ORIGINAL RESEARCH published: 25 May 2020 doi: 10.3389/fpsyt.2020.00455 Glycated Haemoglobin Is Associated With Poorer Cognitive Performance in Patients With Recent-Onset Psychosis Itziar Montalvo 1, Alexandre González-Rodrı́guez 1, Ángel Cabezas 2, Alfonso Gutiérrez-Zotes 2, Montse Solé 2, Maria José Algora 2, Laura Ortega 3, Lourdes Martorell 2, Vanessa Sánchez-Gistau 2, Elisabet Vilella 2 and Javier Labad 1* 1 Department of Mental Health, Parc Taulı´ Hospital Universitari, Institut d’Investigació Sanitària Parc Taulı´ (I3PT), Universitat Autònoma de Barcelona, CIBERSAM, Sabadell, Spain, 2 Hospital Universitari Institut Pere Mata, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili, CIBERSAM, Reus, Spain, 3 Nursing Department, Universitat Rovira i Vigili, Tarragona, Spain Background: Glucose abnormalities and cognitive alterations are present before the onset of schizophrenia. We aimed to study whether glucose metabolism parameters are Edited by: associated with cognitive functioning in recent-onset psychosis (ROP) patients while Grazia Rutigliano, University of Pisa, Italy adjusting for hypothalamic-pituitary adrenal (HPA) axis measures. Reviewed by: Methods: Sixty ROP outpatients and 50 healthy subjects (HS) were studied. Cognitive Domenico Tricò, function was assessed with the MATRICS Consensus Cognitive Battery. Glycated University of Pisa, Italy Zhiqiang Li, haemoglobin (HbA1c), glucose, insulin, and C-peptide levels were determined in Qingdao University, China plasma. The HOMA-insulin resistance index was calculated. Salivary samples were *Correspondence: obtained at home on another day to assess the cortisol awakening response and Javier Labad jlabad@tauli.cat cortisol levels during the day. Univariate analyses were conducted to explore the association between glucose metabolism parameters and cognitive tasks. For those Specialty section: parameters that were more clearly associated with the cognitive outcome, multiple linear This article was submitted to Schizophrenia, regression analyses were conducted to adjust for covariates. Each cognitive task was a section of the journal considered the dependent variable. Covariates were age, sex, education level, diagnosis, Frontiers in Psychiatry antipsychotic and benzodiazepine treatment, body mass index (BMI), smoking, and HPA Received: 25 February 2020 axis measures. Potential interactions between diagnosis and glucose parameters were Accepted: 05 May 2020 Published: 25 May 2020 tested. Citation: Results: There were no significant differences in HPA axis measures or glucose Montalvo I, González-Rodrı´guez A, Cabezas Á, Gutiérrez-Zotes A, Solé M, parameters, with the exception of C-peptide (that was higher in ROP patients), Algora MJ, Ortega L, Martorell L, between groups. ROP patients had a lower performance than HS in all cognitive tasks Sánchez-Gistau V, Vilella E and (p < 0.01 for all tasks). Of all glucose metabolism parameters, HbA1c levels were more Labad J (2020) Glycated Haemoglobin Is Associated With Poorer Cognitive clearly associated with cognitive impairment in cognitive tasks dealing with executive Performance in Patients With functions and visual memory in both ROP patients and HS. Multivariate analyses found a Recent-Onset Psychosis. Front. Psychiatry 11:455. significant negative association between HbA1c and cognitive functioning in five cognitive doi: 10.3389/fpsyt.2020.00455 tasks dealing with executive functions, visual memory and attention/vigilance (a ROP Frontiers in Psychiatry | www.frontiersin.org 1 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis diagnosis by HbA1c negative interaction was found in this latter cognitive domain, suggesting that HBA1c levels are associated with impaired attention only in ROP patients). Conclusions: Our study found that HbA1c was negatively associated with cognitive functioning in both ROP patients and HS in tasks dealing with executive functions and visual memory. In ROP patients, HbA1c was also associated with impaired attention. These results were independent of BMI and measures of HPA axis activity. Keywords: glucose, glycated haemoglobin, cognition, early psychosis, cortisol INTRODUCTION insulin concentration, insulin resistance, and glucose-lowering treatment) and cognitive function in people with type 2 diabetes Cognitive alterations are well-known predictors of social without dementia, high HbA1c and glucose variability were functioning in people with schizophrenia and related psychotic negatively associated with cognitive function. HbA1c is a disorders (1). These cognitive alterations are present at early promising biomarker for cognitive impairment because it is stages of the psychotic illness, even before the development of also associated with poorer cognitive abilities in people without positive psychotic symptoms (delusions, hallucinations) (2). diabetes (17, 22). A recent study suggests that HbA1c is Biological mechanisms explaining these cognitive deficits are associated to both cognitive performance and white matter complex and include the potential role of hypothalamic- integrity in healthy young adults (22). pituitary-adrenal (HPA) axis hormones (3, 4), thyroid Few studies have explored the potential relationship between hormones (5, 6), prolactin (7, 8), inflammatory markers (9, 10) glucose metabolism indices and cognitive functioning in patients and the genetic background (11). with psychotic disorders. In a study conducted in first-episode In our current study, we aimed to explore whether glucose drug-naïve patients with schizophrenia, glucose intolerance metabolism parameters might contribute to the cognitive (measured with a 75 g oral glucose tolerance test) was impairment of people with recent-onset psychosis (ROP). associated with more negative symptoms and poorer social Previous studies including drug-naïve first-episode psychosis cognition, but not with poorer neurocognitive performance and healthy controls have reported increased glucose and (23). In another study that measured HbA1c, this parameter insulin resistance (12) and impaired glucose tolerance (13), was associated with poorer global cognition and attention in men suggesting that glucose-related parameters may be altered in (but not women) with schizophrenia (24). Insulin resistance has patients with psychosis at the early stages of the illness. Previous been associated with alterations in dopaminergic reward systems studies have also reported an increased prevalence of type 2 and homeostatic signals affecting food intake, glucose diabetes in the parents of people with non-affective psychosis metabolism, body weight, and cognitive performance (25), (14). It was initially thought that this association may be due to being a potential moderator of the cognitive outcome in shared environmental or genetic risk factors, or both. However, a patients with psychotic disorders. Although several studies recent study (15) exploring the association between polygenic have reported an association between diabetes and cognition risk score of schizophrenia and glycated haemoglobin (HbA1c) on schizophrenia, few investigations have explored the role of while adjusting for polygenic risk score of type 2 diabetes, and glucose parameters on cognition in patients with early psychosis. clinical and demographic covariables suggests that the We aimed to explore the previous hypothesis while adjusting mechanisms of hyperglycemia or diabetes are at least partly for HPA axis measures, as some indices, such as a blunted independent from genetic predisposition to schizophrenia. cortisol awakening response (CAR) (3, 26, 27) and elevated It is also known that comorbidity with diabetes mellitus is cortisol diurnal levels during the day (26), have been reported associated with more severe cognitive deficits in schizophrenia to be associated with a poorer cognitive outcome in people with (16). Type 2 diabetes is a risk factor for cognitive decline (17), ROP. Moreover, elevated glucocorticoids contribute to the mild cognitive impairment (18), and progression to dementia cognitive impairment of patients with type 2 diabetes (28). (19). Although the exact pathophysiology of mild cognitive Taking into account that HbA1c has been associated with impairment in type 2 diabetes is unclear, many studies suggest poorer cognitive performance in both patients with that several coexisting risk factors contribute to the cognitive schizophrenia (24) and healthy individuals (22), we impairment (20): chronic hyperglycaemia, diabetic hypothesized that HbA1c would be associated with poorer complications (macrovascular and microvascular disease), cognitive performance in both people with ROP and healthy inflammatory reaction and advanced glycation end products, individuals. We also aimed to conduct exploratory analyses and psychological status (e.g. depressive symptoms). In a regarding the contribution of other glucose-related parameters systematic review (21) that included 86 studies exploring the (fasting glucose, c-peptide, insulin resistance) on poorer role of glucose regulation (glycaemia, hypoglycaemic events, cognitive functioning. Frontiers in Psychiatry | www.frontiersin.org 2 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis METHODS Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index was calculated using the formula HOMA- Sample IR = [insulin (µUI/mL) x glucose (mg/dL)]/405. Sixty ROP outpatients and 50 healthy subjects (HS) were studied. Salivary samples were obtained at home on another day with All patients (aged between 18 and 35 years) were attending the Salivette® tubes to assess the cortisol awakening response Early Intervention Service for Psychosis from Reus (Hospital (calculated as the area under the curve with respect to the Universitari Institut Pere Mata, Spain) had a DSM-IV diagnosis increase, considering three samples: awakening, 30’ post- of a psychotic disorder [schizophreniform disorder (n=14); awakening, and 60’ post-awakening) and cortisol levels during schizophrenia (n=10); schizoaffective disorder (n=8) or a the day (calculated as the area under the curve with respect to the psychotic disorder not otherwise specified (n=28)]. All patients ground, considering 5 samples: awakening, 30’ post-awakening, had a duration of illness of <3 years (65% were patients with first- 60’ post-awakening, 10:00 a.m., and 11:00 p.m.). Both formulas episode psychosis). A control population of 50 HS matched by were computed using the trapezoid formula (34). A full sex and age was recruited from the community using explanation of the processing of the samples and cortisol advertisements. The sample of the study belongs to a project determination with a high-sensitivity enzyme-linked aiming to study the relationship between hormones and immunosorbent assay (ELISA) kit has been described cognitive abilities in early psychosis. For this reason, elsewhere (3). participants of our study participated in a previous study that tested a different hypothesis focused on HPA axis hormones (3). Statistical Analyses The exclusion criteria were severe neurological disease or mental We used SPSS v 23.0 for conducting statistical analyses. Cortisol retardation; pregnancy; language difficulties; visual impairment; measures were transformed with a Box-Cox transformation (35), alcohol, heroin or cocaine dependence; or treatment and the Trail Making Test (part A) was log transformed (ln) to with glucocorticoids. reduce skewness. Chi-squared tests and T-tests were used to The research protocol was approved by the Ethics Committee compare categorical and continuous data between both of Hospital Universitari Sant Joan, and all participants provided diagnostic groups. Non-parametric tests (Mann Whitney U written informed consent after having received a full explanation test) were used to compare ordinal variables or continuous of the study. measures that were skewed (e.g. insulin, c-peptide). Pearson correlation analyses (and Spearman when needed) were used Clinical Assessment to explore associations between continuous variables. A p value All patients were interviewed by an experienced psychiatrist using <0.05 (two-tailed) was considered to be significant. the Schedules for Clinical Assessment in Neuropsychiatry (29). As HbA1c was considered the glucose-related parameter to be The OPCRIT checklist version 4.0 (available at http://sgdp.iop.kcl. studied in our main hypothesis, we verified that this value ac.uk/opcrit/) was used to obtain DSM-IV diagnoses. The severity followed a normal distribution and checked for potential of positive, negative and general symptoms was assessed with the outliers with the 1.5 quartile (Q) rule for outliers (36). With Positive and Negative Syndrome Scale (PANSS) (30, 31) to assess this definition, any observation is a suspected outlier if it falls the severity of psychotic symptoms. more than 1.5 x interquartile range (IQR) above the third The Spanish version of the MATRICS Consensus Cognitive quartile or below the first quartile. In our sample, the Battery (MCCB) was used to assess neurocognitive functioning distribution for HbA1c values was: minimum value= 4.6, Q1 = (32), and it includes 10 cognitive tests assessing 7 cognitive 4.9, Q2 (median)= 5.1, Q3 (5.3), maximum value 5.8, IQR= 0.4. domains: processing speed, attention and vigilance, working Therefore, none of the values were considered outliers because memory, verbal learning, visual learning, reasoning and they were within the limits 1.5xIQR (lower interval: 4.3, upper problem solving, and social cognition. interval: 5.9). Sociodemographic and clinical variables were obtained in a Although our main hypothesis was conducted with multiple semi-structured interview. Substance use was recorded as the linear regression analyses, we first conducted an exploratory and consumption of alcohol (standard units/day), tobacco (cigarettes/ univariate analysis to test the associations between different day), and cannabis (joints/day). Current psychopharmacological glucose-related parameters and cognitive outcomes. We also treatment was recorded during the neuropsychological assessment, included exploratory correlational analyses between cognitive as described previously (3). The dose of antipsychotics scores. These exploratory analyses were not adjusted for multiple was converted to chlorpromazine equivalents following an comparisons following some recommendations that indicate that international consensus of antipsychotic dosing (33). is it not strictly necessary to correct for multiple testing in Weight, height, waist circumference, and blood pressure were analyses that are exploratory in nature (37). Multiple linear assessed by physical examination. Body mass index (BMI) was regression analyses were conducted for testing the association calculated with the formula weight (kg)/height (m)2. between HbA1c and cognitive variable while adjusting for covariates. Several multiple linear regression analyses were Biochemical Measures conducted, considering each cognitive task as the dependent A fasting morning blood analysis (between 8:30 a.m. and 9:30 variable. HbA1c was considered the main independent variable. a.m.) was obtained by antecubital venepuncture. HbA1c, glucose, We avoided the inclusion of different glucose metabolism insulin, and C-peptide were determined in plasma. The parameters in the same equation because they were highly Frontiers in Psychiatry | www.frontiersin.org 3 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis correlated. The following covariates were included in each RESULTS equation with the enter procedure: age, sex, education level, diagnosis, antipsychotic and benzodiazepine treatment, BMI, Clinical and hormonal variables from the sample are described in smoking, and HPA axis measures. Potential interactions Table 1. Both groups were well matched in age and sex, although between diagnosis and HbA1 c were tested, and those ROP patients had a lower education status and reported more significant interactions were included in the final model. smoking and alcohol consumption. In relation to glucose-related parameters, C-peptide concentrations were higher in ROP Sample Size and Power Analysis patients than in HS. There were no significant differences in G* Power 3.1.9.4. was used for sample size and power HPA axis measures between groups. calculations. The original sample was calculated for detecting a ROP patients had a lower performance in all cognitive tasks moderate effect size (f2 = 0.2) with multiple linear regression than HS (Table 2). The correlation matrix between cognitive analyses, considering an alpha error of 0.05 and a beta error of measures in all participants is described in Table 3. 0.15 (statistical power of 85%), and 12 predictors. The needed Of all glucose metabolism parameters, HbA1c levels were sample size was 108. It is important to note that our sample is more clearly associated with cognitive impairment in cognitive small for detecting small effects. Moreover, in the stratified tasks dealing with executive functions and visual memory in both analysis by diagnosis (e.g. correlation analyses), the statistical ROP patients and HS (Table 4). power can decrease: the statistical power for detecting moderate A multivariate analysis conducted in all participants (ROP effect sizes (r= 0.3) was 59% for healthy individuals and 67% for patients and HS) found a significant negative association ROP patients. between HbA1c and cognitive functioning in five cognitive TABLE 1 | Clinical characteristics and hormonal measures from the sample. HS ROP patients p value N= 50 N=60 Female sex, N (%) 22 44% 21 35% 0.335 Age (years) 23.8 4.8 24.5 5.4 0.465 Education level (years of study) 13.4 2.7 11.3 2.8 <0.001 Smoking, N (%) 10 20% 41 68.3% <0.001 Smoking (cig/day), all participants 1.6 4.4 9.0 9.6 <0.001 Smoking (cig/day), only smokers 8.0 7.0 13.1 9.0 0.101 Cannabis use, N (%) No 38 76% 43 71.7% 0.215 Sporadic 10 20% 9 15% Continuous 2 4% 8 13.3% Alcohol consumption, N (%) No 5 10% 27 45% <0.001 Sporadic 44 88% 28 46.7% Continuous 1 2% 5 8.3% BMI (kg/m2) 22.5 3.2 24.1 4.1 0.053 Antipsychotic treatment: 0.0 0.0 371.1 334.0 <0.001 Chlorpromazine equivalents (mg/day) Benzodiazepine treatment: 0.0 0.0 2.6 7.7 0.021 Diazepam equivalents (mg/day) Glucose metabolism parameters Glucose (mg/dL) 78.6 11.2 78.7 11.1 0.956 Insulin (mIU/mL) 6.6 0 to 22.9 9.5 0 to 114 0.595 C-peptide (mg/L) 1.3 0.6 to 4.2 1.6 0.7 to 12.7 0.003 HbA1c (%) 5.1 0.3 5.1 0.3 0.250 HOMA-IR 1.4 0 to 4.9 1.3 0 to 26.18 0.802 HPA axis measures Cortisol at awakening (nmol/L) 14.7 9.0 13.0 8.6 0.381 Cortisol 30’ post-awakening (nmol/L) 23.8 13.4 20.3 10.7 0.342 Cortisol 60’ post-awakening (nmol/L) 21.0 12.8 16.3 7.5 0.234 10:00 a.m. 12.5 7.4 12.0 6.4 0.971 11:00 p.m. 2.7 2.1 3.0 3.0 0.971 CAR (AUCi) 39.7 63.6 40.5 53.7 0.942 Cortisol during the day (AUCg) 2049.6 837.3 2082.3 733.4 0.834 Data are mean (SD), median (range) or N (%). Cortisol raw data are shown. However, p values were obtained using transformed cortisol values (Box-Cox transformation). BMI, Body mass index; HbA1c, Glycated haemoglobin; HOMA-IR, Homeostatic Model Assessment for Insulin Resistance; HPA, Hypothalamic-pituitary-adrenal; CAR, Cortisol awakening response; AUCi, Area under the curve (calculated with respect to the increase); AUCg, Area under the curve (calculated with respect to the ground). Significant associations (p < 0.05) are represented in bold. Frontiers in Psychiatry | www.frontiersin.org 4 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis TABLE 2 | Cognitive functioning by diagnostic group. HS ROP patients p value N=50 N=60 Mean SD Mean SD Verbal learning and memory HVLT-R 27.5 3.8 22.8 4.9 <0.001 Visual learning and memory BVMT-R 27.0 5.9 19.6 7.2 <0.001 Working memory WMS-III-SS (nonverbal) 16.2 2.9 14.2 3.7 0.002 LNS (verbal) 14.2 2.9 12.0 2.3 <0.001 Processing speed TMT-A† (seconds) 24.7 8.5 38.2 13.4 <0.001 BACS SC 61.9 9.6 45.9 12.3 <0.001 Category Fluency 24.1 5.1 18.3 5.2 <0.001 Reasoning and problem solving NAB Mazes 27.0 5.9 19.6 7.2 <0.001 Attention/vigilance CPT-IP 2.7 0.6 2.0 0.7 <0.001 Social cognition MSCEIT-ME 94.4 9.2 86.8 9.8 <0.001 † As this cognitive test is measured in seconds, higher scores reflect poorer cognitive performance. HVLT-R, Hopkins Verbal Learning Test-Revised; BVMT-R, Brief Visuospatial Memory Test-Revised; WMS-III-SS, Corsi Block-Tapping Test; Weschler Memory Scale (3rd edition) spatial span; LNS, Letter Number Span; TMT-A, Trail Making Test part A; BACS-SC, Brief Assessment of Cognition in Schizophrenia-Symbol Coding; NAB, Neuropsychological Assessment Battery; CPT-IP, Continuous Performance Test – Identical Pairs; MSCEIT-ME, Mayer-Salovey-Caruso Emotional Intelligence Test – Managing emotions. Significant associations (p < 0.05) are represented in bold. tasks dealing with executive functions, visual memory and attention and vigilance, but this pattern does not apply to HS. attention/vigilance (Table 5). A diagnosis by HbA1 c This interaction is also described in Figure 1. As it is observed in interaction was found in this latter cognitive domain, which this figure, the interaction is driven by higher HbA1c values. means that the pattern in the relationship between HbA1c and Although there were no outliers in our sample, we repeated a attention/vigilance differs between ROP patients and HS: in ROP sensitivity analysis excluding the two higher values (HbA1c= patients, higher HbA1c levels are associated with impaired 5.8%) to explore whether the interaction was influenced for these TABLE 3 | Pearson's correlations studying the relationship between cognitive tasks in 110 participants. HVLT-R BVMT-R WMS-III SS LNS TMT-A† BACS SC Fluency NAB Mazes CPT-IP MSCEIT-ME HVLT-R r 1 0.596 0.469 0.539 -0.601 0.675 0.594 0.256 0.504 0.401 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 .007 < 0.001 < 0.001 BVMT-R r 0.596 1 0.599 0.554 -0.622 0.690 0.624 0.549 0.491 0.168 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.086 WMS-III SS r 0.469 0.599 1 0.387 -0.546 0.504 0.417 0.553 0.376 0.300 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.002 LNS r 0.539 0.554 0.387 1 -0.536 0.605 0.473 0.367 0.610 0.286 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.004 TMT-A† r -0.601 -0.622 -0.546 -0.536 1 -0.707 -0.559 -0.545 -0.573 -0.308 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 .001 BACS SC r 0.675 0.690 0.504 0.605 -0.707 1 0.653 0.494 0.635 0.312 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.001 Fluency r 0.594 0.624 0.417 0.473 -0.559 0.653 1 0.495 0.519 0.220 p value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.024 NAB Mazes r 0.256 0.549 0.553 0.367 -0.545 0.494 0.495 1 0.447 0.173 p value 0.007 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.078 CPT-IP r 0.504 0.491 0.376 0.610 -0.573 0.635 0.519 0.447 1 0.294 value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.002 MSCEIT-ME r 0.401 0.168 0.300 0.286 -0.308 0.312 0.220 0.173 0.294 1 p value < 0.001 0.086 0.002 0.004 0.001 0.001 0.024 0.078 0.002 † As TMT-A is measured in seconds, greater scores in this variable reflect poorer cognitive performance. For this reason, this variable showed negative correlations with other cognitive tasks. The log transformed variable (ln TMT-A) was used. HVLT-R, Hopkins Verbal Learning Test-Revised; BVMT-R, Brief Visuospatial Memory Test-Revised; WMS-III-SS, Corsi Block-Tapping Test; Weschler Memory Scale (3rd edition) spatial span; LNS, Letter Number Span; TMT-A, Trail Making Test part A; BACS-SC, Brief Assessment of Cognition in Schizophrenia-Symbol Coding; NAB, Neuropsychological Assessment Battery; CPT-IP, Continuous Performance Test – Identical Pairs; MSCEIT-ME, Mayer-Salovey-Caruso Emotional Intelligence Test – Managing emotions. Frontiers in Psychiatry | www.frontiersin.org 5 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis TABLE 4 | Correlations between glucose-related parameters and cognitive tasks: Stratified analyses by diagnosis. HS ROP patients HbA1c Glucose C-peptide Insulin HOMA-IR HbA1c Glucose C-peptide Insulin HOMA-IR HVLT-R r 0.012 -0.080 -0.014 -0.152 -0.160 -0.076 0.120 0.023 0.076 0.063 p value 0.935 0.582 0.921 0.292 0.271 0.567 0.366 0.863 0.567 0.634 BVMT-R r -0.350 -0.238 0.000 -0.169 -0.184 -0.262 -0.002 -0.031 0.033 0.028 p value 0.013 0.096 0.999 0.242 0.205 0.047 0.985 0.817 0.806 0.835 WMS-III SS r -0.295 -0.285 -0.155 -0.395 -0.370 -0.218 0.052 -0.343 -0.102 -0.072 p value 0.037 0.045 0.283 0.005 0.009 0.097 0.695 0.008 0.442 0.590 LNS r -0.157 -0.092 0.055 -0.231 -0.258 -0.348 -0.134 -0.128 -0.104 -0.102 p value 0.276 0.524 0.707 0.106 0.073 0.010 0.332 0.357 0.454 0.461 TMT-A r 0.135 0.047 -0.050 0.091 0.081 0.330 -0.046 0.199 0.016 -0.008 p value 0.349 0.747 0.732 0.528 0.579 0.011 0.729 0.131 0.901 0.955 BACS SC r -0.329 -0.250 -0.152 -0.351 -0.375 -0.176 0.048 -0.002 0.055 0.050 p value 0.020 0.080 0.292 0.013 0.008 0.182 0.721 0.986 0.677 0.706 Fluency r -0.002 -0.070 0.076 -0.215 -0.202 -0.106 0.214 -0.044 0.061 0.073 p value 0.987 0.629 0.598 0.134 0.165 0.426 0.107 0.745 0.648 0.585 NAB Mazes r -0.243 -0.093 0.151 0.020 0.010 -0.425 -0.067 -0.174 0.021 0.050 p value 0.089 0.520 0.295 0.890 0.944 0.001 0.620 0.191 0.877 0.712 CPT-IP r -0.037 -0.042 -0.123 -0.248 -0.265 -0.262 0.049 -0.015 0.138 0.145 p value 0.800 0.775 0.397 0.082 0.066 0.047 0.717 0.912 0.303 0.277 MSCEIT-ME r -0.252 -0.268 -0.038 -0.295 -0.323 -0.137 0.036 -0.155 0.024 0.018 p value 0.078 0.060 0.793 0.037 0.024 0.318 0.797 0.259 0.863 0.897 HVLT-R, Hopkins Verbal Learning Test-Revised; BVMT-R, Brief Visuospatial Memory Test-Revised; WMS-III-SS, Corsi Block-Tapping Test; Weschler Memory Scale (3rd edition) spatial span; LNS, Letter Number Span; TMT-A, Trail Making Test part A; BACS-SC, Brief Assessment of Cognition in Schizophrenia-Symbol Coding; NAB, Neuropsychological Assessment Battery; CPT-IP, Continuous Performance Test – Identical Pairs; MSCEIT-ME, Mayer-Salovey-Caruso Emotional Intelligence Test – Managing emotions. Pearson’s correlation analyses were used for exploring associations between HbA1c and glucose measures and cognitive tasks. Spearman’s correlation analyses were used for exploring associations between c-peptide, insulin and HOMA-IR, and cognitive tasks. values, and this was the case because the interaction term lost its contributed to a poorer cognitive performance in domains related to significance when these two higher values were excluded from processing speed, executive functions and visual memory in both the analyses. the ROP patients and the HS, whereas it was associated with poorer attention and vigilance only in the ROP group. With the main aim of a better understanding of the molecular, DISCUSSION cellular, and other system disturbances in patients with schizophrenia, biomarkers of diagnosis, prognosis, or treatment In our study that explored whether glucose metabolism parameters response have been recommended (38). The study of glucose may contribute to the explanation, at least in part, of the cognitive metabolism parameters in this population is of special interest deficits of individuals diagnosed with a ROP, we found that HbA1c since patients with schizophrenia have a three-fold risk of TABLE 5 | Multiple linear regression analyses exploring the relationship between HbA1c and cognitive abilities. Unadjusted model Final model (adjusted for covariates† and interactions between HbA1c and diagnosis) R2 b p value R2 b p value Significant interactions HVLT-R 0.0002 0.016 0.871 0.465 -0.014 0.862 None BVMT-R 0.038 -0.194 0.043 0.486 -0.189 0.017 None WMS-III SS 0.041 -0.202 0.034 0.371 -0.143 0.100 None LNS 0.029 -0.169 0.077 0.292 -0.170 0.065 None TMT-A 0.02 0.143 0.137 0.474 0.160 0.044 None BACS SC 0.015 -0.124 0.197 0.617 -0.136 0.044 None Category fluency 0.0001 0.010 0.914 0.417 -0.014 0.864 None NAB Mazes 0.082 -0.287 0.002 0.407 -0.290 0.001 None CPT-IP 0.008 -0.089 0.355 0.489 0.021 0.816 ROP x HbA1c: b= -1.888; p=0.016 MSCEIT-ME 0.015 -0.121 0.208 0.337 -0.099 0.266 None b, Standardized beta regression coefficient (for HbA1c); HVLT-R, Hopkins Verbal Learning Test-Revised; BVMT-R, Brief Visuospatial Memory Test-Revised; WMS-III-SS, Corsi Block- Tapping Test; Weschler Memory Scale (3rd edition) spatial span; LNS, Letter Number Span; TMT-A, Trail Making Test part A; BACS-SC, Brief Assessment of Cognition in Schizophrenia- Symbol Coding; NAB, Neuropsychological Assessment Battery; CPT-IP, Continuous Performance Test – Identical Pairs; MSCEIT-ME, Mayer-Salovey-Caruso Emotional Intelligence Test – Managing emotions. † Covariates: age, sex, education level, diagnosis, antipsychotic and benzodiazepine treatment, BMI, smoking, cortisol at awakening, cortisol awakening response, cortisol levels during the day (AUCg). Significant associations (p < 0.05) are represented in bold. Frontiers in Psychiatry | www.frontiersin.org 6 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis FIGURE 1 | Scatterplot graph of the association between glycated haemoglobin and attention in patients with a recent-onset psychosis and healthy subjects. ROP, Recent-onset psychosis; HS, Healthy subjects. diabetes compared to the general population (39), and it gives us the Other studies (23) have reported an association between glucose opportunity to investigate pathogenic processes underlying both intolerance and more severe negative symptoms and poorer disturbances, with the aim of discovering new treatment strategies. social cognition, although no associations were found for Biomarkers of schizophrenia have been widely used in recent neurocognitive performance. There is also a meta-analysis years. They are frequently divided into two groups: peripheral and suggesting that type 2 diabetes is associated with more severe central biomarkers. The central nervous system and the periphery cognitive deficits in schizophrenia (16). Interestingly, in a meta- are strongly connected, a fact that has revealed the relevance of analysis (21) exploring different glucose-related biomarkers and blood-based parameters as biomarkers in schizophrenia. Once cognitive impairment in people with type 2 diabetes, high HbA1c again, several classifications for biomarkers have examined was negatively associated with cognitive function. Our study is in molecules modulating brain functions. Biomarkers have then been accordance with this last study, as we found a greater association divided into inflammatory biomarkers, neuroendocrine biomarkers, for HbA1c than for other fasting-related glucose parameters. neurotransmitters (well-documented and deeply understood), and These results are seemingly in agreement with a recent study metabolic biomarkers (38). The last may include indicators of investigating glucose metabolic parameters associated with metabolic syndrome or insulin resistance (13) that have been cognition and white matter microstructure in healthy young proven to discriminate between patients with or without populations (22). HbA1c levels (even under the diagnostic values metabolic syndrome. Furthermore, for many years, increased for diabetes mellitus) were inversely correlated with measures of glucose concentrations, insulin resistance, and impaired glucose cognitive performance. Moreover, this low-grade HbA1 c tolerance (13, 40) have been reported to be present in drug-naïve variation negatively affected white matter integrity, that also first-episode psychosis patients compared to HS. However, in our correlated with cognitive function. This study supports our study, we did not find significant differences in most glucose-related findings related to the transdiagnostic relationship between parameters, except for C-peptide between ROP patients and HS. HbA1c and cognitive function, as associations between these In our study, in terms of all glucose parameters, HbA1c levels measures were observed in both ROP patients and healthy controls. were found to be associated with poorer cognitive performance, In contrast with other cognitive domains, attention was particularly in those cognitive tasks assessing executive function negatively associated with HbA1c in ROP patients but not in HS. and visual memory in both groups, ROP patients and HS. These It is not clear why a distinct pattern could exist between ROP findings agree with a recent study carried out by Zhang et al. (24), patients and HS in this particular domain. Previous studies that who found this parameter to be correlated with poorer global have measured allostatic load, an index that reflects systemic cognition and attention in men suffering from schizophrenia. biological dysregulations including glucose homeostasis Frontiers in Psychiatry | www.frontiersin.org 7 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis parameters (glucose and insulin), have reported associations with system has an important role in glucose homeostasis control poorer attention in ROP patients but not in HS (41). In another because the dopaminergic and insulin signalling pathways double-blind, placebo-controlled experimental study that assessed influence each other (53–55) and that both central nervous the effects of multiple-dose oral glucose administration on cognition system insulin and striatal dopamine can regulate peripheral in younger and older patients with schizophrenia and HS, a decrease glucose homeostasis (56). Given the central importance of in attentional performance at the 75 g glucose dose, when compared dopaminergic dysregulation, cognitive deficits, and metabolic to placebo, was found in younger patients with schizophrenia (42). dysfunction in schizophrenia (57–59), the potential role of These findings suggest that glucose metabolism parameters might central nervous system insulin signalling in the differentially affect ROP patients and HS in the attention and pathophysiology of schizophrenia is an interesting field to vigilance domains. However, it is also important to mention that be explored. This knowledge could help in the exploration and this interaction was driven by higher HbA1c values, as the development of future therapeutic strategies. interaction lost its significance when analyses were restricted to For most cognitive domains, with the exception of attention people with HbA1c below 5.8%. The HbA1c range of our sample and vigilance, the association between HbA1c, and cognition was was also low, which limits the possibility of finding associations not specific for patients with ROP. Moreover, ROP patients and between cognitive outcomes and this glucose-related biomarker. HS had similar HbA1c levels, which were in the normal range. Further studies might improve this issue by including a sample with These findings suggest that subtle differences in HbA1c could a greater proportion of patients with glucose intolerance. This can have a significant impact on cognitive processing independent of be achieved by recruiting patients with a longer duration of the diagnosis. As our study has a cross-sectional design and includes illness, because pre-diabetes and diabetes might increase over time. psychotic patients who are at early stages of the disease, our study As only 16% of patients with first episode psychosis show abnormal does not allow us to infer causality. Future longitudinal studies glucose tolerance (13), the recruitment of patients with psychotic are needed to explore whether longitudinal changes in glucose disorders at early stages of the illness might explain the narrow metabolic parameters (mainly HbA1c) could contribute to range of HbA1c levels in our sample. cognitive impairment in patients with schizophrenia. This is an The negative correlation between HbA1c and cognitive important hypothesis to be tested, as chronic antipsychotic performance found in our study may be partially explained by the treatment is associated with weight gain and metabolic fact that cognitive tasks associated with HbA1c are mainly those abnormalities, including the risk of type 2 diabetes (60). If our implicating hippocampal functions and the prefrontal cortex, a results are replicated in longitudinal studies, therapeutic agents hypothesis that is supported by a recent review (43). Continuous that improve insulin sensitivity and promote neurogenesis, such exposure to glucose and prediabetes have been significantly as metformin (61), could be considered cognitive enhancement associated with structural brain abnormalities such as decreased options for people with ROP and higher HbA1c values. brain volume and grey matter and white matter volume (44). The results regarding HbA1c and cognitive performance Further, the risk of brain infarcts and decreased hippocampal were independent of HPA axis activity, as all multivariate volume may be associated with continuous exposure to glucose, analyses were adjusted for cortisol levels during the day and which is reflected by higher levels of HbA1c. This indicator of long- the CAR. These two HPA axis measures have been reported to term glycaemic control is also thought to impact negatively on white be associated with impaired cognitive functioning in ROP matter structure even in healthy individuals (22). This last study patients (4): a blunted CAR has been associated with poorer suggests that biological processes other than microvascular and verbal memory in ROP patients (27), higher afternoon plasma macrovascular disease could be playing a role in this associations. As cortisol levels are associated with poorer verbal memory (62), pointed out by Repple et al. (22), it is plausible that inflammatory and a more flattened diurnal cortisol slope has been associated processes might constitute one of several biological mechanisms with poorer working memory in women with ROP (3). It is potentially mediating the relationship between glycose also important to control for HPA axis activity when dysregulation and brain structural damage. This is a particularly exploring the role of glucose-related parameters on important issue to be studied because the low-grade inflammation is cognition because a central dysregulation of the HPA axis also found in people with psychotic disorders (45–47), even before has been reported in type 2 diabetes and because higher the onset of the disease (48, 49), and is associated with poorer morning cortisol levels are associated with poorer cognitive cognitive function (9, 50). The duration of postpandrial glucose abilities in people with type 2 diabetes (28). In patients with increase, a major contributor to chronic hyperglycaemia (and type 2 diabetes, there are elevated basal plasma cortisol and higher HbA1c), is also thought to contribute to excessive protein ACTH levels (63–65), higher late-night cortisol (66), and glycation, generation of oxidative stress and inflammation (51). increased cortisol levels following overnight dexamethasone Future longitudinal studies are needed to explore whether the suppression (67, 68). association between HbA1c levels and impaired cognitive function Several strengths of our study should be noted. The patients could be explained by changes in inflammatory markers. in our study seemed to be representative of our catchment area, Recently, some authors have hypothesized that central and our first-episode psychosis unit is a referral center in our insulin resistance could have an important role in the area. On the other hand, to the best of our knowledge, few studies relationship between metabolic and cognitive disorders (52). have tried to specifically investigate metabolic biomarkers for There is consistent evidence pointing out that the dopamine cognition in schizophrenia. Although some studies have Frontiers in Psychiatry | www.frontiersin.org 8 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis explored the association between diabetes mellitus and poorer DATA AVAILABILITY STATEMENT cognitive functioning in patients with schizophrenia (16, 24), our study is the first to specifically highlight the relationship between The datasets generated for this study will not be made publicly HbA1c and cognitive function in the early stages of the psychotic available. The datasets are not publicly available due to privacy or illness. The search for biomarkers in cognition has been the focus ethical restrictions. However, additional analyses might be of interest in research on patients with schizophrenia (50). available from authors by request to the corresponding author. However, in recent decades, the vast majority of studies have investigated whether neurotrophic factors or inflammatory markers may be correlated with cognitive deficits or cognitive recovery in schizophrenia (50), and metabolic parameters have ETHICS STATEMENT been a second focus of interest. The studies involving human participants were reviewed and The main limitation of our study is the cross-sectional approved by Hospital Sant Joan Ethics Committee. The patients/ design. Therefore, no causal relationships between glucose participants provided their written informed consent to metabolism parameters and cognitive functioning can be participate in this study. inferred. The relatively small sample size limits the possibility of the conduction of specific subanalyses regarding sex differences or psychotic phenotypes. Larger studies are needed to test whether the role of HbA1c on AUTHOR CONTRIBUTIONS cognitive outcomes differs by subtypes of psychotic JL, AG-Z, and EV designed the study. IM, Á C, MS, VS-G, MA, disorders. The CAR was obtained only on one day, as and LO participated in the recruitment of participants. LM and consensus guidelines (69) recommend obtaining repeated EV participated in the biochemical determinations. JL and IM measures for this parameter on separate days. As in the analyzed the data. IM and AG-R reviewed the scientific literature original study (3), we administered dexamethasone to all and wrote the first draft of the manuscript. All authors participants, and we decided to measure the CAR only on participated in the discussion of the results and approved the one day. Finally, a replication dataset was not included. final manuscript. In summary, the present study suggests that long-term exposure to higher glucose levels, although within the normal range, is negatively associated with cognitive performance in both ROP patients and HS in tasks dealing with executive FUNDING functions and visual memory, two cognitive domains that involve the hippocampus and prefrontal cortex. Our study This work was funded in part by the Instituto de Salud Carlos III suggests that this association is independent of BMI and HPA (PI10/01607; PI15/01386) and by La Fundació de la Marató de TV3 axis functioning. These findings highlight the importance of (92230). JL and IM have received an Intensification of the Research the consideration of the inclusion of HbA1 c in future Activity Grant by the Health Department from the Generalitat de longitudinal studies exploring cognitive changes in patients Catalunya (SLT006/17/00012 and SLT008/18/00074). JL has also with a psychotic disorder at early stages of the disease to received an Intensification of the Research Activity Grant by the disentangle a potential negative effect on cognitive outcomes. Instituto de Salud Carlos III in 2020 (INT19/00071). REFERENCES early psychosis. Schizophr Res (2015) 166:37–42. doi: 10.1016/ j.schres.2015.04.030 1. Fett AKJ, Viechtbauer W, Dominguez M de G, Penn DL, van Os J, 6. Labad J, Barbero JD, Gutié rrez-Zotes A, Montalvo I, Creus M, Cabezas Á , Krabbendam L. The relationship between neurocognition and social et al. Free thyroxine levels are associated with cognitive changes in cognition with functional outcomes in schizophrenia: A meta-analysis. individuals with a first episode of psychosis: A prospective 1-year Neurosci Biobehav Rev (2011) 35:573–88. doi: 10.1016/j.neubiorev. follow-up study. Schizophr Res (2016) 171:182–6. doi: 10.1016/j.schres. 2010.07.001 2016.01.036 2. Fusar-Poli P, Deste G, Smieskova R, Barlati S, Yung AR, Howes O, et al. 7. Montalvo I, Nadal R, Armario A, Gutié rrez-Zotes A, Creus M, Cabezas Á , Cognitive functioning in prodromal psychosis: a meta-analysis. Arch Gen et al. Sex differences in the relationship between prolactin levels and impaired Psychiatry (2012) 69:562–71. doi: 10.1001/archgenpsychiatry.2011.1592 processing speed in early psychosis. Aust N Z J Psychiatry (2018) 52:585–95. 3. Labad J, Gutié rrez-Zotes A, Creus M, Montalvo I, Cabezas Á , Solé M, et al. doi: 10.1177/0004867417744254 Hypothalamic-pituitary-adrenal axis measures and cognitive abilities in early 8. Montalvo I, Gutié rrez-Zotes A, Creus M, Monseny R, Ortega L, Franch J, et al. psychosis: Are there sex differences? Psychoneuroendocrinology (2016) 72:54– Increased prolactin levels are associated with impaired processing speed in 62. doi: 10.1016/j.psyneuen.2016.06.006 subjects with early psychosis. PloS One (2014) 9:e89428. doi: 10.1371/ 4. Labad J. The role of cortisol and prolactin in the pathogenesis and clinical journal.pone.0089428 expression of psychotic disorders. Psychoneuroendocrinology (2019) 102:24– 9. Cabrera B, Bioque M, Penadé s R, Gonzá lez-Pinto A, Parellada M, Bobes J, 36. doi: 10.1016/j.psyneuen.2018.11.028 et al. Cognition and psychopathology in first-episode psychosis: are they 5. Barbero JD, Gutié rrez-Zotes A, Montalvo I, Creus M, Cabezas Á , Solé M, et al. related to inflammation? Psychol Med (2016) 46:2133–44. doi: 10.1017/ Free thyroxine levels are associated with cognitive abilities in subjects with S0033291716000659 Frontiers in Psychiatry | www.frontiersin.org 9 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis 10. Ribeiro-Santos A, Lucio Teixeira A, Salgado JV. Evidence for an immune role The Edinburgh type 2 diabetes study. Diabetes Care (2010) 33:714–20. on cognition in schizophrenia: a systematic review. Curr Neuropharmacol doi: 10.2337/dc09-1796 (2014) 12:273–80. doi: 10.2174/1570159X1203140511160832 29. Wing JK, Babor T, Brugha T, Burke J, Cooper JE, Giel R, et al. SCAN. 11. Fanous AH, Kendler KS. Genetics of clinical features and subtypes of Schedules for Clinical Assessment in Neuropsychiatry. Arch Gen Psychiatry schizophrenia: A review of the recent literature. Curr Psychiatry Rep (2008) (1990) 47:589–93. doi: 10.1001/archpsyc.1990.01810180089012 10:164–70. doi: 10.1007/s11920-008-0028-z 30. Kay SR, Fiszbein A, Vital-Herne M, Fuentes LS. The Positive and Negative 12. Ryan MCM, Collins P, Thakore JH. Impaired fasting glucose tolerance in first- Syndrome Scale–Spanish adaptation. J Nerv Ment Dis (1990) 178:510–7. episode, drug-naive patients with schizophrenia. Am J Psychiatry (2003) doi: 10.1097/00005053-199017880-00007 160:284–9. doi: 10.1176/appi.ajp.160.2.284 31. Peralta V, Cuesta MJ. Validacion de la escala de los sı́ndromes positivo y 13. Fernandez-Egea E, Bernardo M, Donner T, Conget I, Parellada E, Justicia A, negativo (PANSS) en una muestra de esquizofré nicos españoles. Actas Luso et al. Metabolic profile of antipsychotic-naive individuals with non-affective Esp Neurol Psiquiatr Cienc Afines (1994) 22:171–7. psychosis. Br J Psychiatry (2009) 194:434–8. doi: 10.1192/bjp.bp.108.052605 32. Nuechterlein KH, Green MF, Kern RS, Baade LE, Barch DM, Cohen JD, et al. The 14. Fernandez-Egea E, Miller B, Bernardo M, Donner T, Kirkpatrick B. Parental MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and history of Type 2 diabetes in patients with nonaffective psychosis. Schizophr validity. Am J Psychiatry (2008) 165:203–13. doi: 10.1176/appi.ajp.2007.07010042 Res (2008) 98:302–6. doi: 10.1016/j.schres.2007.10.002 33. Gardner DM, Murphy AL, O’Donnell H, Centorrino F, Baldessarini RJ. 15. Habtewold TD, Islam MA, Liemburg EJ, Bartels-Velthuis AAA, van Beveren International consensus study of antipsychotic dosing. Am J Psychiatry NJ, Cahn W, et al. Polygenic risk score for schizophrenia was not associated (2010) 167:686–93. doi: 10.1176/appi.ajp.2009.09060802 with glycemic level (HbA1c) in patients with non-affective psychosis: Genetic 34. Pruessner JC, Kirschbaum C, Meinlschmid G, Hellhammer DH. Two formulas for Risk and Outcome of Psychosis (GROUP) cohort study. J Psychosom Res computation of the area under the curve represent measures of total hormone (2020) 132:109968. doi: 10.1016/j.jpsychores.2020.109968 concentration versus time-dependent change. Psychoneuroendocrinology (2003) 16. Bora E, Akdede BB, Alptekin K. The relationship between cognitive 28:916–31. doi: 10.1016/S0306-4530(02)00108-7 impairment in schizophrenia and metabolic syndrome: A systematic review 35. Miller R, Plessow F. Transformation techniques for cross-sectional and and meta-analysis. Psychol Med (2017) 47:1030–40. doi: 10.1017/ longitudinal endocrine data: Application to salivary cortisol concentrations. S0033291716003366 Psychoneuroendocrinology (2013) 38:941–6. doi: 10.1016/j.psyneuen.2012.09.013 17. Marden JR, Mayeda ER, Tchetgen Tchetgen EJ, Kawachi I, Glymour MM. 36. Olsen W. Outliers. In: Data Collection: Key Debates and Methods in Social High Hemoglobin A1c and Diabetes Predict Memory Decline in the Health Research. London: SAGE Publications Ltd. (2012). doi: 10.4135/ and Retirement Study. Alzheimer Dis Assoc Disord (2017) 31:48–54. 9781473914230.n32 doi: 10.1097/WAD.0000000000000182 37. Bender R, Lange S. Adjusting for multiple testing - When and how? J Clin 18. Gao Y, Xiao Y, Miao R, Zhao J, Cui M, Huang G, et al. The prevalence of mild Epidemiol (2001) 54:343–9. doi: 10.1016/S0895-4356(00)00314-0 cognitive impairment with type 2 diabetes mellitus among elderly people in 38. Perkovic MN, Erjavec GN, Strac DS, Uzun S, Kozumplik O, Pivac N. China: A cross-sectional study. Arch Gerontol Geriatr (2016) 62:138–42. Theranostic biomarkers for schizophrenia. Int J Mol Sci (2017) 18:pii: E733. doi: 10.1016/j.archger.2015.09.003 doi: 10.3390/ijms18040733 19. Cooper C, Sommerlad A, Lyketsos CG, Livingston G. Modifiable predictors of 39. Rajkumar AP, Horsdal HT, Wimberley T, Cohen D, Mors O, Børglum AD, dementia in mild cognitive impairment: A systematic review and meta- et al. Endogenous and antipsychotic-related risks for diabetes mellitus in analysis. Am J Psychiatry (2015) 172:323–34. doi: 10.1176/appi.ajp.2014. young people with schizophrenia: A danish population-based cohort study. 14070878 Am J Psychiatry (2017) 174:686–94. doi: 10.1176/appi.ajp.2016.16040442 20. Yuan XY, Wang XG. Mild cognitive impairment in type 2 diabetes mellitus 40. Petrikis P, Tigas S, Tzallas AT, Papadopoulos I, Skapinakis P, Mavreas V. and related risk factors: A review. Rev Neurosci (2017) 28:715–23. Parameters of glucose and lipid metabolism at the fasted state in drug-naïve doi: 10.1515/revneuro-2017-0016 first-episode patients with psychosis: Evidence for insulin resistance. 21. Geijselaers SLC, Sep SJS, Stehouwer CDA, Biessels GJ. Glucose regulation, Psychiatry Res (2015) 229:901–4. doi: 10.1016/j.psychres.2015.07.041 cognition, and brain MRI in type 2 diabetes: A systematic review. Lancet 41. Piotrowski P, Kotowicz K, Rymaszewska J, Beszłej JA, Plichta P, Samochowiec Diabetes Endocrinol (2015) 3:75–89. doi: 10.1016/S2213-8587(14)70148-2 J, et al. Allostatic load index and its clinical correlates at various stages of 22. Repple J, Karliczek G, Meinert S, Förster K, Grotegerd D, Goltermann J, et al. psychosis. Schizophr Res (2019) 210:73–80. doi: 10.1016/j.schres.2019.06.009 Variation of HbA1c affects cognition and white matter microstructure in 42. Fucetola R, Newcomer JW, Craft S, Melson AK. Age- and dose-dependent healthy, young adults. Mol Psychiatry (2019). doi: 10.1038/s41380-019-0504-3 glucose-induced increases in memory and attention in schizophrenia. 23. Chen DC, Du XD, Yin GZ, Yang KB, Nie Y, Wang N, et al. Impaired glucose Psychiatry Res (1999) 88:1–13. doi: 10.1016/S0165-1781(99)00063-3 tolerance in first-episode drug-naïve patients with schizophrenia: 43. Zhou J, Zhang Z, Zhou H, Qian G. Diabetic Cognitive Dysfunction: From Bench Relationships with clinical phenotypes and cognitive deficits. Psychol Med to Clinic. Curr Med Chem (2019). doi: 10.2174/1871530319666190206225635 (2016) 46:3219–30. doi: 10.1017/S0033291716001902 44. van Agtmaal MJM, Houben AJHM, de Wit V, Henry RMA, Schaper NC, 24. Zhang BH, Han M, Zhang XY, Hui L, Jiang SR, De YF, et al. Gender Dagnelie PC, et al. Prediabetes is associated with structural brain differences in cognitive deficits in schizophrenia with and without diabetes. abnormalities: The Maastricht study. Diabetes Care (2018) 41:2535–43. Compr Psychiatry (2015) 63:1–9. doi: 10.1016/j.comppsych.2015.07.003 doi: 10.2337/dc18-1132 25. Agarwal SM, Kowalchuk C, Castellani L, Costa-Dookhan KA, Caravaggio F, 45. Kirkpatrick B, Miller BJ. Inflammation and schizophrenia. Schizophr Bull Asgariroozbehani R, et al. Brain insulin action: Implications for the treatment (2013) 39:1174–9. doi: 10.1093/schbul/sbt141 of schizophrenia. Neuropharmacology (2019) 168:107655. doi: 10.1016/ 46. Soria V, Uribe J, Salvat-Pujol N, Palao D, Menchó n JM, Labad J. j.neuropharm.2019.05.032 Psychoneuroimmunology of mental disorders. Rev Psiquiatr Salud Ment 26. Cullen AE, Zunszain PA, Dickson H, Roberts RE, Fisher HL, Pariante CM, (2018) 11:115–24. doi: 10.1016/j.rpsm.2017.07.006 et al. Cortisol awakening response and diurnal cortisol among children at 47. Miller BJ, Culpepper N. Rapaport MH. C-reactive protein levels in elevated risk for schizophrenia: Relationship to psychosocial stress and schizophrenia: a review and meta-analysis. Clin Schizophr Relat Psychoses cognition. Psychoneuroendocrinology (2014) 46:1–13. doi: 10.1016/ (2014) 7:223–30. doi: 10.3371/CSRP.MICU.020813 j.psyneuen.2014.03.010 48. Stojanovic A, Martorell L, Montalvo I, Ortega L, Monseny R, Vilella E, et al. 27. Aas M, Dazzan P, Mondelli V, Toulopoulou T, Reichenberg A, Di Forti M, Increased serum interleukin-6 levels in early stages of psychosis: Associations et al. Abnormal cortisol awakening response predicts worse cognitive function with at-risk mental states and the severity of psychotic symptoms. in patients with first-episode psychosis. Psychol Med (2011) 41:463–76. Psychoneuroendocrinology (2014) 41:23–32. doi: 10.1016/j.psyneuen. doi: 10.1017/S0033291710001170 2013.12.005 28. Reynolds RM, Strachan MWJ, Labad J, Lee AJ, Frier BM, Fowkes FG, et al. 49. Khandaker GM, Pearson RM, Zammit S, Lewis G, Jones PB. Association of Morning cortisol levels and cognitive abilities in people with type 2 diabetes: serum interleukin 6 and C-reactive protein in childhood with depression and Frontiers in Psychiatry | www.frontiersin.org 10 May 2020 | Volume 11 | Article 455 Montalvo et al. HbA1c and Cognition in Psychosis psychosis in young adult life. JAMA Psychiatry (2014) 71:1121–8. 62. Havelka D, Prikrylova-Kucerova H, Prikryl R, Ceskova E. Cognitive doi: 10.1001/jamapsychiatry.2014.1332 impairment and cortisol levels in first-episode schizophrenia patients. Stress 50. Penadés R, Garcı́a-Rizo C, Bioque M, González-Rodrı́guez A, Cabrera B, Mezquida (2016) 19:383–9. doi: 10.1080/10253890.2016.1193146 G, et al. The search for new biomarkers for cognition in schizophrenia. Schizophr 63. Cameron OG, Thomas B, Tiongco D, Hariharan M, Greden JF. Res Cognit (2015) 2:172–8. doi: 10.1016/j.scog.2015.10.004 Hypercortisolism in diabetes mellitus. Diabetes Care (1987) 10:662–4. 51. Blaak EE, Antoine JM, Benton D, Björck I, Bozzetto L, Brouns F, et al. Impact doi: 10.2337/diacare.10.5.662 of postprandial glycaemia on health and prevention of disease. Obes Rev 64. Lee ZSK, Chan JCN, Yeung VTF, Chow CC, Lau MSW, Ko GTC, et al. Plasma (2012) 13:923–84. doi: 10.1111/j.1467-789X.2012.01011.x insulin, growth hormone, cortisol, and central obesity among young Chinese 52. Kullmann S, Heni M, Hallschmid M, Fritsche A, Preissl H, Häring HU. Brain type 2 diabetic patients. Diabetes Care (1999) 22:1450–357. doi: 10.2337/ insulin resistance at the crossroads of metabolic and cognitive disorders in diacare.22.9.1450 humans. Physiol Rev (2016) 96:1169–209. doi: 10.1152/physrev.00032.2015 65. Reynolds RM, Walker BR, Syddall HE, Andrew R, Wood PJ, Whorwood CB, 53. Lopez Vicchi F, Luque GM, Brie B, Nogueira JP, Garcia Tornadu I, Becu- et al. Altered control of cortisol secretion in adult men with low birth weight Villalobos D. Dopaminergic drugs in type 2 diabetes and glucose homeostasis. and cardiovascular risk factors. J Clin Endocrinol Metab (2001) 86:245–50. Pharmacol Res (2016) 109:74–80. doi: 10.1016/j.phrs.2015.12.029 doi: 10.1210/jcem.86.1.7145 54. Nash AI. Crosstalk between insulin and dopamine signaling: A basis for the 66. Liu H, Bravata DM, Cabaccan J, Raff H, Ryzen E. Elevated late-night salivary metabolic effects of antipsychotic drugs. J Chem Neuroanat (2017) 83-84:59– cortisol levels in elderly male type 2 diabetic veterans. Clin Endocrinol (Oxf) 68. doi: 10.1016/j.jchemneu.2016.07.010 (2005) 63:642–9. doi: 10.1111/j.1365-2265.2005.02395.x 55. Daws LC, Avison MJ, Robertson SD, Niswender KD, Galli A, Saunders C. 67. Cameron OG, Kronfol Z, Greden JF, Carroll BJ. Hypothalamic-Pituitary- Insulin signaling and addiction. Neuropharmacology (2011) 61:1123–8. Adrenocortical Activity in Patients With Diabetes Mellitus. Arch Gen doi: 10.1016/j.neuropharm.2011.02.028 Psychiatry (1984) 41:1090–5. doi: 10.1001/archpsyc.1983.0179022 56. ter Horst DM, Schene AH, Figueroa CA, Assies J, Lok A, Bockting CLH, et al. 0080013 Cortisol, dehydroepiandrosterone sulfate, fatty acids, and their relation in 68. Hudson JI, Hudson MS, Rothschild AJ, Vignati L, Schatzberg AF, Melby JC. recurrent depression. Psychoneuroendocrinology (2019) 100:203–12. Abnormal Results of Dexamethasone Suppression Tests in Nondepressed doi: 10.1016/j.psyneuen.2018.10.012 Patients With Diabetes Mellitus. Arch Gen Psychiatry (1984) 41:1086–9. 57. Tripathi A, Kar SK, Shukla R. Cognitive deficits in schizophrenia: doi: 10.1001/archpsyc.1983.01790220076012 Understanding the biological correlates and remediation strategies. Clin 69. Stalder T, Kirschbaum C, Kudielka BM, Adam EK, Pruessner JC, Wüst S, et al. Psychopharmacol Neurosci (2018) 16:7–17. doi: 10.9758/cpn.2018.16.1.7 Assessment of the cortisol awakening response: Expert consensus guidelines. 58. Pillinger T, Beck K, Gobjila C, Donocik JG, Jauhar S, Howes OD. Impaired Psychoneuroendocrinology (2016) 63:414–32. doi: 10.1016/j.psyneuen.2015. glucose homeostasis in first-episode schizophrenia: A systematic review and 10.010 meta-analysis. JAMA Psychiatry (2017) 74:261–9. doi: 10.1001/ jamapsychiatry.2016.3803 Conflict of Interest: JL and VS-G have received honoraria for lectures or advisory 59. Caravaggio F, Hahn M, Nakajima S, Gerretsen P, Remington G, Graff- boards from Jannsen, Otsuka and Lundbeck. Guerrero A. Reduced insulin-receptor mediated modulation of striatal dopamine release by basal insulin as a possible contributing factor to The remaining authors declare that the research was conducted in the absence of hyperdopaminergia in schizophrenia. Med Hypotheses (2015) 85:391–6. any commercial or financial relationships that could be construed as a potential doi: 10.1016/j.mehy.2015.06.011 conflict of interest. 60. Galling B, Roldá n A, Nielsen RE, Nielsen J, Gerhard T, Carbon M, et al. Type 2 diabetes mellitus in youth exposed to antipsychotics: A systematic review and Copyright © 2020 Montalvo, González-Rodrı ́guez, Cabezas, Gutiérrez-Zotes, Solé, meta-analysis. JAMA Psychiatry (2016) 73:247–59. doi: 10.1001/ Algora, Ortega, Martorell, Sánchez-Gistau, Vilella and Labad. This is an open-access jamapsychiatry.2015.2923 article distributed under the terms of the Creative Commons Attribution License (CC 61. Ahmed S, Mahmood Z, Javed A, Hashmi SN, Zerr I, Zafar S, et al. Effect of BY). The use, distribution or reproduction in other forums is permitted, provided the Metformin on Adult Hippocampal Neurogenesis: Comparison with original author(s) and the copyright owner(s) are credited and that the original Donepezil and Links to Cognition. J Mol Neurosci (2017) 62:88–98. publication in this journal is cited, in accordance with accepted academic practice. No doi: 10.1007/s12031-017-0915-z use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Psychiatry | www.frontiersin.org 11 May 2020 | Volume 11 | Article 455