Guest Editorial

“The Depression–Executive Dysfunction Syndrome of Late Life”: A Specific Target for D₃ Agonists?

This study aimed to understand the long-term symptom trajectories of Chinese patients with major depressive disorder (MDD) using piecewise latent growth modeling and growth mixture modeling. The investigation also aimed to identify the baseline characteristics indicative of poorer treatment outcomes.

A total of 558 outpatients with MDD were assessed using a sequence of surveys. The Hamilton Rating Scale for Depression (HRSD), Hamilton Anxiety Rating Scale (HAMA), and Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) were used to evaluate baseline depression, anxiety, and cognitive function. Depression symptom severity was subsequently measured at the 1-month, 2-month, 6-month, 1-year, and 2-year follow-ups.

Results indicated three depressive symptomology trajectories, including (a) severe, improving class (12.72 %), (b) partially responding, later deteriorating class (6.09 %), and (c) moderate, improving class (81.18 %). Logistic regression analyses showed that a history of cardiovascular disease (CVD) increased the odds of belonging to the partially responding, later deteriorating class, whereas higher baseline depression increased the odds of belonging to the severe, improving class compared to the moderate, improving class. Patients who experienced less depression relief during the first month of treatment had a lower probability of belonging to the moderate, improving class.

Participant attrition in this study may have inflated the estimated rate of treatment-resistant patients.

The burden of CVD and poorer initial treatment response are plausible risk factors for poorer treatment outcomes, highlighting targets for intervention in Chinese MDD patients.

Precision Nutrition through genetics, epigenetics, the microbiome, and metabolomics, promises to improve personalized nutrition recommendations to maintain brain health and prevent common forms of dementia. Healthy aging is increasingly being viewed as related to many lifestyle factors that affect the rate of aging among individuals. Inflammation is associated with abdominal adiposity and overweight and is a risk factor for dementia and premature aging. Alzheimer’s and Parkinson’s dementias afflict tens of millions of people worldwide. Numerous factors, including genetics, nutrition, sleep, and exercise, affect brain health. Precision Nutrition may play a role in defining individualized recommendations for patients with early forms of these diseases, including mild cognitive impairment (MCI), and instilling lifetime habits of diet and exercise that may promote brain health and healthy brain aging.

Vascular cognitive impairment (VCI) and depression frequently coexist in geriatric populations and reciprocally increase disease risks. We assert that a shared pre-disease state of the psycho-immune-neuroendocrine (PINE) network model mechanistically explains bidirectional associations between VCI and depression. Five pathophysiological sub-networks are identified that are shared by VCI and depression: neuroinflammation, kynurenine pathway imbalance, hypothalamic-pituitary-adrenal (HPA) axis overactivity, impaired neurotrophic support and cerebrovascular dysfunction. These do not act independently, and their complex interactions necessitate a systems biology approach to better define disease pathogenesis. The PINE network is already established in the context of non-communicable diseases (NCDs) such as depression, hypertension, atherosclerosis, coronary heart disease and type 2 diabetes mellitus. We build on previous literature to specifically explore mechanistic links between MDD and VCI in the context of PINE pathways and discuss key mechanistic commonalities linking these comorbid conditions and identify a common pre-disease state which precedes transition to VCI and MDD. We expand the model to incorporate bidirectional interactions with biological ageing. Diathesis factors for both VCI and depression feed into this network and the culmination of shared mechanisms (on an ageing substrate) lead to a critical network transition to one or both disease states. A common pre-disease state underlying VCI and depression can provide clinicians a unique opportunity for early risk assessment and intervention in disease development. Establishing the mechanistic elements and systems biology of this network can reveal early warning or predictive biomarkers together with novel therapeutic targets. Integrative studies are recommended to elucidate the dynamic networked biology of VCI and depression over time.

Late life major depression (LLD) is often accompanied by cognitive deficits. When patients have specific deficits in cognitive control functions (CCD), they are not only distressing and debilitating, they often predict poor clinical outcomes such as reduced response to SSRI/SNRI antidepressants, increased disability, suicide and all-cause mortality. We recently reported that in an open label trial, our treatment designed to target these specific CCD with neuroplasticity-based computerized cognitive remediation (nCCR) improved depression and CCD in patients who failed to remit with conventional antidepressant treatment. This study tested the hypothesis that in patients with LLD who have failed at least one trial of an SSRI/SNRI antidepressant at an adequate dose for at least 8 weeks, nCCR will improve both depressive symptoms and the CCD associated with poor antidepressant response (i.e. semantic strategy, inhibition of prepotent responses) more than an active control group. Participants were randomized (1:1) to receive either 30 hours/ 4 weeks of neuroplasticity based computerized cognitive remediation (nCCR) designed to target CCD, or the active control condition matched for duration, engagement, reward, computer presentation, and contact with study staff. All participants and raters were blinded. Mixed effects model analysis the time effect (week) (F(1,71.22)=25.2, p<0.0001) and treatment group X time interaction (F(1,61.8)=11.37, p=.002) reached significance indicating that the slope of decline in MADRS was steeper in the nCCR-GD group. Further, the nCCR group improved their semantic clustering strategy(t(28)=9.5; p=.006), as well as performance on the Stroop interference condition, and cognitive flexibility (Trails B). Further, results transferred to memory performance, which was not a function trained by nCCR. clinicaltrials.gov.

As the world's population ages and people live longer, the changes in the aging brain present substantial challenges to our health and society. With greater longevity come age-related diseases, many of which have direct and indirect influences on the health of the brain. Although there is some degree of predictable decline in brain functioning with aging, meaningful cognitive decline is not inevitable and is perhaps preventable. In this review, we present the case that the course of aging-related brain disease and dysfunction can be modified. We present the evidence for conditions and risk factors that may contribute to cognitive decline and dementia and for interventions that may mitigate their impact on cognitive functioning later in life, or even prevent them and their cognitive sequelae from developing. Although much work remains to be done to meet the challenges of the aging brain, strategies to promote its health have been demonstrated and offer much promise, which can only be realized if we mount a vigorous public health effort to implement these strategies.

Depression often co-occurs in late-life in the context of declining cognitive functions, but it is not clear whether specific depression symptom dimensions are differentially associated with cognitive abilities.

The study sample comprised 3107 community-dwelling older adults from the Longitudinal Aging Study Amsterdam (LASA). We applied a Multiple Indicators Multiple Causes (MIMIC) model to examine the association between cognitive abilities and latent dimensions of the Center for Epidemiologic Studies Depression Scale (CES-D), while accounting for differential item functioning (DIF) due to age, gender and cognitive function levels.

A factor structure consisting of somatic symptoms, positive affect, depressed affect, and interpersonal difficulties fitted the data well. Higher levels of inductive reasoning were significantly associated with lower levels of depressed affect and somatic symptoms, whereas faster processing speed was significantly associated with lower levels of somatic symptoms. DIF due to age and gender was found, but the magnitude of the effects was small and did not alter substantive conclusions.

Due to the cross-sectional context of this investigation, the direction of influence between depression symptom levels and cognitive function levels cannot be established. Furthermore, findings are relevant to non-clinical populations, and they do not clarify whether certain DIF effects may be found only at high or low levels of depression.

Our findings suggest differential associations between late-life depression dimensions and cognitive abilities in old age, and point towards potential etiological mechanisms that may underline these associations. These findings carry implications for the prognosis of cognitive outcomes in depressed older adults.