Researchers in this study examined the natural variations in lithium (Li) isotopes (δ⁷Li) in serum (δ⁷Liserum) as a novel and objective biomarker to differentiate schizophrenia (SZ) from bipolar disorder (BD) in patients undergoing chronic lithium therapy. This differentiation addresses a longstanding diagnostic challenge driven by the limitations of subjective DSM-5 and ICD-10 criteria. Researchers quantified δ⁷Li concentrations, alongside the concentrations other of biologically relevant elements (BREs) (Ca, Mg, Zn, and Se) to explore underlying metabolic differences. Data was obtained by collecting serum samples from clinically stable BD and SZ patients 12 hours after their last oral Li dose. The 12 hour mark ensured a fixed time point to minimize variations from absorption and excretion kinetics. Samples were analyzed with high precision using a multiple collector inductively coupled plasma mass spectrometer (MC-ICP-MS) to resolve subtle mass-dependent fractionation effects. The main finding was that the δ⁷Li values were significantly heavier in SZ patients (p < 0.01) compared to BD patients and healthy controls. Additionally, a machine learning model classifier (Random Forest model) integrating the δ⁷Liserum data with the BRE profiled achieved an area under the curve (AUC) of 1.000 (100% diagnostic accuracy) in the dataset. Further experiments using induced pluripotent stem cell (iPSC) models and correlation analyses suggest that this isotopic divergence arises from preferential intracellular enrichment of the heavier isotope (⁷Li) during competition with Mg2+ for binding sites on key enzymes such as inositol monophosphatase (IMPase) and GSK-3β, a process theorized to be compromised in SZ patients due to mitochondrial dysfunction.