Hostname: page-component-7c8c6479df-p566r Total loading time: 0 Render date: 2024-03-29T02:04:35.334Z Has data issue: false hasContentIssue false

Peripheral insulin sensitivity predicting cognitive function in euthymic bipolar disorder patients

Published online by Cambridge University Press:  11 March 2021

Hui Hua Chang
Affiliation:
Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan School of Pharmacy, College of Medicine, National Cheng Kung University, Tainan, Taiwan Department of Pharmacy, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan Department of Pharmacy, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
Huai-Hsuan Tseng
Affiliation:
Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
Wei Hung Chang
Affiliation:
Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan Department of Psychiatry, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
Kuan-Chung Huang
Affiliation:
Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
Tsung-Hua Lu
Affiliation:
Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
Yen Kuang Yang
Affiliation:
Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan Department of Psychiatry, Tainan Hospital, Ministry of Health and Welfare, Tainan, Taiwan
Po See Chen*
Affiliation:
Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan Department of Psychiatry, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
*
*Author for correspondence: Po See Chen, Email: chenps@mail.ncku.edu.tw
Rights & Permissions [Opens in a new window]

Abstract

Objective

High prevalence of insulin resistance (IR) has been reported in bipolar disorder (BD) patients. Importantly, impaired insulin sensitivity could modulate the course and treatment outcome in BD. Here, we hypothesized that insulin sensitivity could be potentially associated with the neurocognitive trajectory in euthymic BD. We aimed to examine differences in insulin sensitivity and executive function between BD patients and controls.

Methods

Sixty-two patients with BD receiving mood stabilizer treatment and 62 controls, matching age, sex, and body mass index, were recruited in this study. Insulin sensitivity was estimated using the homeostasis model assessment of insulin resistance (HOMA-IR). The Wisconsin card-sorting test (WCST) was applied to test participants’ ability to shift cognitive set. Group differences were measured and multivariate regression analysis was performed to examine relationships among factors.

Results

The results indicated that the HOMA-IR (P = .048) value in the patients with BD were significantly higher than those in controls. With regards to executive function, the BD patients performed significantly poorer than the control subjects (P < .05). Moreover, the interaction effect between BD diagnosis and HOMA-IR value on the WCST-preservation errors was significant (P = .01), and post-hoc analyses showed that the cognitive abilities were worse in the BD patients with a higher IR than in the others groups.

Conclusion

Insulin sensitivity is associated with the neurocognitive performance in euthymic BD patients. Although the underlying mechanisms remain unclear, interventions to improve insulin sensitivity could potentially improve the functional outcome of BD.

Type
Original Research
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Introduction

Neurocognitive performance is an important factor related to the prognosis and functional outcome in patients with bipolar disorder (BD).Reference Tse, Chan and Ng 1 , Reference Samalin, de Chazeron and Vieta 2 The presence of neurocognitive impairment has been found to be associated with greater disability, and cognitive impairment has been proposed as a marker of neurodegeneration in BD.Reference Samalin, Boyer and Murru 3 Neurocognitive impairment has been increasingly recognized as an integral part of the BD phenotype.Reference Sole, Jimenez and Torrent 4 BD patients have significant cognitive impairment, especially in terms of executive function, attention/working memory, speed/reaction time, and verbal and visual memory.Reference Cullen, Ward and Graham 5 Phases of BD have differential cognitive profiles with regards to executive function.Reference Ryan, Vederman and McFadden 6 In patients with long-standing BD who are in a euthymic state, persistent neurocognitive difficulties remain.Reference Zubieta, Huguelet and O’Neil 7 , Reference Langenecker, Saunders and Kade 8 One meta-analysis showed that performance in category fluency, mental manipulation, and verbal learning remained significantly impaired in euthymic BD patients.Reference Robinson, Thompson and Gallagher 9 However, there is heterogeneity of neurocognitive function among patients with BD.Reference Lima, Rabelo-da-Ponte and Bucker 10 The proportion of BD patients with significant neurocognitive function impairment is approximately 60%.Reference Burdick, Russo and Frangou 11 The decline in neurocognitive abilities over the course of BD seems to be associated with the allostatic load.Reference Cardoso, Bauer and Meyer 12 Factors that affect the neurocognitive trajectory in euthymic BD patients remain unclear.Reference Sanchez-Morla, Lopez-Villarreal and Jimenez-Lopez 13 , Reference Roux, Etain and Cannavo 14

In previous literature, a 30% to 50% prevalence of metabolic syndrome in BD patients was reported, which was higher than that in the general population.Reference Chang, Chou and Chen 15 , Reference Chang, Yang and Gean 16 Other studies indicated that 8% to 17% of BD patients have hyperglycemia and type 2 diabetes, 17% to 36% have a high triglyceride level, 20% to 23% have a low high-density lipoprotein cholesterol level, 36% to 49% have a large waist circumference, and 29% to 39% have hypertension.Reference Chang, Chou and Chen 15 , Reference van Winkel, De Hert and Van Eyck 17 These metabolic abnormalities, which include abnormalities in glucose and lipid levels, body mass index, and blood pressure, also indicate high risks of cardiovascular diseases and diabetes. High levels of adipokines and hepatokines are also involved in chronic inflammation and are correlated with higher morbidity and mortality.Reference Deng and Scherer 18 , Reference Hotamisligil 19 In addition, there is growing evidence to suggest that an impaired glucose metabolism moderates the course of the illness and treatment outcomes in BD. 20–23 Insulin resistance (IR), as one of the consequences of the cumulative allostatic load identified through key inflammation, glucose and lipid factors, is known to contribute to neuroprogression in BD.Reference Wiley, Gruenewald and Karlamangla 24 , Reference Calkin, Gardner and Ransom 25 The odds of a chronic course of BD and rapid cycling in patients with BD and type 2 diabetes or IR was three times higher than that in euglycemic patients.Reference Calkin, Ruzickova and Uher 23 However, whether peripheral insulin sensitivity represents brain insulin IR and is associated with the neurocognitive trajectory in BD remains unclear.Reference Burdick, Russo and Frangou 11 , Reference Cigliobianco, Paoli and Caletti 26

It is important to achieve a better understanding of potential moderators contributing to neurocognitive impairment in BD in order to develop prevention strategies and effective treatments.Reference Sole, Jimenez and Torrent 4 As metabolic disturbances are associated with neurocognitive deficits, we hypothesized that insulin sensitivity could be potentially associated with neurocognitive trajectory in the euthymic phase of BD.Reference Bora, McIntyre and Ozerdem 27 Here, we aimed to measure the differences in insulin sensitivity and executive function between euthymic BD patients and healthy controls, and examined the possible interaction effects of IR on executive function in BD patients.

Methods

Subject enrollment and measurement of psychopathology

All participants provided written informed consent to their participation in the trial, and the National Cheng Kung University Hospital Institutional Review Board reviewed and approved the study protocol prior to patient enrollment. Eligible participants were aged between 18 and 70 years. Patients diagnosed with BD according to the DSM 5 criteria who were receiving mood stabilizer treatment, including valproic acid (VPA) (n = 21, 33.9%), VPA + antipsychotics (n = 19, 30.6%), lithium + antipsychotics (n = 12, 19.4%), antipsychotics (n = 10, 16.1%), were enrolled consecutively. Patient psychopathology was evaluated using the Hamilton Depression Rating Scale (HDRS) and the Young Mania Rating Scale (YMRS). The HDRS and YMRS scores were not higher than 8 in all of the participants. Patients were excluded if they had (i) a diagnosis of organic mood disorder, (ii) a mood disorder not otherwise specified, (iii) received more than one course of electroconvulsive therapy (ECT) or undergone ECT within the last 6 months, (iv) cerebrovascular disease, (v) neurodegenerative disorders, or (vi) macrovascular disorders. We also recruited 62 controls, matching age, sex, and body mass index, from the community after exclusion of individuals with mental illnesses by a senior psychiatrist using the Chinese version of the Mini International Neuropsychiatry Interview. To avoid confounding factors interfering with the IR and cognitive function, all of the control meeting the following criteria were excluded through chart reviews and patient-reported questionnaires: (i) a serious surgical condition or physical illness including all chronic diseases, heart disease, stroke, kidney dialysis, transplant, etc., (ii) cerebrovascular disease, (iii) neurodegenerative disorders, (iv) macrovascular disorders.

Diagnosis of IR and type 2 diabetes mellitus (T2DM)

Tests of fasting plasma glucose (FPG) and fasting serum insulin (FSI) levels was performed in all patients and analyzed in a single laboratory using the same assay to eliminate variability. If the FPG level was elevated (>7 mmol/L), the test was repeated on another day to confirm the diagnosis of T2DM. If the diagnosis of T2DM was equivocal (repeated test was not >7 mmol/L, or initial FPG level was between 5.7 and 6.9 mmol/L), then a 2-h 75 g oral glucose tolerance test was performed. Glucose intolerance (GI) was defined as a FPG level < 7.0 mmol/L, and a glucose level >7.8 and <11.1 mmol/L measured 2 h after ingestion of 75 g of glucose. A diagnosis of T2DM was made if the 2-h glucose level was >11.1 mmol/L, irrespective of the FPG level. These are standard diagnostic procedures for T2DM. In patients who did not meet the laboratory criteria for T2DM or GI, IR was estimated using the homeostatic model assessment-IR (HOMA-IR) equation (HOMA-IR = FPG (mmol/L) × FSI (U/mL)/22.5), and participants were classified into groups with and without IR according to a cut-off point of 2.6. HOMA-IR ≥ 2.6 is a suitable cutoff point of HOMA-IR value for diagnosis of metabolic syndrome, abdominal obesity, fasting hyperglycemia, hypertriglyceridemia, low-HDL, and greater cardiovascular risk. 28–32 Furthermore, an observational study has revealed that subjects with HOMA-IR ≥ 2.6 had larger odds of cognitive dysfunction.Reference Neergaard, Dragsbaek and Christiansen 28 The participants with IR and GI were combined into a single group for the analyses. Among all of the subjects (BD and controls), there were only two BD patients having T2DM in the study.

Wisconsin card-sorting test (WCST)

The WCST was conducted by an experienced clinical neuropsychologist. There were 64 cards in the test. All definitions of indices were as described in the WCST manual.Reference Heaton, Chelune and Talley 33 Using a computerized version of the WCST, the patients were required to match response cards to four stimulus cards along one of three dimensions (color, form, or number) on the basis of sign feedback (correct or incorrect). The subjects were not given any information about the dimensions. After sorting a series of 10 cards in one category, the subject was asked to sort the cards again in a different category. The indexes of preservative errors and completed categories were used to assess performance in the WCST.Reference Volkow, Gur and Wang 34

Statistical analyses

SPSS Statistics 20.0 (SPSS Inc., Chicago, IL) was used for all of the analyses. The results were considered significant at P < .05 (two-tailed). Chi-square tests or independent t-tests were conducted to examine group (patients with BD vs controls) differences in demographic characteristics, HDRS score, YMRS score, IR, and WCST score. Because educational year was significantly different between groups, multivariate regression analysis, controlling educational year, was used to test the interaction effects between groups in IR and the WCST score.

Results

We recruited 62 euthymic BD patients, 32 (51.6%) of whom had BD I, and 62 age, sex, and body mass index matched control subjects. The demographic characteristics are shown in Table 1. The BD patients also had a lower educational year, higher YMRS score, and higher HOMA-IR. However, the frequency of IR, defined as HOMA-IR ≥ 2.6, was no significantly different in the BD patients than in the controls (53.2% vs 45.2%, P = .369). Moreover, performance in the WCST-preservation errors (12.31 ± 9.80 vs 8.37 ± 5.74, P = .007) and WCST-completed categories (2.73 ± 1.66 vs 3.53 ± 1.42, P = .004) was poorer in the BD patients as compared with the controls (Table 1). The results were similar even after adjustment for educational years (Table 1).

Table 1. Demographic Characteristics of the Euthymic BD Patients and the Control Subjects

Abbreviations: BD, bipolar disorder; HDRS, Hamilton Depression Rating Scale; HOMA-IR, homeostasis model assessment of insulin resistance; WCST, Wisconsin card-sorting test; YMRS, Young Mania Rating Scale.

When considering stratification of IR, we further subgrouped patients according to a cut-off point for HOMA-IR. The results showed that there was a significant interaction effect between BD diagnosis and IR in the WCST-preservation errors (F = 6.80, P = .010) (Table 2). The post-hoc analyses showed that the cognitive abilities were worse in the BD patients with a higher IR than in the other groups (Figure 1).

Table 2. Performance of the Euthymic BD Patients and the Control Subjects in the Neuropsychological Functional Tests, Subgrouped by HOMA-IR

Abbreviations: BD, bipolar disorder; HOMA-IR, homeostasis model assessment of insulin resistance; IR, insulin resistance (HOMA-IR ≥ 2.6); WCST, Wisconsin card-sorting test.

a Educational year was controlled.

b Educational year and body mass index were controlled.

* P < .05.

Figure 1. Post-hoc analyses of WCST preservative errors and HOMA-IR in the euthymic bipolar disorder patients and controls. Abbreviations: WCST, Wisconsin card-sorting test; HOMA-IR, homeostasis model assessment of insulin resistance; BD, bipolar disorder. *P < .05.

Discussion

The results here again showed significant differences in insulin sensitivity and executive function between BD patients and healthy controls. Moreover, the results demonstrated that insulin sensitivity was associated with neurocognitive performance in euthymic BD patients. Importantly, insulin sensitivity impairment significantly aggravates the impaired executive function of cognitive set shifting (ie, perseverative errors in WCST) in BD patients. The neurocognitive trajectory in BD is highly variable and the progression of cognitive decline is not a general rule in BD.Reference Lima, Rabelo-da-Ponte and Bucker 10 Factors reflecting differences in illness severity but not the clinical subtypes might explain observed variation.Reference Bonnin, Jimenez and Sole 35 , Reference Bora 36 Before, a cohort study showed BD patients who have a greater number of manic or hypomanic episodes may present significant neuroprogression.Reference Sanchez-Morla, Lopez-Villarreal and Jimenez-Lopez 13 And the impact of pharmacological treatments upon cognitive function is inconclusive.Reference Xu, Huggon and Saunders 37 Here we demonstrated IR could be a testable and potentially modifiable factor for early screening and intervention that prevent neuroprogression advance in BD.Reference Calkin 38

IR as one of the consequences of the cumulative allostatic load identified through key inflammation, glucose and lipid factors. Therefore, BD patients, especially those with IR, might have a higher C reactive protein (CRP) level that associated with greater impairments in neurocognitive function and altered brain functional connectivity.Reference Mansur, Lee and Subramaniapillai 39 , Reference Tseng, Chang and Wei 40 In addition, levels of inflammatory biomarkers, such as peripheral CRP, has also been considered to help stratifying the outcomes in treating mood disorders.Reference Chang and Chen 41 In BD, the peripheral CRP level is elevated prominently during the manic state, but is still moderately elevated during the depressive and euthymic statesReference Fernandes, Steiner and Molendijk 42 , In this study, we have compared the CRP levels between groups, however, the difference was not significant although the CRP levels were significantly associated with HOMA-IR in both groups (Supplementary Table 6). Moreover, the interaction effect between BD diagnosis and CRP levels on the WCST-preservation errors was not significant.

IR could contribute to neuroprogression through blood–brain barrier (BBB) leakage and pro-inflammatory cytokines activating in brain.Reference Craft and Stennis Watson 43 Before, an image study had found increased BBB dysfunction in BD subject with IR. The extensive BBB leakage is associated with worse neuropsychiatric status (including more frequent of chronic illness episodes, greater severity of depression, and socio/occupational dysfunction) and with metabolic dysregulation (including higher body mass indices, increased risk of cardiovascular disease, advanced heart age, and higher levels of IR) in BD patients.Reference Kamintsky, Cairns and Veksler 44 Systemic insulin sensitivity might also indicate the degree of insulin sensitivity in the brain.Reference Kullmann, Heni and Hallschmid 45 Importantly, brain IR is related to a greater amyloid burden post-mortem and increased deposition within areas affected by early Alzheimer’s disease (AD).Reference De Felice, Lourenco and Ferreira 46 , Reference Mullins, Mustapic and Goetzl 47 In addition, brain IR is known to contribute to a poorer memory performance and beta amyloid deposition in brain regions affected by AD.Reference Willette, Bendlin and Starks 48 , Reference Willette, Johnson and Birdsill 49 Importantly, patients with BD have been associated with future risk of dementia.Reference Wu, Chang and Liang 50 , Reference Diniz, Teixeira and Cao 51 Moreover, clear independent roles of BD and IR in the risk of dementia have been demonstrated.Reference Vancampfort, Mitchell and De Hert 52 Future studies are warranted to understand the detail mechanisms of the role IR in neuroprogression in BD patients.

Taken together, the results indicated that IR might play a key role in cognitive deficit in BD.Reference Hamer, Testani and Mansur 53 Therefore, medications or therapies approved for treating IR may help to treat mood and neurocognitive symptoms in BD.Reference Grigolon, Brietzke and Mansur 54 Several anti-hyperglycemic agents have been observed to have effects on depressive symptoms and cognitive decline, and this efficacy is probably the result of action on shared brain targets between the two conditions.Reference Chang and Chen 41 These medications include subcutaneous insulin, intranasal insulin, metformin, and liraglutide. Other promising brain stimulating, behavioral, and chronotherapeutic approaches are currently being investigated.Reference McIntyre, Lee and Carmona 55 , Reference Ott, Vinberg and Bowie 56

Although the data were presented carefully, this study has certain limitations. The first limitation is the relatively small sample size of the BD patients and controls. The second limitation is that the BD patients received different kinds of mood stabilizer treatment, which might influence the status of insulin homeostasis and neurocognitive function in different degrees. In the current study, in order to decrease the confounding factor, all of the BD patients received the same treatment at least for 3 months. Further study is needed to clarify whether insulin sensitivity could be a useful clinical indicator for monitoring neurocognitive function in BD patients.

Conclusions

In summary, our study suggested that insulin sensitivity is associated with the neurocognitive performance in euthymic BD patients. Although the underlying mechanisms remain unclear, interventions to improve insulin sensitivity could potentially improve the functional outcome of BD. The course of BD is highly variable, with a subset of patients presenting with a progressive course associated with brain changes and functional impairment.Reference Kapczinski, Mwangi and Cassidy 57 Further study about enhancing brain insulin signaling would be beneficial for the treatment of metabolic and cognitive deficits in BD.

Acknowledgement

The authors are also indebted to the research participants.

Funding

This work was supported by the Ministry of Science and Technology, Taiwan (MOST 106-2320-B-006-040, MOST 107-2320-B-006-071, MOST 107-2628-B-006-005, MOST 108-2320-B-006-047-MY3, MOST 108-2321-B-006-026-MY2, and MOST 108-2628-B-006-004) and National Cheng Kung University Hospital (NCKUH-10902014, NCKUH-11001003).

Disclosures

The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Hui Hua Chang, Huai-Hsuan Tseng, Wei Hung Chang, Kuan-Chung Huang, Tsung-Hua Lu, Yen Kuang Yang, and Po See Chen declare that they have no conflicts of interest.

Supplementary Materials

To view supplementary material for this article, please visit http://doi.org/10.1017/S1092852921000158.

References

Tse, S, Chan, S, Ng, KL, et al. Meta-analysis of predictors of favorable employment outcomes among individuals with bipolar disorder. Bipolar Disord. 2014;16(3):217229.CrossRefGoogle ScholarPubMed
Samalin, L, de Chazeron, I, Vieta, E, et al. Residual symptoms and specific functional impairments in euthymic patients with bipolar disorder. Bipolar Disord. 2016;18(2):164173.CrossRefGoogle ScholarPubMed
Samalin, L, Boyer, L, Murru, A, et al. Residual depressive symptoms, sleep disturbance and perceived cognitive impairment as determinants of functioning in patients with bipolar disorder. J Affect Disord. 2017;210:280286.CrossRefGoogle ScholarPubMed
Sole, B, Jimenez, E, Torrent, C, et al. Cognitive impairment in bipolar disorder: treatment and prevention strategies. Int J Neuropsychopharmacol. 2017;20(8):670680.CrossRefGoogle ScholarPubMed
Cullen, B, Ward, J, Graham, NA, et al. Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: a systematic review. J Affect Disord. 2016;205:165181.CrossRefGoogle ScholarPubMed
Ryan, KA, Vederman, AC, McFadden, EM, et al. Differential executive functioning performance by phase of bipolar disorder. Bipolar Disord. 2012;14(5):527536.CrossRefGoogle ScholarPubMed
Zubieta, JK, Huguelet, P, O’Neil, RL, et al. Cognitive function in euthymic bipolar I disorder. Psychiatry Res. 2001;102(1):920.CrossRefGoogle ScholarPubMed
Langenecker, SA, Saunders, EF, Kade, AM, et al. Intermediate: cognitive phenotypes in bipolar disorder. J Affect Disord. 2010;122(3):285293.CrossRefGoogle ScholarPubMed
Robinson, LJ, Thompson, JM, Gallagher, P, et al. A meta-analysis of cognitive deficits in euthymic patients with bipolar disorder. J Affect Disord. 2006;93(1–3):105115.CrossRefGoogle ScholarPubMed
Lima, F, Rabelo-da-Ponte, FD, Bucker, J, et al. Identifying cognitive subgroups in bipolar disorder: a cluster analysis. J Affect Disord. 2019;246:252261.CrossRefGoogle ScholarPubMed
Burdick, KE, Russo, M, Frangou, S, et al. Empirical evidence for discrete neurocognitive subgroups in bipolar disorder: clinical implications. Psychol Med. 2014;44(14):30833096.CrossRefGoogle ScholarPubMed
Cardoso, T, Bauer, IE, Meyer, TD, et al. Neuroprogression and cognitive functioning in bipolar disorder: a systematic review. Curr Psychiatry Rep. 2015;17(9):75.CrossRefGoogle ScholarPubMed
Sanchez-Morla, EM, Lopez-Villarreal, A, Jimenez-Lopez, E, et al. Impact of number of episodes on neurocognitive trajectory in bipolar disorder patients: a 5-year follow-up study. Psychol Med. 2019;49(8):12991307.CrossRefGoogle ScholarPubMed
Roux, P, Etain, B, Cannavo, AS, et al. Prevalence and determinants of cognitive impairment in the euthymic phase of bipolar disorders: results from the FACE-BD cohort. Psychol Med. 2019;49(3):519527.CrossRefGoogle ScholarPubMed
Chang, HH, Chou, CH, Chen, PS, et al. High prevalence of metabolic disturbances in patients with bipolar disorder in Taiwan. J Affect Disord. 2009;117(1–2):124129.CrossRefGoogle ScholarPubMed
Chang, HH, Yang, YK, Gean, PW, et al. The role of valproate in metabolic disturbances in bipolar disorder patients. J Affect Disord. 2010;124(3):319323.CrossRefGoogle ScholarPubMed
van Winkel, R, De Hert, M, Van Eyck, D, et al. Prevalence of diabetes and the metabolic syndrome in a sample of patients with bipolar disorder. Bipolar Disord. 2008;10(2):342348.CrossRefGoogle Scholar
Deng, Y, Scherer, PE. Adipokines as novel biomarkers and regulators of the metabolic syndrome. Ann N Y Acad Sci. 2010;1212:E1E19.CrossRefGoogle ScholarPubMed
Hotamisligil, GS. Inflammation and metabolic disorders. Nature. 2006;444(7121):860867.CrossRefGoogle ScholarPubMed
Cairns, K, McCarvill, T, Ruzickova, M, et al. Course of bipolar illness worsens after onset of insulin resistance. J Psychiatr Res. 2018;102:3437.CrossRefGoogle ScholarPubMed
Mansur, RB, Santos, CM, Rizzo, LB, et al. Brain-derived neurotrophic factor, impaired glucose metabolism, and bipolar disorder course. Bipolar Disord. 2016;18(4):373378.CrossRefGoogle ScholarPubMed
Mansur, RB, Rizzo, LB, Santos, CM, et al. Impaired glucose metabolism moderates the course of illness in bipolar disorder. J Affect Disord. 2016;195:5762.CrossRefGoogle ScholarPubMed
Calkin, CV, Ruzickova, M, Uher, R, et al. Insulin resistance and outcome in bipolar disorder. Br J Psychiatry. 2015;206(1):5257.CrossRefGoogle ScholarPubMed
Wiley, JF, Gruenewald, TL, Karlamangla, AS, et al. Modeling multisystem physiological dysregulation. Psychosom Med. 2016;78(3):290301.CrossRefGoogle ScholarPubMed
Calkin, CV, Gardner, DM, Ransom, T, et al. The relationship between bipolar disorder and type 2 diabetes: more than just co-morbid disorders. Ann Med. 2013;45(2):171181.CrossRefGoogle ScholarPubMed
Cigliobianco, M, Paoli, RA, Caletti, E, et al. Possible association between social cognition and metabolic dysfunctions in bipolar disorder and schizophrenia: preliminary results. J Affect Disord. 2019;246:828835.CrossRefGoogle ScholarPubMed
Bora, E, McIntyre, RS, Ozerdem, A. Neurococognitive and neuroimaging correlates of obesity and components of metabolic syndrome in bipolar disorder: a systematic review. Psychol Med. 2019;49(5):738749.CrossRefGoogle ScholarPubMed
Neergaard, JS, Dragsbaek, K, Christiansen, C, et al. Metabolic syndrome, insulin resistance, and cognitive dysfunction: does your metabolic profile affect your brain? Diabetes. 2017;66(7):19571963.CrossRefGoogle ScholarPubMed
Angelico, F, Del Ben, M, Conti, R, et al. Insulin resistance, the metabolic syndrome, and nonalcoholic fatty liver disease. J Clin Endocrinol Metab. 2005;90(3):15781582.CrossRefGoogle ScholarPubMed
Burrows, R, Correa-Burrows, P, Reyes, M, et al. Healthy chilean adolescents with HOMA-IR ≥ 2.6 have increased cardiometabolic risk: association with genetic, biological, and environmental factors. J Diabetes Res. 2015;2015:783296783296.CrossRefGoogle Scholar
Singh, Y, Garg, MK, Tandon, N, et al. A study of insulin resistance by HOMA-IR and its cut-off value to identify metabolic syndrome in urban Indian adolescents. J Clin Res Pediatr Endocrinol. 2013;5(4):245251.Google ScholarPubMed
Yin, J, Li, M, Xu, L, et al. Insulin resistance determined by Homeostasis Model Assessment(HOMA) and associations with metabolic syndrome among Chinese children and teenagers. Diabetol Metab Syndr. 2013;5(1):71.CrossRefGoogle ScholarPubMed
Heaton, R, Chelune, G, Talley, J, et al. Wisconsin Card Sorting Test Manual: Revised and Expanded. Florida: Psychological Assessment Resources; 1993.Google Scholar
Volkow, ND, Gur, RC, Wang, GJ, et al. Association between decline in brain dopamine activity with age and cognitive and motor impairment in healthy individuals. Am J Psychiatry. 1998;155(3):344349.Google ScholarPubMed
Bonnin, CM, Jimenez, E, Sole, B, et al. Lifetime psychotic symptoms, subthreshold depression and cognitive impairment as barriers to functional recovery in patients with bipolar disorder. J Clin Med. 2019;8(7)1046.CrossRefGoogle ScholarPubMed
Bora, E. Neurocognitive features in clinical subgroups of bipolar disorder: a meta-analysis. J Affect Disord. 2018;229:125134.CrossRefGoogle ScholarPubMed
Xu, N, Huggon, B, Saunders, KEA. Cognitive impairment in patients with bipolar disorder: impact of pharmacological treatment. CNS Drugs. 2020;34(1):2946.CrossRefGoogle ScholarPubMed
Calkin, CV. Insulin resistance takes center stage: a new paradigm in the progression of bipolar disorder. Ann Med. 2019;51(5–6):281293.CrossRefGoogle ScholarPubMed
Mansur, RB, Lee, Y, Subramaniapillai, M, et al. Parsing metabolic heterogeneity in mood disorders: a hypothesis-driven cluster analysis of glucose and insulin abnormalities. Bipolar Disord. 2020;22(1):7988.Google ScholarPubMed
Tseng, HH, Chang, HH, Wei, SY, et al. Peripheral inflammation is associated with dysfunctional corticostriatal circuitry and executive dysfunction in bipolar disorder patients. Brain Behav Immun. 2021;91:695702.CrossRefGoogle ScholarPubMed
Chang, HH, Chen, PS. Inflammatory biomarkers for mood disorders—a brief narrative review. Curr Pharm Des. 2020;26(2):236243.CrossRefGoogle ScholarPubMed
Fernandes, BS, Steiner, J, Molendijk, ML, et al. C-reactive protein concentrations across the mood spectrum in bipolar disorder: a systematic review and meta-analysis. Lancet Psychiatry. 2016;3(12):11471156.CrossRefGoogle ScholarPubMed
Craft, S, Stennis Watson, G. Insulin and neurodegenerative disease: shared and specific mechanisms. Lancet Neurol. 2004;3(3):169178.CrossRefGoogle ScholarPubMed
Kamintsky, L, Cairns, KA, Veksler, R, et al. Blood-brain barrier imaging as a potential biomarker for bipolar disorder progression. NeuroImage: Clin. 2020;26:102049.CrossRefGoogle ScholarPubMed
Kullmann, S, Heni, M, Hallschmid, M, et al. Brain insulin resistance at the crossroads of metabolic and cognitive disorders in humans. Physiol Rev. 2016;96(4):11691209.CrossRefGoogle ScholarPubMed
De Felice, FG, Lourenco, MV, Ferreira, ST. How does brain insulin resistance develop in Alzheimer’s disease? Alzheimers Dement. 2014;10(Suppl 1):S26, S32CrossRefGoogle ScholarPubMed
Mullins, RJ, Mustapic, M, Goetzl, EJ, et al. Exosomal biomarkers of brain insulin resistance associated with regional atrophy in Alzheimer’s disease. Hum Brain Mapp. 2017;38(4):19331940.CrossRefGoogle ScholarPubMed
Willette, AA, Bendlin, BB, Starks, EJ, et al. Association of insulin resistance with cerebral glucose uptake in late middle-aged adults at risk for Alzheimer disease. JAMA Neurol. 2015;72(9):10131020.CrossRefGoogle ScholarPubMed
Willette, AA, Johnson, SC, Birdsill, AC, et al. Insulin resistance predicts brain amyloid deposition in late middle-aged adults. Alzheimers Dement. 2015;11(5):504510, e501.CrossRefGoogle ScholarPubMed
Wu, KY, Chang, CM, Liang, HY, et al. Increased risk of developing dementia in patients with bipolar disorder: a nested matched case-control study. Bipolar Disord. 2013;15(7):787794.CrossRefGoogle ScholarPubMed
Diniz, BS, Teixeira, AL, Cao, F, et al. History of bipolar disorder and the risk of dementia: a systematic review and meta-analysis. Am J Geriatr Psychiatry. 2017;25(4):357362.CrossRefGoogle ScholarPubMed
Vancampfort, D, Mitchell, AJ, De Hert, M, et al. Prevalence and predictors of type 2 diabetes mellitus in people with bipolar disorder: a systematic review and meta-analysis. J Clin Psychiatry. 2015;76(11):14901499.CrossRefGoogle ScholarPubMed
Hamer, JA, Testani, D, Mansur, RB, et al. Brain insulin resistance: a treatment target for cognitive impairment and anhedonia in depression. Exp Neurol. 2019;315:18.CrossRefGoogle ScholarPubMed
Grigolon, RB, Brietzke, E, Mansur, RB, et al. Association between diabetes and mood disorders and the potential use of anti-hyperglycemic agents as antidepressants. Prog Neuropsychopharmacol Biol Psychiatry. 2019;95:109720.CrossRefGoogle ScholarPubMed
McIntyre, RS, Lee, Y, Carmona, NE, et al. Characterizing, assessing, and treating cognitive dysfunction in major depressive disorder. Harv Rev Psychiatry. 2018;26(5):241249.CrossRefGoogle ScholarPubMed
Ott, CV, Vinberg, M, Bowie, CR, et al. Effect of action-based cognitive remediation on cognition and neural activity in bipolar disorder: study protocol for a randomized controlled trial. Trials. 2018;19(1):487.CrossRefGoogle ScholarPubMed
Kapczinski, NS, Mwangi, B, Cassidy, RM, et al. Neuroprogression and illness trajectories in bipolar disorder. Expert Rev Neurother. 2017;17(3):277285.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Demographic Characteristics of the Euthymic BD Patients and the Control Subjects

Figure 1

Table 2. Performance of the Euthymic BD Patients and the Control Subjects in the Neuropsychological Functional Tests, Subgrouped by HOMA-IR

Figure 2

Figure 1. Post-hoc analyses of WCST preservative errors and HOMA-IR in the euthymic bipolar disorder patients and controls. Abbreviations: WCST, Wisconsin card-sorting test; HOMA-IR, homeostasis model assessment of insulin resistance; BD, bipolar disorder. *P < .05.

Supplementary material: File

Chang et al. supplementary material

Chang et al. supplementary material 1

Download Chang et al. supplementary material(File)
File 28.5 KB
Supplementary material: File

Chang et al. supplementary material

Chang et al. supplementary material 2

Download Chang et al. supplementary material(File)
File 33.1 KB