Kidney biomarker insights through factor analysis

• RATIONALE & OBJECTIVE: SPRINT compared the effect of intensive versus standard systolic blood pressure targets on cardiovascular morbidity and mortality. In this ancillary study, we evaluated the use of exploratory factor analysis (EFA) to combine biomarkers of kidney tubule health in urine and plasma and then study their role in longitudinal eGFR change and risk of acute kidney injury (AKI). • STUDY DESIGN: Observational cohort nested in a clinical trial. • SETTING & PARTICIPANTS: 2,351 SPRINT participants with eGFR < 60 ml/min/1.73m(2) at baseline. • EXPOSURE(S): Levels of neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18), chitinase-3-like protein (YKL-40), kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), alpha-1 microglobulin (α1m) and beta-2 microglobulin (β2m), uromodulin (UMOD), fibroblast growth factor-23 (FGF23), and intact parathyroid hormone (PTH). • OUTCOME(S): Longitudinal changes in eGFR and risk of AKI. • ANALYTICAL APPROACH: We performed EFA to capture different tubule pathophysiologic processes. We used linear mixed effects models to evaluate the association of each factor with longitudinal changes in eGFR. We evaluated the association of the tubular factors scores with AKI using Cox proportional hazards regression. • RESULTS: From ten biomarkers, EFA generated four factors reflecting tubule injury/repair (NGAL, IL-18 and YKL-40), tubule injury/fibrosis (KIM-1 and MCP-1), tubule reabsorption (α1m and β2m), and tubule reserve/mineral metabolism (UMOD, FGF23, and PTH). Each SD higher tubule reserve/mineral metabolism factor scores were associated with a 0.58% (0.39%, 0.67%) faster eGFR decline independent of baseline eGFR and albuminuria. Both the tubule injury/repair (HR per SD higher 1.18 [1.10, 1.37]) and tubule injury/fibrosis factors (HR 1.23 [1.02, 1.48]) were independently associated with future risk of AKI. • LIMITATIONS: The factors require validation in other settings. • CONCLUSIONS: EFA allows parsimonious subgrouping of biomarkers into factors which are differentially associated with progressive eGFR decline and AKI. These subgroups may provide insights into the pathological processes driving adverse kidney outcomes.