Treatment resistant late-life depression: A narrative review of psychosocial risk factors, non-pharmacological interventions, and the role of clinical phenotyping.

BACKGROUND: Treatment resistant depression (TRD) is a subset of major depressive disorder (MDD) in which symptoms do not respond to front line therapies. In older adults, the assessment and treatment of TRD is complicated by psychosocial risk factors unique to this population, as well as a relative paucity of research. METHODS: Narrative review aimed at (1) defining TRLLD for clinical practice and research; (2) describing psychosocial risk factors; (3) reviewing psychological and non-pharmacological treatments; (4) discussing the role of clinical phenotyping for personalized treatment; and (5) outlining research priorities. RESULTS: Our definition of TRLLD centers on response to medication and neuromodulation in primary depressive disorders. Psychosocial risk factors include trauma and early life adversity, chronic physical illness, social isolation, personality, and barriers to care. Promising non-pharmacological treatments include cognitive training, psychotherapy, and lifestyle interventions. The utility of clinical phenotyping is highlighted by studies examining the impact of comorbidities, symptom dimensions (e.g., apathy), and structural/functional brain changes. LIMITATIONS: There is a relative paucity of TRLLD research. This limits the scope of empirical data from which to derive reliable patterns and complicates efforts to evaluate the literature quantitatively. CONCLUSIONS: TRLLD is a complex disorder that demands further investigation given our aging population. While this review highlights the promising breadth of TRLLD research to date, more research is needed to help elucidate, for example, the optimal timing for implementing risk mitigation strategies, the value of collaborative care approaches, specific treatment components associated with more robust response, and phenotyping to help inform treatment decisions.

Cognitive Symptoms of Post-COVID-19 Condition and Daily Functioning.

Importance: The frequent occurrence of cognitive symptoms in post-COVID-19 condition has been described, but the nature of these symptoms and their demographic and functional factors are not well characterized in generalizable populations. Objective: To investigate the prevalence of self-reported cognitive symptoms in post-COVID-19 condition, in comparison with individuals with prior acute SARS-CoV-2 infection who did not develop post-COVID-19 condition, and their association with other individual features, including depressive symptoms and functional status. Design, Setting, and Participants: Two waves of a 50-state nonprobability population-based internet survey conducted between December 22, 2022, and May 5, 2023. Participants included survey respondents aged 18 years and older. Exposure: Post-COVID-19 condition, defined as self-report of symptoms attributed to COVID-19 beyond 2 months after the initial month of illness. Main Outcomes and Measures: Seven items from the Neuro-QoL cognition battery assessing the frequency of cognitive symptoms in the past week and patient Health Questionnaire-9. Results: The 14 767 individuals reporting test-confirmed COVID-19 illness at least 2 months before the survey had a mean (SD) age of 44.6 (16.3) years; 568 (3.8%) were Asian, 1484 (10.0%) were Black, 1408 (9.5%) were Hispanic, and 10 811 (73.2%) were White. A total of 10 037 respondents (68.0%) were women and 4730 (32.0%) were men. Of the 1683 individuals reporting post-COVID-19 condition, 955 (56.7%) reported at least 1 cognitive symptom experienced daily, compared with 3552 of 13 084 (27.1%) of those who did not report post-COVID-19 condition. More daily cognitive symptoms were associated with a greater likelihood of reporting at least moderate interference with functioning (unadjusted odds ratio [OR], 1.31 [95% CI, 1.25-1.36]; adjusted [AOR], 1.30 [95% CI, 1.25-1.36]), lesser likelihood of full-time employment (unadjusted OR, 0.95 [95% CI, 0.91-0.99]; AOR, 0.92 [95% CI, 0.88-0.96]) and greater severity of depressive symptoms (unadjusted coefficient, 1.40 [95% CI, 1.29-1.51]; adjusted coefficient 1.27 [95% CI, 1.17-1.38). After including depressive symptoms in regression models, associations were also found between cognitive symptoms and at least moderate interference with everyday functioning (AOR, 1.27 [95% CI, 1.21-1.33]) and between cognitive symptoms and lower odds of full-time employment (AOR, 0.92 [95% CI, 0.88-0.97]). Conclusions and Relevance: The findings of this survey study of US adults suggest that cognitive symptoms are common among individuals with post-COVID-19 condition and associated with greater self-reported functional impairment, lesser likelihood of full-time employment, and greater depressive symptom severity. Screening for and addressing cognitive symptoms is an important component of the public health response to post-COVID-19 condition.

Perception of Social Support and Cognitive Performance in Older Adults With Depression.

This cross-sectional study assesses the association between perceived social support and cognitive performance in older adults with depression.

Comparison of Functional and Structural Neural Network Features in Older Adults With Depression With vs Without Apathy and Association With Response to Escitalopram: Secondary Analysis of a Nonrandomized Clinical Trial.

Importance: Apathy is prevalent among individuals with late-life depression and is associated with poor response to pharmacotherapy, including chronicity and disability. Elucidating brain networks associated with apathy and poor treatment outcomes can inform intervention development. Objectives: To assess the brain network features of apathy among individuals with late-life depression and identify brain network abnormalities associated with poor antidepressant response. Design, Setting, and Participants: This secondary analysis of a single-group, open-label nonrandomized clinical trial of escitalopram conducted at an outpatient geriatric psychiatry clinic enrolled 40 adults aged 59 to 85 years with major depressive disorder from July 1, 2012, to July 31, 2019. Interventions: After a 2-week washout period, participants received escitalopram titrated to a target of 20 mg/d for 12 weeks. Main Outcomes and Measures: Baseline and posttreatment magnetic resonance imaging (MRI), clinical, and cognitive assessments were conducted. Functional MRI was used to map group differences in resting state functional connectivity (rsFC) of the salience network, and diffusion MRI connectometry was performed to evaluate pathway-level disruptions in structural connectivity. The Apathy Evaluation Scale was used to quantify apathy, and the Hamilton Depression Rating Scale (HAM-D) was used to quantify the primary outcome of depression severity. Results: Forty participants (26 women [65%]; mean [SD] age, 70.0 [6.6] years [range, 59-85 years]) with depression were included; 20 participants (50%) also had apathy. Relative to nonapathetic participants with depression, those with depression and apathy had lower rsFC of salience network seeds with the dorsolateral prefrontal cortex (DLPFC), premotor cortex, midcingulate cortex, and paracentral lobule and greater rsFC with the lateral temporal cortex and temporal pole (z score >2.7; Bonferroni-corrected threshold of P < .0125). Compared with participants without apathy, those with apathy had lower structural connectivity in the splenium, cingulum, and fronto-occipital fasciculus (t score >2.5; false discovery rate-corrected P = .02). Twenty-seven participants completed escitalopram treatment; 16 (59%) achieved remission (HAM-D score <10). Lower insula-DLPFC/midcingulate cortex rsFC was associated with less symptomatic improvement (HAM-D % change) (ß [df] = 0.588 [26]; P = .001) and a higher likelihood of nonremission (odds ratio, 1.041 [95% CI, 1.003-1.081]; P = .04) after treatment and, in regression models, was a mediator of the association between baseline apathy and persistence of depression. Lower dorsal anterior cingulate-DLPFC/paracentral rsFC was associated with residual cognitive difficulties on measures of attention (ß [df] = 0.445 [26]; P = .04) and executive function (ß [df] = 0.384 [26]; P = .04). Conclusions and Relevance: This study suggests that disturbances in connectivity between the salience network and other large-scale networks that support goal-directed behavior may give rise to apathy and may be associated with poor response of late-life depression to antidepressant pharmacotherapy. These network disturbances may serve as targets for novel interventions. Trial Registration: ClinicalTrials.gov Identifier: NCT01728194.

Strategies to Promote Cognitive Health in Aging: Recent Evidence and Innovations.

PURPOSE OF REVIEW: We review recent work on applications of non-pharmacologic strategies to promote cognitive health in older adulthood and discuss potential network mechanisms, limitations, and considerations for improving intervention uptake and efficacy. RECENT FINDINGS: In healthy older adults and patients with mild cognitive impairment, cognitive training produces global and domain-specific cognitive gains, though effect sizes tend to be modest and transfer is variable. Non-invasive brain stimulation has shown moderate success in enhancing cognitive function, though the optimum approach, parameters, and cortical targets require further investigation. Physical activity improves cognitive functions in late life, with emerging trials highlighting key intervention components that may maximize treatment outcomes. Multimodal interventions may be superior to single-component interventions in conferring cognitive gains, although interpretation is limited by modest sample sizes and variability in training components and parameters. Across modalities, individual differences in patient characteristics predict therapeutic response. These interventions may advance cognitive health by modulating functional networks that support core cognitive abilities including the default mode, executive control, and salience networks. Effectiveness of cognitive enhancement strategies may be increased with clinician-led coaching, booster sessions, gamification, integration of multiple intervention modalities, and concrete applications to everyday functioning. Future trials involving rigorous comparisons of training components, parameters, and delivery formats will be essential in establishing the precise approaches needed to maximize cognitive outcomes. Novel studies using patient-level clinical and neuroimaging features to predict individual differences in training gains may inform the development of personalized intervention prescriptions to optimize cognitive health in late life.

Relationships between Diffusion Tensor Imaging and Resting State Functional Connectivity in Patients with Schizophrenia and Healthy Controls: A Preliminary Study.

Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schizophrenia and 25 healthy control subjects, and we acquired resting state fMRI and diffusion tensor imaging. We used the Functional and Tractographic Connectivity Analysis Toolbox (FATCAT) to estimate functional and structural connectivity of the default mode network. Correlations between modalities were investigated, and multimodal connectivity scores (MCS) were created using principal component analysis. Of the 28 possible region pairs, 9 showed consistent (>80%) tracts across participants. Correlations between modalities were found among those with schizophrenia for the prefrontal cortex, posterior cingulate, and lateral temporal lobes, with frontal and parietal regions, consistent with frontotemporoparietal network involvement in the disorder. In patients, MCS correlated with several aspects of the Positive and Negative Syndrome Scale, with higher multimodal connectivity associated with outward-directed (externalizing) behavior and lower multimodal connectivity related to psychosis per se. In this preliminary sample, we found FATCAT to be a useful toolbox to directly integrate and examine connectivity between imaging modalities. A consideration of conjoint structural and functional connectivity can provide important information about the network mechanisms of schizophrenia.

Late-life depression accentuates cognitive weaknesses in older adults with small vessel disease.

Neuroimaging features of small vessel disease (SVD) are highly prevalent in older adulthood and associated with significant variability in clinical symptoms, yet the factors predicting these symptom disparities are poorly understood. We employed a novel metric of SVD, peak width of skeletonized mean diffusivity (PSMD), to elucidate the relationship of late-life depression (LLD) to the cognitive presentation of vascular pathology. A total of 109 older adults without a diagnosis of a neurocognitive disorder were enrolled in the study; 44 with major depressive disorder and 65 age-matched controls. Subjects completed neuropsychological testing and magnetic resonance imaging including FLAIR and diffusion tensor imaging sequences, from which white matter hyperintensity volume and diffusion metrics (fractional anisotropy, mean diffusivity, PSMD) were quantified. In hierarchical models, the relationship between vascular burden and cognitive performance varied as a function of diagnostic status, such that the negative association between PSMD and processing speed was significantly stronger in participants with LLD compared to controls. Greater PSMD also predicted poorer performance on delayed memory and executive function tasks specifically among those with LLD, while there were no associations between PSMD and task performance among controls. PSMD outperformed conventional SVD and diffusion markers in predicting cognitive performance and dysexecutive behaviors in participants with LLD. These data suggest that LLD may confer a vulnerability to the cognitive manifestations of white matter abnormalities in older adulthood. PSMD, a novel biomarker of diffuse microstructural changes in SVD, may be a more sensitive marker of subtle cognitive deficits stemming from vascular pathology in LLD.

A systematic review of neuropsychological and psychiatric sequalae of COVID-19: implications for treatment.

PURPOSE OF REVIEW: COVID-19 impacts multiple organ systems and is associated with high rates of morbidity and mortality. Pathogenesis of viral infection, co-morbidities, medical treatments, and psychosocial factors may contribute to COVID-19 related neuropsychological and psychiatric sequelae. This systematic review aims to synthesize available literature on psychiatric and cognitive characteristics of community-dwelling survivors of COVID-19 infection. RECENT FINDINGS: Thirty-three studies met inclusion/exclusion criteria for review. Emerging findings link COVID-19 to cognitive deficits, particularly attention, executive function, and memory. Psychiatric symptoms occur at high rates in COVID-19 survivors, including anxiety, depression, fatigue, sleep disruption, and to a lesser extent posttraumatic stress. Symptoms appear to endure, and severity of acute illness is not directly predictive of severity of cognitive or mental health issues. The course of cognitive and psychiatric sequelae is limited by lack of longitudinal data at this time. Although heterogeneity of study design and sociocultural differences limit definitive conclusions, emerging risk factors for psychiatric symptoms include female sex, perceived stigma related to COVID-19, infection of a family member, social isolation, and prior psychiatry history. SUMMARY: The extant literature elucidates treatment targets for cognitive and psychosocial interventions. Research using longitudinal, prospective study designs is needed to characterize cognitive and psychiatric functioning of COVID-19 survivors over the course of illness and across illness severity. Emphasis on delineating the unique contributions of premorbid functioning, viral infection, co-morbidities, treatments, and psychosocial factors to cognitive and psychiatric sequelae of COVID-19 is warranted.

Brain-based mechanisms of late-life depression: Implications for novel interventions.

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Peripheral inflammatory biomarkers predict the deposition and progression of amyloid-ß in cognitively unimpaired older adults.

INTRODUCTION: Systemic inflammation has been increasingly implicated in the pathogenesis of Alzheimer's disease (AD), yet the mechanistic and temporal specificity of this relationship is poorly understood. We aimed to characterize the cross-sectional and longitudinal associations between peripheral inflammatory biomarkers, cognition, and Aß deposition in oldest-old cognitively unimpaired (CU) adults. METHODS: A large sample of 139 CU older adults (mean age (range) = 85.4 (82-95)) underwent neuropsychological testing, Pittsburgh compound-B (PiB)-PET imaging and structural MRI. Hierarchical regression models examined associations between circulating inflammatory biomarkers (Interleukin-6 (IL-6), soluble Tumor Necrosis Factor receptors 1 and 2 (sTNFr1 and sTNFr2), soluble cluster of differentiation 14 (sCD14), C-reactive protein (CRP)), cognition, and global and regional Aß deposition at baseline and over follow-up. Indices of preclinical disease, including pathologic Aß status and hippocampal volume, were incorporated to assess conditional associations. RESULTS: At baseline evaluation, higher concentrations of IL-6 and sTNFr2 were associated with greater global Aß burden in those with lower hippocampal volume. In longitudinal models, IL-6 predicted subsequent conversion to MCI and both IL-6 and CRP predicted greater change in global and regional Aß deposition specifically among participants PiB-positive at baseline. These relationships withstood adjustment for demographic factors, anti-hypertensive medication use, history of diabetes, heart disease, APOE ε4 carrier status, and white matter lesions. DISCUSSION: In a large prospective sample of CU adults aged 80 and over, peripheral inflammatory biomarkers were associated with and predictive of the progression of Aß deposition. This was specific to those with biomarker evidence of preclinical AD at baseline, supporting recent evidence of disease-state-dependent differences in inflammatory expression profiles. Chronic, low-level systemic inflammation may exacerbate the deposition of Aß pathology among those with emerging disease processes, and place individuals at a higher risk of developing clinically significant cognitive impairment.

Technology-assisted cognitive-behavioral therapy intervention for end-stage renal disease.

Technology-assisted cognitive-behavioral therapy (CBT) interventions have been conducted for symptoms including depression, pain, and fatigue in patients with chronic illnesses but not in end-stage renal disease (ESRD). The purpose of this study was to pilot the feasibility and acceptability of a technology-assisted CBT intervention in ESRD patients on hemodialysis (HD), share design and implementation lessons learned, and provide preliminary results on changes in select patient-reported symptoms. This was a single-center pilot feasibility study of adult ESRD patients on HD. Study eligibility required clinically elevated levels of at least one symptom (depression, pain, or fatigue). Patients met weekly with a CBT therapist for eight sessions, each 45-60 min, during HD sessions via a video-conferencing platform. Symptom questionnaires were completed at baseline and 3 months follow-up. Of 10 patients screened, 100% screened positive for at least one symptom, 100% of eligible patients consented, and eight (of 10) completed the intervention (mean age 59 years, 50% male, 50% African American). Patient adherence and satisfaction was high, and seven of the eight patients completed all eight prescribed sessions. Minimal interference with HD was reported. Preliminary results indicate no statistically significant changes in depression, fatigue, or pain at follow-up. However, there was small improvement in SF-36 Physical Component score [t(7) = -2.60, p = .035], and four of the six patients (67%) with clinically elevated pain at baseline reported improvement at follow-up. A technology-assisted CBT intervention for ESRD patients was feasible, well-accepted, and required minimal additional resources in the HD setting. Larger, adequately powered clinical trials are needed to evaluate the effect on ESRD patient-reported outcomes.

Role of Brain Structure in Predicting Adherence to a Physical Activity Regimen.

OBJECTIVE: Physical activity (PA) is important for maintaining health throughout the lifespan. However, adherence to PA regimens is poor with approximately 50% of older adults terminating activity intervention programs within 6 months. In this study, we tested whether gray matter volume and white matter microstructural integrity before the initiation of a PA intervention predicts PA adherence. METHODS: One hundred fifty-nine adults aged 60 to 80 years were randomly assigned to a moderate-intensity aerobic walking condition or a nonaerobic stretching and toning condition. Participants engaged in supervised exercise 3 times per week for 12 months. Data were collected for a period of 1 year. Voxel-based morphometry and tract-based spatial statistics protocols were used to process neuroimaging data, and ordinary least squares regression models with bootstrapping were used to analyze voxelwise neural predictors of PA adherence. RESULTS: Greater volume in several regions predicted greater PA adherence, including prefrontal, motor, somatosensory, temporal, and parietal regions (p < .01). We also found that higher fractional anisotropy in several white matter tracts predicted greater PA adherence (pFDR-corrected < .05), including the superior longitudinal fasciculus, anterior thalamic radiation, forceps minor, and body of the corpus callosum. CONCLUSIONS: These findings provide preliminary support for macro- and microstructural neural predictors of PA adherence and may translate to other health behaviors and behavioral goal pursuit more broadly.

Effects of Physical Activity on Poststroke Cognitive Function: A Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND PURPOSE: Despite the social, health, and economic burdens associated with cognitive impairment poststroke, there is considerable uncertainty about the types of interventions that might preserve or restore cognitive abilities. The objective of this systematic review and meta-analysis was to evaluate the effects of physical activity (PA) training on cognitive function poststroke and identify intervention and sample characteristics that may moderate treatment effects. METHODS: Randomized controlled trials examining the association between structured PA training and cognitive performance poststroke were identified using electronic databases EMBASE and MEDLINE. Intervention effects were represented by Hedges' g and combined into pooled effect sizes using random- and mixed-effects models. Effect sizes were subjected to moderation analyses using the between-group heterogeneity test. RESULTS: Fourteen studies met inclusion criteria, representing data from 736 participants. The primary analysis yielded a positive overall effect of PA training on cognitive performance (Hedges' g [95% confidence interval]=0.304 [0.14-0.47]). Mixed-effects analyses demonstrated that combined aerobic and strength training programs generated the largest cognitive gains and that improvements in cognitive performance were achieved even in the chronic stroke phase (mean=2.6 years poststroke). Positive moderate treatment effects were found for attention/processing speed measures (Hedges' g [confidence interval]=0.37 [0.10-0.63]), while the executive function and working memory domains did not reach significance (P>0.05). CONCLUSIONS: We found a significant positive effect of PA training on cognition poststroke with small to moderate treatment effects that are apparent even in the chronic stroke phase. Our findings support the use of PA training as a treatment strategy to promote cognitive recovery in stroke survivors.

White matter microstructure mediates the relationship between cardiorespiratory fitness and spatial working memory in older adults.

White matter structure declines with advancing age and has been associated with a decline in memory and executive processes in older adulthood. Yet, recent research suggests that higher physical activity and fitness levels may be associated with less white matter degeneration in late life, although the tract-specificity of this relationship is not well understood. In addition, these prior studies infrequently associate measures of white matter microstructure to cognitive outcomes, so the behavioral importance of higher levels of white matter microstructural organization with greater fitness levels remains a matter of speculation. Here we tested whether cardiorespiratory fitness (VO2max) levels were associated with white matter microstructure and whether this relationship constituted an indirect pathway between cardiorespiratory fitness and spatial working memory in two large, cognitively and neurologically healthy older adult samples. Diffusion tensor imaging was used to determine white matter microstructure in two separate groups: Experiment 1, N=113 (mean age=66.61) and Experiment 2, N=154 (mean age=65.66). Using a voxel-based regression approach, we found that higher VO2max was associated with higher fractional anisotropy (FA), a measure of white matter microstructure, in a diverse network of white matter tracts, including the anterior corona radiata, anterior internal capsule, fornix, cingulum, and corpus callosum (PFDR-corrected<.05). This effect was consistent across both samples even after controlling for age, gender, and education. Further, a statistical mediation analysis revealed that white matter microstructure within these regions, among others, constituted a significant indirect path between VO2max and spatial working memory performance. These results suggest that greater aerobic fitness levels are associated with higher levels of white matter microstructural organization, which may, in turn, preserve spatial memory performance in older adulthood.

Blood pressure interacts with APOE ε4 to predict memory performance in a midlife sample.

OBJECTIVE: Elevated blood pressure and the Apolipoprotein ε4 allele (APOE ε4) are independent risk factors for Alzheimer's disease. We sought to determine whether the combined presence of the APOE ε4 allele and elevated blood pressure is associated with lower cognitive performance in cognitively healthy middle-aged adults. METHODS: A total of 975 participants aged 30-54 (mean age = 44.47) were genotyped for APOE. Cardiometabolic risk factors including blood pressure, lipids, and glucose were assessed and cognitive function was measured using the Trail Making Test and the Visual Reproduction and Logical Memory subtests from the Wechsler Memory Scale. RESULTS: Multivariable regression analysis showed that the association between APOE ε4 and episodic memory performance varied as a function of systolic blood pressure (SBP), such that elevated SBP was predictive of poorer episodic memory performance only in APOE ε4 carriers (ß = -.092; t = -2.614; p = .009). Notably, this association was apparent at prehypertensive levels (≥130 mmHg), even after adjusting for physical activity, depression, smoking, and other cardiometabolic risk factors. CONCLUSIONS: The joint presence of APOE ε4 and elevated SBP, even at prehypertensive levels, is associated with lower cognitive performance in healthy, middle-aged adults. Results of this study suggest that the combination of APOE ε4 and elevated SBP may synergistically compromise memory function well before the appearance of clinically significant impairments. Interventions targeting blood pressure control in APOE ε4 carriers during midlife should be studied as a possible means to reduce the risk of cognitive decline in genetically susceptible samples.

BDNF mediates improvements in executive function following a 1-year exercise intervention.

Executive function declines with age, but engaging in aerobic exercise may attenuate decline. One mechanism by which aerobic exercise may preserve executive function is through the up-regulation of brain-derived neurotropic factor (BDNF), which also declines with age. The present study examined BDNF as a mediator of the effects of a 1-year walking intervention on executive function in 90 older adults (mean age = 66.82). Participants were randomized to a stretching and toning control group or a moderate intensity walking intervention group. BDNF serum levels and performance on a task-switching paradigm were collected at baseline and follow-up. We found that age moderated the effect of intervention group on changes in BDNF levels, with those in the highest age quartile showing the greatest increase in BDNF after 1-year of moderate intensity walking exercise (p = 0.036). The mediation analyses revealed that BDNF mediated the effect of the intervention on task-switch accuracy, but did so as a function of age, such that exercise-induced changes in BDNF mediated the effect of exercise on task-switch performance only for individuals over the age of 71. These results demonstrate that both age and BDNF serum levels are important factors to consider when investigating the mechanisms by which exercise interventions influence cognitive outcomes, particularly in elderly populations.