patient care perspectives

The Obesity-Depression Cycle: Insights From Functional Imaging

by Roger McIntyre, MD

Overview

In the “pathophysiologic Venn diagram” of 3 prevalent clinical entities – mood disorders, cognitive impairment (or, trajectory of cognitive decline), and obesity – the intersection of these 3 circles has launched new research with results that are spurring scientific interest and generating novel hypotheses. Major depressive disorder (MDD) and obesity may have an additive effect on cognition that leads to measurable deficits in cognitive performance on neuropsychological tests. Here, emerging research utilizing functional brain magnetic resonance imaging (fMRI) modeling evaluates networks believed to be important in obesity, psychiatric illness, and perhaps both.

Expert Commentary

Roger McIntyre, MD

Professor of Psychiatry and Pharmacology
University of Toronto
Head, Mood Disorders Psychopharmacology Unit
University Health Network
Toronto, Ontario

Epidemiological studies have revealed an association between obesity and cognitive impairment in otherwise healthy subjects. Additionally, obesity is associated with significant reductions in both gray and white matter volumes, particularly within the frontal lobes.

Mechanisms underlying the associations between obesity and diabetes and cognitive dysfunction are unclear; however, one hypothesis proposes that adaptations in dopamine signaling secondary to diet, adiposity, and metabolic dysfunction underlie neurocognitive impairment in diabetes and obesity.

 

Obesity Depression graph

 

In MDD, cognitive impairment is recognized as a principal mediator of psychosocial impairment, although antidepressant medications have not generally been shown to improve measures of cognitive control and executive function. Vortioxetine is an exception in that it is a multimodal antidepressant that has been reported to improve performance in objective measures of cognition.

Over the years, the cognitive impairment of MDD has been the source of considerable debate: do cognitive deficits simply reflect a state marker of the depressive episode; or perhaps a manifestation of pre-existing susceptibility or vulnerability to MDD; or, perhaps “the scar hypothesis” has more merit, whereby cognitive dysfunction is predominantly a consequence of the first episode of MDD and is thereafter expected to persist or worsen with subsequent episodes.

More recently, results from a systematic review including 29 publications, representing 34 unique samples and 121,749 participants, suggested that the cognitive deficits predicting MDD likely represent deleterious effects of subclinical depression symptoms on performance, rather than premorbid risk factors for disorder. While the debate over state vs trait continues, evidence supports the concept that the association between obesity and MDD at the observational level may be explained, at least in part, by shared genetic factors.

In parallel, there has been growing interest in the differences between obese and lean subjects in the activation of certain brain regions or networks, spurred on by fMRI techniques that measure brain activity by detecting changes associated with blood oxygenation level-dependent (BOLD) signals. Recently, Chao and colleagues applied such techniques to the study of obesity and psychiatric illness in a group of patients ranging in age from 22 to 58 years. Patients were assessed for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS):

Multimodality imaging models were used to assess brain functional connectivity differences between normal weight, control, and obese participants. Investigators identified a disruption in the default mode network (DMN) and dysfunction in reward-based learning and reward processing (including differences in the anterior cingulate cortex, the orbitofrontal cortex, and the amygdala) in patients with morbid obesity when compared to normal weight individuals.

The authors suggested that a larger sample size study with specific eating behavior phenotype subgroups and longitudinal design in the future might help delineate the dysfunction brain circuits in obesity in detail and clarify the causal relationships.

Adiposity is clearly only a piece of the broader picture of MDD and cognition. Moderately vigorous physical activity has shown a positive influence on cognitive control that persists following the adjustment of significant covariates and adiposity. Nonetheless, the overlap between obesity and MDD as relates to cognitive function is intriguing and promises to spur advances across disciplines.

 

References

Baumgartner NW, Walk AD, Edwards CG, et al. Relationship between physical activity, adiposity, and attentional inhibition. J Phys Act Health. September 5, 2017;1-20. doi: 10.1123/jpah.2017-0181. [Epub ahead of print].

Beyer F, Kharabian Masouleh S, Huntenburg JM, et al. Higher body mass index is associated with reduced posterior default mode connectivity in older adults. Hum Brain Mapp. April 11, 2017. doi: 10.1002/hbm.23605. [Epub ahead of print].

Boeka AG, Lokken KL. Neuropsychological performance of a clinical sample of extremely obese individuals.
Arch Clin Neuropsychol. 2008;23(4):467-474.

Chao SH, Liao YT, Chen VC, et al. Correlation between brain circuit segregation and obesity. Behav Brain Res. September 8, 2017. pii: S0166-4328(17)31064-1. doi: 10.1016/j.bbr.2017.09.017. [Epub ahead of print].

Garasia S, Samaan Z, Gerstein HC, et al. Influence of depression on genetic predisposition to type 2 diabetes in a multiethnic longitudinal study. Sci Rep. 2017;7:1629.

Hsu FC, Yuan M, Bowden DW, et al. Adiposity is inversely associated with hippocampal volume in African Americans and European Americans with diabetes. J Diabetes Complications. 2016;30(8):1506-1512.

Kaur S, Gonzales MM, Tarumi T, et al. Serum brain-derived neurotrophic factor mediates the relationship between abdominal adiposity and executive function in middle age. J Int Neuropsychol Soc. 2016;22(5):493-500.

Luppino FS, de Wit LM, Bouvy PF, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010;67(3):220-229.

Mansur RB, Zugman A, Ahmed J, et al. Treatment with a GLP-1R agonist over four weeks promotes weight loss-moderated changes in frontal-striatal brain structures in individuals with mood disorders. Eur Neuropsychopharmacol. August 31, 2017. pii: S0924-977X(17)30900-8. doi: 10.1016/j.euroneuro.2017.08.433. [Epub ahead of print].

Marsland AL, Gianaros PJ, Kuan DC-H, et al. Brain morphology links systemic inflammation to cognitive function in midlife adults. Brain Behav Immun. 2015;48:195-204.

Restivo MR, McKinnon MC, Frey BN, et al. The impact of obesity on neuropsychological functioning in adults with and without major depressive disorder. In: Gualtieri C, ed. PLoS ONE. 2017;12(5):e0176898.

Samaan Z, Lee YK, Gerstein HC, et al. Obesity genes and risk of major depressive disorder in a multiethnic population: a cross-sectional study. J Clin Psychiatry. 2015;76(12):e1611-e1618.

Scult MA, Paulli AR, Mazure ES, et al. The association between cognitive function and subsequent depression: a systematic review and meta-analysis. Psychol Med. 2017;47(1):1-17.

Simon GE, Von Korff M, Saunders, et al. Association between obesity and psychiatric disorders in the US adult population. Arch Gen Psychiatry. 2006;63(7):824-830.

West NA, Lirette ST, Cannon VA, et al. Adiposity, change in adiposity, and cognitive decline in mid- and late life. J Am Geriatr Soc. 2017;65(6):1282-1288.

Yokum S, Ng J, Stice E. Relation of regional grey and white matter volumes to current BMI and future increases in BMI: a prospective MRI study. Int J Obes (Lond). 2012;36(5):656-664.

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