Design of Multi‐Shelled Hollow Cr2O3 Spheres for Metabolic Fingerprinting

Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi‐shelled hollow Cr2O3 spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 μL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future. Multi‐shelled hollow Cr2O3 spheres displayed strong photo‐response for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites, thereby enabling fast and sensitive metabolic profiling in bio‐fluids. Based on the decoded urine and serum metabolic fingerprints, we performed machine learning to discriminate schizophrenia patients from healthy controls with high specificity and selectivity.