Increased prefrontal cortex connectivity associated with depression vulnerability and relapse

Altered resting-state amplitudes of low-frequency fluctuations in offspring of parents with a diagnosis of bipolar disorder or major depressive disorder

Offspring of parents with bipolar disorder (BD) or major depressive disorder (MDD) are at high biological risk (HR) of these disorders given their significant heritability. Thus, studying neural correlates in youths at HR-MDD and HR-BD appears essential to understand the development of mood disorders before their onset. Resting-state amplitudes of low-frequency fluctuations (ALFF) and fractioned ALFF (fALFF) shows moderate to high test-retest reliability which makes it a great tool to identify biomarkers. However, this avenue is still largely unexplored. Using the Healthy Brain Network biobank, we identified 150 children and adolescents HR-MDD, 50 HR-BD and 150 not at risk of any psychiatric disorder (i.e., the control group). We then examined differences in relative ALFF/fALFF signals during resting-state. At a corrected threshold, participants HR-MDD displayed lower resting-state ALFF signals in the dorsal caudate nucleus compared to the control group. The HR-BD group showed increased fALFF values in the primary motor cortex compared to the control group. Therefore, robust differences were noted in regions that could be linked to important symptoms of mood disorders, namely psychomotor retardation, and agitation. At an uncorrected threshold, differences were noted in the central opercular cortex and the cerebellar. The database is a community-referred cohort and heterogeneous in terms of children's psychiatric diagnosis and symptomatology, which may have altered the results. ALFF and fALFF results for the comparison between both HR groups and the control group overlapped, suggesting good convergence. More studies measuring ALFF/fALFF in HR are needed to replicate these results.

Shared and distinct patterns of default mode network dysfunction in major depressive disorder and bipolar disorder: A comparative meta-analysis

BACKGROUND

While patients with major depressive disorder (MDD) and bipolar disorder (BD) exhibited default mode network (DMN) dysfunction revealed by aberrant resting-state functional connectivity (rsFC) patterns, previous findings have been inconsistent. Little is known about the similarities and differences in DMN rsFC between MDD and BD.

METHODS

A voxel-wise meta-analysis of seed-based DMN rsFC studies on MDD or BD was performed using the Seed-based d Mapping software with permutation of subject images (SDM-PSI). Aberrant DMN rsFC in both disorders was investigated separately, followed by conjunction and between-disorder comparison analyses. Functional decoding was performed to implicate the psychophysiological underpinnings of derived brain abnormalities.

RESULTS

Thirty-four studies comparing 1316 MDD patients with 1327 HC, and 22 studies comparing 1059 BD patients with 1396 HC were included. Compared to HC, MDD patients exhibited DMN hyperconnectivity with frontolimbic systems, and hypoconnectivity with temporal lobe and posterior cingulate cortex. BD patients displayed increased DMN connectivity with bilateral precuneus, and reduced connectivity with prefrontal cortex and middle temporal gyrus. No common patterns of DMN rsFC abnormalities were observed between MDD and BD. Compared to BD, MDD patients showed DMN hyperconnectivity with triangular part of the left inferior frontal gyrus and left fusiform gyrus. Functional decoding found that patterns of DMN rsFC alteration between MDD and BD were primarily related to action and perception domains.

CONCLUSION

Distinct DMN dysfunction patterns in MDD and BD enhance current understanding of the neural substrates of mood disorders and may provide a potential biomarker for differentiation.

Local brain abnormalities in emotional disorders: Evidence from resting state fMRI studies

Emotional disorders inflict an enormous burden on society. Research on brain abnormalities implicated in emotional disorders has witnessed great progress over the past decades. Using cross-sectional and longitudinal designs, resting state functional magnetic resonance imaging (rs-fMRI) and its analytic approaches have been applied to characterize the local properties of patients with emotional disorders. Additionally, brain activity alterations of emotional disorders have shown frequency-specific. Despite the gains in understanding the roles of brain abnormalities in emotional disorders, the limitation of the small sample size needs to be highlighted. Lastly, we proposed that evidence from the positive psychology research stream presents it as a viable discipline, whose suggestions could be developed in future emotional disorders research. Such interdisciplinary research may produce novel treatments and intervention options. This article is categorized under: Psychology > Brain Function and Dysfunction.

Role of Prefrontal Cortex Circuitry in Maintaining Social Homeostasis

Homeostasis is a fundamental concept in biology and ensures the stability of life by maintaining the constancy of physiological processes. Recent years have witnessed a surge in research interest in these physiological processes, with a growing focus on understanding the mechanisms underlying social homeostasis. This shift in focus underscores our increasing understanding of the importance of social interactions and their impact on individual well-being. In this review, we explore the interconnected research across 3 primary categories: understanding the neural mechanisms influencing set points, defining contemporary factors that can disrupt social homeostasis, and identifying the potential contributions of social homeostatic failure in the development of psychiatric diseases. We also delve into the role of the prefrontal cortex and its circuitry in regulating social behavior, decision-making processes, and the manifestation of neuropsychiatric disorders, such as depression and anxiety. Finally, we examine the influence of more recent factors such as growing social media exposure and the COVID-19 pandemic on mental health, highlighting their disruptive effects. We also identify gaps in current literature through the analysis of research trends and propose future research directions to advance our understanding of social homeostasis, with implications for mental health interventions.

Abnormal alterations of regional spontaneous neuronal activity and functional connectivity in insomnia patients with difficulty falling asleep: a resting-state fMRI study

BACKGROUND

Insomnia disorder (ID) seriously affects people's daily life. Difficulty falling asleep is the most commonly reported complaint in patients with ID. However, the mechanism of prolonged sleep latency (SL) is still obscure. The aim of our present study was to investigate the relationship between prolonged SL and alterations in spontaneous neural activity and brain functional connectivity (FC) in ID patients using functional magnetic resonance imaging (fMRI).

METHODS

A total of 52 insomniacs with difficulty falling asleep and 30 matched healthy controls (HCs) underwent resting-state fMRI. The amplitude of low-frequency fluctuation (ALFF) was measured and group differences were compared. The peak areas with significantly different ALFF values were identified as the seed regions to calculate FC to the whole brain. SL was assessed by a wrist actigraphy device in ID patients. The Pittsburgh Sleep Quality Index (PSQI), Hamilton Anxiety Rating Scale (HAMA), and Hyperarousal Scale (HAS) were evaluated in both ID patients and HCs. Finally, correlation analyses were performed between the clinical features and FC/ALFF values.

RESULTS

ID patients showed higher PSQI, HAMA, HAS scores than HCs. The functional MRI results indicated increased ALFF value in the left insula and right amygdala and decreased ALFF value in the right superior parietal lobe (SPL) in ID patients. The seed-based FC analysis demonstrated increased FC between the left insula and the bilateral precentral gyrus and FC between the right amygdala and the left posterior cingulate cortex (PCC) in patients with ID. Correlation analysis indicated that the increased FC value of the right amygdala-left PCC was positively correlated with SL measured by actigraphy.

CONCLUSION

This study revealed abnormal regional spontaneous fluctuations in the right amygdala, left insula, and right SPL, as well as increased FC in the left insula-precentral and right amygdala-left PCC. Moreover, the prolonged SL was positively correlated with the abnormal FC in the right amygdala-left PCC in ID patients. The current study showed the correlation between prolonged SL and the abnormal function of emotion-related brain regions in ID patients, which may contribute to a better understanding of the neural mechanisms underlying difficulty falling asleep in patients with ID.

CLINICAL TRIAL REGISTRATION

http://www.chictr.org.cn ., ChiCTR1800015282. Registered on 20th March 2018.

Proteomic association with age-dependent sex differences in Wisconsin Card Sorting Test performance in healthy Thai subjects

Sex differences in cognitive function exist, but they are not stable and undergo dynamic change during the lifespan. However, our understanding of how sex-related neural information transmission evolves with age is still in its infancy. This study utilized the Wisconsin Card Sorting Test (WCST) and the label-free proteomics method with bioinformatic analysis to investigate the molecular mechanisms underlying age-related sex differences in cognitive performance in 199 healthy Thai subjects (aged 20-70 years), as well as explore the sex-dependent protein complexes for predicting cognitive aging. The results showed that males outperformed females in two of the five WCST sub-scores: %Corrects and %Errors. Sex differences in these scores were related to aging, becoming noticeable in those over 60. At the molecular level, differently expressed individual proteins and protein complexes between both sexes are associated with the potential N-methyl-D-aspartate type glutamate receptor (NMDAR)-mediated excitotoxicity, with the NMDAR complex being enriched exclusively in elderly female samples. These findings provided a preliminary indication that healthy Thai females might be more susceptible to such neurotoxicity, as evidenced by their cognitive performance. NMDAR protein complex enrichment in serum could be proposed as a potential indication for predicting cognitive aging in healthy Thai females.

Distress, burden, and wellbeing in siblings of people with mental illness: a mixed studies systematic review and meta-analysis

BACKGROUND

Family members of people with mental illness (MI) may experience a host of psychological adversities such as increased stress, burden, and reduced wellbeing. However, relatively little is known about siblings. This study aimed to characterise the experience of distress (viz. depressive and anxiety symptoms), burden, and wellbeing in siblings of people with MI.

METHODS

Studies reporting on quantitative measures of depression, anxiety, burden, or wellbeing in siblings; and/or qualitative findings on siblings' experience were eligible. The literature search was conducted up until 20th October 2022.

RESULTS

Sixty-two studies comprising data from 3744 siblings were included. The pooled mean percentage of depressive symptoms fell in the mild range at 15.71 (k = 28, N = 2187, 95% CI 12.99-18.43) and anxiety symptoms fell in the minimal range at 22.45 (k = 16, N = 1122, 95% CI 17.09-27.80). Moderator analyses indicate that siblings of people with a schizophrenia spectrum disorder experience greater depressive symptoms than siblings of people with other types of MI (β = -16.38, p < 0.001). Qualitative findings suggest that individuals may be particularly vulnerable during their siblings' illness onset and times of relapse. Limited communication, confusion about MI, and the need to compensate may contribute to siblings' distress and/or burden. Siblings' experience of wellbeing and caregiving were closely related.

CONCLUSION

This review highlights the complex psychological experience of siblings and the need for greater research and clinical support for this important yet often overlooked cohort.

Lower Dorsal Lateral Prefrontal Cortex Functional Connectivity in Late-Life Depression With Suicidal Ideation

OBJECTIVE

The dorsal lateral prefrontal cortex (DLPFC) has been identified as a neuromodulation target for alleviating suicidal ideation. Dysfunctional DLPFC has been implicated in suicidality in depression. This study aimed to investigate the functional connectivity (FC) of the DLPFC in late-life depression (LLD) with suicidal ideation.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data from 32 LLD patients with suicidal ideation (LLD-S), 41 LLD patients without suicidal ideation (LLD-NS), and 54 healthy older adults (HOA) were analyzed using DLPFC seed-based FC analyses. Group differences in FC were examined, and machine learning was applied to explore the potential of DLPFC-FC for classifying LLD-S from LLD-NS.

RESULTS

Abnormal DLPFC-FC patterns were observed in LLD-S, characterized by lower connectivity with the angular gyrus, precuneus, and superior frontal gyrus compared to LLD-NS and healthy controls. A classification model based on the identified DLPFC-FC achieved an accuracy of 75%.

CONCLUSION

The lower FC of DLPFC networks may contribute to the neurobiological mechanism of suicidal ideation in late-life depression. These findings may facilitate suicide prevention for LLD by providing potential neuroimaging markers and network-based neuromodulation targets. However, further confirmation with larger sample sizes and experimental designs is warranted.

Trait- and state-like co-activation pattern dynamics in current and remitted major depressive disorder

BACKGROUND

Distinguishing between trait- and state-like neural alternations in major depressive disorder (MDD) may advance our understanding of this recurring disorder. We aimed to investigate dynamic functional connectivity alternations in unmedicated individuals with current or past MDD using co-activation pattern analyses.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from individuals with first-episode current MDD (cMDD, n = 50), remitted MDD (rMDD, n = 44), and healthy controls (HCs, n = 64). Using a data-driven consensus clustering technique, four whole-brain states of spatial co-activation were identified and associated metrics (dominance, entries, transition frequency) were analyzed with respect to clinical characteristics.

RESULTS

Relative to rMDD and HC, cMDD showed increased dominance and entries of state 1 (primarily involving default mode network (DMN)), and decreased dominance of state 4 (mostly involving frontal-parietal network (FPN)). Among cMDD, state 1 entries correlated positively with trait rumination. Conversely, relative to cMDD and HC, individuals with rMDD were characterized by increased state 4 entries. Relative to HC, both MDD groups showed increased state 4-to-1 (FPN to DMN) transition frequency but reduction in state 3 (spanning visual attention, somatosensory, limbic networks), with the former metric specifically related to trait rumination.

LIMITATIONS

Further confirmation with longitudinal studies are required.

CONCLUSIONS

Regardless of symptoms, MDD was characterized by increased FPN-to-DMN transitions and reduced dominance of a hybrid network. State-related effect emerged in regions critically implicated in repetitive introspection and cognitive control. Asymptomatic individuals with past MDD were uniquely linked to increased FPN entries. Our findings identify trait-like brain network dynamics that might increase vulnerability to future MDD.

Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review

Mental disorders are rapidly increasing each year and have become a major challenge affecting the social and financial well-being of individuals. There is a need for phenotypic characterization of psychiatric disorders with biomarkers to provide a rich signature for Major Depressive Disorder, improving the understanding of the pathophysiological mechanisms underlying these mental disorders. This comprehensive review focuses on depression and relapse detection modalities such as self-questionnaires, audiovisuals, and EEG, highlighting noteworthy publications in the last ten years. The article concentrates on the literature that adopts machine learning by audiovisual and EEG signals. It also outlines preprocessing, feature extraction, and public datasets for depression detection. The review concludes with recommendations that will help improve the reliability of developed models and the determinism of computational intelligence-based systems in psychiatry. To the best of our knowledge, this survey is the first comprehensive review on depression and relapse prediction by self-questionnaires, audiovisual, and EEG-based approaches. The findings of this review will serve as a useful and structured starting point for researchers studying clinical and non-clinical depression recognition and relapse through machine learning-based approaches.

Abnormal functional connectivity in psoriasis patients with depression is associated with their clinical symptoms

Psoriasis is a chronic, autoimmune disorder that is related to mental health disorders such as depression. However, few studies have focused on the features of brain activity in psoriasis patients with depression (PPD) and the association between brain activity and disease severity. A total of 29 PPD and 24 healthy controls were involved in this study, and all participants underwent resting-state functional magnetic resonance imaging (fMRI) scanning. The psoriasis area and severity index (PASI) and the self-rating depression scale (SDS) were used to measure clinical symptoms. Compared with HCs, PPD patients showed increased fractional amplitude of low-frequency fluctuation (fALFF) in the Frontal_Mid_L and increased functional connectivity (FC) between the hypothalamus-R and the Cingulum_Mid_R. Correlation analysis suggested a positive correlation between PASI and SDS scores in PPD, while the fALFF and FC values were negatively correlated with their SDS and PASI scores. These brain regions may be associated with the development of depressive symptoms and disease severity in psoriasis patients.

Psychological distress in siblings of people with mental illness: A systematic review and meta-analysis

OBJECTIVE

The objective of this study was to characterise the prevalence and/or severity of psychological distress (namely, depression and anxiety symptoms) in siblings of people with mental illness (MI) and to examine correlates of distress in siblings of people with MI.

METHOD

Studies comparing distress in individuals with and without a sibling with MI were eligible. Studies reporting on correlates of distress in siblings were also eligible. A search of MEDLINE Complete, PsycINFO and Embase was conducted up until 17 March 2022.

RESULTS

Fifteen studies comprising 2304 siblings and 2263 comparison individuals were included. Meta-analyses indicated individuals with a sibling with MI experience significantly greater depressive symptoms (Hedges's g = 0.53, 95% CI = [0.32, 0.73], siblings n = 1962, comparison individuals n = 2248) and anxiety symptoms (Hedges's g = 0.40, 95% CI = [0.19, 0.61], siblings n = 653, comparison individuals n = 533) than those without. The sibling relationship, siblings' locus of control, interpersonal functioning and their appraisal of the impacts of MI were identified as important and potentially modifiable correlates.

CONCLUSION

Individuals with a sibling with MI experience greater depressive and anxiety symptoms than those without and would likely benefit from support. Future studies are required to elucidate the mechanisms underlying distress in siblings.