SUITPy: A Python-based toolbox for the analysis of cerebellar functional and anatomical imaging data across the human lifespan.

People with severe mental illness (SMI)—defined here as schizophrenia, bipolar disorder, and major depressive disorder (MDD)—have a life expectancy up to 20 years shorter than that of people without SMI (, , ). Most of this premature mortality is due to physical health conditions (,). Poor physical health in SMI is often attributed to the secondary effects of psychiatric illness, e.g., negative/depressive symptoms leading to a sedentary lifestyle (), physical health side effects of psychotropics (, , , ), and inequitable health care access (). However, metabolic and immune alterations are present at SMI onset (, , ); this suggests that dysregulation of organ systems outside the central nervous system is intrinsic to SMI (). Elucidating these effects will improve understanding of SMI pathophysiology and may help identify novel therapeutic targets. Cardiac disease is a major cause of excess mortality in people with SMI (). Mendelian randomization (MR) studies have supported a causal relationship between some psychiatric conditions and cardiac disease risk, but not all. For example, genetically predicted schizophrenia and depression, but not bipolar disorder, associate with increased heart failure risk (, , ). Furthermore, genetically predicted depression, but not schizophrenia or bipolar disorder, is associated with increased coronary artery disease (CAD) risk (,,). Some associations exhibit sex-specific effects, with genetic predisposition to depression conferring a greater risk of CAD in females (). High polygenic risk scores (PRSs) for schizophrenia associated with more marked cardiac structural and functional variation as assessed using magnetic resonance imaging (MRI) (). These alterations include reduced peak diastolic strain rates (PDSRs), indicating myocardial stiffness and diastolic dysfunction, which predict adverse cardiac outcomes and mortality (,). While PRS studies link schizophrenia to structural cardiac changes that worsen cardiac outcomes, they cannot establish causality. It is also unclear if similar effects occur in bipolar disorder and depression and if SMIs influence structural variations of other peripheral organs or body composition. Depression is causally associated with high body mass index (BMI) (), while schizophrenia is linked to lower BMI (); however, no previous studies have examined the causal effects of SMI on peripheral organ fat and abdominal fat volumes. Finally, the extent to which any causal effects of SMI on peripheral anatomical variation are mediated by lifestyle, metabolic, or sex-specific mechanisms is unknown. Metabolic and immune disturbance may be intrinsic to SMI, with insulin resistance and a proinflammatory state observed even in antipsychotic-naïve people with first-episode psychosis (,); such abnormalities may affect cardiopulmonary and abdominal organ structure. Smoking, which is more common among individuals with SMI (), further contributes to systemic organ dysfunction. These pathways may mediate the effects of SMI on peripheral anatomy. MR leverages the random allocation of genetic variants at conception to assess whether exposure has a causal influence on the outcome. As genetic variants are fixed prior to disease onset, MR can approximate a randomized trial, mitigating confounding and reverse causation. Here, we used 2-sample MR, with the largest available genome-wide association studies (GWASs), to test the causal association effects of schizophrenia, bipolar disorder, and MDD on the structure (e.g., organ volumes) and composition (e.g., fat content) of key cardiometabolic organs (e.g., heart, liver, and pancreas), as well as abdominal adiposity. Then, we used multivariate MR to assess whether these effects were mediated by BMI, insulin resistance, inflammation, and smoking. Finally, we analyzed individual-level data from UK Biobank (UKB), applying 1-sample MR to examine sex-specific associations.