From non-specific biomarker to targeted action: transdiagnostic and sex-specific drivers of high-CRP status in severe mental illness across the FondaMental Advanced Centers of Expertise (FACE) cohorts.

BACKGROUND AND OBJECTIVES: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset of patients, who often experience greater disease burden and poorer treatment response. Elevated C-reactive protein (CRP), defined as CRP ≥ 3 mg/L, has been proposed to identify this group, but its non-specificity limits the biomarker's ability to guide targeted intervention. We aimed to determine the most consistent drivers of high CRP across bipolar disorder (BD), schizophrenia (SZ) and major depressive disorder (MDD), and to translate these into clinically actionable intervention targets using robust data-driven methods.

METHODS: We pooled and harmonised data from three large French national SMI cohorts (n = 7149: 4797 bipolar disorder, 1958 schizophrenia and 394 resistant major depression) and classified participants by CRP ≥ 3 mg/L, as well as an alternative cut-off of 5 mg/L. We applied penalised logistic regression (PLR), random forests (RF) and unsupervised clustering, using 28 biopsychosocial variables to identify robust drivers of high-CRP status. We then grouped these into actionable targets and assessed relative dominance.

RESULTS: In total, 30.16% of participants had CRP ≥ 3 mg/L. PLR identified female sex (OR [95% CI]: 1.60 [1.27, 1.93]), higher BMI (OR: 1.09 [1.07, 1.13]), current nicotine dependence (OR: 1.05 [1.02, 1.09]), lower HDL cholesterol (OR: 0.57 [0.44, 0.73]) and smoking (ex-smoker status OR: 0.84 [0.66, 0.98]) as consistent drivers. RF highlighted a similar set of key drivers, also including waist circumference, triglycerides and cardiovascular comorbidities. Clustering of the high-CRP group was almost entirely driven by smoking status and nicotine dependence. When grouped into actionable targets, the identified drivers accounted for 16% of variance in CRP status, with obesity emerging as most dominant contributor. This pattern was most pronounced in females; in males it was more diffuse, with a more prominent role for smoking.

CONCLUSIONS: We propose a decision tree framework where CRP can serve as a first-line screening marker for inflammation in SMI, with subsequent steps focusing on the main contributing factors to guide targeted interventions. Priority should be given to targeting obesity and metabolic dysregulation. Among females, hyperuricemia represents the next most appropriate target, whereas in males, smoking warrants greater attention. This stepwise approach provides a route from a non-specific biomarker to targeted treatment strategies and should be validated in prospective studies.