Tissue sodium stores in peritoneal dialysis and hemodialysis patients determined by 23-sodium magnetic resonance imaging.

BACKGROUND: Tissue sodium content in patients on maintenance hemodialysis (MHD) and peritoneal dialysis (PD) were previously explored using 23Sodium magnetic resonance imaging (23NaMRI). Larger studies would provide a better understanding of sodium stores in patients on dialysis as well as the factors influencing this sodium accumulation. METHODS: In this cross-sectional study, we quantified the calf muscle and skin sodium content in 162 subjects (10 PD, 33 MHD patients, and 119 controls) using 23NaMRI. Plasma levels of interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hsCRP) were measured to assess systemic inflammation. Sixty-four subjects had repeat 23NaMRI scans that were analyzed to assess the repeatability of the 23NaMRI measurements. RESULTS: Patients on MHD and PD exhibited significantly higher muscle and skin sodium accumulation compared to controls. African American patients on dialysis exhibited greater muscle and skin sodium content compared to non-African Americans. Multivariable analysis showed that older age was associated with both higher muscle and skin sodium. Male sex was also associated with increased skin sodium deposition. Greater ultrafiltration was associated with lower skin sodium in patients on PD (Spearman's rho=-0.68, P = 0.035). Higher plasma IL-6 and hsCRP levels correlated with increased muscle and skin sodium content in the overall study population. Patients with higher baseline tissue sodium content exhibited greater variability in tissue sodium stores on repeat measurements. CONCLUSIONS: Our findings highlight greater muscle and skin sodium content in dialysis patients compared to controls without kidney disease. Tissue sodium deposition and systemic inflammation seen in dialysis patients might influence one another bidirectionally.

Human and Machine Intelligence Together Drive Drug Repurposing in Rare Diseases.

Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has generated significant interest in the realm of rare disease treatment as an innovative strategy for finding ways to manage these complex conditions. The selection of which agents should be tested in which conditions is currently informed by both human and machine discovery, yet the appropriate balance between these approaches, including the role of artificial intelligence (AI), remains a significant topic of discussion in drug discovery for rare diseases and other conditions. Our drug repurposing team at Vanderbilt University Medical Center synergizes machine learning techniques like phenome-wide association study-a powerful regression method for generating hypotheses about new indications for an approved drug-with the knowledge and creativity of scientific, legal, and clinical domain experts. While our computational approaches generate drug repurposing hits with a high probability of success in a clinical trial, human knowledge remains essential for the hypothesis creation, interpretation, "go-no go" decisions with which machines continue to struggle. Here, we reflect on our experience synergizing AI and human knowledge toward realizable patient outcomes, providing case studies from our portfolio that inform how we balance human knowledge and machine intelligence for drug repurposing in rare disease.

Fibroblast Growth Factor 23 Associates with Death in Critically Ill Patients.

BACKGROUND AND OBJECTIVES: Dysregulated mineral metabolism is a common and potentially maladaptive feature of critical illness, especially in patients with AKI, but its association with death has not been comprehensively investigated. We sought to determine whether elevated plasma levels of the osteocyte-derived, vitamin D-regulating hormone, fibroblast growth factor 23 (FGF23), are prospectively associated with death in critically ill patients with AKI requiring RRT, and in a general cohort of critically ill patients with and without AKI. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We measured plasma FGF23 and other mineral metabolite levels in two cohorts of critically ill patients (n=1527). We included 817 patients with AKI requiring RRT who enrolled in the ARF Trial Network (ATN) study, and 710 patients with and without AKI who enrolled in the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study. We hypothesized that higher FGF23 levels at enrollment are independently associated with higher 60-day mortality. RESULTS: In the ATN study, patients in the highest compared with lowest quartiles of C-terminal (cFGF23) and intact FGF23 (iFGF23) had 3.84 (95% confidence interval, 2.31 to 6.41) and 2.08 (95% confidence interval, 1.03 to 4.21) fold higher odds of death, respectively, after adjustment for demographics, comorbidities, and severity of illness. In contrast, plasma/serum levels of parathyroid hormone, vitamin D metabolites, calcium, and phosphate were not associated with 60-day mortality. In the VALID study, patients in the highest compared with lowest quartiles of cFGF23 and iFGF23 had 3.52 (95% confidence interval, 1.96 to 6.33) and 1.93 (95% confidence interval, 1.12 to 3.33) fold higher adjusted odds of death. CONCLUSIONS: Higher FGF23 levels are independently associated with greater mortality in critically ill patients.