Brain age is not a significant predictor of relapse risk in late-life depression.

INTRODUCTION: Late-life depression (LLD) has been associated cross-sectionally with lower brain structural volumes and accelerated brain aging compared to healthy controls (HC). There are few longitudinal studies on the neurobiological predictors of recurrence in LLD. We tested a machine learning (ML) brain age model and its prospective association with LLD recurrence risk. METHODS: We recruited individuals with LLD (n=102) and HC (n=43) into a multi-site 2-yr longitudinal study. Individuals with LLD were enrolled within 4 months of remission. Remitted LLD participants underwent baseline neuroimaging and longitudinal clinical follow-up. Over 2 years, 43 LLD participants relapsed (REL) and 59 stayed in remission (REM). We used a previously developed ML brain age algorithm to compute brain age at baseline and we evaluated brain age group differences (HC vs. LLD and HC vs. REM vs. REL). We conducted a Cox proportional hazards model to evaluate whether baseline brain age predicted time to relapse. RESULTS: We found that brain age did not significantly differ between HC and LLD as well as HC, REM, and REL groups. Brain age did not significantly predict time to relapse. DISCUSSION: In contrast to our hypothesis, we found that brain age did not differ between non-depressed controls and individuals with remitted LLD, and brain age was not associated with subsequent recurrence. This is in contrast to existing literature which has identified baseline brain age differences in late life but in line with work that shows no differences between those who do and do not relapse on gross structural measures.

A preliminary investigation of worry, cortical amyloid burden, and stressor-evoked brain and cardiovascular reactivity in older adults.

Worry is a transdiagnostic symptom common to many neurocognitive disorders of aging, including early stages of Alzheimer's disease and related dementias (ADRD). Severe worry is associated with amyloid burden in cognitively intact older adults, yet the mechanisms underlying this association are not well understood. We hypothesize that this relationship involves altered brain and cardiovascular reactivity to acute stressors, a brain-body phenotype that also increases risk for cardiovascular disease. Twenty cognitively normal older adults (age 60 to 80) with varying levels of worry severity underwent positron emission tomography using Pittsburgh Compound-B and functional magnetic resonance imaging. We examined associations of worry severity and amyloid burden with cardiovascular reactivity, brain activation, and brain connectivity using a cognitive stressor task. Worry severity was not associated with global amyloid burden, but was associated with greater resting levels of cardiovascular physiology and lower systolic blood pressure reactivity. Worry severity also was associated with altered stressor-evoked activation and effective connectivity in brain circuits implicated in stress processing, emotion perception, and physiological regulation. These associations showed small to medium effect sizes. These preliminary findings introduce key components of a model that may link severe worry to ADRD risk via stressor-evoked brain-body interactions.

Hippocampal subfield volume in older adults with and without mild cognitive impairment: Effects of worry and cognitive reappraisal.

Studies have confirmed that anxiety, especially worry and rumination, are associated with increased risk for cognitive decline, including Alzheimer's disease and related dementias (ADRD). Hippocampal atrophy is a hallmark of ADRD. We investigated the association between hippocampus and its subfield volumes and late-life global anxiety, worry, and rumination, and emotion regulation strategies. We recruited 110 participants with varying worry severity who underwent magnetic resonance imaging and clinical interviews. We conducted cross-sectional regression analysis between each subfield and anxiety, worry, rumination, reappraisal, and suppression while adjusting for age, sex, race, education, cumulative illness burden, stress, neuroticism, and intracranial volume. We imputed missing data and corrected for multiple comparisons across regions. Greater worry was associated with smaller subiculum volume, whereas greater use of reappraisal was associated with larger subiculum and CA1 volume. Greater worry may be detrimental to the hippocampus and to subfields involved in early ADRD pathology. Use of reappraisal appears protective of hippocampal structure. Worry and reappraisal may be modifiable targets for ADRD prevention.

Assessing depression recurrence, cognitive burden, and neurobiological homeostasis in late life: Design and rationale of the REMBRANDT Study.

Background: Late-life depression is characterized by disability, cognitive impairment and decline, and a high risk of recurrence following remission. Aside from past psychiatric history, prognostic neurobiological and clinical factors influencing recurrence risk are unclear. Moreover, it is unclear if cognitive impairment predisposes to recurrence, or whether recurrent episodes may accelerate brain aging and cognitive decline. The purpose of the REMBRANDT study (Recurrence markers, cognitive burden, and neurobiological homeostasis in late-life depression) is to better elucidate these relationships and identify phenotypic, cognitive, environmental, and neurobiological factors contributing to and predictive of depression recurrence. Methods: Across three sites, REMBRANDT will enroll 300 depressed elders who will receive antidepressant treatment. The goal is to enroll 210 remitted depressed participants and 75 participants with no mental health history into a two-year longitudinal phase focusing on depression recurrence. Participants are evaluated every 2 months with deeper assessments occurring every 8 months, including structural and functional neuroimaging, environmental stress assessments, deep symptom phenotyping, and two weeks of 'burst' ecological momentary assessments to elucidate variability in symptoms and cognitive performance. A broad neuropsychological test battery is completed at the beginning and end of the longitudinal study. Significance: REMBRANDT will improve our understanding of how alterations in neural circuits and cognition that persist during remission contribute to depression recurrence vulnerability. It will also elucidate how these processes may contribute to cognitive impairment and decline. This project will obtain deep phenotypic data that will help identify vulnerability and resilience factors that can help stratify individual clinical risk.

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.

Impact of symptomatic menopausal transition on the occurrence of depression, anxiety, and sleep disorders: A real-world multi-site study.

BACKGROUND: The menopause transition is a vulnerable period that can be associated with changes in mood and cognition. The present study aimed to investigate whether a symptomatic menopausal transition increases the risks of depression, anxiety, and sleep disorders. METHODS: This population-based, retrospective cohort study analysed data from five electronic health record databases in South Korea. Women aged 45-64 years with and without symptomatic menopausal transition were matched 1:1 using propensity-score matching. Subgroup analyses were conducted according to age and use of hormone replacement therapy (HRT). A primary analysis of 5-year follow-up data was conducted, and an intention-to-treat analysis was performed to identify different risk windows over 5 or 10 years. The primary outcome was first-time diagnosis of depression, anxiety, and sleep disorder. We used Cox proportional hazard models and a meta-analysis to calculate the summary hazard ratio (HR) estimates across the databases. RESULTS: Propensity-score matching resulted in a sample of 17,098 women. Summary HRs for depression (2.10; 95% confidence interval [CI] 1.63-2.71), anxiety (1.64; 95% CI 1.01-2.66), and sleep disorders (1.47; 95% CI 1.16-1.88) were higher in the symptomatic menopausal transition group. In the subgroup analysis, the use of HRT was associated with an increased risk of depression (2.21; 95% CI 1.07-4.55) and sleep disorders (2.51; 95% CI 1.25-5.04) when compared with non-use of HRT. CONCLUSIONS: Our findings suggest that women with symptomatic menopausal transition exhibit an increased risk of developing depression, anxiety, and sleep disorders. Therefore, women experiencing a symptomatic menopausal transition should be monitored closely so that interventions can be applied early.

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.

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.

It goes both ways: The relationship between anxiety and mild cognitive impairment.

OBJECTIVE: To investigate the relationship between anxiety and mild cognitive impairment (MCI), and whether it is mediated by perceived stress, at the population level. METHOD AND DESIGN: In a longitudinal study of 368 adults aged 65+ from a population-based cohort, we annually assessed anxiety symptoms (GAD-7), perceived stress (PSS-4), and ratings on the Clinical Dementia Rating (CDR®), where CDR = 0.5 was operationalized as MCI. Examining data from three consecutive assessment waves, we first determined the associations between anxiety at the first wave with MCI at the third wave, and vice versa. We then used mediation analyses to determine whether the pathways in both directions were mediated by perceived stress at the second wave, adjusting for demographics and other relevant covariates. RESULTS: We confirmed significant bidirectional longitudinal associations between anxiety and MCI. Perceived stress was detected as a significant mediator for both pathways between anxiety and MCI, explaining 37.1% of the total effect (TE) of anxiety on incident MCI while conversely explaining 27.1% of the TE of MCI on anxiety. CONCLUSIONS: A bidirectional relationship with a 2-year lag between anxiety and MCI was mediated through perceived stress. Clinicians should be sensitive both to potential consequent anxiety when patients present with cognitive impairment, and to potential incipient MCI when the presenting complaint is anxiety. Managing stress may help mitigate adverse outcomes.

Is Anxiety in Late Life an Uncharted Territory?-Questioning the USPSTF Draft Recommendation Statement for Anxiety Screening in Older Adults.

This Viewpoint discusses the updated US Preventive Services Task Force recommendations for anxiety screening in adults.

Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction.

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49-89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06-1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76-3.61), p < 0.001 for dementia]. Baseline brain age residual was predictive of future cognitive worsening even after adjusting for apolipoprotein E e4 and amyloid status [Hazard Ratio, (95% CI): 1.94 (1.33-2.81), p = 0.001 for total 336 follow-up sample; 2.31 (1.44-3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43-4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment 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.

Thinking of Me or Thinking of You? Behavioral Correlates of Self vs. Other Centered Worry and Reappraisal in Late-Life.

Psychotherapeutic approaches in late-life anxiety have limited effect on reducing worry severity. The self-referential processing of worry contents (self- vs. other-focused worry) and reappraisal styles (internal vs. external locus of control) are important elements in psychotherapy, but little is known about these processes in late-life. We aimed to characterize severe worry from a self-referential processing perspective. We recruited 104 older adults with various levels of worry and used a personalized task to induce and reappraise worry. We analyzed the association between (1) worry severity/frequency for worry content (self- or other-focused) and (2) for reappraisal style (internal vs. external locus of control) with clinical inventories measuring anxiety, worry, depression, rumination, neuroticism, emotion regulation strategies, perceived stress, and physical illness burden. Higher self-worry severity was associated with higher scores of clinical inventories of worry, depression, perceived stress, and neuroticism, whereas other-worry severity did not show any association. Greater self-worry frequency was associated with higher medical burden. External locus of control in reappraisal statements was associated with lower worry severity in men. Overall, more severe and frequent self-focused worry was associated with a greater psychological and physiological burden. These results are useful in tailoring psychotherapy for older adults with severe worry.

Are All Anxieties Created Equal? Stress-related Networks and Anxiety Phenotypes in Old Age.

OBJECTIVE: The dysregulation of stress-related networks due to chronic symptoms such as severe worry and/or rumination is one of the putative pathways linking anxiety in late-life with cognitive decline and increased cardiovascular burden. Symptoms such as severe worry or rumination respond poorly to standard treatment and drive the morbidity associated with anxiety in older adults. We assessed if any of the neural networks anchored in the stress-related regions of interest (ROIs) are associated with distinct anxiety phenotypes (worry, rumination and global anxiety). METHODS: We recruited older participants (over 50 years of age) with varying levels of worry (N = 91) to undergo resting state fMRI. We computed seed-based connectivity for each ROI: the bed nucleus of the stria terminalis, the paraventricular nucleus of the hypothalamus, habenula, and amygdala. We limited our connectivity analyses to extracted regions for each seeded ROI-based network based on their canonical networks in 1,000 participants (Neurosynth). Using connectivity and clinical factors, we fit cross-validated elastic net models to predict scores on Penn State Worry Questionnaire, Rumination Subscale Questionnaire, Hamilton Anxiety Rating Scale, and Perceived Stress Scale. RESULTS: We identified several distinct connectivity patterns that predict anxiety phenotypes' severity. Greater worry was associated with greater paraventricular nucleus of the hypothalamus -subgenual anterior cingulate cortex, parahippocampal, and olfactory and amygdala-PHC connectivity. Greater global anxiety was associated with lower amygdala-superior temporal gyrus connectivity. Greater perceived stress was associated with lower amygdala-inferior temporal gyrus and amygdala-fusiform gyrus connectivity. CONCLUSION: Our study suggests that various late-life anxiety phenotypes (worry, global anxiety, rumination) may be associated with varying functional connectivity related to stress and emotion regulation. This may aid in the development of future targeted interventions.

Network modeling of anxiety and psychological characteristics on suicidal behavior: Cross-sectional study.

BACKGROUND: Suicide is influenced by complex interactions among various psychopathological features. We aimed to examine the relationship between suicide risk and psychological risk factors such as defense mechanisms, personality, and anxiety. METHODS: We established a psychiatric database by utilizing the Observational Medical Outcomes Partnership Common Data Model. We conducted a 1:1 propensity score matching with age, sex, and depression severity, and identified a sample (n = 258) with two groups: those with suicidal behavior and those with non-suicidal behavior. Using principal component analysis, we extracted nine psychological scales and applied network analysis to compare relationships among psychological factors between the two groups. RESULTS: Patients with non-suicidal behaviors showed associations between trait anxiety and defense mechanisms, while those with suicidal behaviors did not. For patients with suicidal ideation there was an association between somatization and trait anxiety. Patients with suicide attempts showed associations between paranoia and dissociation connected to trait anxiety. LIMITATIONS: Longitudinal research is required to fully observe transitions from suicidal ideation to attempts and recurrent suicidal events. In addition, these networks may not generalize suicidal behaviors because the group participants are not homogeneous. Lastly, data from self-report questionnaires limits the reliability of responses. CONCLUSIONS: We presented important new insights on suicidal behavior by estimating psychological networks. Patients with non-suicidal behavior may exhibit discrete relationships between defense mechanisms and anxiety, compared to those with suicidal behavior. Patients with suicidal ideation and suicide attempts may show distinct associations between anxiety and psychopathological features.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

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.