Structural abnormalities of cingulate cortex in patients with first-episode drug-naïve schizophrenia comorbid with depressive symptoms

Improve the diagnosis of idiopathic normal pressure hydrocephalus by combining abnormal cortical thickness and ventricular morphometry

Background

The primary imaging markers for idiopathic Normal Pressure Hydrocephalus (iNPH) emphasize morphological measurements within the ventricular system, with no attention given to alterations in brain parenchyma. This study aimed to investigate the potential effectiveness of combining ventricular morphometry and cortical structural measurements as diagnostic biomarkers for iNPH.

Methods

A total of 57 iNPH patients and 55 age-matched healthy controls (HC) were recruited in this study. Firstly, manual measurements of ventricular morphology, including Evans Index (EI), z-Evans Index (z-EI), Cella Media Width (CMW), Callosal Angle (CA), and Callosal Height (CH), were conducted based on MRI scans. Cortical thickness measurements were obtained, and statistical analyses were performed using surface-based morphometric analysis. Secondly, three distinct models were developed using machine learning algorithms, each based on a different input feature: a ventricular morphology model (LVM), a cortical thickness model (CT), and a fusion model (All) incorporating both features. Model performances were assessed using 10-fold cross validation and tested on an independent dataset. Model interpretation utilized Shapley Additive Interpretation (SHAP), providing a visualization of the contribution of each variable in the predictive model. Finally, Spearman correlation coefficients were calculated to evaluate the relationship between imaging biomarkers and clinical symptoms.

Results

iNPH patients exhibited notable differences in cortical thickness compared to HC. This included reduced thickness in the frontal, temporal, and cingulate cortices, along with increased thickness in the supracentral gyrus. The diagnostic performance of the fusion model (All) for iNPH surpassed that of the single-feature models, achieving an average accuracy of 90.43%, sensitivity of 90.00%, specificity of 90.91%, and Matthews correlation coefficient (MCC) of 81.03%. This improvement in accuracy (6.09%), sensitivity (11.67%), and MCC (11.25%) compared to the LVM strategy was significant. Shap analysis revealed the crucial role of cortical thickness in the right isthmus cingulate cortex, emerging as the most influential factor in distinguishing iNPH from HC. Additionally, significant correlations were observed between the typical triad symptoms of iNPH patients and cortical structural alterations.

Conclusion

This study emphasizes the significant role of cortical structure changes in the diagnosis of iNPH, providing a novel insights for assisting clinicians in improving the identification and detection of iNPH.

Association between serum omega-3 PUFAs levels and cognitive impairment in never medically treated first-episode patients with geriatric depression: A cross-sectional study

BACKGROUND

Geriatric depression increases the public health burden and health care costs, reduces quality of life. Studies have shown the association between ω-3 PUFAs levels and inflammatory markers levels and depression, but few have explored the relationship between omega-3 PUFAs, inflammatory markers, and cognitive function in geriatric depression. This study aimed to compare the differences in ω-3 PUFAs levels and inflammatory markers between geriatric depression with cognitive impairment (CI) and those without CI.

METHODS

A total of three hundred and five elderly patients were recruited. In addition to collecting basic information, their blood specimens were collected to detect serum EPA, DHA, AA, TC, LDL-C, IL-6, TNF-α, and hs-CRP levels. The Hamilton depression scale (HAMD), Hamilton anxiety scale (HAMA), and The Montreal cognitive assessment (MoCA) were used to assess their depression, anxiety, and cognitive function, respectively.

RESULTS

Compared to those without CI, geriatric depression patients with CI had higher serum TC, LDL-C levels, lower EPA, DHA, and AA levels, and more elevated IL-6, TNF-α, and hs-CRP levels (all P < 0.05). Further linear regression analysis showed that EPA, DHA, and TNF-α, hs-CRP levels were significantly associated with the occurrence and the severity of CI.

LIMITATIONS

No causal relationship could be drawn due to the cross-sectional design.

CONCLUSIONS

Omega-3 PUFAs and inflammatory factors levels may predict CI in elderly patients with MDD in the future. Our findings suggest that ω-3 PUFAs (EPA and DHA) and inflammatory factors (TNF-α and CRP) may predict the occurrence and the severity of CI among elderly MDD patients.

Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Identifying functional biomarkers related to treatment success can aid in expediting therapy optimization, as well as contribute to a better understanding of the neural mechanisms of the treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. The first objective of the study was to identify region-specific oscillatory modulations that both (i) discriminate individuals with TRD (with SCC-DBS OFF) from healthy controls, and (ii) discriminate TRD treatment responders from non-responders (with SCC-DBS ON). The second objective of this work was to further explore the effects of stimulation intensity and frequency on oscillatory activity in the identified brain regions of interest. Oscillatory power analyses led to the identification of brain regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca's area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity. The identified functional network biomarkers implicate modulation of TRD-related activity in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or reducing frequency, which may represent potential avenues of direction in non-responders.

Sleep Traits Causally Affect the Brain Cortical Structure: A Mendelian Randomization Study

Background: Brain imaging results in sleep deprived patients showed structural changes in the cerebral cortex; however, the reasons for this phenomenon need to be further explored. Methods: This MR study evaluated causal associations between morningness, ease of getting up, insomnia, long sleep, short sleep, and the cortex structure. Results: At the functional level, morningness increased the surface area (SA) of cuneus with global weighted (beta(b) (95% CI): 32.63 (10.35, 54.90), p = 0.004). Short sleep increased SA of the lateral occipital with global weighted (b (95% CI): 394.37(107.89, 680.85), p = 0.007. Short sleep reduced cortical thickness (TH) of paracentral with global weighted (OR (95% CI): -0.11 (-0.19, -0.03), p = 0.006). Short sleep reduced TH of parahippocampal with global weighted (b (95% CI): -0.25 (-0.42, -0.07), p = 0.006). No pleiotropy was detected. However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and the five types of sleep traits met the threshold. Conclusions: Our results potentially show evidence of a higher risk association between neuropsychiatric disorders and not only paracentral and parahippocampal brain areas atrophy, but also an increase in the middle temporal zone. Our findings shed light on the associations of cortical structure with the occurrence of five types of sleep traits.

The contribution of the cingulate cortex: treating depressive symptoms in first-episode drug naïve schizophrenia

Background

Our previous study has shown the cingulate cortex abnormalities in first-episode drug naïve (FEDN) schizophrenia patients with comorbid depressive symptoms. However, it remains largely unknown whether antipsychotics may induce morphometric change in cingulate cortex and its relationship with depressive symptoms. The purpose of this study was to further clarify the important role of cingulate cortex in the treatment on depressive symptoms in FEDN schizophrenia patients.

Method

In this study, 42 FEDN schizophrenia patients were assigned into depressed patients group (DP, n = 24) and non-depressed patients group (NDP, n = 18) measured by the 24-item Hamilton Depression Rating Scale (HAMD). Clinical assessments and anatomical images were obtained from all patients before and after 12-week treatment with risperidone.

Results

Although risperidone alleviated psychotic symptoms in all patients, depressive symptoms were decreased only in DP. Significant group by time interaction effects were found in the right rostral anterior cingulate cortex (rACC) and other subcortical regions in the left hemisphere. After risperidone treatment, the right rACC were increased in DP. Further, the increasing volume of right rACC was negatively associated with improvement in depressive symptoms.

Conclusion

These findings suggested that the abnormality of the rACC is the typical characteristics in schizophrenia with depressive symptoms. It's likely key region contributing to the neural mechanisms underlying the effects of risperidone treatment on depressive symptoms in schizophrenia.

The development of functional connectivity within the dorsal striatum from early childhood to adulthood

Dorsal striatum, principally comprising of caudate and putamen, is well-known to support motor function but also various higher-order cognitive functions. This is enabled by developing short- and long-range connections to distributed cortical regions throughout the life span, but few studies have examined developmental changes from young children to adults in the same cohort. Here we investigated the development of dorsal-striatal network in a large (n = 476), single-site sample of healthy subjects 3-42 years of age in three groups (children, adolescence, adults). The results showed that the connectivity within the striatum and to sensorimotor regions was established at an early stage of life and remained strong in adolescence, supporting that sensory-seeking behaviours and habit formation are important learning mechanisms during the developmental periods. This connectivity diminished with age, as many behaviours become more efficient and automated. Adolescence demonstrated a remarkable transition phase where the connectivity to dorsolateral prefrontal cortex emerged but connectivity to the dorsomedial prefrontal and posterior brain, which belong to the ventral attentional and default mode networks, was only seen in adults. This prolonged maturation in between-network integration may explain the behavioural characteristics of adolescents in that they exhibit elaborated cognitive performance but also demonstrate high risk-taking behaviours.

A comparison of uni- and multi-variate methods for identifying brain networks activated by cognitive tasks using intracranial EEG

Cognitive tasks are commonly used to identify brain networks involved in the underlying cognitive process. However, inferring the brain networks from intracranial EEG data presents several challenges related to the sparse spatial sampling of the brain and the high variability of the EEG trace due to concurrent brain processes. In this manuscript, we use a well-known facial emotion recognition task to compare three different ways of analyzing the contrasts between task conditions: permutation cluster tests, machine learning (ML) classifiers, and a searchlight implementation of multivariate pattern analysis (MVPA) for intracranial sparse data recorded from 13 patients undergoing presurgical evaluation for drug-resistant epilepsy. Using all three methods, we aim at highlighting the brain structures with significant contrast between conditions. In the absence of ground truth, we use the scientific literature to validate our results. The comparison of the three methods’ results shows moderate agreement, measured by the Jaccard coefficient, between the permutation cluster tests and the machine learning [0.33 and 0.52 for the left (LH) and right (RH) hemispheres], and 0.44 and 0.37 for the LH and RH between the permutation cluster tests and MVPA. The agreement between ML and MVPA is higher: 0.65 for the LH and 0.62 for the RH. To put these results in context, we performed a brief review of the literature and we discuss how each brain structure’s involvement in the facial emotion recognition task.

Structural abnormalities of cingulate cortex in patients with first-episode drug-naïve schizophrenia comorbid with depressive symptoms

Depressive symptoms are common in patients with first-episode psychosis. However, the neural mechanisms underlying the comorbid depression in schizophrenia are still unknown. The main purpose of this study was to characterize the structural abnormalities of first-episodes drug-naïve (FEDN) schizophrenia comorbid with depression by utilizing both volume-based and surface-based morphometric measurements. Forty-two patients with FEDN schizophrenia and 29 healthy controls were recruited. The 24-item Hamilton Depression Rating Scale (HAMD-24) was administrated to divide all patients into depressive patients (DP) and non-depressive patients (NDP). Compared with NDP, DP had a significantly larger volume and surface area in the left isthmus cingulate cortex and also had a greater volume in the left posterior cingulate cortex. Correlation analysis showed that HAMD total score was positively correlated with the surface area of the left isthmus cingulate and gray matter volume of the left isthmus cingulate cortex. In addition, gray matter volume of the left isthmus cingulate was also correlated with the PANSS general psychopathology or total score. The findings suggest that prominent structural abnormalities of gray matter are mainly concentrated on the cingulate cortex in FEDN schizophrenia patients comorbid with depression, which may contribute to depressive symptoms and psychopathological symptoms.