Parsing metabolic heterogeneity in mood disorders: A hypothesis‐driven cluster analysis of glucose and insulin abnormalities

Abstract

Objectives Metabolically based distinctions for disturbances in glucose and insulin may provide meaningful insights both clinically and mechanistically. Methods Data were derived from 352 subjects of previously completed clinical studies with a mood disorder (MD) (bipolar disorder: n = 179, major depressive disorder: n = 173) and 218 healthy controls from the Comprehensive Assessment of Long‐Term Effects of Reducing Intake of Energy. We conducted a factor analysis to replicate a priori dissociable factors informed by glucose and insulin levels and indices of insulin resistance and beta‐cell function: elevated insulin and insulin resistance (“insulin‐IR”), and increased fasting glucose and reduced insulin secretion (“glucotoxicity”). Cluster analyses were conducted, separately in men and women, to evaluate the clinical relevance of subtyping individuals with MDs using insulin‐IR and glucotoxicity (GT) factor scores. Results Factors insulin‐IR and GT explained 92.64% and 92.09% of the variance in men and women respectively. Three clusters were replicated in men and women separately: metabolically healthy (MH), high GT, and insulin‐resistant (IR). After adjusting for age, gender, study cohort, MD diagnosis, and antipsychotics use, body mass index (BMI) and mean arterial pressure were higher in IR‐ vs GT‐ or MH‐clustered individuals; GT‐clustered individuals had more metabolic syndrome components and higher C‐reactive protein. Glucotoxic‐clustered subjects reported greater impairments in cognitive function and global functioning when compared to MH‐ or IR‐clustered subjects. Conclusions Using simple, cost‐effective, and accessible measures, we identified stable, gender‐convergent, subgroups of individuals that significantly diverged on measures of cognitive dysfunction, self‐reported anhedonia, functional disability, BMI, and blood pressure.

Mental health status of individuals with a mood-disorder during the COVID-19 pandemic in Australia: Initial results from the COLLATE project

“…Further, in mood disorders there is a heightened prevalence of cooccurring medical conditions such as obesity, diabetes and cardiovascular disease (Coello et al, 2019;Dalack and Roose, 1990;Goldstein et al, 2020;Mansur et al, 2019). These have been linked to a more severe coronavirus 2 (SARS-CoV-2) manifestation (Zaman et al, 2020), and may amplify psychological distress by increasing a patient's worries about the heightened personal risk of infection-related mortality or poor long-term health outcomes (Goldstein, 2017;Mansur et al, 2015;Zaman et al, 2020).…”

Peripheral insulin sensitivity predicting cognitive function in euthymic bipolar disorder patients

“…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 39 40 In addition, levels of inflammatory biomarkers, such as peripheral CRP, has also been considered to help stratifying the outcomes in treating mood disorders 41 .…”

“…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. 39,40 In addition, levels of inflammatory biomarkers, such as peripheral CRP, has also been considered to help stratifying the outcomes in treating mood disorders. 41 In BD, the peripheral CRP level is elevated prominently during the manic state, but is still moderately elevated during the depressive and euthymic states 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).…”

A Possible Antidepressive Effect of Dietary Interventions: Emergent Findings and Research Challenges

“…Opposed to the application of pharmacological interventions which is largely symptom-based, nutritional interventions may integrate with the RDoC to address certain aspects of mood disorder pathophysiology. For example, some authors postulate that metabolic and nutritional variables could be more strongly associated to some domains of the depressive psychopathology (e.g., anhedonia) than to the general depressive symptomatic expression [ 85 ]. Therefore, it may even become clear that some constructs (e.g., mood changes and metabolic imbalances) should be treated together.…”