Runqi Zhao

Background: Chronic diseases may injure the pancreas and result in a reduction in pancreas volume (PV), which may adversely impact its critical role in endocrine and exocrine function. Less is known about whether individuals with smaller PV face higher risks of adverse clinical outcomes. Methods: We estimated baseline age‐adjusted predicted PV (pPV) from abdominal magnetic resonance imaging in 36 592 UK Biobank participants. Since the initial magnetic resonance imaging occurred 9.0 (interquartile range, 7.5–10.1) years after baseline, we fit a linear regression equation that included age for the outcome of PV slope in 451 participants with repeat magnetic resonance imaging 2.8 (interquartile range, 2.2–4.8) years after the initial scan. Using these data, we calculated baseline age‐adjusted pPV slope by adding or subtracting the annual change to the initial PV measurement assuming linear change in PV over time. Multivariable‐adjusted proportional hazards models tested associations of pPV with incident chronic kidney disease, cardiovascular disease (CVD; myocardial infarction, heart failure, or stroke), and death. Results: Participants (52.2% women) were 55±8 years old and had a pPV of 63.3±15.3 mL. During median follow‐up of 13.9 years, there were 757 incident chronic kidney disease, 1392 CVD, and 702 death events. In final adjusted models, participants in the first pPV quartile had a 1.67‐fold (95% CI, 1.34–2.07) and 1.28‐fold (95% CI, 1.10–1.49) increased risk of incident CVD and death compared with the fourth quartile, respectively. pPV had nonlinear associations with incident CVD and death (each P <0.001). pPV was not associated with incident chronic kidney disease. Conclusions: Lower pPV is associated with increased risk of incident CVD and death but not incident chronic kidney disease. Future studies should investigate the pathophysiologic mechanisms driving these associations.

Two observational studies were conducted to support an initiative to qualify translational kidney safety biomarkers as clinical drug development tools that identify tubular injury prior to changes in estimated glomerular filtration rate (eGFR). Normal healthy volunteers provided three morning spot urine collections over 4 weeks. Patients undergoing surgical resection and intrathoracic cisplatin for malignant pleural mesothelioma provided urine samples pre‐ and postoperatively at 4, 8, and 12 hours and daily for 6 days. Using receiver‐operating characteristics curves, “statistically significant thresholds” established peak longitudinal changes for 8 biomarkers to differentiate mesothelioma patients who developed acute kidney injury (AKI) from normal healthy volunteers. We also assessed “medically significant thresholds” to differentiate mesothelioma patients who did vs. did not develop AKI. Statistically and medically significant thresholds for a fold‐change from baseline of urine creatinine (UCr)‐normalized values were established for 6 biomarkers: clusterin (2.2, 5.1); osteopontin (3.1, 7.1); N‐acetyl‐ß‐D‐glucosaminidase (2.7, 8.1); kidney injury molecule‐1 (4.3, 7.5); cystatin C (1.8, 4.5); neutrophil gelatinase‐associated lipocalin (2.9, 7.8). For urine albumin and total protein, thresholds were established based on UCr‐normalized absolute values: (> upper limit normal, > 10× upper limit normal). Statistically significant thresholds for all biomarkers outperformed eGFR at discriminating mesothelioma subjects exposed to cisplatin from healthy volunteers, demonstrating their utility for enhancing safe drug development. Medically significant thresholds provide perspective on when patients begin to exhibit AKI. These studies have established guideposts for confirmatory studies with additional cohorts and nephrotoxicants to formally qualify the selected biomarkers with worldwide regulatory authorities.

The kidney tubules constitute two-thirds of the cells of the kidney and account for the majority of the organ’s metabolic energy expenditure. Acute tubular injury (ATI) is observed across various types of kidney diseases and may significantly contribute to progression to kidney failure. Non-invasive biomarkers of ATI may allow for early detection and drug development. Using the SomaScan proteomics platform on 434 patients with biopsy-confirmed kidney disease, we here identify plasma biomarkers associated with ATI severity. We employ regional transcriptomics and proteomics, single-cell RNA sequencing, and pathway analysis to explore biomarker protein and gene expression and enriched biological pathways. Additionally, we examine ATI biomarker associations with acute kidney injury (AKI) in the Kidney Precision Medicine Project (KPMP) (n = 44), the Atherosclerosis Risk in Communities (ARIC) study (n = 4610), and the COVID-19 Host Response and Clinical Outcomes (CHROME) study (n = 268). Our findings indicate 156 plasma proteins significantly linked to ATI with osteopontin, macrophage mannose receptor 1, and tenascin C showing the strongest associations. Pathway analysis highlight immune regulation and organelle stress responses in ATI pathogenesis.