Anterior cingulate cortical volumes and treatment remission of geriatric depression

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.

Oxytocin attenuates neuroinflammation-induced anxiety through restoration of excitation and inhibition balance in the anterior cingulate cortex in mice

BACKGROUND

Accumulative evidence suggested that the oxytocin system plays a role in socio-emotional disorders, although its role in neuroinflammation-induced anxiety remains unclear.

METHOD

In the present study, anxiety-like behavior was induced in cohorts of animals through repeated lipopolysaccharide (LPS, 0.5 mg/kg, daily, Escherichia coli O55:B5) i.p. injections for seven consecutive days. These different cohorts were subsequently used for anxiety-like behavior assessment with open field test, elevated plus maze, and novelty-suppressed feeding test or for electrophysiology (EEG) recordings of miniature excitatory postsynaptic currents (mEPSCs), miniature inhibitory postsynaptic currents (mIPSCs), or local field potential (LFP) in vivo or ex vivo settings. Samples of the anterior cingulate cortex (ACC) from some cohorts were harvested to conduct immunostaining or western blotting analysis of oxytocin, oxytocin receptor, CamkII, GABA, vGAT, vGLUT2, and c-fos. The dendritic spine density was assessed by Golgi-Cox staining.

RESULTS

Repeated LPS injections induced anxiety-like behavior with concurrent decreases of oxytocin, vGLUT2, mEPSC, dendritic spine, c-fos, membrane excitability, and EEG beta and gamma oscillations, but increased oxytocin receptor and vGAT expressions in the ACC; all these changes were ameliorated by oxytocin intranasal or local brain (via cannula) administration.

CONCLUSION

Taken together, our data suggested that oxytocin system may be a therapeutic target for developing treatment to tackle neuroinflammation-induced anxiety.

Estrogen receptor GPR30 in the anterior cingulate cortex mediates exacerbated neuropathic pain in ovariectomized mice

Menopausal women experience neuropathic pain 63% more frequently than men do, which may attribute to the estrogen withdrawal. However, the underlying mechanisms remain unclear. Here, the role of estrogen receptors (ERs) in ovariectomized (OVX) female mice following chronic constriction injury (CCI) was investigated. With 17β-estradiol (E2) supplemented, aggravated mechanical allodynia in OVX mice could be significantly alleviated, particularly after intra-anterior cingulate cortex (ACC) E2 delivery. Pharmacological interventions further demonstrated that the agonist of G-protein-coupled estrogen receptor 30 (GPR30), rather than ERα or ERβ in the ACC, exhibited the similar analgesic effect as E2, whereas antagonist of GPR30 exacerbated allodynia. Furthermore, OVX surgery reduced GPR30 expression in the ACC, which could be restored with estrogen supplementation. Selective downregulation of GPR30 in the ACC of naïve female mice induces mechanical allodynia, whereas GPR30 overexpression in the ACC remarkedly alleviated OVX-exacerbated allodynia. Collectively, estrogen withdrawal could downregulate the ACC GPR30 expression, resulting in exacerbated neuropathic pain. Our findings highlight the importance of GPR30 in the ACC in aggravated neuropathic pain during menopause, and offer a potential therapeutic candidate for neuropathic pain management in menopausal women.

Grey matter volume predicts improvement in geriatric depression in response to Tai Chi compared to Health Education

OBJECTIVES

Geriatric depression (GD) is associated with cognitive impairment and brain atrophy. Tai-Chi-Chih (TCC) is a promising adjunct treatment to antidepressants. We previously found beneficial effects of TCC on resting state connectivity in GD. We now tested the effect of TCC on gray matter volume (GMV) change and the association between baseline GMV and clinical outcome.

PARTICIPANTS

Forty-nine participants with GD (>=60 y) underwent antidepressant treatment (38 women).

INTERVENTION

Participants completed 3 months of TCC (N = 26) or health and wellness education control (HEW; N = 23).

MEASUREMENTS

Depression and anxiety symptoms and MRI scans were acquired at baseline and 3-month follow-up. General linear models (GLMs) tested group-by-time interactions on clinical scores. Freesurfer 6.0 was used to process T1-weighted images and to perform voxel-wise whole-brain GLMs of group on symmetrized percent GMV change, and on the baseline GMV and symptom change association, controlling for baseline symptom severity. Age and sex served as covariates in all models.

RESULTS

There were no group differences in baseline demographics or clinical scores, symptom change from baseline to follow-up, or treatment-related GMV change. However, whole-brain analysis revealed that lower baseline GMV in several clusters in the TCC, but not the HEW group, was associated with larger improvements in anxiety. This was similar for right precuneus GMV and depressive symptoms.

CONCLUSIONS

While we observed no effect on GMV due to the interventions, baseline regional GMV predicted symptom improvements with TCC but not HEW. Longer trials are needed to investigate the long-term effects of TCC on clinical symptoms and neuroplasticity.

Understanding the benefits of extrinsic emotion regulation in depression

Depression is a serious psychiatric illness that negatively affects people's feelings, thoughts, and actions. Providing emotion regulation support to others, also termed Extrinsic Emotion Regulation (EER), reduces depressive symptoms such as perseverative thinking and negative mood. In this conceptual review paper, we argue that EER may be especially beneficial for individuals with depression because it enhances the cognitive and affective processes known to be impaired in depression. Behavioral studies have shown that EER recruits processes related to cognitive empathy, intrinsic emotion regulation (IER), and reward, all impaired in depression. Neuroimaging data support these findings by showing that EER recruits brain regions related to these three processes, such as the ventrolateral prefrontal cortex which is associated with IER, the ventral striatum, which is associated with reward-related processes, and medial frontal regions related to cognitive empathy. This conceptual review paper sheds light on the mechanisms underlying the effectiveness of EER for individuals with depression and therefore offers novel avenues for treatment.

Assessment of Characteristics of Imaging Biomarkers for Quantifying Anterior Cingulate Cortex Changes: A Twin Study of Middle- to Advanced-Aged Populations in East Asia

Background and Objectives: Our aim was to assess genetic and environmental effects on surface morphological parameters for quantifying anterior cingulate cortex (ACC) changes in middle- to advanced-age East Asians using twin analysis. Materials and Methods: Normal twins over 39 years old comprising 37 monozygotic pairs and 17 dizygotic pairs underwent 3-dimensional (3D) T1-weighted imaging of the brain at 3T. Freesurfer-derived ACC parameters including thickness, standard deviation of thickness (STDthickness), volume, surface area, and sulcal morphological parameters (folding, mean, and Gaussian curvatures) were calculated from 3D T1-weighted volume images. Twin analysis with a model involving phenotype variance components of additive genetic effects (A), common environmental effects (C), and unique environmental effects (E) was performed to assess the magnitude of each genetic and environmental influence on parameters. Results: Most parameters fit best with an AE model. Both thickness (A: left 0.73/right 0.71) and surface area (A: left 0.63/right 0.71) were highly heritable. STDthickness was low to moderately heritable (A: left 0.48/right 0.29). Volume was moderately heritable (A: left 0.37). Folding was low to moderately heritable (A: left 0.44/right 0.28). Mean curvature (A: left 0.37/right 0.65) and Gaussian curvature (A: right 0.79) were moderately to highly heritable. Right volume and left Gaussian curvature fit best with a CE model, indicating a relatively weak contribution of genetic factors to these parameters. Conclusions: When assessing ACC changes in middle- to advanced-age East Asians, one must keep in mind that thickness and surface area appear to be strongly affected by genetic factors, whereas sulcal morphological parameters tend to involve environmental factors.

Combined fractional anisotropy and subcortical volumetric deficits in patients with mild-to-moderate depression: Evidence from the treatment of antidepressant traditional Chinese medicine

Numerous neuroimaging studies have demonstrated that diverse brain structural plasticity could occur in a human brain during a depressive episode. However, there is a lack of knowledge regarding the underlying mechanisms of mild-to-moderate depression (MMD), especially the changes of brain structural characteristics after treatment with the Shuganjieyu capsule (SG), a kind of traditional Chinese medicine that has been recommended for the specialized treatment of MMD. In this study, we investigated the structural brain plasticity in MMD that have been undergoing 8 weeks of SG treatment compared with age- and sex-matched healthy controls (HCs) and assessed the relationship between these brain structural alternations and clinical symptoms in MMD. At the baseline, we found that: (1) fractional anisotropy (FA) values in patients with MMD were found to be significantly increased in the regions of anterior limb of internal capsule (ALIC) [MNI coordinates: Peak (x/y/z) = 102, 126, 77; MMD FA_peak (Mean ± SD) = 0.621 ± 0.043; HCs FA_peak (Mean ± SD) = 0.524 ± 0.052; MMD > HCs, t = 9.625, p < 0.001] and posterior limb of internal capsule (PLIC) [MNI coordinates: Peak (x/y/z) = 109, 117, 87; MMD FA_peak (Mean ± SD) = 0.694 ± 0.042; HCs FA_peak (Mean ± SD) = 0.581 ± 0.041; MMD > HCs, t = 12.90, p < 0.001], and FA values were significantly positively correlated with HAMD scores in patients with MMD. (2) Patients with MMD showed smaller gray matter volume (GMV) of the dorsolateral prefrontal cortex (DLPFC), frontal cortex, occipital cortex, and precuneus, and the GMV of DLPFC was negatively correlated with HAMD scores. After SG treatment, we found that (1) the HAMD scores decreased; (2) FA values were significantly decreased in the regions of the ALIC and PLIC compared to those at baseline and TBSS revealed no significant differences in FA values between patients with MMD and HCs. (3) The structural characteristics of DLPFC in patients with MMD obtained at the 8th week were improved, e.g., no significant differences in GMV of DLPFC between the two groups. Taken together, our results provided neuroimaging evidence suggesting that SG is an effective treatment for patients with MMD. Moreover, alterations of GMV after 8 weeks of SG treatment indicated a potential modulation mechanism in brain structural plasticity within the DLPFC in patients with MMD.

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.

White matter markers and predictors for subject-specific rTMS response in major depressive disorder

Repetitive transcranial magnetic stimulation (rTMS) has established therapeutic efficacy for major depressive disorder (MDD). While translational research has focused primarily on understanding the mechanism of action of TMS on functional activation and connectivity, the effects on structural connectivity remain largely unknown especially when rTMS is applied using subject-specific brain targets. This study aims to use novel diffusion magnetic resonance imaging (dMRI) analysis to examine microstructural changes related to rTMS treatment response using a unique cohort of 21 patients with MDD treated using rTMS with subject-specific targets. White matter dMRI microstructural measures and clinical scores were captured before and after the full course of treatment. We defined disease-relevant fiber bundles connected to different subregions of the left prefrontal cortex and analyzed changes in diffusion properties as well as correlations between the changes of dMRI measures and the changes in Hamilton Depression Rating Scale (HAMD). No significant changes were observed in tracts connected to the TMS targets. rTMS significantly increased the extra-axonal free-water volume, fractional anisotropy and decreased the radial diffusivity in anterior-medial prefrontal fiber bundles but did not lead to raw changes in lateral prefrontal tracts. That said, the microstructural changes in the lateral prefrontal white matter were significantly correlated with treatment response. Moreover, pre-rTMS dMRI measures of the dorsal anterior cingulate cortex and lateral prefrontal cortex connections are correlated with changes in HAMD scores. Microstructural changes in the anterior-medial and lateral prefrontal white matter are potentially involved in treatment response to TMS, though further investigation is needed using larger datasets.

Nutritional therapy can reduce the burden of depression management in low income countries: A review

Depression is a serious mental and mood disorder with global health and economic burden. This burden may be overwhelming in low income countries, although there are insufficient data. Most antidepressant formulations are predicated on the monoamine, neuroendocrine and neuro-inflammation hypotheses, with little or no cognizance to other neurochemicals altered in depression. A nutritional strategy with or without conventional antidepressants is recommended, as nutrition plays vital roles in the onset, severity and duration of depression, with poor nutrition contributing to its pathogenesis. This review discusses nutritional potentials of utilizing omega-3 fatty acids, proteins, vitamins, minerals and herbs or their phytochemicals in the management of depression with the aim of reducing depression burden. Literature search of empirical data in books and journals in data bases including but not limited to PubMed, Scopus, Science Direct, Web of Science and Google Scholar that might contain discussions of sampling were sought, their full text obtained, and searched for relevant content to determine eligibility. Omega-3 fatty and amino acids had significant positive anti-depression outcomes, while vitamins and minerals although essential, enhanced omega-3 fatty and amino acids activities. Some herbs either as whole extracts or their phytochemicals/metabolites had significant positive anti-depression efficacy. Nutrition through the application of necessary food classes or herbs as well as their phytochemicals, may go a long way to effectively manage depression. This therefore will provide inexpensive, natural, and non-invasive therapeutic means with reduced adverse effects that can also be applied alongside clinical management. This nutritional strategy should be given more attention in research, assessment and treatment for those with depression and other mental illness in low income countries, especially in Africa.

Coordinate-Based Network Mapping of Brain Structure in Major Depressive Disorder in Younger and Older Adults: A Systematic Review and Meta-Analysis

OBJECTIVE

Structural neuroimaging findings in younger and older adults with major depressive disorder (MDD) are highly heterogeneous, possibly as a result of methodological limitations, lack of distinction between MDD and late-life depression (LLD), or clinical moderators. Using a novel meta-analytic network mapping approach, the authors sought to identify the circuits affected in different clinical subtypes of MDD.

METHODS

The authors identified all voxel-based and surface-based morphometry studies published through October 2020 that compared younger adults with MDD or older adults with LLD to nonpsychiatric control participants. An activation likelihood estimation (ALE) analysis and a novel coordinate-based network mapping approach were used to identify brain circuits affected in MDD and LLD. Meta-regressions examined the impact of age at onset in older patients with LLD and treatment with antidepressants in younger patients with MDD.

RESULTS

The authors analyzed 145 comparisons from 143 articles, including a total of 14,318 participants (MDD: N=6,362; LLD: N=535; control subjects: N=7,421). Significant ALE results confirmed previous findings implicating the left and right parahippocampus and anterior cingulate in MDD and the anterior cingulate in LLD. In contrast, coordinate-based network mapping showed differences in the frontoparietal, dorsal attention, and visual networks both in MDD and LLD. Meta-regressions showed that late onset was significantly associated with widespread structural abnormalities in LLD, and treatment with antidepressants showed a significant association with abnormalities in the anterior cingulate (Brodmann's area 32) and dorsolateral prefrontal cortex (Brodmann's area 9) in MDD.

CONCLUSIONS

These findings help to clarify the shared circuitry of depression across the adult lifespan and highlight some unique circuitry relevant to late-onset depression, which may explain some of the risk for cognitive decline and dementia.

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.

Interactions Between Age, Sex, Menopause, and Brain Structure at Midlife: A UK Biobank Study

OBJECTIVES

Age and female sex are risk factors for dementia, and menopause is associated with cognitive dysfunction. Previous work largely considered the effects of sex and menopause as being independent of age. We studied whether age interacts with sex or menopause in explaining imaging biomarkers of dementia during midlife.

METHODS

In this cross-sectional study of UK Biobank participants with brain magnetic resonance imaging (MRI), we explored the interaction of age with sex or menopausal status in explaining total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMHV), regional cortical volume , and subcortical volume.

RESULTS

Data were available for 1827 postmenopausal women, 230 pre/perimenopausal women and 2165 men (median age 63.3 years). There was a significant interaction between age and sex (P = .024) for TBV, where the inverse association age with TBV was steeper in women (β = -5.35 mL/year) than in men (β = -4.77 mL/year). Similar age-sex interactions were also observed for GMV and WMV. In women, there was a significant interaction between age and menopausal status (P = .007) where the inverse association of age with TBV was steeper in postmenopausal (β = -5.89 mL/year) than in pre/perimenopausal women (β = -1.61 mL/year). Similar age-menopause interactions were found in predicting lower GMV and higher WMHV. Differences in the direction of these age-sex and age-menopause interactions were found for regional cortical and subcortical brain volumes.

CONCLUSION

Sex and menopause both interact with age during midlife in explaining MRI biomarkers of dementia. Further work is required to understand the mechanisms driving these interactions to develop strategies for delaying dementia.

Exergames and Depressive Symptoms in Older Adults: A Systematic Review

To synthesize and critique studies that examined the impact of exergames on depressive symptoms in older adults. Articles were retrieved from the databases CINAHL, Embase, PsychINFO, and Medline. Studies were included in the review if they involved a physical activity/videogame intervention and measured outcomes of depressive symptoms in older adults. The search generated 957 articles for consideration, which were narrowed to 17 articles after applying exclusion criteria. In studies that required depressive symptoms as an inclusion criterion, there was an improvement in depressive symptoms in older adults following the exergame intervention. In studies that did not require depressive symptoms as an inclusion criterion, researchers found mixed results. Future older adult exergame research should measure depression as a primary outcome, utilize control groups with random sampling, consist of larger sample sizes, and include people with disabilities.

Neuroanatomical predictors of L-DOPA response in older adults with psychomotor slowing and depression: A pilot study

BACKGROUND

Declining function in dopamine circuits is implicated in normal aging and late-life depression (LLD). Dopamine augmentation recently has shown therapeutic promise, but predictors of response are unknown.

METHODS

Depressed elders with slowed gait underwent baseline magnetic resonance imaging (MRI) and [¹¹C]raclopride positron emission tomography (PET). Subjects then received open treatment with carbidopa/levodopa (L-DOPA) for three weeks. Linear regressions examined relationships between baseline MRI measures, [¹¹C]raclopride binding, and behavioral outcomes.

RESULTS

Among N = 16 participants aged 72.5 ± 6.8 years, higher left superior temporal gyrus volume was associated with higher processing speed at baseline, while cortical thinning in a processing speed network was associated with greater improvement following L-DOPA. Greater volume and cortical thickness in brain regions associated with mobility were associated with higher baseline gait speed. Higher baseline white matter hyperintensity volume predicted less post-L-DOPA improvement on dual task gait speed and IDS-SR scores. Higher [¹¹C]raclopride binding in the associative striatum was associated with cortical thickness in some, but not all, processing speed brain regions, while higher binding in sensorimotor striatum was significantly associated with left caudate volume.

LIMITATIONS

Limiting the conclusions drawn from this pilot study are the small sample size and open administration of L-DOPA.

CONCLUSIONS

Greater baseline brain volumes and cortical thickness in regions supporting cognition and gait were associated with higher behavioral performance, while lower structural integrity was associated with increased responsivity to L-DOPA. If substantiated in larger studies, these findings could facilitate the targeting of dopaminergic treatments to those LLD patients most likely to respond.

Cognitive Control Network Homogeneity and Executive Functions in Late-Life Depression

BACKGROUND

Late-life depression is characterized by network abnormalities, especially within the cognitive control network. We used alternative functional connectivity approaches, regional homogeneity (ReHo) and network homogeneity, to investigate late-life depression functional homogeneity. We examined the association between cognitive control network homogeneity and executive functions.

METHODS

Resting-state functional magnetic resonance imaging data were analyzed for 33 older adults with depression and 43 healthy control subjects. ReHo was performed as the correlation between each voxel and the 27 neighbor voxels. Network homogeneity was calculated as global brain connectivity restricted to 7 networks. T-maps were generated for group comparisons. We measured cognitive performance and executive functions with the Dementia Rating Scale, Trail-Making Test (A and B), Stroop Color Word Test, and Digit Span Test.

RESULTS

Older adults with depression showed increased ReHo in the bilateral dorsal anterior cingulate cortex (dACC) and the right middle temporal gyrus, with no significant findings for network homogeneity. Hierarchical linear regression models showed that higher ReHo in the dACC predicted better performance on Trail-Making Test B (p < .001; R2 = .49), Digit Span Backward (p < .05; R2 = .23), and Digit Span Total (p < .05; R2 = .23). Used as a seed, the dACC cluster of higher ReHo showed lower functional connectivity with bilateral precuneus.

CONCLUSIONS

Higher ReHo within the dACC and right middle temporal gyrus distinguish older adults with depression from control subjects. The correlations with executive function performance support increased ReHo in the dACC as a meaningful measure of the organization of the cognitive control network and a potential compensatory mechanism. Lower functional connectivity between the dACC and the precuneus in late-life depression suggests that clusters of increased ReHo may be functionally segregated.

[Personalized approach to the treatment of depression in the elderly]

AIM

To develop a personalized approach to the appointment of a complex antidepressant therapy in combination with drugs of neuroprotective and neurotrophic action in depressed elderly patients based on the selection of predictors of low therapeutic response (LTR).

MATERIAL AND METHODS

The study included 152 hospitalized patients, aged 60 years and older, with moderate and mild depression (ICD-10) who received monotherapy (44 people) with antidepressants of the new generation and complex therapy (108 people) with the same antidepressants in combination with neuroprotective drugs. In the monotherapy group, correlations between treatment efficacy (change in average total HAMD-17 scores) and a set of parameters, including socio-demographic data, results of psychopathological, somatic, standardized assessment and neuroimaging (CT) of the brain were analyzed. The validity of the established correlations as predictors of LTR was estimated based on a comparison of their frequency among the responders (≥50% reduction) and non-responders (<50% reduction). Comparison of the efficacy of therapy in groups of patients with mono - and complex therapy was carried out depending on the presence or absence of predictors of LTR.

RESULTS

LTR predictors are living alone, complaints about memory loss and signs of pronounced diffuse lesions of the subcortical white matter of the brain, which are significantly more frequently observed in non-responders (p<0.05). The increase in the number of predictors (2 and more) correlates with a significant decrease in therapeutic efficacy (p<0.001). Patients with complex in structure and protracted depressions tend to decrease in efficiency, and in most of them (more than 87% of cases) LTR predictors are detected. In patients with LTR predictors, the complex therapy is significantly more effective than monotherapy, allowing in all cases to achieve 50% reduction of depressive symptoms by the 4th week of treatment.

CONCLUSION

Personalized indications for the appointment of complex antidepressant therapy in combination with neuroprotective drugs in depressed elderly patients are formulated.

Structural and functional neuroimaging studies in generalized anxiety disorder: a systematic review

OBJECTIVES

Brain imaging studies carried out in patients suffering from generalized anxiety disorder (GAD) have contributed to better characterize the pathophysiological mechanisms underlying this disorder. The present study reviews the available functional and structural brain imaging evidence on GAD, and suggests further strategies for investigations in this field.

METHODS

A systematic literature review was performed in PubMed, PsycINFO, and Google Scholar, aiming to identify original research evaluating GAD patients with the use of structural and functional magnetic resonance imaging as well as diffusion tensor imaging.

RESULTS

The available studies have shown impairments in ventrolateral and dorsolateral prefrontal cortex, anterior cingulate, posterior parietal regions, and amygdala in both pediatric and adult GAD patients, mostly in the right hemisphere. However, the literature is often tentative, given that most studies have employed small samples and included patients with comorbidities or in current use of various medications. Finally, different methodological aspects, such as the type of imaging equipment used, also complicate the generalizability of the findings.

CONCLUSIONS

Longitudinal neuroimaging studies with larger samples of both juvenile and adult GAD patients, as well as at risk individuals and unaffected relatives, should be carried out in order to shed light on the specific biological signature of GAD.

Intrinsic Brain Network Biomarkers of Antidepressant Response: a Review

PURPOSE OF REVIEW

Poor treatment response is a hallmark of major depressive disorder. To tackle this problem, recent neuroimaging studies have sought to characterize antidepressant response in terms of pretreatment differences in intrinsic functional brain networks. Our aim is to review recent studies that predict antidepressant response using intrinsic network connectivity. We discuss current methodological limitations and directions for future antidepressant biomarker studies.

RECENT FINDINGS

Functional connectivity stemming from the subgenual and rostral anterior cingulate has shown particular consistency in predicting antidepressant response. Differences in this connectivity may prove fruitful in differentiating treatment responders to many antidepressant interventions. Future biomarker studies should integrate biological MDD subtypes to address the disorder's inherent clinical heterogeneity. These clinical and scientific advancements have the potential to address this population marked by limited treatment response. Methodological considerations, including patient selection, response criteria, and model overfitting, will require future investigation to ensure that biomarkers generalize for prospective prediction of treatment response.

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

BACKGROUND

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.

METHOD

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.

MAIN FINDINGS

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.

CONCLUSION

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.

Intrinsic Functional Network Connectivity Is Associated With Clinical Symptoms and Cognition in Late-Life Depression

BACKGROUND

Late-life depression (LLD) has been associated with alterations in intrinsic functional networks, best characterized in the default mode network (DMN), cognitive control network (CCN), and salience network. However, these findings often derive from small samples, and it is not well understood how network findings relate to clinical and cognitive symptomatology.

METHODS

We studied 100 older adults (n = 79 with LLD, n = 21 nondepressed) and collected resting-state functional magnetic resonance imaging, clinical measures of depression, and performance on cognitive tests. We selected canonical network regions for each intrinsic functional network (DMN, CCN, and salience network) as seeds in seed-to-voxel analysis. We compared connectivity between the depressed and nondepressed groups and correlated connectivity with depression severity among depressed subjects. We then investigated whether the observed connectivity findings were associated with greater severity of common neuropsychiatric symptoms or poorer cognitive performance.

RESULTS

LLD was characterized by decreased DMN connectivity to the frontal pole, a CCN region (Wald χ²₁ = 22.33, p < .001). No significant group differences in connectivity were found for the CCN or salience network. However, in the LLD group, increased CCN connectivity was associated with increased depression severity (Wald χ²₁ > 20.14, p < .001), greater anhedonia (Wald χ²₁ = 7.02, p = .008) and fatigue (Wald χ²₁ = 6.31, p = .012), and poorer performance on tests of episodic memory (Wald χ²₁ > 4.65, p < .031), executive function (Wald χ²₁ = 7.18, p = .007), and working memory (Wald χ²₁ > 4.29, p < .038).

CONCLUSIONS

LLD is characterized by differences in DMN connectivity, while CCN connectivity is associated with LLD symptomology, including poorer performance in several cognitive domains.

Specific Cognitive-Psychopathological Phenotypes in Patients With Early Stages of Subcortical Vascular Neurocognitive Disorders: A Hospital-Based Case-Control Study

BACKGROUND

Diagnosis of subcortical vascular neurocognitive disorders' (ScVNCDs) is currently based on neuropsychological and neuroimaging approaches; nevertheless, clinical features, apart from cognitive impairments (CI), may provide additional information about ScVNCD phenotypes. We aimed to determine whether CI and neuropsychiatric symptoms (NPS) form such clinical phenotypes in the mild and early stage of major ScVNCD.

METHODS

Our sample included 88 cognitively normal elderly individuals, 100 patients with mild ScVNCD, and 60 patients with early major ScVNCD. All participants had neuropsychological, neuropsychiatric, neurological, and functional evaluations. The prevalence of NPS was based on the neuropsychiatric inventory. The statistical analyses included parametric and nonparametric tests and multivariate regression.

RESULTS

The severity of executive dysfunction increased through stages of ScVNCD progression ( P < .0001). The NPS with significant predictive value for mild ScVNCD membership was depression (odds ratio [OR] = 7.4), whereas for early major ScVNCD were depression (OR = 5.5) and apathy (OR = 7.6). Those distinguishing NPS and impairments of executive tests' performance significantly correlated ( P < .05) in patients with mild/major ScVNCD.

CONCLUSION

Significant correlation between pathognomonic cognitive and NPS in compared groups suggest that dysexecutive-depressive syndrome can be the main phenotype in mild ScVNCD, while dysexecutive-depressive-apathetic syndrome in the early stage of major ScVNCD. Obtained cognitive-psychopathological phenotypes may allow a better comprehension of the ScVNCD pathophysiology and improve the diagnostic and therapeutic approach.

Smaller hippocampal volume in current but not in past depression in comparison to healthy controls: Minor evidence from an older adults sample

BACKGROUND

Structural neuroimaging studies revealed a consistent pattern of volumetric reductions in both hippocampus (HC) and anterior cingulate cortex (ACC) of individuals with major depressive episode(s) (MDE). This study investigated HC and ACC volume differences in currently depressed individuals (n = 150), individuals with a past lifetime MDE history (n = 79) and healthy controls (n = 287).

METHODS

Non-demented individuals were recruited from a cohort of community-dwelling older adults (ESPRIT study). T1-weighted magnetic resonance images and FreeSurfer Software (automated method) were used. Concerning HC, a manual method of measurement dividing HC into head, body, and tail was also used. General Linear Model was applied adjusting for covariates.

RESULTS

Current depression was associated with lower left posterior HC volume, using manual measurement, in comparison to healthy status. However, when we slightly changed sub-group inclusion criteria, results did not survive to correction for multiple comparisons.

CONCLUSIONS

The finding of lower left posterior HC volume in currently depressed individuals but not in those with a past MDE compared to healthy controls could be related to brain neuroplasticity. Additionally, our results may suggest manual measures to be more sensitive than automated methods.

Advances and Barriers for Clinical Neuroimaging in Late-Life Mood and Anxiety Disorders

PURPOSE OF REVIEW

Mood and anxiety disorders are very commonly experienced by older adults and are becoming a growing concern due to the rapidly aging global population. Recent advances in neuroimaging may help in improving outcomes in late-life mood and anxiety disorders. The elucidation of mechanisms contributing to late-life mental health disorders may ultimately lead to the identification of novel therapeutic interventions. Alternatively, clinically validated imaging biomarkers may allow for the prediction of treatment response and identification of better therapeutic approaches in late-life mood and anxiety disorders.

RECENT FINDINGS

In community samples, late-life depression and late-life generalized anxiety disorder occur up to 38 and 15%, respectively, while late-life bipolar disorder is less common and occur in approximately 0.5% of the population. There are significant challenges in treating and improving outcome in late-life mood and anxiety disorders. Time to treatment response and treatment resistance are increased in older adults. Novel neuroimaging techniques have the potential to improve diagnostic and therapeutic outcome in late-life mood and anxiety disorders either through "personalized pharmacotherapy" or through identifying dysfunction regions/networks to be subsequently used for direct interventions such as transcranial magnetic stimulation. This review will provide an overview of recent literature that substantiates the potential role of neuroimaging in clinical practice, as well as the barriers that must be overcome prior to clinical translation.

Rostral Anterior Cingulate Cortex Morphology Predicts Treatment Response to Internet-Based Cognitive Behavioral Therapy for Depression

BACKGROUND

Rostral and subgenual anterior cingulate cortex (rACC and sgACC) activity and, to a lesser extent, volume have been shown to predict depressive symptom improvement across different antidepressant treatments. This study extends prior work by examining whether rACC and/or sgACC morphology predicts treatment response to Internet-based cognitive behavioral therapy (iCBT) for major depressive disorder. This is the first study to examine neural predictors of response to iCBT.

METHODS

Hierarchical linear modeling tested whether pretreatment rACC and sgACC volumes predicted depressive symptom improvement during a six-session (10-week) randomized clinical trial of iCBT (n = 35) versus a monitored attention control condition (n = 38). Analyses also tested whether pretreatment rACC and sgACC volumes differed between patients who achieved depression remission versus patients who did not remit.

RESULTS

Larger pretreatment right rACC volume was a significant predictor of greater depressive symptom improvement in iCBT even when controlling for demographic (age, gender, race) and clinical (baseline depression, anhedonia, and anxiety) variables previously linked to treatment response. In addition, pretreatment right rACC volume was larger among patients receiving iCBT whose depression eventually remitted relative to patients who did not remit. Corresponding analyses in the monitored attention control group and for the sgACC were not significant.

CONCLUSIONS

rACC volume before iCBT demonstrated incremental predictive validity beyond clinical and demographic variables previously found to predict symptom improvement. Such findings may help inform our understanding of the mediating anatomy of iCBT and, if replicated, may suggest neural targets to augment treatment response (e.g., via modulation of rACC function).

Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression

Prior studies have demonstrated dysfunctions within the core neurocognitive networks (the executive control [ECN], default mode [DMN] and salience [SN] networks) in late-life depression (LLD). Whether inter-network dysfunctional connectivity is present in LLD, and if such disruptions are associated with core symptom dimensions is unknown. A cross-sectional resting-state functional connectivity magnetic resonance imaging investigation was conducted of LLD (n = 39) and age- and gender-equated healthy comparison (HC) (n = 29) participants. Dual regression independent component analysis approach was used to identify components that represented the ECN, DMN and SN. The intrinsic inter-network connectivity was compared between LLD and HC participants and the relationship of inter-network connectivity abnormalities with dimensional measures was examined. Relative to HC participants, LLD subjects showed decreased inter-network connectivity between the bilateral ECN and default mode subcortical (thalamus, basal ganglia and ventral striatum) networks, and the left ECN and SN insula component; and increased inter-network connections between the left ECN and posterior DMN and salience (dorsal anterior cingulate) network components. Distinct inter-network connectivity abnormalities correlated with depression and anxiety severity, and executive dysfunction in LLD participants. LLD subjects also showed pronounced intra-network connectivity differences within the ECN, whereas fewer but significant DMN and SN disruptions were also detected. Investigating the intrinsic inter-network functional connectivity could provide a mechanistic framework to better understand the neural basis that underlies core symptom dimensions in LLD. Inter-network connectivity measures have the potential to be neuroimaging biomarkers of symptom dimensions comprising LLD, and may assist in developing symptom-specific treatment algorithms.

Subgenual Cingulate Cortex Functional Connectivity in Relation to Depressive Symptoms and Cognitive Functioning in Type 1 Diabetes Mellitus Patients

OBJECTIVES

Patients with Type 1 diabetes mellitus (T1DM) are at an increased risk for major depression, but its underlying mechanisms are still poorly understood. In nondiabetic participants, mood disturbances are related to altered subgenual cingulate cortex (SGC) resting-state functional connectivity. We tested for SGC connectivity alterations in T1DM, whether these alterations were related to depressive symptoms, and if depressive symptoms were associated with cognition.

METHODS

A bilateral SGC seed-based resting-state functional magnetic resonance imaging analysis was performed in 104 T1DM patients and 49 controls without known psychiatric diagnosis or treatment. Depressive symptoms were self-reported using the Center for Epidemiological Studies Depression scale. Cognition was assessed with a battery of standardized tests.

RESULTS

In patients versus controls, SGC to right inferior frontal gyrus and frontal pole connectivity was decreased (52 voxels, z valuepeak = 3.56, pcluster-FWE = .002), whereas SGC to bilateral precuneus (33 voxels, z valuepeak = 3.34, pcluster-FWE = .04) and left inferior parietal lobule (50 voxels, z valuepeak = 3.50, pcluster-FWE = .003) connectivity was increased. In all participants, increased depressive symptoms was related to lower SGC to inferior frontal gyrus and frontal pole connectivity (β = -0.156, p = .053), and poorer general cognitive ability (β = -0.194, p = .023), information processing speed (β = -0.222, p = .008), and motor speed (β = -0.180, p = .035).

CONCLUSIONS

T1DM patients showed a pattern of SGC connectivity that is characterized by lower executive control and higher default mode network connectivity. Depressive symptoms are partially related to these alterations and seem to exacerbate T1DM-related cognitive dysfunction. Future studies should detail the effect of diagnosed major depressive disorder in this population and establish what alterations are diabetes specific.

Applications of magnetic resonance imaging for treatment-resistant late-life depression

Late-life depression (LLD) is a growing public and global health concern with diverse clinical manifestations and etiology. This literature review summarizes neuroimaging findings associated with depression in older adults and treatment-response variability. LLD has been associated with cerebral atrophy, diminished myelin integrity, and cerebral lesions in frontostriatal-limbic regions. These associations help explain the depression-executive dysfunction syndrome observed in LLD, and support cerebrovascular burden as a pathogenic mechanism. Furthermore, this review suggests that neuroimaging determinants of treatment resistance also reflect cerebrovascular burden. Of the theoretical etiologies of LLD, cerebrovascular burden may mediate treatment resistance. This review proposes that neuroimaging has the potential for clinical translation. Controlled trials may identify neuroimaging biomarkers that may inform treatment by identifying depressed adults likely to remit with pharmacotherapy, identifying individualized therapeutic dose, and facilitating earlier treatment response measures. Neuroimaging also has the potential to similarly inform treatment response variability from treatment with aripiprazole (dopamine modulator) and buprenorphine (opiate modulator).

Dimensions of depressive symptoms and cingulate volumes in older adults

Clinical depression and subthreshold depressive symptoms in older adults have been linked to structural changes in the cingulate gyrus. The cingulate comprises functionally distinct subregions that may have distinct associations with different types, or symptom dimensions, of depression. This study examined the relationship between symptom dimensions of depression and gray matter volumes in the anterior cingulate, posterior cingulate and isthmus of the cingulate in a nonclinical sample. The study included 41 community-dwelling older adults between the ages of 55 and 81. Participants received a structural magnetic resonance imaging scan and completed the Center for Epidemiologic Studies Depression Scale. Subscale scores for depressed mood, somatic symptoms and lack of positive affect were calculated, and Freesurfer was used to extract cingulate gray matter volumes. Regression analyses were conducted to examine the relationship between depressive symptoms and volumes of cingulate subregions while controlling for sex, age and estimated total intracranial volume. Higher scores on the depressed mood subscale were associated with larger volumes in the left posterior cingulate and smaller volumes in the isthmus cingulate. Higher scores on the somatic symptoms subscale were significantly related to smaller volumes in the posterior cingulate. A trend was observed for a positive relationship between higher scores on the lack of positive affect subscale and larger volumes in the anterior cingulate cortex. These results are consistent with previous findings of altered cingulate volumes with increased depressive symptomatology and suggest specific symptom dimensions of depression may differ in their relationship with subregions of the cingulate.

Amyloid Hypothesis: Is There a Role for Antiamyloid Treatment in Late-Life Depression?

Antidepressants have modest efficacy in late-life depression (LLD), perhaps because various neurobiologic processes compromise frontolimbic networks required for antidepressant response. We propose that amyloid accumulation is an etiologic factor for frontolimbic compromise that predisposes to depression and increases treatment resistance in a subgroup of older adults. In patients without history of depression, amyloid accumulation during the preclinical phase of Alzheimer disease (AD) may result in the prodromal depression syndrome that precedes cognitive impairment. In patients with early-onset depression, pathophysiologic changes during recurrent episodes may promote amyloid accumulation, further compromise neurocircuitry required for antidepressant response, and increase treatment resistance during successive depressive episodes. The findings that support the amyloid hypothesis of LLD are (1) Depression is a risk factor, a prodrome, and a common behavioral manifestation of AD; (2) amyloid deposition occurs during a long predementia period when depression is prevalent; (3) patients with lifetime history of depression have significant amyloid accumulation in brain regions related to mood regulation; and (4) amyloid deposition leads to neurobiologic processes, including vascular damage, neurodegeneration, neuroinflammation, and disrupted functional connectivity, that impair networks implicated in depression. The amyloid hypothesis of LLD is timely because availability of ligands allows in vivo assessment of amyloid in the human brain, a number of antiamyloid agents are relatively safe, and there is evidence that some antidepressants may reduce amyloid production. A model of LLD introducing the role of amyloid may guide the design of studies aiming to identify novel antidepressant approaches and prevention strategies of AD.

Imaging predictors of remission to anti-depressant medications in major depressive disorder

BACKGROUND

We review what is currently known about neuroimaging predictors of remission in major depressive disorder (MDD) after antidepressant medication (ADM) treatment.

METHODS

A systematic literature search found a total of twenty-seven studies comparing baseline neuroimaging findings in depressed patients who achieved remission with non-remitters following treatment with ADMs.

RESULTS

Eighteen of these studies utilised structural magnetic resonance imaging (MRI). These studies associated larger hippocampal (four studies) and cingulate volume (two studies) with remission. Two diffusion MRI studies identified a positive relationship between the fractional anisotropy of the cingulum bundle and remission. White matter signal hyperintensities were quantified in two papers - both observing decreased remission rates with increasing lesion burden. Nine studies on functional imaging met inclusion criteria - three using functional MRI, one with single photon emission computed tomography (SPECT), and five which evaluated patients with positron emission tomography (PET). These findings were not convergent, with different regions of interest interrogated.

LIMITATIONS

The studies were generally underpowered. Overall these data were heterogeneous with only a small number identifying concordant findings.

CONCLUSIONS

At present, the data remains inconsistent. The more promising biomarker of remission to ADMs appears to be hippocampal size, although this marker also has conflicting reports. Given remission should be the primary end-point of treatment, and that ADMs are the front-line treatment type for MDD, more focussed research is required to focus specifically on the imaging correlates of remission to ADMs.

Cognitive control, reward-related decision making and outcomes of late-life depression treated with an antidepressant

BACKGROUND

Executive processes consist of at least two sets of functions: one concerned with cognitive control and the other with reward-related decision making. Abnormal performance in both sets occurs in late-life depression. This study tested the hypothesis that only abnormal performance in cognitive control tasks predicts poor outcomes of late-life depression treated with escitalopram.

METHOD

We studied older subjects with major depression (N = 53) and non-depressed subjects (N = 30). Executive functions were tested with the Iowa Gambling Test (IGT), Stroop Color-Word Test, Tower of London (ToL), and Dementia Rating Scale - Initiation/Perseveration domain (DRS-IP). After a 2-week placebo washout, depressed subjects received escitalopram (target daily dose: 20 mg) for 12 weeks.

RESULTS

There were no significant differences between depressed and non-depressed subjects on executive function tests. Hierarchical cluster analysis of depressed subjects identified a Cognitive Control cluster (abnormal Stroop, ToL, DRS-IP), a Reward-Related cluster (IGT), and an Executively Unimpaired cluster. Decline in depression was greater in the Executively Unimpaired (t = -2.09, df = 331, p = 0.0375) and the Reward-Related (t = -2.33, df = 331, p = 0.0202) clusters than the Cognitive Control cluster. The Executively Unimpaired cluster (t = 2.17, df = 331, p = 0.03) and the Reward-Related cluster (t = 2.03, df = 331, p = 0.0433) had a higher probability of remission than the Cognitive Control cluster.

CONCLUSIONS

Dysfunction of cognitive control functions, but not reward-related decision making, may influence the decline of symptoms and the probability of remission of late-life depression treated with escitalopram. If replicated, simple to administer cognitive control tests may be used to select depressed older patients at risk for poor outcomes to selective serotonin reuptake inhibitors who may require structured psychotherapy.

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction

OBJECTIVE

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features.

METHODS

Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models.

RESULTS

A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity.

CONCLUSIONS

Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment.

Specificity of abnormal brain volume in major depressive disorder: a comparison with borderline personality disorder

BACKGROUND

Abnormal brain volume has been frequently demonstrated in major depressive disorder (MDD). It is unclear if these findings are specific for MDD since aberrant brain structure is also present in disorders with depressive comorbidity and affective dysregulation, such as borderline personality disorder (BPD). In this transdiagnostic study, we aimed to investigate if regional brain volume loss differentiates between MDD and BPD. Further, we tested for associations between brain volume and clinical variables within and between diagnostic groups.

METHODS

22 Females with a DSM-IV diagnosis of MDD, 17 females with a DSM-IV diagnosis of BPD and without comorbid posttraumatic stress disorder, and 22 age-matched female healthy controls (HC) were investigated using magnetic resonance imaging. High-resolution structural data were analyzed using voxel-based morphometry.

RESULTS

A significant (p<0.05, cluster-corrected) volume decrease of the anterior cingulate cortex (ACC) was found in MDD compared to HC, as opposed to volume decreases of the amygdala in BPD compared to both HC and MDD. Sensitivity and specificity of regional gray matter volume for a diagnosis of MDD were modest to fair. Amygdala volume was related to depressive symptoms across the entire patient sample.

LIMITATIONS

Potential limitations of this study include the modest sample size and the heterogeneous psychotropic drug treatment.

CONCLUSIONS

ACC volume reduction is more pronounced in MDD with an intermediate degree of volume loss in BPD compared to HC. In contrast, amygdala volume loss is more pronounced in BPD compared to MDD, yet amygdala volume is associated with affective symptom expression in both disorders.

Diagnosis and treatment of depression and cognitive impairment in late life

Cognitive impairment in late-life depression is prevalent, disabling, and heterogeneous. Although mild cognitive impairment in depression does not usually progress to dementia, accurate assessment of cognition is vital to prognosis and treatment planning. For example, executive dysfunction often accompanies late-life depression, influences performance across cognitive domains, and is associated with poor antidepressant treatment outcomes. Here, we review how assessment can capture dysfunction across cognitive domains and discuss cognitive trajectories frequently observed in late-life depression in the context of the neurobiology of this disorder. We also review the efficacy of a sample of interventions tailored to specific cognitive profiles.

Brain Structural Effects of Antidepressant Treatment in Major Depression

Depressive disorder is a very frequent and heterogeneous syndrome. Structural imaging techniques offer a useful tool in the comprehension of neurobiological alterations that concern depressive disorder. Altered brain structures in depressive disorder have been particularly located in the prefrontal cortex (medial prefrontal cortex and orbitofrontal cortex, OFC) and medial temporal cortex areas (hippocampus). These brain areas belong to a structural and functional network related to cognitive and emotional processes putatively implicated in depressive symptoms. These volumetric alterations may also represent biological predictors of response to pharmacological treatment. In this context, major findings of magnetic resonance (MR) imaging, in relation to treatment response in depressive disorder, will here be presented and discussed.

Structural imaging in late-life depression: association with mood and cognitive responses to antidepressant treatment

OBJECTIVES

Recent positron emission tomography studies of cerebral glucose metabolism have identified the functional neural circuitry associated with mood and cognitive responses to antidepressant treatment in late life depression (LLD). The structural alterations in these networks are not well understood. The present study used magnetic resonance (MR) imaging and voxel-based morphometry to evaluate the association between gray matter volumes and changes in mood symptoms and cognitive function with treatment with the antidepressant citalopram.

DESIGN

Open-label trial with baseline brain MR scan. Mood and cognitive assessments performed at baseline and during citalopram treatment.

SETTING

Outpatient clinics of an academic medical center.

PARTICIPANTS

17 previously unmedicated patients age 55 years or older with a major depressive episode and 17 non-depressed comparison subjects.

INTERVENTION

12-week trial of flexibly dosed citalopram.

MEASUREMENTS

Gray matter volumes, Hamilton Depression Rating Scale, California Verbal Learning Test, Delis-Kaplan Executive Function System.

RESULTS

In LLD, higher gray matter volumes in the cingulate gyrus, superior and middle frontal gyri, middle temporal gyrus, and precuneus was associated with greater mood improvement. Higher gray matter volumes in primarily frontal areas were associated with greater improvement in verbal memory and verbal fluency performance.

CONCLUSIONS

Associations with antidepressant induced improvements in mood and cognition were observed in several brain regions previously correlated with normalization of glucose metabolism after citalopram treatment in LLD. Future studies will investigate molecular mechanisms underlying these associations (e.g., beta-amyloid, inflammation, glutamate).

Depression versus dementia: is this construct still relevant?

Cognitive impairment has long been identified as a component of late-life depression (LLD), and depressive symptoms are common in neurodegeneration. Depression may confer a greater risk of cognitive decline in a cognitively intact population and further cognitive decline in a mild cognitive impairment population compared with those without depression. Exploration of the link between cognitive impairment in LLD and the depressive features of neurodegeneration is an essential part of a diagnostic algorithm. In this review, we will discuss these links; we will address depressive symptoms as a risk factor for dementia and as a prodrome to dementia. We will review clinical subtypes and imaging markers as predictors of development of dementia in depressed patients and explore vascular etiologies. We will also explore LLD and dementia as a spectrum, rather than mutually exclusive diagnostic entities.

Comparison of brain structural variables, neuropsychological factors, and treatment outcome in early-onset versus late-onset late-life depression

OBJECTIVE

To compare differences in gray matter volumes, white matter and subcortical gray matter hyperintensities, neuropsychological factors, and treatment outcome between early- and late-onset late-life depressed (LLD) subjects.

METHODS

We conducted a prospective, nonrandomized, controlled trial at the outpatient clinics at Washington University and Duke University on 126 subjects, aged 60 years or older, who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for major depression, scored 20 or more on the Montgomery-Asberg Depression Rating Scale (MADRS), and received neuropsychological testing and magnetic resonance imaging. Subjects were excluded for cognitive impairment or severe medical disorders. After 12 weeks of sertraline treatment, subjects' MADRS scores over time and neuropsychological factors were studied.

RESULTS

Left anterior cingulate thickness was significantly smaller in the late-onset depressed group than in the early-onset LLD subjects. The late-onset group also had more hyperintensities than the early-onset LLD subjects. No differences were found in neuropsychological factor scores or treatment outcome between early-onset and late-onset LLD subjects.

CONCLUSION

Age at onset of depressive symptoms in LLD subjects are associated with differences in cortical thickness and white matter and subcortical gray matter hyperintensities, but age at onset did not affect neuropsychological factors or treatment outcome.

Neuroanatomical correlates of apathy in late-life depression and antidepressant treatment response

BACKGROUND

Apathy is a prominent feature of geriatric depression that predicts poor clinical outcomes and hinders depression treatment. Yet little is known about the neurobiology and treatment of apathy in late-life depression. This study examined apathy prevalence in a clinical sample of depressed elderly, response of apathy to selective serotonin reuptake inhibitor (SSRI) treatment, and neuroanatomical correlates that distinguished responders from non-responders and healthy controls.

METHODS

Participants included 45 non-demented, elderly with major depression and 43 elderly comparison individuals. After a 2-week single-blind placebo period, depressed participants received escitalopram 10mg daily for 12 weeks. The Apathy Evaluation Scale (AES) and 24-item Hamilton Depression Rating Scale (HDRS) were administered at baseline and 12 weeks. MRI scans were acquired at baseline for concurrent structural and diffusion tensor imaging of anterior cingulate gray matter and associated white matter tracts.

RESULTS

35.5% of depressed patients suffered from apathy. This declined to 15.6% (p<0.1) following treatment, but 43% of initial sufferers continued to report significant apathy. Improvement of apathy with SSRI was independent of change in depression but correlated with larger left posterior subgenual cingulate volumes and greater fractional anisotropy of left uncinate fasciculi.

LIMITATIONS

Modest sample size, no placebo control, post-hoc secondary analysis, use of 1.5T MRI scanner

CONCLUSIONS

While prevalent in geriatric depression, apathy is separable from depression with regards to medication response. Structural abnormalities of the posterior subgenual cingulate and uncinate fasciculus may perpetuate apathetic states by interfering with prefrontal cortical recruitment of limbic activity essential to motivated behavior.

Neuroplasticity-based computerized cognitive remediation for treatment-resistant geriatric depression

Executive dysfunction (ED) in geriatric depression (GD) is common, predicts poor clinical outcomes and often persists despite remission of symptoms. Here we develop a neuroplasticity-based computerized cognitive remediation treatment (CCR-GD) to target ED in GD. Our assumption is that remediation of these deficits may modulate the underlying brain network abnormalities shared by executive dysfunction and depression. We compare CCR-GD to a gold standard treatment (escitalopram: 20mgs/12 weeks) in 11 treatment resistant older adults with major depression; and 33 matched historical controls. We find that 91% of participants complete CCR-GD. CCR-GD is equally as effective at reducing depressive symptoms as escitalopram but does so in 4 weeks instead of 12. In addition CCR-GD improves measures of executive function more than the escitalopram. We conclude that CCR-GD may be equally effective as escitalopram in treating GD. In addition, CCR-GD participants showed greater improvement in executive functions than historical controls treated with escitalopram.

Choosing treatment for depression in older adults and evaluating response

An update is provided on the current information regarding late life depression with regard to assessment, clinical implications, and treatment recommendations. Several treatments are considered evidence-based, but when deployed into field trials, the efficacy of these treatments falls short. It is thought that the lower impact in community trials is due in large part to patient, clinical, environmental, socio-economic, and cognitive correlates that influence treatment response. The aim is to assist providers in making decisions about what type of treatment to recommend based on a sound assessment of these clinical correlates.

Frontal-insula gray matter deficits in first-episode medication-naïve patients with major depressive disorder

OBJECTIVE

This study is designed to investigate the gray matter volume (GMV) deficits in patients with first-episode medication-naïve major depressive disorder (MDD).

METHODS

We enrolled 38 patients with first-episode medication-naïve MDD and 27 controls in this project. Voxel-based morphometry was used to compare GMV differences between two groups. Besides, the relationship between GMV of patients and the severity of clinical symptoms was estimated to confirm the role of GMV deficits in clinical symptoms. The correlation between total GMV and illness duration was also performed to elucidate the impacts of untreated duration on the GMV.

RESULTS

We found that first-episode medication-naïve MDD patients had significant GMV deficits in bilateral superior frontal gyri, left middle frontal gyrus, left medial frontal gyrus and left insula. The GMV of patient group was negatively correlated with the severity of clinical symptoms and the illness duration.

CONCLUSION

A pattern of GMV deficits in fronto-insula might represent the biomarker for first-episode medication-naïve MDD.

Magnetic resonance imaging predictors of treatment response in late-life depression

In older adults, depression not only results in more years lived with disability than any other disease but it also carries additional risks of suicide, medical comorbidities, and family caregiving burden. Because it can take many months to identify an effective treatment regimen, it is of utmost importance to shorten the window of time and identify early on what medications and dosages will work effectively for individuals having depression. Late-life depression (LLD) has been associated with greater burden of age-related changes (eg, atrophy, white matter ischemic changes, and functional connectivity). Depression in midlife has been shown to alter affective reactivity and regulation, and functional magnetic resonance imaging (fMRI) studies in LLD have replicated the same abnormalities. Effective treatment can normalize these alterations. This article provides a review of the current literature using structural and functional neuroimaging to identify MRI predictors of treatment response in LLD. The majority of the literature on structural MRI has focused on the vascular depression hypothesis, and studies support the view that loss of brain volume and white matter integrity was associated with poorer treatment outcomes. Studies using fMRI have reported that lower task-based activity in the prefrontal cortex and limbic regions was associated with poorer outcome. These imaging markers may be integrated into clinical decision making to attain better treatment outcomes in the future.

Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study

The relationship between structural changes in grey matter and treatment response in patients with late-life depression remains an intriguing area of research. This magnetic resonance imaging (MRI) study compares the baseline grey matter volume of elderly people with and without major depression (according to the DSM-IV-TR criteria) and assesses its association with antidepressant treatment response. Brain MRI scans were processed using statistical parametric mapping and voxel-based morphometry. The sample consisted of 30 patients with depression and 22 healthy controls. We found a significant volumetric reduction in the orbitofrontal cortex bilaterally in patients in comparison with controls. According to their remission status after antidepressant treatment, patients were classified as remitted or not remitted. Compared with controls, remitted patients showed a volumetric reduction in the orbitofrontal cortex bilaterally and in another cluster in the right middle temporal pole. Non-remitted patients showed an even greater volumetric reduction in the orbitofrontal cortex bilaterally compared with controls. To investigate predictive factors of remission after antidepressant treatment, we used a logistic regression. Both baseline Mini Mental State Examination score and baseline left superior lateral orbitofrontal cortex volume (standardized to the total grey matter volume) were associated with remission status. Our findings support the use of regional brain atrophy as a potential biomarker for depression. In addition, baseline cognitive impairment and regional grey matter abnormalities predict antidepressant response in patients with late-life depression.

Neuropsychiatry of corticobasal degeneration and progressive supranuclear palsy

Corticobasal syndrome (CBS) and progressive supranuclear palsy syndrome (PSPS) are two of the atypical Parkinsonism syndromes, in that patients exhibit rigidity, occasional tremor and postural instability, but do not symptomatically respond to dopamine replacement. CBS and PSPS can often present with complex cognitive difficulties and neuropsychiatric disturbances. Symptoms of depression, apathy, or agitation can be subtle and are often overlooked as reactions to learning a new diagnosis of Parkinsonism. These symptoms may be the earliest presenting evidence of CBS or PSPS, and these syndromes can be misdiagnosed with a primary psychiatric disorder rather than a neurodegenerative condition. Patients may be inappropriately treated with antipsychotic medications that exacerbate the extra-pyramidal motor features of the syndromes. When symptoms are considered to comprise a neurodegenerative syndrome, it may be an inaccurate diagnosis as many features of CBS and PSPS not only overlap with each other, but also with other dementia syndromes. This review discusses similarities and differences between the syndromes of CBS and PSPS in terms of neuropsychiatric features. Improved characterization of the clinical syndromes is necessary to better predict underlying pathology. Improved education about these diseases would help patients, caregivers and clinicians to anticipate symptom progression and avoid premature nursing home placement.