Metabolic dysregulation is currently considered a major risk factor for hippocampal pathology. The aim of the present study was to characterize the influence of key metabolic drivers on functional connectivity of the hippocampus in healthy adults.

Insulin resistance was directly quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test and fasting levels of insulin, glucose, leptin, and cortisol, and measurements of body mass index and waist circumference were obtained in a sample of healthy cognitively intact adults (n = 104). Resting-state neuroimaging data were also acquired for the quantification of hippocampal functional cohesiveness and integration with the major resting-state networks (RSNs). Data-driven analysis using unsupervised machine learning (k-means clustering) was then employed to identify clusters of individuals based on their metabolic and functional connectivity profiles.

K-means clustering identified two clusters of increasing metabolic deviance evidenced by cluster differences in the plasma levels of leptin (40.36 (29.97) vs. 27.59 (25.58) μg/L) and the degree of insulin resistance (SSPG concentration: 161.63 (65.27) vs. 125.72 (66.81) mg/dL). Individuals in the cluster with higher metabolic deviance showed lower functional cohesiveness within each hippocampus and lower integration of posterior and anterior components of the left and right hippocampus with the major RSNs. The two clusters did not differ in general intellectual ability or episodic memory.

We identified two clusters of individuals differentiated by abnormalities in insulin resistance, leptin levels, and hippocampal connectivity, with one of the clusters showing greater deviance. These findings support the link between metabolic dysregulation and hippocampal function even in nonclinical samples.

Early life adversity is associated with both metabolic impairment and depression in adulthood, as well as with poorer responses to antidepressant medications. It is not yet known whether individual differences in sensitivity to antidiabetic medications could also be related to early life adversity. We examined whether a history of early life adversity affected the observed changes in metabolic function and depressive symptoms in a randomized trial of pioglitazone for augmentation of standard treatments for depression.

Early life adversity is associated with both metabolic impairment and depression in adulthood, as well as with poorer responses to antidepressant medications. It is not yet known whether individual differences in sensitivity to antidiabetic medications could also be related to early life adversity. We examined whether a history of early life adversity affected the observed changes in metabolic function and depressive symptoms in a randomized trial of pioglitazone for augmentation of standard treatments for depression.

We found that early life adversity significantly impaired the metabolic response to pioglitazone. Effects on depressive symptoms did not reach significance, but nonetheless suggested that pioglitazone could mitigate the depressant effects of childhood adversity, only among those insulin resistant at baseline.

We conclude that a history of early life adversity may impair the body’s ability to respond to insulin sensitizing pharmacotherapy, and furthermore that its contribution to resistant depression may function in part via the generation of an insulin resistant phenotype.