Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex.

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

White Noise-Is Anxiety in Late-Life Associated With White Matter Hyperintensity Burden?

OBJECTIVE: We investigated the relationship between anxiety phenotypes (global anxiety, worry, and rumination) and white matter hyperintensities (WMH), with special consideration for the roles of age and executive function (EF). Our hypotheses were 1) anxiety phenotypes would be associated with WMH and 2) EF would moderate this relationship. DESIGN: Cross-sectional. SETTING: Participants were recruited from the local community (Pittsburgh, PA). PARTICIPANTS: We recruited 110 older adults (age ≥ 50) with varying worry severity and clinical comorbidity. INTERVENTIONS: Not applicable. MEASUREMENTS: Demographics (age, sex, race, education), clinical measures (cumulative illness burden, global anxiety, worry, and rumination), EF, and WMH quantified with magnetic resonance imaging. RESULTS: Lower global anxiety and worry severity were significantly correlated with higher WMH volume, though the global anxiety relationship was not significant after controlling for age. Rumination as not associated with WMH burden. EF was not correlated with either global anxiety, worry, rumination, or WMH. However, in those with advanced age and/or greater WMH burden, there was an association between worry and EF as well as EF and WMH. CONCLUSION: Longitudinal studies are needed in order to clarify the complex interactions between anxiety phenotypes, WMH, and EF.

Biological factors influencing depression in later life: role of aging processes and treatment implications.

Late-life depression occurring in older adults is common, recurrent, and malignant. It is characterized by affective symptoms, but also cognitive decline, medical comorbidity, and physical disability. This behavioral and cognitive presentation results from altered function of discrete functional brain networks and circuits. A wide range of factors across the lifespan contributes to fragility and vulnerability of those networks to dysfunction. In many cases, these factors occur earlier in life and contribute to adolescent or earlier adulthood depressive episodes, where the onset was related to adverse childhood events, maladaptive personality traits, reproductive events, or other factors. Other individuals exhibit a later-life onset characterized by medical comorbidity, pro-inflammatory processes, cerebrovascular disease, or developing neurodegenerative processes. These later-life processes may not only lead to vulnerability to the affective symptoms, but also contribute to the comorbid cognitive and physical symptoms. Importantly, repeated depressive episodes themselves may accelerate the aging process by shifting allostatic processes to dysfunctional states and increasing allostatic load through the hypothalamic-pituitary-adrenal axis and inflammatory processes. Over time, this may accelerate the path of biological aging, leading to greater brain atrophy, cognitive decline, and the development of physical decline and frailty. It is unclear whether successful treatment of depression and avoidance of recurrent episodes would shift biological aging processes back towards a more normative trajectory. However, current antidepressant treatments exhibit good efficacy for older adults, including pharmacotherapy, neuromodulation, and psychotherapy, with recent work in these areas providing new guidance on optimal treatment approaches. Moreover, there is a host of nonpharmacological treatment approaches being examined that take advantage of resiliency factors and decrease vulnerability to depression. Thus, while late-life depression is a recurrent yet highly heterogeneous disorder, better phenotypic characterization provides opportunities to better utilize a range of nonspecific and targeted interventions that can promote recovery, resilience, and maintenance of remission.

Depressive symptoms anticipate behavioral and emotional factors among older adults: A prospective cross-lagged panel design.

This study examined the temporal relationship among depression, anxiety, insomnia, perceived stress, and physical activity in adults aged 60+ years with a history of major depressive disorder. We conducted a longitudinal study with 12 weeks of follow-up. Assessments consisted of phone or video interviews and included questionnaires evaluating depression, anxiety, insomnia, perceived stress, and physical activity. Our analytic approach consisted of a depression-focused cross-lagged panel model (CLPM) to examine week-to-week correlations among the five measures. The depression-focused CLPM identified statistically significant week-to-week self-predictive effects for each of the five measures. Higher depressive symptom burden was a strong predictor of increased stress, greater insomnia, and less physical activity the following week. No other cross-measure predictions were statistically significant. Our analytical approach clarifies the directional relationship among variables that typically co-occur with depression showing that higher depression symptom burden predisposes older adults to poor sleep, a reduced level of daytime activity, and a greater sense of stress. These findings support the need for longitudinal assessments and targeted interventions for reducing symptoms of depression in older adults.

MRI predictors of pharmacotherapy response in major depressive disorder.

Major depressive disorder is among the most prevalent psychiatric disorders, exacting a substantial personal, social, and economic toll. Antidepressant treatment typically involves an individualized trial and error approach with an inconsistent success rate. Despite a pressing need, no reliable biomarkers for predicting treatment outcome have yet been discovered. Brain MRI measures hold promise in this regard, though clinical translation remains elusive. In this review, we summarize structural MRI and functional MRI (fMRI) measures that have been investigated as predictors of treatment outcome. We broadly divide these into five categories including three structural measures: volumetric, white matter burden, and white matter integrity; and two functional measures: resting state fMRI and task fMRI. Currently, larger hippocampal volume is the most widely replicated predictor of successful treatment. Lower white matter hyperintensity burden has shown robustness in late life depression. However, both have modest discriminative power. Higher fractional anisotropy of the cingulum bundle and frontal white matter, amygdala hypoactivation and anterior cingulate cortex hyperactivation in response to negative emotional stimuli, and hyperconnectivity within the default mode network (DMN) and between the DMN and executive control network also show promise as predictors of successful treatment. Such network-focused measures may ultimately provide a higher-dimensional measure of treatment response with closer ties to the underlying neurobiology.

Networks of worry-towards a connectivity-based signature of late-life worry using higher criticism.

Severe worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults.