Quantitative imaging of native tissue architecture combined with deep multi-omics reveals the spatial biology of kidney aging
Aging alters tissue architecture and metabolism in spatially heterogeneous ways, yet the connections between these measurable structural and compositional phenotypes and underlying molecular changes are largely unknown. Here, we introduce NORIGAMI (NoRI-Guided AI for Multimodal Integration), a pipeline combining Normalized Raman Imaging (NoRI), deep learning, quantitative morphology, deep proteomics, and metabolomics to investigate renal aging. Unlike conventional histology, NoRI provides label-free, scattering-corrected measurements of absolute total protein and lipid mass concentrations (mg/mL). In 32 male rats aged 9, 18, 21 and 25 months, NORIGAMI predicted the chronological age of held-out rats from NoRI images (mean absolute error 0.78 months; R^2 = 0.97), and whole-tissue images outperformed models trained on isolated tubules. Quantitative imaging identified 41 age-associated morphological and compositional features (FDR < 0.05), revealing anatomically heterogeneous and non-linear changes in lipid droplet concentration, droplet size, cytoplasmic lipid concentration and tubular architecture. Deep molecular profiling quantified 11,485 proteins and 269 metabolites, revealing coordinated declines in differentiated proximal tubule (PT) identity and oxidative metabolism, selective increases in basement-membrane collagen-IV chains, and increasing molecular heterogeneity with age. A protein clock, built mainly from extracellular-matrix and heparan-sulfate proteins, predicted age with a mean absolute error of 1.6 months. Old kidneys diverged along a dominant injury-remodeling axis, seen separately in the proteome, in kidney RNA from 54 other rats and in the metabolome, in which tubular-injury and immune proteins, including the NAD+ consuming enzyme CD38, rise as differentiated-tubule proteins and NAD+ fall. NORIGAMI subsequently linked NAD+ associated molecular changes to quantitative features of tubular geometry and protein-lipid organization, while complementary KIM-1-centered analyses identified overlapping morphological associations involving epithelial injury and lipid handling and yielded additional molecular candidates for mechanistic validation. Collectively, these findings suggest that declining tubular metabolic function, altered lipid organization and injury-associated molecular programs represent interconnected features of renal aging. NORIGAMI establishes a framework for identifying the quantitative structural manifestations of molecular aging and generating spatially informed, experimentally testable hypotheses about tissue dysfunction.