Pathophysiology Of Late-life Depression Research Articles

A novel biomarker selection method using multimodal neuroimaging data.

Identifying biomarkers is essential to obtain the optimal therapeutic benefit while treating patients with late-life depression (LLD). We compare LLD patients with healthy controls (HC) using resting-state functional magnetic resonance and diffusion tensor imaging data to identify neuroimaging biomarkers that may be potentially associated with the underlying pathophysiology of LLD. We implement a Bayesian multimodal local false discovery rate approach for functional connectivity, borrowing strength from structural connectivity to identify disrupted functional connectivity of LLD compared to HC. In the Bayesian framework, we develop an algorithm to control the overall false discovery rate of our findings. We compare our findings with the literature and show that our approach can better detect some regions never discovered before for LLD patients. The Hub of our discovery related to various neurobehavioral disorders can be used to develop behavioral interventions to treat LLD patients who do not respond to antidepressants.

Transcranial Magnetic Stimulation Indices of Cortical Excitability Enhance the Prediction of Response to Pharmacotherapy in Late-Life Depression

BackgroundOlder adults with late-life depression (LLD) often experience incomplete or lack of response to first-line pharmacotherapy. The treatment of LLD could be improved using objective biological measures to predict response. Transcranial magnetic stimulation (TMS) can be used to measure cortical excitability, inhibition, and plasticity, which have been implicated in LLD pathophysiology and associated with brain stimulation treatment outcomes in younger adults with depression. TMS measures have not yet been investigated as predictors of treatment outcomes in LLD or pharmacotherapy outcomes in adults of any age with depression. MethodsWe assessed whether pretreatment single-pulse and paired-pulse TMS measures, combined with clinical and demographic measures, predict venlafaxine treatment response in 76 outpatients with LLD. We compared the predictive performance of machine learning models including or excluding TMS predictors. ResultsTwo single-pulse TMS measures predicted venlafaxine response: cortical excitability (neuronal membrane excitability) and the variability of cortical excitability (dynamic fluctuations in excitability levels). In cross-validation, models using a combination of these TMS predictors, clinical markers of treatment resistance, and age classified patients with 73% ± 11% balanced accuracy (average correct classification rate of responders and nonresponders; permutation testing, p < .005); these models significantly outperformed (corrected t test, p = .025) models using clinical and demographic predictors alone (60% ± 10% balanced accuracy). ConclusionsThese preliminary findings suggest that single-pulse TMS measures of cortical excitability may be useful predictors of response to pharmacotherapy in LLD. Future studies are needed to confirm these findings and determine whether combining TMS predictors with other biomarkers further improves the accuracy of predicting LLD treatment outcome.

Young plasma administration mitigates depression-like behaviours in chronic mild stress-exposed aged rats by attenuating apoptosis in prefrontal cortex.

What is the central question of this study? Young plasma contains several rejuvenating factors that exert beneficial effects in ageing and neurodegenerative diseases: can repeated transfusion of young plasma improve depressive behaviour in aged rats? What is the main finding and its importance? Following chronic transfusion of young plasma, depressive behaviour was improved in the depression model of aged rats, which was associated with reduced apoptosis process in the prefrontal cortex. Brain ageing alters brain responses to stress, playing an essential role in the pathophysiology of late-life depression. Moreover, apoptotic activity is up-regulated in the prefrontal cortex in ageing and stress-related mood disorders. Considerable evidence suggests that factors in young blood could reverse age-related dysfunctions in organs, especially in the brain. Therefore, this study investigated the effect of young plasma administration on depressive behaviours in aged rats exposed to chronic unpredictable mild stress (CUMS), with a focus on the apoptosis process. Young (3months old) and aged (22months old) male rats were randomly assigned into four groups: young control (YC), aged control (AC), aged rats subjected to CUMS (A+CUMS) and aged rats subjected to CUMS and treated with young plasma (A+CUMS+YP). In the A+CUMS and A+CUMS+YP groups, CUMS was used to generate the depression rat model. Moreover, the A+CUMS+YP group received pooled plasma (1ml, intravenously), collected from young rats, three times per week for 4weeks. Young plasma administration significantly improved CUMS-induced depression-like behaviours, including decreased sucrose consumption ratio, reduced locomotor activity and prolonged immobility time. Importantly, young plasma reduced neuronal apoptosis in the prefrontal cortex that was associated with reduced TUNEL-positive cells and cleaved caspase-3 protein levels in the A+CUMS+YP compared with the A+CUMS group. Young plasma can partially improve the neuropathology of late-life depression through the apoptotic signalling pathways.

Increased levels of circulating cell-free mtDNA in plasma of late life depression subjects

BackgroundOxidative stress (OS) has been implicated in the pathophysiology of late-life depression (LLD). Mitochondria are the primary source of oxidative stress and can be significantly damaged with increased OS. Circulating cell-free mtDNA (ccf-mtDNA) is a marker of cellular stress and mitochondria damage triggered by oxidative stress. MethodsWe evaluated the plasma levels of ccf-mtDNA in between 32 LLD and 21 never-depressed participants. We also investigated the association between ccf-mtDNA and the severity of depressive episodes and cognition performance. ResultsWe found a higher ccf-mtDNA level in LLD cases compared with controls (t = −2.91, p = 0.005). Also, ccf-mtDNA was significantly correlated with the severity of depression (r = 0.42, p = 0.001). There was no significant correlation between ccf-mtDNA and measures of cognitive decline. LimitationsThe small sample size and cross-sectional design were the main limitations of this study. ConclusionOur results suggest that LLD is associated with elevated mitochondrial damage and cellular stress. If validated, the measurement of ccf-mtDNA in LLD can guide the development of novel treatments focused on cytoprotection and reduction of mitochondrial dysfunction for this condition.

Metabolomic predictors for late-life depression

<h3>Introduction</h3> Depression is a major public health problem among older adults and among the leading causes of global burden of disease and disability. Yet, current understanding of pathophysiology and optimal prevention and/or treatment of late-life depression (LLD) is limited. Advanced approaches involving methods such as metabolomics present an innovative path to identify novel biomarkers of LLD outcomes. Several known biological pathways involving tryptophan and lipid-inflammatory molecules (eicosanoids) are relevant to depression; however, there have been few systematic investigations of metabolomic predictors of long-term trajectories of LLD. <h3>Methods</h3> This is a convenience sample of ∼7000 Nurses' Health Study (NHS) participants with known metabolites and who completed depression items every four years from 1992-2016. Between 1989 and 1990, blood samples were collected and stored under standard conditions. In NHS, data on known metabolites were generated by merging the data from multiple case-control studies; however, all metabolites were profiled using liquid chromatography mass spectrometry in the same laboratory. Continuous metabolite values were transformed to probit scores to account for batch effects. We used a previously developed harmonized depressive symptom scale that was indexed to the five-item Mental Health Inventory (MHI-5, range=0-100 points). For cross-sectional analysis, we performed multivariable logistic regression models to evaluate the associations of baseline metabolite levels and likelihood of the moderate or severe depressive symptoms (MHI-5 cut-off=60); for longitudinal analysis, we used latent growth-curve analysis to identify group-based trajectories of depressive symptoms and then related baseline metabolite levels to long-term trajectories. <h3>Results</h3> The mean age of female nurses at blood draw was 57.0 (range=42.6-70.2) years. There were ∼6300 NHS participants with available data on tryptophan metabolites and ∼1300 NHS participants with available data on eicosanoids. We observed stronger signals for cross-sectional associations of higher circulating levels of tryptophan, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) with lower risk of moderate or severe depressive symptoms, adjusted for age at blood draw, fasting status, case-control status, physical activity, body mass index, diet index, alcohol use, and cigarette smoking [multivariable odds ratio (95% confidence interval): for tryptophan=0.86 (0.80-0.93), p<0.01; for EPA=0.84 (0.71-1.01), p=0.06; for DHA=0.85 (0.71-1.02), p=0.07]. From 1992-2016, we identified four depressive symptom trajectory groups: minimal depressive symptoms (63%), worsening depressive symptoms (12%), improving depressive symptoms (20%), and persistent severe depressive symptoms (5%). Additional results from multinomial models evaluating the associations between metabolites and long-term LLD trajectories will be presented. <h3>Conclusions</h3> In this sample, tryptophan and omega-3 fatty acid metabolites were significantly related to LLD outcomes; these metabolites may play a role in the pathophysiology of LLD. <h3>Funding</h3> HMS Livingston Fellowship Award

Abnormal Voxel-Wise Degree Centrality in Patients With Late-Life Depression: A Resting-State Functional Magnetic Resonance Imaging Study.

ObjectivesLate-life depression (LLD) has negative impacts on somatic, emotional and cognitive domains of the lives of patients. Elucidating the abnormality in the brain networks of LLD patients could help to strengthen the understanding of LLD pathophysiology, however, the studies exploring the spontaneous brain activity in LLD during the resting state remain limited. This study aimed at identifying the voxel-level whole-brain functional connectivity changes in LLD patients.MethodsFifty patients with late-life depression (LLD) and 33 healthy controls were recruited. All participants underwent a resting-state functional magnetic resonance imaging scan to assess the voxel-wise degree centrality (DC) changes in the patients. Furthermore, DC was compared between two patient subgroups, the late-onset depression (LOD) and the early-onset depression (EOD).ResultsCompared with the healthy controls, LLD patients showed increased DC in the inferior parietal lobule, parahippocampal gyrus, brainstem and cerebellum (p < 0.05, AlphaSim-corrected). LLD patients also showed decreased DC in the somatosensory and motor cortices and cerebellum (p < 0.05, AlphaSim-corrected). Compared with EOD patients, LOD patients showed increased centrality in the superior and middle temporal gyrus and decreased centrality in the occipital region (p < 0.05, AlphaSim-corrected). No significant correlation was found between the DC value and the symptom severity or disease duration in the patients after the correction for multiple comparisons.ConclusionsThese findings indicate that the intrinsic abnormality of network centrality exists in a wide range of brain areas in LLD patients. LOD patients differ with EOD patients in cortical network centrality. Our study might help to strengthen the understanding of the pathophysiology of LLD and the potential neural substrates underlie related emotional and cognitive impairments observed in the patients.

Predictors of Response and Remission to Antidepressants in Geriatric Depression: A Systematic Review.

Geriatric depression is a heterogeneous disorder that increases morbidity and mortality in a population that is already vulnerable. Predicting response and remission to antidepressants could help clinicians to optimize the management of antidepressants and reduce the consequences of depression. The aim of this article is to present results of a systematic review of the literature on predictive factors related to antidepressant response and remission in older adults with depression. We identified sociodemographic, clinical, neuropsychological, neuroimaging, and genetic factors that could be potential predictors of outcomes. Inconsistent findings and methodological differences among studies, however, limit the generalizability and application of these predictors in clinical practice. The results of our review confirm that geriatric depression includes many subgroups of patients with particular endophenotypes that may influence the course of depression. Further studies are needed to characterize depression subgroups in order to better understand the pathophysiology of late life depression and to find specific predictors for each group of patients.

Assessment of neuroplasticity in late-life depression with transcranial magnetic stimulation

BackgroundStudies using Transcranial Magnetic Stimulation (TMS), a non-invasive method of brain stimulation, have implicated impaired neuroplasticity in the pathophysiology of depression in younger adults. The role of neuroplasticity in late-life depression (LLD) has not yet been explored using TMS. ObjectiveThis study aimed at evaluating motor cortical neuroplasticity using paired associative stimulation (PAS). Single-pulse TMS was used to induce motor-evoked potentials (MEP) in the contralateral hand muscle before and after PAS. The potentiation of MEP amplitudes after PAS was used as an indirect index of associative plasticity and long-term potentiation (LTP) (i.e. PAS-LTP). Results48 older adults with depression and 34 age-matched healthy controls (HC) were compared. PAS- LTP was successfully induced in 68.8% of older adults with depression and 47.1% of HC. At the group level, older adults with depression failed to show statistically significant induction of neuroplasticity, which was observed in HC. However, no significant differences were observed between the two groups for PAS-LTP. ConclusionOur results suggest that associative plasticity does not differ substantially between older adults with depression and age-matched HC. Continued research is needed to more comprehensively understand the role of neuroplasticity in the pathophysiology of LLD.

The neural correlates of perceived energy levels in older adults with late-life depression

Late-life depression is common among older adults. Although white-matter abnormality is highly implicated, the extent to which the corticospinal tract is associated with the pathophysiology of late-life depression is unclear. The current study aims to investigate the white-matter structural integrity of the corticospinal tract and determine its cognitive and functional correlates in older adults with late-life depression. Twenty-eight older adults with clinical depression and 23 healthy age-matched older adults participated in the study. The white matter volume and the white matter hyperintensities (WMHs) of the corticospinal tract, as well as the global WMHs, were measured. Psychomotor processing speed, severity of depression, perceived levels of energy and physical functioning were measured to examine the relationships among the correlates in the depressed participants. The right corticospinal tract volume was significantly higher in depressed older adults relative to healthy controls. Moreover, the right corticospinal tract volume was significantly associated with the overall severity of depression and accounted for 17% of its variance. It further attenuated the relationship between the severity of depression and perceived levels of energy. Our findings suggested that higher volume in the right corticospinal tract is implicated in LLD and may relate to lower perceived levels of energy experienced by older adults with depression.

Impaired biophysical integrity of macromolecular protein pools in the uncinate circuit in late-life depression

Major depressive disorder is a common mood disorder in the elderly. Although the neuroanatomical abnormalities have been identified in patients with late-life depression (LLD), the precise biological basis of LLD remains largely unknown. The purpose of this study was to examine the biophysical integrity of macromolecular protein pools in the nodal regions of the "uncinate circuit," a component of fronto-limbic circuitry that is connected by the uncinate fasciculus and is critical in the regulation of mood and emotions, using novel magnetization transfer (MT) imaging. Twenty-four patients with LLD and 27 non-depressed healthy control subjects (HCs) of comparable age, sex, and race were recruited from the communities of the greater Chicago Area. The nodal regions of the uncinate circuit, i.e., bilateral amygdala, hippocampus, and lateral and medial orbitofrontal cortices (OFCs), were examined. Compared with HCs, patients with LLD had significantly lower magnetization transfer ratio (MTR), a measure of the biophysical integrity of macromolecular protein pools, in bilateral amygdala and hippocampus. The lower MTR was negatively correlated with the depression score. Moreover, the MTR of these regions decreased with age and positively correlated with neuropsychological performance in the LLD group but not in the HC group. These findings suggest that LLD is associated with compromised biophysical integrity of macromolecular protein pools in nodal regions of the uncinate circuit, and that major depression may accentuate age-related attenuation of the biophysical integrity of macromolecular protein pools in this circuit. These findings provide important new insights into the neurobiological mechanisms of the pathophysiology of LLD.

Biological Age, Not Chronological Age, Is Associated with Late-Life Depression.

The pathophysiology of late-life depression (LLD) is complex and heterogeneous, with age-related processes implicated in its pathogenesis. This study examined the cross-sectional and longitudinal association between depressive symptoms and a baseline multibiomarker algorithm of biological age (BA) that aggregates indicators of inflammatory, metabolic, cardiovascular, lung, liver, and kidney functioning. Data were analyzed from 2,776 men and women from the prospective observational Health Aging and Body Composition Study, who had both evaluable chronological age (CA) and BA. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CES-D) scale. A covariate-adjusted regression model showed that BA (B = 0.03, p = .0471) but not CA (B = -0.01, p = .7185) is associated with baseline CES-D scores. The mean baseline BA for individuals with a CES-D ≥ 10 was 1.28 years greater than in those with a CES-D < 10. Comparatively, there is only a 0.05-year difference in mean CA between the two depression groups. A covariate-adjusted longitudinal model found that baseline BA predicts CES-D score at follow-up (B = 0.04, p = .0058), whereas CA does not (B = 0.03, p = .4125). Additionally, an older BA significantly predicted a CES-D ≥ 10 (B = 0.02, p = .032) over a 10-year period. A multibiomarker index of an older adult's BA outperformed their CA in predicting subsequent increased and clinically significant depressive symptoms. This result supports the evolving view of LLD as a brain disorder resulting from deleterious age-associated changes across numerous physiological systems.

Late-Life Depression: Modifications of Brain Resting State Activity

Late-life depression (LLD) is a common emotional and mental disability in the elderly population characterized by the presence of depressed mood, the loss of interest or pleasure in daily activities, and other depression symptoms. It has a serious effect on the quality of life of elderly individuals and increases their risk of developing physical and mental diseases. It is an important area of research, given the growing elderly population. Brain functional connectivity modifications represent one of the neurobiological biomarker for LLD even if to date remains poorly understood. In our study, we enrolled 10 elderly patients with depressive symptoms compared to 11 age-matched healthy controls. All participants were evaluated by means of neuropsychological tests and underwent the same functional magnetic resonance imaging (fMRI) protocol to evaluate modifications of brain resting state functional connectivity. Between-group differences were observed for the Geriatric Depression Scale and Hamilton Depression Rating Scale, with higher scores for patients with LLD. Voxel-wise, 1-way analysis of variance revealed between-group differences in left frontoparietal network (lFPN) and sensory motor network (SMN): Increased intrinsic connectivity in the LLD group was observed in the left dorsolateral prefrontal cortex and in the left superior parietal lobule of the lFPN and increased intrinsic connectivity in the LLD group was observed in the bilateral primary somatosensory cortex of the SMN. Our findings support the use of resting state fMRI as a potential biomarker for LLD; even if to confirm the relationship between brain changes and the pathophysiology of LLD, longitudinal neuroimaging studies are required.

Circulating biosignatures of late-life depression (LLD): Towards a comprehensive, data-driven approach to understanding LLD pathophysiology

There is scarce information about the pathophysiological processes underlying Late-Life Depression (LLD). We aimed to determine the neurobiological abnormalities related to LLD through a multi-modal biomarker approach combining a large, unbiased peripheral proteomic panel and structural brain imaging. We examined data from 44 LLD and 31 control participants. Plasma proteomic analysis was performed using a multiplex immunoassay. We evaluated the differential protein expression between groups with random intercept models. We carried out enrichment pathway analyses (EPA) to uncover biological pathways and processes related to LLD. Machine learning analysis was applied to the combined dataset to determine the accuracy with which specific proteins could correctly discriminate LLD versus control participants. Sixty-one proteins were differentially expressed in LLD (p < 0.05 and FDR < 0.01). EPA showed that these proteins were related to abnormal immune-inflammatory control, cell survival and proliferation, proteostasis control, lipid metabolism, intracellular signaling. Machine learning analysis showed that a panel of three proteins (C-peptide, FABP-liver, ApoA-IV) discriminated LLD and control participants with 100% accuracy. The plasma proteomic profile in LLD revealed dysregulation in biological processes essential to the maintenance of homeostasis at cellular and systemic levels. These abnormalities increase brain and systemic allostatic load leading to the downstream negative outcomes of LLD, including increased risk of medical comorbidities and dementia. The peripheral biosignature of LLD has predictive power and may suggest novel putative therapeutic targets for prevention, treatment, and neuroprotection in LLD.

Altered resting-state functional connectivity in late-life depression: A cross-sectional study

BackgroundDisrupted brain connectivity is implicated in the pathophysiology of late-life depression (LLD). There are few studies in this area using resting-state functional magnetic resonance imaging (rs-fMRI). In this pilot case-control study, we compare rs-fMRI data between age-matched depressed and non-depressed older adults. MethodsOlder participants (≥55 years) with current major depressive disorder (MDD) were recruited to participate in an ongoing study of LLD, and were compared to the age-matched, non-depressed controls. Rs-fMRI data were collected using a 3-Tesla MRI system. In this study, a data-driven approach was chosen and an independent component analysis (ICA) was performed. ResultsSeventeen subjects with MDD were compared to 31 controls. The depressed group showed increased connectivity in three main networks compared to the controls (p(corr)<0.05), including connectivity between the default mode network (DMN) and the posterior superior temporal sulcus (pSTS). Increased connectivity was also observed within the visual network in the medial, lateral and ventral regions of the occipital lobes, and within the auditory network throughout the right superior temporal cortex. ConclusionThis data-driven, pilot study finds patterns of increased connectivity that may be unique to LLD in the DMN, as well as visual and auditory networks. The functional implications of this aberrant connectivity remains to be determined. These findings should be further explored in larger samples.

Corpus callosum size may predict late-life depression in women: A 10-year follow-up study

BackgroundRecent research on late-life depression (LLD) pathophysiology suggests the implication of abnormalities in cerebral white matter [1] and particularly in interhemispheric transfer [2]. Corpus callosum (CC) is the main brain interhemispheric commissure [3]. Hence, we investigated the association between baseline CC measures and risk of LDD.MethodsWe studied 467 non-demented individuals without LLD at baseline from a cohort of community-dwelling people aged 80 years or younger (the ESPRIT study). LLD was assessed at year 2, 4, 7 and 10 of the study follow-up. At baseline, T1-weighted magnetic resonance images were manually traced to measure the mid-sagittal areas of the anterior, mid and posterior CC. Multivariate Cox proportional hazards models stratified by sex were used to predict LLD incidence over 10 years.ResultsA significant interaction between gender and CC size was found (P = 0.02). LLD incidence in elderly women, but not in men, was significantly associated with smaller anterior (HR 1.37 [1.05–1.79] P = 0.017), mid (HR 1.43 [1.09–1.86] P = 0.008), posterior (HR1.39 [1.12–1.74] P = 0.002) and total (HR 1.53 [1.16–2.00] P = 0.002) CC areas at baseline in Cox models adjusted for age, education, global cognitive impairment, ischemic pathologies, left-handedness, white matter lesion, intracranial volume and past depression.LimitationsThe main limitation was the retrospective assessment of major depression.ConclusionsSmaller CC size is a predictive factor of incident LLD over 10 years in elderly women. Our finding suggests a possible role of CC and reduced interhemispheric connectivity in LLD pathophysiology. Extensive explorations are needed to clarify the mechanisms leading to CC morphometric changes in mood disorders.

Brain grey matter volume alterations in late-life depression.

Voxel-based morphometry (VBM) studies have demonstrated that grey matter abnormalities are involved in the pathophysiology of late-life depression (LLD), but the findings are inconsistent and have not been quantitatively reviewed. The aim of the present study was to conduct a meta-analysis that integrated the reported VBM studies, to determine consistent grey matter alterations in individuals with LLD. A systematic search was conducted to identify VBM studies that compared patients with LLD and healthy controls. We performed a meta-analysis using the effect size signed differential mapping method to quantitatively estimate regional grey matter abnormalities in patients with LLD. We included 9 studies with 11 data sets comprising 292 patients with LLD and 278 healthy controls in our meta-analysis. The pooled and subgroup meta-analyses showed robust grey matter reductions in the right lentiform nucleus extending into the parahippocampus, the hippocampus and the amygdala, the bilateral medial frontal gyrus and the right subcallosal gyrus as well as a grey matter increase in the right lingual gyrus. Meta-regression analyses showed that mean age and the percentage of female patients with LLD were not significantly related to grey matter changes. The analysis techniques, patient characteristics and clinical variables of the studies included were heterogeneous, and most participants were medicated. The present meta-analysis is, to our knowledge, the first to overcome previous inconsistencies in the VBM studies of LLD and provide robust evidence for grey matter alterations within fronto-striatal-limbic networks, thereby implicating them in the pathophysiology of LLD. The mean age and the percentage of female patients with LLD did not appear to have a measurable impact on grey matter changes, although we cannot rule out the contributory effects of medication.

Reduced cerebrospinal fluid levels of brain-derived neurotrophic factor is associated with cognitive impairment in late-life major depression.

Late-life depression (LLD) is associated with reduced neurotrophic support and abnormalities in neurodegenerative cascades. The aim of the present study is to determine the concentrations of brain-derived neurotrophic factor (BDNF), amyloid-β42, total Tau, and phosphorylated Tau in the cerebrospinal fluid (CSF) of patients with LLD and cognitive impairment compared to healthy older adults. We included 25 antidepressant-free patients with LLD (10 with mild cognitive impairment [LLD + MCI] and 15 with no cognitive decline [LLD + NCD]) and 25 healthy older adults as a comparison group. Depressive symptoms were assessed by the 21-item Hamilton Depression Rating Scale (HDRS-21) and cognitive performance by a comprehensive cognitive battery. Patients with LLD + MCI showed significantly lower CSF BDNF levels compared to LLD + NCD and healthy controls (p = .003). There were no significant differences in Alzheimer's disease-related CSF biomarkers between groups. CSF BDNF concentrations were positively correlated with Cambridge Cognitive Test (CAMCOG) scores (r = .36, p = .02). The present study adds to the growing body of evidence that abnormalities in the BDNF system are involved in the pathophysiology of LLD. The reduction of the availability of BDNF in the central nervous system may indicate increased vulnerability to the development of several age-related neuropsychiatric disorders as well as to adverse cognitive outcomes.

Corpus callosum size may predict late-life depression in women: A 10-year follow-up study

BackgroundRecent research on late-life depression (LLD) pathophysiology suggests the implication of abnormalities in cerebral white matter and particularly in interhemispheric transfer. Corpus callosum (CC) is the main brain interhemispheric commissure. Hence, we investigated the association between baseline CC measures and risk of LDD. MethodsWe studied 467 non-demented individuals without LLD at baseline from a cohort of elderly community-dwelling people (the ESPRIT study). LLD was assessed at year 2, 4, 7 and 10 of the study follow-up. At baseline, T1-weighted magnetic resonance images were manually traced to measure the mid-sagittal areas of the anterior, mid and posterior CC. Multivariate Cox proportional hazards models stratified by sex were used to predict LLD incidence over 10 years. ResultsA significant interaction between gender and CC size was found (p=0.02). LLD incidence in elderly women, but not in men, was significantly associated with smaller anterior (HR 1.37 [1.05–1.79] p=0.017), mid (HR 1.43 [1.09–1.86] p=0.008), posterior (HR 1.39 [1.12–1.74] p=0.002) and total (HR 1.53 [1.16–2.00] p=0.002) CC areas at baseline in Cox models adjusted for age, education, global cognitive impairment, ischemic pathologies, left-handedness, white matter lesion, intracranial volume and past depression. LimitationsThe main limitation was the retrospective assessment of major depression. ConclusionSmaller CC size is a predictive factor of incident LLD over 10 years in elderly women independently of cognitive deterioration. Our finding suggests a possible role of CC and reduced interhemispheric connectivity in LLD pathophysiology. Extensive explorations are needed to clarify the mechanisms leading to CC morphometric changes in mood disorders.

Executive Functioning Complaints and Escitalopram Treatment Response in Late-Life Depression

Executive dysfunction may play a key role in the pathophysiology of late-life depression. Executive dysfunction can be assessed with cognitive tests and subjective report of difficulties with executive skills. The present study investigated the association between subjective report of executive functioning complaints and time to escitalopram treatment response in older adults with major depressive disorder (MDD). 100 older adults with MDD (58 with executive functioning complaints and 42 without executive functioning complaints) completed a 12-week trial of escitalopram. Treatment response over 12 weeks, as measured by repeated Hamilton Depression Rating Scale scores, was compared for adults with and without executive complaints using mixed-effects modeling. Mixed effects analysis revealed a significant group × time interaction, F(1, 523.34) = 6.00, p = 0.01. Depressed older adults who reported executive functioning complaints at baseline demonstrated a slower response to escitalopram treatment than those without executive functioning complaints. Self-report of executive functioning difficulties may be a useful prognostic indicator for subsequent speed of response to antidepressant medication.

Reduced Serum Nerve Growth Factor in Patients With Late-Life Depression

Nerve growth factor (NGF) is one of the most abundant neurotrophic factors in the central nervous system and has been involved in several neuropsychiatric disorders. We recruited 77 age- and gender-matched elderly subjects (38 with late-life depression, 17 with previous major depressive episode, and 22 healthy subjects in the comparison group). Serum concentration of NGF was determined by enzyme-linked immunosorbent assay. NGF levels were significantly reduced in the depressed patients (p = 0.002) as compared with healthy elderly controls. Elderly control subjects with previous depressive episode also showed a significant reduction in NGF levels as compared with controls (p <0.01); NGF levels were similar between patients with current depressive episode and previous depressive episode (p = 0.2). The present findings provide additional evidence to the relevance of reduced neurotrophic support in the pathophysiology of late-life depression. Also, reduced serum NGF level may be a state marker of depression in elderly subjects.