Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Oct 1.
Published in final edited form as: Early Interv Psychiatry. 2018 Oct 2;13(5):1021–1031. doi: 10.1111/eip.12749

Glucose Metabolism Dysregulation at The Onset of Mental Illness Is Not Limited To First Episode Psychosis: A Systematic Review and Meta-Analysis

Suat Kucukgoncu 1, Urska Kosir 2, Elton Zhou 3, Erin Sullivan 4, Vinod H Srihari 5, Cenk Tek 6
PMCID: PMC6445792  NIHMSID: NIHMS991112  PMID: 30277314

Abstract

Background

Research in treatment-naïve, first episode patients with severe mental illnesses (SMIs) suggest a pre-diabetic condition at the onset of illness. However, we have limited knowledge on glucose metabolism differences across diagnostic categories of SMIs.

Aims

To compare the differences of glucose metabolism outcomes between treatment-naïve, patients with first episode psychosis (FEP) and mood disorders.

Method

We conducted a systematic review and meta-analysis of glucose intolerance in treatment-naïve, first episode patients with SMIs.

Results

We identified 31 eligible studies. Compared to healthy controls, FEP group have higher insulin and insulin resistance levels, and both groups have higher glucose tolerance test results. No significant differences were found in glucose metabolism outcomes between FEP and mood disorder groups.

Conclusions

Our results highlight impaired glucose metabolism at the onset of SMIs, suggesting both patients with psychosis and mood disorders are high-risk groups for diabetes development.

Keywords: First episode, psychosis, insulin, diabetes, mood disorders

Introduction

It is widely acknowledged that type 2 diabetes mellitus (DM2) incidence is significantly higher in patients with schizophrenia compared to the general population.(McIntyre et al., 2005; Mitchell, Vancampfort, De Herdt, Yu, & De Hert, 2013; Vancampfort et al., 2016) Several factors, including adverse effects of antipsychotic medications, altered inflammatory processes and possibly shared genetic links between schizophrenia and DM2 likely contribute to comorbidity between these two disorders.(Calkin, Gardner, Ransom, & Alda, 2013; Ferentinos & Dikeos, 2012; Garcia-Rizo, Kirkpatrick, Fernandez-Egea, Oliveira, & Bernardo, 2016; Perry, McIntosh, Weich, Singh, & Rees, 2016; Yamagata et al., 2016) Research dating back to the pre-anti-psychotic era (Henneman, Altschule, & Goncz, 1954) as well as findings from treatment-naïve, first episode psychosis (FEP) patients suggest a pre-diabetic condition with impaired glucose metabolism at the onset of the psychotic illness.(Arranz et al., 2004; Greenhalgh et al., 2016; Misiak et al., 2016; Perry et al., 2016; Ryan, Collins, & Thakore, 2003; Spelman, Walsh, Sharifi, Collins, & Thakore, 2007) A recent Danish register study published in by Rajkumar et al. reported 3.07 adjusted hazard ratio of diabetes diagnosis in treatment-naïve FEP patients compared to population sample, suggesting an increased endogenic risk for DM2 in FEP patients.(Cohen & De Hert, 2011; Rajkumar et al., 2017) Three recent meta-analyses have shown significantly higher insulin resistance (IR), HbA1c, fasting insulin and glucose levels after oral glucose tolerance test (OGTT) in treatment-naïve, FEP compared to healthy controls. (Greenhalgh et al., 2016; Perry et al., 2016; Pillinger et al., 2017) One of these meta-analyses (Greenhalgh et al., 2016) also showed higher fasting glucose levels in patients with FEP compared to healthy controls, whereas others reported no difference on fasting glucose levels between these two groups.

If the association between schizophrenia and DM2 reflected shared biological vulnerability, this might suggest new avenues to explore the pathophysiology of both disorders. Increased DM2 prevalence, however, is an emerging medical problem not only in patients with schizophrenia, but also in patients with other severe mental illnesses (SMI), such as bipolar disorder and depression. (McIntyre et al., 2005; Vancampfort et al., 2016) Epidemiological studies have indicated higher DM2 incidence, as well as increased insulin resistance in patients with bipolar disorder and depression.(Calkin et al., 2013; Charles, Lambert, & Kerner, 2016; Fagiolini, Frank, Scott, Turkin, & Kupfer, 2005; McIntyre et al., 2005; Roy & Lloyd, 2012) Furthermore, findings in treatment-naïve first episode patients with bipolar disorder (C. Garcia-Rizo et al., 2016; Guha et al., 2014) and depression (Chang et al., 2013; Clemente Garcia-Rizo et al., 2013) indicated impaired glucose tolerance, insulin resistance and increased rates of DM2, similar as FEP patients. Impaired glucose metabolism may thus be a non-specific finding common to SMIs near illness onset.

One way to test this hypothesis is to compare the differences of glucose metabolism between different diagnostic groups of treatment-naïve, first episode patients with SMIs. However, only one study has tested this hypothesis and only did so in a relatively small sample. The sample consisted of treatment-naïve patients with FEP (n=84), first episode patients with bipolar I disorder (n=6), first episode patients with depression (n=12), patients with adjustment disorder (n=17) and healthy controls (n=98). (C. Garcia-Rizo et al., 2016) Findings from this study showed an increased 2-hour glucose load value in patients with FEP, bipolar I disorder, and depression, compared to both adjustment disorder and healthy controls. No significant differences were found in fasting blood glucose and insulin levels between patients with FEP, bipolar I disorder and depression in this study.

While research regarding glucose metabolism in treatment-naïve, first episode patients with individual SMI suggest a pre-diabetic condition, we have limited knowledge on the differences of glucose metabolism across different diagnostic categories of SMIs. Therefore, the first aim of this study is to extend previous findings in patients with FEP (Greenhalgh et al., 2016; Perry et al., 2016; Pillinger et al., 2017) by conducting a systematic review and a meta-analysis of glucose intolerance in first episode, treatment-naïve patients with FEP, as well as first episode, treatment-naïve patients with depression and bipolar disorder. The second aim of this study is to compare the differences of pooled results from glucose metabolism outcomes between these diagnostic categories.

Methods

Studies were identified using PubMed, Psych INFO, Science Direct, and Web of Science (1950 to June 2017). Additionally, a manual search was used to find relevant references from retrieved articles, related review articles and meta-analyses. Two reviewers (SK and UK) independently conducted the literature search using the following MESH and free-text search terms: first-episode, antipsychotic-naïve, treatment-naïve, unmedicated, bipolar, mania, manic episode, bipolar depression, euthymic, depression, dysthymia, mood, psychosis, schizophrenia, insulin, insulin resistance, glucose, HbA1c, metabolic disturbances and diabetes.

Selection Criteria

The following inclusion criteria was used: (i) studies that were conducted with first episode patients who were either treatment-naïve or with life-time prior treatment for less than two weeks and diagnosed with schizophrenia spectrum disorders, bipolar disorders or depressive disorders according to DSM or ICD criteria, (ii) studies that included healthy control subjects, (iii) subjects were with a mean age of ≥15 years of age, (iv) studies that reported fasting blood glucose, insulin, HbA1c, OGTT or IR levels in both first episode patients and healthy controls. The present meta-analysis was conducted and reported according to the PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-analysis) guidelines (Supplementary Table 1).(Moher, Liberati, Tetzlaff, Altman, & Group, 2009)

Data Extraction

Two reviewers (UK and EZ) independently reviewed each article and extracted all data. A third reviewer (SK) checked all extracted data to clarify missing data. Any conflicts were discussed with the third reviewer (SK). The following data were extracted: study design, sample size characteristics of participants (age, gender), body mass index (BMI), fasting blood glucose, insulin, IR, HbA1c levels and OGTT results. To obtain the missing information, we contacted the authors to request relevant data. Outcomes of overlapping samples from the same investigators were extracted from the more detailed report.

The quality of the cohort and case-control studies was peer-reviewed using the Newcastle-Ottawa Scale (NOS) for observational studies.(Wells, 2009) A modified version for NOS was used to asses cross-sectional studies (Supplementary Table 2).

Statistical Analyses

To avoid publication bias, we conducted a comprehensive search among published studies. We examined the differences on metabolic outcomes between healthy controls and first episode patients by calculating effect size (ES) estimates (Hedges’ g) using the software Comprehensive Meta-Analysis Version 2 (Biostat, Englewood, NJ, USA). Statistical heterogeneity was assessed using Q and I2 test, in which I2 ≥ 50% was considered to indicate heterogeneity. Publication bias was assessed visually with funnel plots and statistically with Egger’s regression test.(Egger, Davey Smith, Schneider, & Minder, 1997)

We performed subgroup and meta-regression analysis to examine the relationship between glucose metabolism outcomes and BMI, age and gender. There are differences on weight outcomes and weight gain liabilities on FEP patients from Western countries as opposed to patients from Asian countries.(Tek et al., 2016) Previous studies has also shown differences in prevalence of type II diabetes and in glucose metabolism outcomes between different ethnicities.(Li, Dong, Wu, & Tong, 2016; Whiting, Guariguata, Weil, & Shaw, 2011) Therefore, we also performed a sub-group analysis to compare glucose metabolism outcomes between different regions (Asian vs Non-Asian). The random-effects model was used to compare ES estimate differences. The results for a fixed-effects model were presented as a sensitivity analysis.

Results

Our research strategy resulted in a total of 1616 articles, excluding duplicates. After screening the title and abstract, 152 articles were selected for further evaluation. After full-text review, 121 articles that were not fulfilling the selection criteria were excluded. Of the excluded studies, 47 did not report relevant metabolic outcomes, 23 did not have a healthy control group, and 29 were not conducted with treatment-naïve first episode patients. Our study selection process is presented in Figure 1.

Figure 1.

Figure 1.

Open in a new tab

PRISMA Flow Diagram

Overall, we identified 31 eligible studies for inclusion in this meta-analysis (Supplementary Table 3–4).(Arranz et al., 2004; Basoglu et al., 2010; Cai et al., 2012; Canan et al., 2014; Chang et al., 2013; D. C. Chen et al., 2016; S. Chen et al., 2016; Dasgupta, Singh, Rout, Saha, & Mandal, 2010; Enez Darcin, Yalcin Cavus, Dilbaz, Kaya, & Dogan, 2015; E. Fernandez-Egea et al., 2009; Clemente Garcia-Rizo et al., 2013; C. Garcia-Rizo et al., 2016; Grover, Nebhinani, Chakrabarti, Avasthi, & Kulhara, 2013; Kavzoglu & Hariri, 2013; Keinanen et al., 2015; Leo et al., 2006; Misiak et al., 2016; Nyboe, Vestergaard, Moeller, Lund, & Videbech, 2015; Petrikis et al., 2015; Ryan et al., 2003; Saddichha, Manjunatha, Ameen, & Akhtar, 2008; Saloojee, Burns, & Motala, 2017; Sengupta et al., 2008; Spelman et al., 2007; Turan, Kesebir, & Suner, 2014; van Nimwegen et al., 2008; Venkatasubramanian et al., 2007; Wani et al., 2015; Wu et al., 2013; Yildirim et al., 2014; Zhang et al., 2015) Of these studies, one was conducted with patients who had a first episode mania, (Turan et al., 2014) five were conducted with patients who had first episode depression, (Canan et al., 2014; Chang et al., 2013; Clemente Garcia-Rizo et al., 2013; Grover et al., 2013; Leo et al., 2006) and one was conducted with patients who had first episode mania or depression. (Garcia-Rizo et al., 2016) Twenty-four were conducted in patients with FEP. (Arranz et al., 2004; Basoglu et al., 2010; Cai et al., 2012; D. C. Chen et al., 2016; S. Chen et al., 2016; Dasgupta et al., 2010; Enez Darcin et al., 2015; E. Fernandez-Egea et al., 2009; Kavzoglu & Hariri, 2013; Keinanen et al., 2015; Misiak et al., 2016; Nyboe et al., 2015; Petrikis et al., 2015; Ryan et al., 2003; Saddichha et al., 2008; Saloojee et al., 2017; Sengupta et al., 2008; Spelman et al., 2007; van Nimwegen et al., 2008; Venkatasubramanian et al., 2007; Wani et al., 2015; Wu et al., 2013; Yildirim et al., 2014; Zhang et al., 2015) Among FEP studies, one study included patients with schizoaffective disorders (n=4) in their patient group (n=38).(Sengupta et al., 2008) The total number of subjects in these studies was 1242 for FEP group, 214 for mood disorder group and 1361 for healthy control group.

Meta-analyses

In order to evaluate the differences of glucose metabolism outcomes, we first compared the pooled effect size estimates between patient and control samples. We then combined the outcomes from bipolar and depression groups as mood disorder group to compare estimated effect sizes with first episode psychosis group. Finally, we compared the pooled effect size estimates of glucose metabolism outcomes between three diagnostic categories when there is enough outcome from each group.

Fasting Glucose

For the fasting blood glucose analysis, 32 outcomes were extracted from 30 studies. (Arranz et al., 2004; Basoglu et al., 2010; Cai et al., 2012; Canan et al., 2014; Chang et al., 2013; D. C. Chen et al., 2016; S. Chen et al., 2016; Dasgupta et al., 2010; Enez Darcin et al., 2015; E. Fernandez-Egea et al., 2009; Clemente Garcia-Rizo et al., 2013; C. Garcia-Rizo et al., 2016; Grover et al., 2013; Kavzoglu & Hariri, 2013; Keinanen et al., 2015; Leo et al., 2006; Misiak et al., 2016; Nyboe et al., 2015; Petrikis et al., 2015; Ryan et al., 2003; Saddichha et al., 2008; Saloojee et al., 2017; Sengupta et al., 2008; Spelman et al., 2007; Turan et al., 2014; van Nimwegen et al., 2008; Venkatasubramanian et al., 2007; Wani et al., 2015; Wu et al., 2013; Yildirim et al., 2014; Zhang et al., 2015) In our overall analysis, there was no significant difference on fasting glucose levels between patient and control groups (ES=0.10, CI=−0.03 to 0.23). Fasting glucose levels were similar in FEP patients (ES=0.12, CI=−0.02 to 0.27) and mood disorders patients (ES=0.02, CI=−0.25 to 0.29) compared to control subjects (Figure 2).

Figure 2.

Figure 2.

Open in a new tab

Meta-analysis of fasting blood glucose levels in first episode patients Heterogeneity: Tau2=0.07; I2=57.35%; Q=72.69, d.f=31, p<0.001 Overall effect (Fixed): Z=2.977, p=0.003 Overall effect (Random): Z=1.474, p=0.14

Dx: Diagnoses. 1=First episode psychosis, 2=First episode depression, 3=First episode bipolar disorder

In subgroup analysis, there was no significant difference on ES estimates of fasting glucose levels between psychotic patients and mood disorders patients (Q=0.30, df=1, p=0.58). ES estimates of fasting glucose levels between first episode psychosis and mania groups (n=3, ES=−0.01, CI=−0.50 to 0.48)(psychosis vs. mania: Q=0.25, df=1, p=0.61), and first episode psychosis and depression groups (n=5, ES=0.05, CI=−0.22 to 0.32) were similar (psychosis vs. depression: Q=0.20, df=1, p=0.65). ES estimates of fasting glucose levels were also similar between the depression and bipolar subgroups (Q=0.04, df=1, p=0.83).

No evidence of publication bias was found in fasting glucose analysis (Egger’s intercept=−1.64, CI=−3.63 to 0.34). There was a significant heterogeneity on fasting glucose outcomes across all studies included in the meta-analysis (I2=57.35, df=31, p<0.001). Heterogeneity was also significant in subgroup analysis that was carried out in studies with psychotic patients (I2=62.89, df=22, p<0.001). Studies in mood disorders revealed no significant heterogeneity (I2=31.67.78, df=7, p=0.17).

Insulin Levels

We extracted 15 outcomes from FEP samples (Arranz et al., 2004; Cai et al., 2012; D. C. Chen et al., 2016; S. Chen et al., 2016; Enez Darcin et al., 2015; E. Fernandez-Egea et al., 2009; Keinanen et al., 2015; Petrikis et al., 2015; Ryan et al., 2003; Sengupta et al., 2008; Spelman et al., 2007; van Nimwegen et al., 2008; Venkatasubramanian et al., 2007; Wu et al., 2013; Zhang et al., 2015) and 4 outcomes from mood disorder samples (Chang et al., 2013; C. Garcia-Rizo et al., 2016; Leo et al., 2006) for the meta-analysis of fasting insulin levels. In our overall analysis, first episode patients have similar insulin levels compared to the control group (ES=0.21, CI=−0.24 to 0.67). The difference in insulin levels was significant between FEP patients and control groups (ES=0.40, CI=0.16 to 0.64). There was no significant difference in insulin levels between first episode mood disorder and control groups (ES=−0.06, CI=−0.54 to 0.40). (Figure 3).

Figure 3.

Figure 3.

Open in a new tab

Meta-analysis of insulin levels in first episode patients Heterogeneity: Tau2=0.19; I2=76.52%; Q=76.66, d.f= 18, p<0.001

Overall effect (Fixed): Z=4.148, p<0.001

Overall effect: Z=0.092, p=0.35

Dx: Diagnoses. 1=First episode psychosis, 2=First episode depression, 3=First episode bipolar disorder

In subgroup analysis, ES estimates of insulin levels were similar between first episode psychosis and mood disorder groups (Q=3.35, df=1, p=0.06). There was no significant difference in insulin levels between first episode psychosis and depression groups (n=3, ES=−0.08, CI=−0.64 to 0.47)(psychosis vs. depression group: Q=2.55, df=1, p=0.10).

No evidence of publication bias was found in insulin level analysis (Egger’s intercept=3.14, CI=−0.26 to 6.56). There was a significant heterogeneity across all studies included in the meta-analysis (I2=76.66, df=18, p<0.001). Heterogeneity was also significant in subgroup analyses that were carried out in studies with FEP patients (I2=73.46, df=14, p<0.001) and mood disorders (I2=66.06, df=3, p=0.03).

Insulin Resistance

For meta-analysis of IR levels, we extracted 14 outcomes from FEP groups (Arranz et al., 2004; D. C. Chen et al., 2016; S. Chen et al., 2016; Dasgupta et al., 2010; Enez Darcin et al., 2015; E. Fernandez-Egea et al., 2009; Keinanen et al., 2015; Petrikis et al., 2015; Ryan et al., 2003; Sengupta et al., 2008; Spelman et al., 2007; Venkatasubramanian et al., 2007; Wu et al., 2013; Zhang et al., 2015) and 2 outcomes from depressive disorder groups (Chang et al., 2013; Leo et al., 2006). In our overall analysis, no significant difference was found between first episode patients and the healthy controls on ES estimates of IR levels (ES=0.24, CI=−0.08 to 0.56) (Figure 4).

Figure 4.

Figure 4.

Open in a new tab

Meta-analysis of insulin resistance in first episode patients Heterogeneity: Tau2=0.047; I2=47.61%; Q=28.63, d.f=15, p=0.018

Overall effect (Fixed): Z=5.34, p<0.001

Overall effect (Random): Z=1.451, p=0.14

Dx: Diagnoses. 1=First episode psychosis, 2=First episode depression, 3=First episode bipolar disorder

In subgroup analyses, a significant difference in IR levels was found between FEP patients and control groups (ES=0.36, CI=0.21 to 0.52). There was no significant difference on IR levels between first episode depression and control groups (ES=0.02, CI=−0.22 to 0.40). ES estimates of IR levels were similar between first episode psychosis and depression groups (Q=2.64, df=1, p=0.10).

We found no evidence of publication bias in IR analysis (Egger’s intercept=1.94, CI=−1.80 to 5.69). IR levels across all studies included in the meta-analysis showed a significant heterogeneity (I2=47.61, df=15, p=0.018). Heterogeneity was significant in subgroup analysis that was carried out in studies with psychotic patients (I2=43.01, df=13, p=0.04). Heterogeneity was non-significant in subgroup analysis that was carried out in studies with mood disorders patients (I2=0.01, df=1, p=0.47).

HbA1c Levels

For the meta-analysis of HbA1c levels, we extracted 4 outcomes from the FEP group (Petrikis et al., 2015; Sengupta et al., 2008; Spelman et al., 2007; Yildirim et al., 2014) and 2 outcomes from the depressive disorders group. (Canan et al., 2014; Chang et al., 2013) In our overall analysis, no significant difference was found on ES estimate of HbA1c levels between first episode patients and the healthy controls (ES=0.15, CI=−0.07 to 0.37) (Supplementary Figure 1).

In subgroup analyses, compared to the healthy controls no significant difference was found on HbA1c levels in first episode depression (ES=0.40, CI=−0.001 to 0.80) and psychosis group (ES=0.04, CI=−0.22 to 0.30). ES estimates of HbA1c levels were similar between first episode psychosis and depression groups (Q=2.12, df=1, p=0.14).

No evidence of publication bias was found in HbA1c analysis (Egger’s intercept=−1.96, CI=−10.13 to 6.21). There was no significant heterogeneity across all studies included in HbA1c level meta-analysis (I2=48.83, df=5, p=0.08). Heterogeneity was non-significant in subgroup analysis that were carried out in studies with psychotic patients (I2=14.50, df=3, p=0.32) and mood disorders patients (I2=45.84, df=1, p=0.17).

Two-hour oral glucose tolerance test

We extracted 4 outcomes from first episode psychosis patients (E. Fernandez-Egea et al., 2009; Saddichha et al., 2008; Spelman et al., 2007; Wani et al., 2015) and 2 outcomes from depression and bipolar patients (Clemente Garcia-Rizo et al., 2013; C. Garcia-Rizo et al., 2016) for the meta-analysis of fasting insulin levels. In our overall analysis, first episode patients have significantly higher ES estimates of OGTT compared to the control group (ES=0.94, CI=0.59 to 1.29)(Supplementary Figure 1).

Patients with FEP (ES=0.62, CI=0.11 to 1.12) and patients with mood disorders (ES=1.22, CI=0.75 to 1.70) both have higher OGTT levels compared to the healthy controls. ES estimates of OGTT levels were similar between FEP and mood disorder groups (Q=2.929, df=1, p=0.08).

No evidence of publication bias was found in OGTT analysis (Egger’s intercept=5.49, CI=−2.78 to 13.78). There was a significant heterogeneity across all studies included in OGTT level meta-analysis (I2=80.9, df=5, p<0.001). Heterogeneity was also significant in subgroup analyses that were carried out in studies with psychotic patients (I2=84.42, df=3, p<0.001). Studies in mood disorders revealed no significant heterogeneity (I2<0.001, df=1, p=0.44).

Meta-regression analysis

We carried out meta-regression analyses in FEP and mood disorder groups to test the effects of sample age, BMI and gender distribution on glucose metabolism outcomes (Supplementary Table 5). In the FEP group, there was no significant interaction between age, gender, BMI and glucose metabolism outcomes. In the mood disorder group, only age was found to be significantly related with fasting blood glucose levels (PE=0.03, CI= 0.002 to 0.05). In the mood disorder group, we were not able to carry out meta-regression analysis on IR, OGGT and HbA1c outcomes due to the limited data.

There was no significant effect of study regions (Asian vs. Non-Asian) on fasting blood glucose, insulin and IR levels in the FEP group (Supplementary Table 6). Among the studies that included Asian patients with FEP, only one study reported OGTT levels, (Wani et al., 2015) and none of them reported HbA1c levels. Therefore, we were not able to test the effect of study regions in OGTT and HbA1c levels in patients with FEP. In the mood disorder group, only one study in Asian samples reported glucose metabolism outcomes. (Chang et al., 2013) Therefore we were not able to test the differences between Asian and Non-Asian samples in the mood disorder group.

Discussion

To our knowledge, this is the first meta-analysis that compares glucose metabolism outcomes of treatment-naïve patients with SMIs. Cumulative results in this meta-analysis suggest a few differences between patients with SMIs and healthy controls. Compared to healthy controls, treatment-naïve patients with FEP have higher fasting insulin and IR levels. Two-hour OGTT results were also found to be higher in both SMI groups compared to the healthy controls. No significant differences were found in glucose metabolism outcomes between patients with FEP and mood disorders.

In patients with FEP, our cumulative analyses on glucose metabolism outcomes are in line with previous meta-analyses, which showed significant increases in fasting insulin levels and impaired oral glucose tolerance in this patient population. (Greenhalgh et al., 2016; Perry et al., 2016; Pillinger et al., 2017) Our meta-analysis also confirms previous reports of an impaired oral glucose tolerance in first episode, treatment-naïve patients with mood disorders. (Garcia-Rizo et al., 2016; Guha et al., 2014) Previous studies mostly focused on a specific diagnosis of SMIs, particularly FEP, while only one study compared the differences on glucose metabolism outcomes between various SMIs. (C. Garcia-Rizo et al., 2016) Our meta-analysis on insulin, IR and HbA1c levels showed some contrast between patients with FEP and first episode treatment-naïve patients with mood disorders. Compared to healthy controls, patients with FEP have higher insulin and IR levels whereas patients with mood disorders tend to have higher, but non-significant, HbA1c levels. These differences were not significant between SMI groups. Divergence between patient groups are most likely related with the limited number of studies in each arm. Future studies on glucose metabolism outcomes in drug-naïve first episode SMIs are needed to explain the differences and similarities between diagnostic groups. Nevertheless, our results underline abnormalities in glucose metabolism at the beginning of the SMIs, suggesting a pre-diabetic condition in early phases of both SMIs with high-risk of DM2 development and a subsequent increase in the risk of diabetes-related complications such as cardiovascular diseases and cognitive deterioration later in life.

Research suggests that altered systemic inflammation, shared genetic make-up between SMIs and DM2, and adverse gestational events may play a role in this pre-diabetic condition. There is some support for these arguments. (Amare, Schubert, Klingler-Hoffmann, Cohen-Woods, & Baune, 2017; C. Garcia-Rizo, Fernandez-Egea, Bernardo, & Kirkpatrick, 2015; Goldsmith, Rapaport, & Miller, 2016; Greenhalgh et al., 2016; Thakore, 2004; van Nimwegen et al., 2008) Systemic inflammation is a feature of both disorders. SMIs (Drexhage et al., 2010; Goldsmith et al., 2016; Modabbernia, Taslimi, Brietzke, & Ashrafi, 2013; Monji et al., 2013) and DM2 (Calle & Fernandez, 2012; Kubaszek et al., 2003) are associated with increased concentrations of inflammatory cytokines, such as interleukin 6, tumor necrosis factor-alpha, and acute phase reactants like C-reactive protein. Furthermore, mutations in genes encoding these inflammatory markers have been reported in both SMIs and DM2. (Amare et al., 2017; Lin & Shuldiner, 2010) In addition to inflammation, findings from several studies suggest shared genetic liability between DM2 and schizophrenia. Family studies have shown that first-degree relatives of people with psychosis have an increased risk for DM and other abnormalities of glucose regulation. (Emilio Fernandez-Egea et al., 2008; van Welie et al., 2013) It has also been shown that genetic polymorphisms in several genes increase the risk of SMIs and diabetes. (Amare et al., 2017; Chubb, Bradshaw, Soares, Porteous, & Millar, 2008; Jurczyk et al., 2016; Scholz et al., 2010) Finally, early environmental factors can explain the part of the relationship between SMIs and DM2. Both SMIs and DM2 show an increased risk of prenatal and postnatal adverse events, as well as gestational complications. As suggested by the ‘thrifty psychiatric phenotype’ concept early environmental adverse events may interact with genetic programing and lead to SMIs and DM2 in adulthood. (Garcia-Rizo et al., 2015)

In addition to these hypotheses, the hypothalamus-pituitary-adrenal (HPA) axis has been proposed as one locus of common pathophysiologic mechanisms underlying DM2 and SMIs. (Belvederi Murri et al., 2016; Calkin et al., 2013; Joseph & Golden, 2016; Ryan et al., 2003) The HPA axis is a tightly regulated system that responds to acute and chronic stress by increasing cortisol levels through a cascade of physiological events. (Joseph & Golden, 2016) Elevated cortisol levels can lead to glucose metabolism abnormalities, a decrease in insulin secretion and an increase in gluconeogenesis, resulting in hyperglycemia with progression to DM2. (Fitzgerald, 2009; Joseph & Golden, 2016) Increased cortisol response is common in both patients with mood disorders (Belvederi Murri et al., 2016; Watson, Gallagher, Ritchie, Ferrier, & Young, 2004) and with schizophrenia. (Ryan et al., 2003; Spelman et al., 2007; Steen et al., 2014) As an acutely stressful state, onset of any SMI can increase cortisol levels, subsequently impair glycemic control, and lead to a pre-diabetic condition.

It is important to take note of the limitations of this meta-analysis. Our meta-analysis is based on cross-sectional studies, which cannot determine the causality of the relationship between SMIs and glucose metabolism abnormalities. Despite the fact that our analysis revealed no evidence of publication bias in glucose metabolism outcomes, the possibility cannot be ruled out due to the small number of studies included in this meta-analysis, and the possibility of unreported negative findings. On several outcomes, our meta-analysis showed significant heterogeneity between study results in both FEP and mood disorder groups. Our meta-regression analyses on the interaction between BMI and gender distribution with glucose metabolism outcomes did not point to any significant determinants of the ES differences between studies in both samples. Only in the mood disorders group, age was significantly related with fasting glucose outcomes. Although, fasting glucose outcomes in mood disorders group did not show significant heterogeneity, this interaction may explain the heterogeneity in cumulative analysis. It is important to note that the number of studies we could consider for the meta-regression analyses was limited as we had to exclude those that failed to report BMI and/or age outcomes between SMI and healthy control groups. (Chang et al., 2013; Nyboe et al., 2015; Saddichha et al., 2008; Spelman et al., 2007; Wani et al., 2015; Zhang et al., 2015) For future studies on glucose metabolism, it is crucial to match SMI and healthy control samples on BMI and age to report more reliable outcomes. Another possible explanation for not detecting any interaction between BMI levels and glucose metabolism outcomes on meta-regression analyses is that the first episode SMI samples in our analyses typically presented with normal to overweighed BMI levels, between 19.63 to 27.7 (Supplementary Table 3). However, compared to healthy controls BMI levels increases with antipsychotic treatments in patients with first episode SMIs. (Tek et al., 2016; Sengupta et al., 2008) Thus, we posit that the relationship between BMI and glucose metabolism outcomes may emerge later in the course of disease.

We could test the effect of study regions only in FEP sub-group, which revealed no significant differences between Asian and European studies. Although we used the random-effects model to eliminate the heterogeneity between studies, our results should be interpreted with caution. Finally, our meta-analysis included a relatively small number of studies in mood disorder (n=6) groups compared to FEP studies (n=25). Therefore, our sub-group analysis on glucose metabolism outcomes between these two SMI groups should be evaluated cautiously. Small number of studies in mood disorders also limited our ability to compare most glucose metabolism outcomes between depression, bipolar disorder and FEP. It is clear that further studies are necessary to explore glucose metabolism in first episode, treatment-naïve patients with mood disorders.

Despite the limitations of our study, our results highlight impaired glucose metabolism at the onset of all SMIs, suggesting both patients with FEP and mood disorders are high-risk groups for DM2 development. It appears that less attention is paid to non-psychotic first episode illness and glucose metabolism dysregulation. Thus, it is hard to conclude if this phenomenon of glucose metabolism dysregulation is related to psychosis, schizophrenia or a stressful new onset of any serious psychiatric condition. Regardless, it is critically important to determine baseline DM2 risk at initial presentation of SMI. Detailed medical history and physical examination, family history of DM2, smoking status, dietary and physical activity habits, body mass index and fasting blood glucose and insulin, perhaps even oral glucose testing as a gold standard should be obtained before the initiation of psychotropic medications.(Vancampfort et al., 2016) After the initiation of psychotropic treatment, DM2 risk should be evaluated annually, with more frequent assessments in ultra-high-risk patients, such as those with multiple psychotic or mood episodes, significant weight gain, a family history of DM2 and a need of polypharmacy treatments.(De Hert, Detraux, van Winkel, Yu, & Correll, 2011; Gierisch et al., 2014; Vancampfort et al., 2016) Further research is needed to explore the mechanisms underlying early glucose metabolism abnormalities in SMIs.

Supplementary Material

Supp info

Acknowledgments

Funding Source:

The study was funded by a grant to me from the U.S. National Institutes of Health (DK093924).

Contributor Information

Suat Kucukgoncu, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

Urska Kosir, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

Elton Zhou, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

Erin Sullivan, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

Vinod H. Srihari, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

Cenk Tek, Yale University Department of Psychiatry, Connecticut Mental Health Hospital, New Haven, United States

References

  1. Amare AT, Schubert KO, Klingler-Hoffmann M, Cohen-Woods S, & Baune BT (2017). The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies. Transl Psychiatry, 7(1), e1007. doi: 10.1038/tp.2016.261 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arranz B, Rosel P, Ramirez N, Duenas R, Fernandez P, Sanchez JM, … San L (2004). Insulin resistance and increased leptin concentrations in noncompliant schizophrenia patients but not in antipsychotic-naive first-episode schizophrenia patients. J Clin Psychiatry, 65(10), 1335–1342. [DOI] [PubMed] [Google Scholar]
  3. Basoglu C, Oner O, Gunes C, Semiz UB, Ates AM, Algul A, … Ipcioglu O (2010). Plasma orexin A, ghrelin, cholecystokinin, visfatin, leptin and agouti-related protein levels during 6-week olanzapine treatment in first-episode male patients with psychosis. Int Clin Psychopharmacol, 25(3), 165–171. doi: 10.1097/YIC.0b013e3283377850 [DOI] [PubMed] [Google Scholar]
  4. Belvederi Murri M, Prestia D, Mondelli V, Pariante C, Patti S, Olivieri B, … Amore M (2016). The HPA axis in bipolar disorder: Systematic review and meta-analysis. Psychoneuroendocrinology, 63, 327–342. doi: 10.1016/j.psyneuen.2015.10.014 [DOI] [PubMed] [Google Scholar]
  5. Cai H-L, Li H-D, Yan X-Z, Sun B, Zhang Q, Yan M, … Ye H-S (2012). Metabolomic Analysis of Biochemical Changes in the Plasma and Urine of First-Episode Neuroleptic-Naive Schizophrenia Patients after Treatment with Risperidone. J Proteome Res, 11(8), 4338–4350. doi: 10.1021/pr300459d [DOI] [PubMed] [Google Scholar]
  6. Calkin CV, Gardner DM, Ransom T, & Alda M (2013). The relationship between bipolar disorder and type 2 diabetes: more than just co-morbid disorders. Ann Med, 45(2), 171–181. doi: 10.3109/07853890.2012.687835 [DOI] [PubMed] [Google Scholar]
  7. Calle MC, & Fernandez ML (2012). Inflammation and type 2 diabetes. Diabetes Metab, 38(3), 183–191. doi: 10.1016/j.diabet.2011.11.006 [DOI] [PubMed] [Google Scholar]
  8. Canan F, Yildirim O, Tosun M, Kayka N, Tuman TC, & Alcelik A (2014). Serum levels of omentin are not altered in drug-naive patients with major depression: a pilot study. Psychiatr Danub, 26(1), 34–38. [PubMed] [Google Scholar]
  9. Chang HH, Chi MH, Lee IH, Tsai HC, Gean PW, Yang YK, … Chen PS (2013). The change of insulin levels after six weeks antidepressant use in drug-naive major depressive patients. J Affect Disord, 150(2), 295–299. doi: 10.1016/j.jad.2013.04.008 [DOI] [PubMed] [Google Scholar]
  10. Charles EF, Lambert CG, & Kerner B (2016). Bipolar disorder and diabetes mellitus: evidence for disease-modifying effects and treatment implications. Int J Bipolar Disord, 4(1), 13. doi: 10.1186/s40345-016-0054-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chen DC, Du XD, Yin GZ, Yang KB, Nie Y, Wang N, … Zhang XY (2016). Impaired glucose tolerance in first-episode drug-naive patients with schizophrenia: relationships with clinical phenotypes and cognitive deficits. Psychol Med, 1–12. doi: 10.1017/S0033291716001902 [DOI] [PubMed] [Google Scholar]
  12. Chen S, Broqueres-You D, Yang G, Wang Z, Li Y, Yang F, & Tan Y (2016). Male sex may be associated with higher metabolic risk in first-episode schizophrenia patients: A preliminary study. Asian J Psychiatr, 21, 25–30. doi: 10.1016/j.ajp.2015.12.001 [DOI] [PubMed] [Google Scholar]
  13. Chubb JE, Bradshaw NJ, Soares DC, Porteous DJ, & Millar JK (2008). The DISC locus in psychiatric illness. Mol Psychiatry, 13(1), 36–64. doi: 10.1038/sj.mp.4002106 [DOI] [PubMed] [Google Scholar]
  14. Cohen D, & De Hert M (2011). Endogenic and iatrogenic diabetes mellitus in drug-naive schizophrenia: the role of olanzapine and its place in the psychopharmacological treatment algorithm. Neuropsychopharmacology, 36(11), 2368–2369. doi: 10.1038/npp.2011.94 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Dasgupta A, Singh OP, Rout JK, Saha T, & Mandal S (2010). Insulin resistance and metabolic profile in antipsychotic naive schizophrenia patients. Prog Neuropsychopharmacol Biol Psychiatry, 34(7), 1202–1207. doi: 10.1016/j.pnpbp.2010.06.011 [DOI] [PubMed] [Google Scholar]
  16. De Hert M, Detraux J, van Winkel R, Yu W, & Correll CU (2011). Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol, 8(2), 114–126. doi: 10.1038/nrendo.2011.156 [DOI] [PubMed] [Google Scholar]
  17. Drexhage RC, Knijff EM, Padmos RC, Heul-Nieuwenhuijzen L, Beumer W, Versnel MA, & Drexhage HA (2010). The mononuclear phagocyte system and its cytokine inflammatory networks in schizophrenia and bipolar disorder. Expert Rev Neurother, 10(1), 59–76. doi: 10.1586/ern.09.144 [DOI] [PubMed] [Google Scholar]
  18. Egger M, Davey Smith G, Schneider M, & Minder C (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Enez Darcin A, Yalcin Cavus S, Dilbaz N, Kaya H, & Dogan E (2015). Metabolic syndrome in drug-naive and drug-free patients with schizophrenia and in their siblings. Schizophr Res, 166(1–3), 201–206. doi: 10.1016/j.schres.2015.05.004 [DOI] [PubMed] [Google Scholar]
  20. Fagiolini A, Frank E, Scott JA, Turkin S, & Kupfer DJ (2005). Metabolic syndrome in bipolar disorder: findings from the Bipolar Disorder Center for Pennsylvanians. Bipolar Disord, 7(5), 424–430. doi: 10.1111/j.1399-5618.2005.00234.x [DOI] [PubMed] [Google Scholar]
  21. Ferentinos P, & Dikeos D (2012). Genetic correlates of medical comorbidity associated with schizophrenia and treatment with antipsychotics. Curr Opin Psychiatry, 25(5), 381–390. doi: 10.1097/YCO.0b013e3283568537 [DOI] [PubMed] [Google Scholar]
  22. Fernandez-Egea E, Bernardo M, Donner T, Conget I, Parellada E, Justicia A, … Kirkpatrick B (2009). Metabolic profile of antipsychotic-naive individuals with non-affective psychosis. Br J Psychiatry, 194(5), 434–438. doi: 10.1192/bjp.bp.108.052605 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Fernandez-Egea E, Bernardo M, Parellada E, Justicia A, Garcia-Rizo C, Esmatjes E, … Kirkpatrick B (2008). Glucose abnormalities in the siblings of people with schizophrenia. Schizophr Res, 103(1–3), 110–113. doi: 10.1016/j.schres.2008.04.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Fitzgerald PJ (2009). Is elevated noradrenaline an aetiological factor in a number of diseases? Auton Autacoid Pharmacol, 29(4), 143–156. doi: 10.1111/j.1474-8665.2009.00442.x [DOI] [PubMed] [Google Scholar]
  25. Garcia-Rizo C, Fernandez-Egea E, Bernardo M, & Kirkpatrick B (2015). The thrifty psychiatric phenotype. Acta Psychiatr Scand, 131(1), 18–20. doi: 10.1111/acps.12309 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Garcia-Rizo C, Fernandez-Egea E, Miller BJ, Oliveira C, Justicia A, Griffith JK, … Kirkpatrick B (2013). Abnormal glucose tolerance, white blood cell count, and telomere length in newly diagnosed, antidepressant-naïve patients with depression. Brain Behav Immun, 28, 49–53. doi: 10.1016/j.bbi.2012.11.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Garcia-Rizo C, Kirkpatrick B, Fernandez-Egea E, Oliveira C, & Bernardo M (2016). Abnormal glycemic homeostasis at the onset of serious mental illnesses: A common pathway. Psychoneuroendocrinology, 67, 70–75. doi: 10.1016/j.psyneuen.2016.02.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Gierisch JM, Nieuwsma JA, Bradford DW, Wilder CM, Mann-Wrobel MC, McBroom AJ, … Williams JW Jr. (2014). Pharmacologic and behavioral interventions to improve cardiovascular risk factors in adults with serious mental illness: a systematic review and meta-analysis. J Clin Psychiatry, 75(5), e424–440. doi: 10.4088/JCP.13r08558 [DOI] [PubMed] [Google Scholar]
  29. Goldsmith DR, Rapaport MH, & Miller BJ (2016). A meta-analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Mol Psychiatry, 21(12), 1696–1709. doi: 10.1038/mp.2016.3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Greenhalgh AM, Gonzalez-Blanco L, Garcia-Rizo C, Fernandez-Egea E, Miller B, Arroyo MB, & Kirkpatrick B (2016). Meta-analysis of glucose tolerance, insulin, and insulin resistance in antipsychotic-naive patients with nonaffective psychosis. Schizophr Res. doi: 10.1016/j.schres.2016.09.026 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Grover S, Nebhinani N, Chakrabarti S, Avasthi A, & Kulhara P (2013). Metabolic Syndrome in Drug-naive Patients with Depressive Disorders. Indian J Psychol Med, 35(2), 167–173. doi: 10.4103/0253-7176.116247 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Guha P, Bhowmick K, Mazumder P, Ghosal M, Chakraborty I, & Burman P (2014). Assessment of insulin resistance and metabolic syndrome in drug naive patients of bipolar disorder. Indian journal of clinical biochemistry : IJCB, 29(1), 51–56. doi: 10.1007/s12291-012-0292-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Henneman DH, Altschule MD, & Goncz RM (1954). Carbohydrate metabolism in brain disease. II. Glucose metabolism in Schizophrenic, manic-depressive, and involutional psychoses. AMA Arch Intern Med, 94(3), 402–416. [DOI] [PubMed] [Google Scholar]
  34. Joseph JJ, & Golden SH (2016). Cortisol dysregulation: the bidirectional link between stress, depression, and type 2 diabetes mellitus. Ann N Y Acad Sci. doi: 10.1111/nyas.13217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Jurczyk A, Nowosielska A, Przewozniak N, Aryee KE, DiIorio P, Blodgett D, … Bortell R (2016). Beyond the brain: disrupted in schizophrenia 1 regulates pancreatic beta-cell function via glycogen synthase kinase-3beta. Faseb j, 30(2), 983–993. doi: 10.1096/fj.15-279810 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Kavzoglu SO, & Hariri AG (2013). Intracellular Adhesion Molecule (ICAM-1), Vascular Cell Adhesion Molecule (VCAM-1) and E-Selectin Levels in First Episode Schizophrenic Patients. Klinik Psikofarmakoloji Bulteni-Bulletin of Clinical Psychopharmacology, 23(3), 205–214. doi: 10.5455/bcp.20130713091100 [DOI] [Google Scholar]
  37. Keinanen J, Mantere O, Kieseppa T, Mantyla T, Torniainen M, Lindgren M, … Suvisaari J (2015). Early insulin resistance predicts weight gain and waist circumference increase in first-episode psychosis--A one year follow-up study. Schizophr Res, 169(1–3), 458–463. doi: 10.1016/j.schres.2015.11.002 [DOI] [PubMed] [Google Scholar]
  38. Kubaszek A, Pihlajamaki J, Komarovski V, Lindi V, Lindstrom J, Eriksson J, … Finnish Diabetes Prevention, S. (2003). Promoter polymorphisms of the TNF-alpha (G-308A) and IL-6 (C-174G) genes predict the conversion from impaired glucose tolerance to type 2 diabetes: the Finnish Diabetes Prevention Study. Diabetes, 52(7), 1872–1876. [DOI] [PubMed] [Google Scholar]
  39. Leo R, Di Lorenzo G, Tesauro M, Cola C, Fortuna E, Zanasi M, … Romeo F (2006). Decreased plasma adiponectin concentration in major depression. Neurosci Lett, 407(3), 211–213. doi: 10.1016/j.neulet.2006.08.043 [DOI] [PubMed] [Google Scholar]
  40. Li J, Dong YJ, Wu TX, & Tong NW (2016). Differences between Western and Asian type 2 diabetes patients in the incidence of vascular complications and mortality: A systematic review of randomized controlled trials on lowering blood glucose. Journal of Diabetes, 8(6), 824–833. doi: 10.1111/1753-0407.12361 [DOI] [PubMed] [Google Scholar]
  41. Lin PI, & Shuldiner AR (2010). Rethinking the genetic basis for comorbidity of schizophrenia and type 2 diabetes. Schizophr Res, 123(2–3), 234–243. doi: 10.1016/j.schres.2010.08.022 [DOI] [PubMed] [Google Scholar]
  42. McIntyre RS, Mancini DA, Pearce MM, Silverstone P, Chue P, Misener VL, & Konarski JZ (2005). Mood and Psychotic Disorders and Type 2 Diabetes: A Metabolic Triad. Canadian Journal of Diabetes, 29(2), 122–132. [Google Scholar]
  43. Misiak B, Laczmanski L, Sloka NK, Szmida E, Piotrowski P, Loska O, … Frydecka D (2016). Metabolic dysregulation in first-episode schizophrenia patients with respect to genetic variation in one-carbon metabolism. Psychiatry Res, 238, 60–67. doi: 10.1016/j.psychres.2016.01.077 [DOI] [PubMed] [Google Scholar]
  44. Mitchell AJ, Vancampfort D, De Herdt A, Yu W, & De Hert M (2013). Is the prevalence of metabolic syndrome and metabolic abnormalities increased in early schizophrenia? A comparative meta-analysis of first episode, untreated and treated patients. Schizophr Bull, 39(2), 295–305. doi: 10.1093/schbul/sbs082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Modabbernia A, Taslimi S, Brietzke E, & Ashrafi M (2013). Cytokine alterations in bipolar disorder: a meta-analysis of 30 studies. Biol Psychiatry, 74(1), 15–25. doi: 10.1016/j.biopsych.2013.01.007 [DOI] [PubMed] [Google Scholar]
  46. Moher D, Liberati A, Tetzlaff J, Altman DG, & Group P (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol, 62(10), 1006–1012. doi: 10.1016/j.jclinepi.2009.06.005 [DOI] [PubMed] [Google Scholar]
  47. Monji A, Kato TA, Mizoguchi Y, Horikawa H, Seki Y, Kasai M, … Kanba S (2013). Neuroinflammation in schizophrenia especially focused on the role of microglia. Prog Neuropsychopharmacol Biol Psychiatry, 42, 115–121. doi: 10.1016/j.pnpbp.2011.12.002 [DOI] [PubMed] [Google Scholar]
  48. Nyboe L, Vestergaard CH, Moeller MK, Lund H, & Videbech P (2015). Metabolic syndrome and aerobic fitness in patients with first-episode schizophrenia, including a 1-year follow-up. Schizophr Res, 168(1–2), 381–387. doi: 10.1016/j.schres.2015.07.053 [DOI] [PubMed] [Google Scholar]
  49. Perry BI, McIntosh G, Weich S, Singh S, & Rees K (2016). The association between first-episode psychosis and abnormal glycaemic control: systematic review and meta-analysis. Lancet Psychiatry, 3(11), 1049–1058. doi: 10.1016/S2215-0366(16)30262-0 [DOI] [PubMed] [Google Scholar]
  50. Petrikis P, Tigas S, Tzallas AT, Papadopoulos I, Skapinakis P, & Mavreas V (2015). Parameters of glucose and lipid metabolism at the fasted state in drug-naive first-episode patients with psychosis: Evidence for insulin resistance. Psychiatry Res, 229(3), 901–904. doi: 10.1016/j.psychres.2015.07.041 [DOI] [PubMed] [Google Scholar]
  51. Pillinger T, Beck K, Gobjila C, Donocik JG, Jauhar S, & Howes OD (2017). Impaired glucose homeostasis in first-episode schizophrenia: A systematic review and meta-analysis. JAMA Psychiatry. doi: 10.1001/jamapsychiatry.2016.3803 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Rajkumar AP, Horsdal HT, Wimberley T, Cohen D, Mors O, Borglum AD, & Gasse C (2017). Endogenous and Antipsychotic-Related Risks for Diabetes Mellitus in Young People With Schizophrenia: A Danish Population-Based Cohort Study. Am J Psychiatry, 174(7), 686–694. doi: 10.1176/appi.ajp.2016.16040442 [DOI] [PubMed] [Google Scholar]
  53. Roy T, & Lloyd CE (2012). Epidemiology of depression and diabetes: a systematic review. J Affect Disord, 142 Suppl, S8–21. doi: 10.1016/S0165-0327(12)70004-6 [DOI] [PubMed] [Google Scholar]
  54. Ryan MC, Collins P, & Thakore JH (2003). Impaired fasting glucose tolerance in first-episode, drug-naive patients with schizophrenia. Am J Psychiatry, 160(2), 284–289. doi: 10.1176/appi.ajp.160.2.284 [DOI] [PubMed] [Google Scholar]
  55. Saddichha S, Manjunatha N, Ameen S, & Akhtar S (2008). Diabetes and schizophrenia - effect of disease or drug? Results from a randomized, double-blind, controlled prospective study in first-episode schizophrenia. Acta Psychiatr Scand, 117(5), 342–347. doi: 10.1111/j.1600-0447.2008.01158.x [DOI] [PubMed] [Google Scholar]
  56. Saloojee S, Burns JK, & Motala AA (2017). Metabolic syndrome in antipsychotic naive African patients with severe mental illness in usual care. Early Interv Psychiatry. doi: 10.1111/eip.12428 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Scholz CJ, Jacob CP, Buttenschon HN, Kittel-Schneider S, Boreatti-Hummer A, Zimmer M, … Reif A (2010). Functional variants of TSPAN8 are associated with bipolar disorder and schizophrenia. Am J Med Genet B Neuropsychiatr Genet, 153b(4), 967–972. doi: 10.1002/ajmg.b.31057 [DOI] [PubMed] [Google Scholar]
  58. Sengupta S, Parrilla-Escobar MA, Klink R, Fathalli F, Ying Kin N, Stip E, … Joober R (2008). Are metabolic indices different between drug-naive first-episode psychosis patients and healthy controls? Schizophr Res, 102(1–3), 329–336. doi: 10.1016/j.schres.2008.02.013 [DOI] [PubMed] [Google Scholar]
  59. Spelman LM, Walsh PI, Sharifi N, Collins P, & Thakore JH (2007). Impaired glucose tolerance in first-episode drug-naive patients with schizophrenia. Diabet Med, 24(5), 481–485. doi: 10.1111/j.1464-5491.2007.02092.x [DOI] [PubMed] [Google Scholar]
  60. Steen NE, Methlie P, Lorentzen S, Dieset I, Aas M, Nerhus M, … Andreassen OA (2014). Altered systemic cortisol metabolism in bipolar disorder and schizophrenia spectrum disorders. J Psychiatr Res, 52, 57–62. doi: 10.1016/j.jpsychires.2014.01.017 [DOI] [PubMed] [Google Scholar]
  61. Tek C, Kucukgoncu S, Guloksuz S, Woods SW, Srihari VH, & Annamalai A (2016). Antipsychotic-induced weight gain in first-episode psychosis patients: a meta-analysis of differential effects of antipsychotic medications. Early Interv Psychiatry, 10(3), 193–202. doi: 10.1111/eip.12251 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Thakore JH (2004). Metabolic disturbance in first-episode schizophrenia. Br J Psychiatry Suppl, 47, S76–79. [DOI] [PubMed] [Google Scholar]
  63. Turan C, Kesebir S, & Suner O (2014). Are ICAM, VCAM and E-selectin levels different in first manic episode and subsequent remission? J Affect Disord, 163, 76–80. doi: 10.1016/j.jad.2014.03.052 [DOI] [PubMed] [Google Scholar]
  64. van Nimwegen LJM, Storosum JG, Blumer RME, Allick G, Venema HW, de Haan L, … Sauerwein HP (2008). Hepatic insulin resistance in antipsychotic naive schizophrenic patients: Stable isotope studies of glucose metabolism. Journal of Clinical Endocrinology & Metabolism, 93(2), 572–577. doi: 10.1210/jc.2007-1167 [DOI] [PubMed] [Google Scholar]
  65. van Welie H, Derks EM, Verweij KH, de Valk HW, Kahn RS, & Cahn W (2013). The prevalence of diabetes mellitus is increased in relatives of patients with a non-affective psychotic disorder. Schizophr Res, 143(2–3), 354–357. doi: 10.1016/j.schres.2012.11.011 [DOI] [PubMed] [Google Scholar]
  66. Vancampfort D, Correll CU, Galling B, Probst M, De Hert M, Ward PB, … Stubbs B (2016). Diabetes mellitus in people with schizophrenia, bipolar disorder and major depressive disorder: a systematic review and large scale meta-analysis. World Psychiatry, 15(2), 166–174. doi: 10.1002/wps.20309 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Venkatasubramanian G, Chittiprol S, Neelakantachar N, Naveen MN, Thirthall J, Gangadhar BN, & Shetty KT (2007). Insulin and insulin-like growth factor-1 abnormalities in antipsychotic-naive schizophrenia. Am J Psychiatry, 164(10), 1557–1560. doi: 10.1176/appi.ajp.2007.07020233 [DOI] [PubMed] [Google Scholar]
  68. Wani RA, Dar MA, Margoob MA, Rather YH, Haq I, & Shah MS (2015). Diabetes mellitus and impaired glucose tolerance in patients with schizophrenia, before and after antipsychotic treatment. J Neurosci Rural Pract, 6(1), 17–22. doi: 10.4103/0976-3147.143182 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Watson S, Gallagher P, Ritchie JC, Ferrier IN, & Young AH (2004). Hypothalamic-pituitary-adrenal axis function in patients with bipolar disorder. Br J Psychiatry, 184, 496–502. [DOI] [PubMed] [Google Scholar]
  70. Wells GS,B; O’Connell B; Peterson J; Welch V; Losos M; Tugwell P. (2009). The Newcastle-Ottawa scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. Retrieved from http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
  71. Whiting DR, Guariguata L, Weil C, & Shaw J (2011). IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Research and Clinical Practice, 94(3), 311–321. doi: 10.1016/j.diabres.2011.10.029 [DOI] [PubMed] [Google Scholar]
  72. Wu X, Huang Z, Wu R, Zhong Z, Wei Q, Wang H, … Zhang J (2013). The comparison of glycometabolism parameters and lipid profiles between drug-naive, first-episode schizophrenia patients and healthy controls. Schizophr Res, 150(1), 157–162. doi: 10.1016/j.schres.2013.07.051 [DOI] [PubMed] [Google Scholar]
  73. Yamagata AS, Mansur RB, Rizzo LB, Rosenstock T, McIntyre RS, & Brietzke E (2016). Selfish brain and selfish immune system interplay: A theoretical framework for metabolic comorbidities of mood disorders. Neurosci Biobehav Rev, 72, 43–49. doi: 10.1016/j.neubiorev.2016.11.010 [DOI] [PubMed] [Google Scholar]
  74. Yildirim O, Canan F, Tosun M, Kayka N, Tuman TC, Alhan C, & Alcelik A (2014). Plasma Omentin Levels in Drug-Free Patients with Schizophrenia. Neuropsychobiology, 69(3), 159–164. doi: 10.1159/000360736 [DOI] [PubMed] [Google Scholar]
  75. Zhang XY, Chen DC, Tan YL, An HM, Zunta-Soares GB, Huang XF, & Soares JC (2015). Glucose disturbances in first-episode drug-naive schizophrenia: Relationship to psychopathology. Psychoneuroendocrinology, 62, 376–380. doi: 10.1016/j.psyneuen.2015.09.005 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp info
NIHMS991112-supplement-Supp_info.docx (526.9KB, docx)

RESOURCES