A, Association of HOMA2-IR with clinical status. B, Association of HOMA2-IR with the 108 loci schizophrenia polygenic risk score. C, Association of antipsychotic drug switching during the initial 12 months of treatment with baseline HOMA2-IR. Plots show adjusted mean with standard error (A) and marginal effects with 95% confidence intervals (B and C). Statistical tests included analysis of covariance (A) and multivariable linear (B) and logistic (C) regression. Covariates were selected using bidirectional elimination and Bayesian information criterion from age, sex, body mass index, race/ethnicity, smoking, alcohol consumption, cannabis use, and previous psychiatric medication (A-C); baseline Brief Psychiatric Rating Scale, Scale for the Assessment of Positive Symptoms, and Scale for the Assessment of Negative Symptoms scores (B; schizophrenia group); and the initial treatment drug (C). Only cases with complete data were analyzed. P values were obtained by permutation testing (1000 permutations). P less than .05 was considered significant. Numbers: A, 54 control individuals and 56 patients with schizophrenia; B, 53 control individuals and 49 patients with schizophrenia; C, 20 patients with schizophrenia with no drug switch and 21 patients with schizophrenia with drug switch (13 owing to low efficacy, 5 owing to adverse effects, and 3 owing to noncompliance).
aP < .001.
bP < .05.
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Tomasik J, Lago SG, Vázquez-Bourgon J, et al. Association of Insulin Resistance With Schizophrenia Polygenic Risk Score and Response to Antipsychotic Treatment. JAMA Psychiatry. 2019;76(8):864–867. doi:10.1001/jamapsychiatry.2019.0304
Patients with schizophrenia show an increased risk of impaired glucose metabolism,1 yet the mechanism behind this association remains unknown. Multiple studies have attempted to identify the determinants of insulin resistance (IR) in schizophrenia, with evidence suggesting that it cannot be fully explained by disease duration, symptom severity, medication effects, obesity, or hormonal stress axis activation, and other interacting factors are likely involved.1 While family and genome-wide association studies have suggested a shared genetic vulnerability between schizophrenia and abnormal glucose metabolism,2 to our knowledge, a direct link between schizophrenia genetic risk and insulin resistance has not been investigated. Here, we examine the association between IR, schizophrenia polygenic risk, and treatment outcomes in first-episode, antipsychotic-naive patients with schizophrenia and matched healthy individuals while controlling for demographic, lifestyle, and clinical factors.
First-episode, antipsychotic-naive patients with schizophrenia and matched unaffected control individuals (58 patients with schizophrenia and 58 control individuals; Table) were recruited at the University Hospital Marqués de Valdecilla (Santander, Spain) as described previously.3 The study procedures were approved by the medical faculty ethical committee, and written informed consent was obtained from all study participants. Schizophrenia polygenic risk scores (PRS) were calculated based on 108 genome-wide significant schizophrenia loci4 from the Illumina Infinium PsychArray Bead-Chip genotyping data imputed using IMPUTE2/SHAPEIT. The updated Homeostasis Model Assessment (HOMA2)5 was used to infer IR, β cell function, and insulin sensitivity from clinical measurements of fasting serum glucose and insulin levels. Switching antipsychotic medication at least once during the initial 12 months of treatment was used as a heuristic long-term treatment outcome measure. All statistical tests were 2-sided and are described in figure legends. A P value of less than .05 was considered significant. Analyses were conducted in R, version 3.5.0 (R Foundation).
Consistent with previous reports,1 patients with schizophrenia showed increased baseline HOMA2-IR (mean difference [MD] [SE], 0.68 [0.25]; P = .004), HOMA2 β-cell function (MD [SE], 32.2 [13.1]; P = .02), and fasting insulin levels (MD [SE], 5.5 [2.1] μIU/mL [to convert to picomoles per liter, multiply by 6.945]; P = .004), whereas HOMA2 insulin sensitivity (MD [SE], −19.6 [15.5]; P = .20) and fasting glucose levels (MD [SE], 0.6 [2.0] mg/dL [to convert to millimoles per liter, multiply by 0.0555]; P = .76) did not differ significantly from control values (Table). After adjusting for covariates, HOMA2-IR remained significantly increased in patients with schizophrenia (MD [SE], 0.82 [0.25]; P < .001, adjusted for body mass index; Figure, A). The HOMA2-IR was positively associated with schizophrenia PRS in patients with schizophrenia (β [SE], 3.74 [1.68]; P = .02, adjusted for age; Figure, B) but not in the control group (adjusted β [SE], 0.29 [0.40]; P = .45), where body mass index was the most significant risk factor (adjusted β [SE], 0.071 [0.018]; P < .001). Baseline HOMA2-IR was significantly associated with switching antipsychotic medication during the initial 12 months of treatment, with an adjusted odds ratio (OR) of 1.77 (95% CI, 1.10-3.52; P = .02, adjusted for ethnicity; Figure, C). Of the 41 patients for whom complete follow-up information was available, all 8 patients who at baseline satisfied the fasting insulin criteria for IR (≥25 μIU/mL)6 required changing medication within the first year of treatment. Schizophrenia PRS was not significantly associated with medication switching status (adjusted OR, 183; 95% CI, 0.48-504 931; P = .12).
We report that schizophrenia polygenic risk is significantly associated with insulin resistance in first-episode, antipsychotic-naive patients with schizophrenia independent from selected demographic, lifestyle, and clinical factors. This result suggests that IR is a hallmark of schizophrenia rather than a secondary effect of emerging symptoms and supports the hypothesis that multiple susceptibility genes might exert pleiotropic effects cooccurring between the 2 conditions. Furthermore, the results indicate a potential association of IR with diminished response to antipsychotic treatment. Hence, patients with schizophrenia presenting with IR might constitute a distinct patient subgroup and require personalized treatment tailored to this endophenotype.
Limitations of this study include incomplete metadata for subsets of clinical variables and the fact that although nonresponse was the primary factor influencing medication switching, other clinical variables, such as adverse effects and treatment nonadherence, cannot be excluded in a minority of cases. Well-powered pharmacogenomic studies and more specific assays, such as the oral glucose tolerance and cortisol tests,1 are required to further examine the association between IR, schizophrenia, and antipsychotic treatment response, in addition to determining the effects of other lifestyle factors such as diet and exercise.
Corresponding Author: Sabine Bahn, MD, PhD, Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, England (email@example.com).
Accepted for Publication: January 6, 2019.
Published Online: April 3, 2019. doi:10.1001/jamapsychiatry.2019.0304
Author Contributions: Dr Tomasik had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Crespo-Facorro and Bahn contributed equally to this work.
Study concept and design: Tomasik, Lago, Crespo-Facorro, Bahn.
Acquisition, analysis, or interpretation of data: All authors.
Drafting the manuscript: Tomasik, Lago, Bahn.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Tomasik.
Administrative, technical, or material support: Crespo-Facorro, Bahn.
Study supervision: Crespo-Facorro, Bahn.
Conflict of Interest Disclosures: Dr Tomasik was a consultant for Psynova Neurotech, Ltd, until April 2016. Dr Lago was part funded by Psynova Neurotech Ltd until October 2015. Dr Bahn is a director of Psynova Neurotech Ltd and Psyomics Ltd. No other disclosures were reported.
Funding/Support: This work was supported by grants from the Stanley Medical Research Institute (Dr Bahn).
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We are grateful to the individuals who participated in the study for sample donation and the technical and clinical support staff at the affiliated institutions for collection of samples, clinical data, and technical support. Participants were not compensated by the funding sponsor for their contribution.
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