped cell.Intracellular staining flow cytometry can assay up to 11 phosphoproteins from single cells (6). Our SCBC can profile a similar size panel, but only for approximately 100 single cells per chip. Each protein is assayed twice, yielding some statistical assessment for each experiment. The SCBC is a relatively simple platform and only requires a few hundred cells per assay.We used the SCBC to study signal transduction in glioblastoma multiforme (GBM), a primary malignant brain tumor (12). GBM has been genetically characterized, yet the nature of signaling pathways downstream of key oncogenic mutations, such as epidermal growth factor receptor activating mutation (EGFRvIII) and phosphatase and tensin homolog (PTEN) tumor suppressor gene loss associated with receptor tyrosine kinase (RTK)/PI3K signaling, are incompletely understood (13–15). Single-cell experiments may also help resolve the characteristic heterogeneity of GBM.We interrogated 11 proteins directly or potentially associated with PI3K signaling (see SI Appendix, Methods I) through three isogenic GBM cell lines: U87 (expressing wild-type p53, mutant PTEN, and low levels of wild-type EGFR, no EGFRvIII) (16, 17), U87 EGFRvIII (U87 cells stably expressing EGFRvIII deletion mutant), and U87 EGFRvIII PTEN (U87 cells coexpressing EGFRvIII and PTEN) (18). Fig. 1 diagrams this biology. Each cell line was investigated under conditions of standard cell culture, in response to EGF stimulation, and after erlotinib treatment followed by EGF stimulation. The proteins assayed represented RTKs and proteins signifying activation of PI3K and MAPK signaling. They were (p- denotes phosphorylation) p-Src, p-mammalian target of rapamycin (p-mTOR), p-p70 ribosomal protein S6 kinase (p-p70S6K), p-glycogen synthase kinase-3 (p-GSK-3α/β), p-p38 mitogen activated protein kinase (p-p38α), p-extracellular regulated kinase (p-ERK), p-c-Jun N-terminal kinase (p-JNK2), p-platelet derived growth factor receptor β (p-PDGFRβ), p-vascular endothelial growth factor receptor 2 (p-VEGFR2), tumor protein 53 (P53), and total EGFR.Open in a separate windowFig. 1.The PI3K pathway activated by EGF-stimulated EGFR or by the constitutively activated EGFRvIII. All proteins in light blue with central yellow background were assayed. Orange background proteins were expressed in the cell lines U87 EGFRvIII or U87 EGFRvIII PTEN. The oval, yellow background components are the investigated molecular perturbations.     

Emulating Host-Microbiome Ecosystem of Human Gastrointestinal Tract in Vitro

The human gut microbiome performs prodigious physiological functions such as production of microbial metabolites, modulation of nutrient digestion and drug metabolism, control of immune system, and prevention of infection. Paradoxically, gut microbiome can also negatively orchestrate the host responses in diseases or chronic disorders, suggesting that the regulated and balanced host-gut microbiome crosstalk is a salient prerequisite in gastrointestinal physiology. To understand the pathophysiological role of host-microbiome crosstalk, it is critical to recreate in vivo relevant models of the host-gut microbiome ecosystem in human. However, controlling the multi-species microbial communities and their uncontrolled growth has remained a notable technical challenge. Furthermore, conventional two-dimensional (2D) or 3D culture systems do not recapitulate multicellular microarchitectures, mechanical dynamics, and tissue-specific functions. Here, we review recent advances and current pitfalls of in vitro and ex vivo models that display human GI functions. We also discuss how the disruptive technologies such as 3D organoids or a human organ-on-a-chip microphysiological system can contribute to better emulate host-gut microbiome crosstalks in health and disease. Finally, the medical and pharmaceutical significance of the gut microbiome-based personalized interventions is underlined as a future perspective.