Impact of depression on the quality of sleep and immune functions in patients with coronary artery disease.

Background: The risk of major depressive disorder (MDD) and insomnia is higher in patients with coronary heart disease (CHD) than in the general population. In addition, immune inflammation may be a shared aetiological factor for mental disorders and CHD. However, it is unclear whether MDD is associated with poor sleep quality and cell-mediated immune function in patients with CHD. Aims: This study investigated the impact of depression on sleep quality and cell-mediated immune functions in patients with CHD and examined discriminative factors in patients with CHD with and without MDD. Methods: This cross-sectional retrospective study was conducted at the Zhejiang University School of Medicine affiliated with Sir Run Run Shaw Hospital. The study population consisted of 84 patients with CHD assigned to two groups based on their Hamilton Depression Rating Scale (HAMD) score (CHD with MDD (HAMD score of ≥10) vs without MDD). Subjective sleep quality, systemic inflammatory response and cell-mediated immune functions were assessed in patients with CHD with (n=50) and without (n=34) MDD using the Pittsburgh Sleep Quality Index (PSQI), routine blood tests and flow cytometry. The relationships between variables were ascertained using Pearson's product-moment, and linear discriminant analysis was used to explore the discriminative factors between groups. Results: Patients with CHD with MDD had significantly poorer sleep quality than those without MDD (Z=-6.864, p<0.001). The Systemic Inflammation Index (SII) and CD4+/CD8+ T-cell ratios were higher in patients with CHD with MDD than in those without MDD (Z=-3.249, p=0.001). Patients with CHD with MDD had fewer CD3+CD8+ and CD3+ T cells (Z=3.422, p=0.001) than those without MDD (t=2.032, p=0.045). Furthermore, patients with CHD with MDD may be differentiated from those without MDD using the PSQI, SII and T-cell levels, as these variables correctly classified the depressed and non-depressed groups with an accuracy of 96.4%. Conclusions: MDD may be responsible for poor sleep quality, increased cell-mediated immunity and SII in patients with CHD, which are discriminative factors for CHD in the depressive state. Clinicians should be aware of these interactions, as treatment for depressive symptoms may also improve CHD prognosis.

Reduced Plasma Estradiol Levels are Associated with Sleep Apnea in Depressed Peri- and Post-Menopausal Women.

OBJECTIVE: This study aimed at investigating the correlation between estradiol and sleep apnea among women with major depressive disorders during the perimenopausal and postmenopausal periods. METHODS: A total of 84 perimenopausal and postmenopausal women diagnosed with depression, and who had been subjected to whole-night polysomnography (PSG) were retrospectively studied. They were assigned into two groups based on the presence of OSA (apnea-hypopnea index (AHI)≥5) (OSA vs non-OSA). The correlation between estradiol levels and apnea-hypopnea index were assessed by logistic regression models after adjusting for age, body mass index (BMI), Hamilton Depression Rating Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), apnea frequency and progesterone. RESULTS: Among the 84 patients, 45.23% had OSA. Estradiol levels were significantly elevated in non-OSA than in OSA patients (p<0.05). Univariate analysis revealed that elevated estradiol levels are associated with reduced odds of OSA (odds ratio [OR] 0.92, 95% confidence interval [CI] 0.875-0.966, p = 0.001). Multivariate analyses showed that low estradiol levels (OR = 0.859, 95% CI 0.826-0.991, p = 0.031), higher HAMD scores (OR = 1.212, 95% CI 1.012-1.453, p = 0.037), higher apnea frequency (OR = 2.493, 95% CI 1.389-4.473, p = 0.002) and higher BMI (OR=1.635, 95% CI 1.136-2.353, p = 0.008) are correlated with OSA. CONCLUSION: The ratio of depressed perimenopausal to postmenopausal women comorbid OSA was high. Higher BMI, low estradiol levels, high apnea frequency and high HAMD scores were correlated with OSA diagnosis and could be potential diagnostic markers for OSA in depressed perimenopausal and postmenopausal women. Reduced estradiol levels were correlated with an increased risk of OSA among depressed perimenopausal and postmenopausal women.

[Correlation between suicidal ideation and polysomnography parameters in late-life depression patients].

OBJECTIVE: To investigate the relationship between sleep parameters and suicidal ideation in patients with late-life depression (LLD). METHODS: Seventy-seven LLD patients over 60 years old from Sir Run Run Shaw Hospital of Zhejiang University during July 2017 and July 2018 were included in the study. All patients were assessed with Hamilton Depression Rating Scale (HAMD) and polysomnography (PSG) overnight. The suicidal score of item 3 in HAMD (HAM-D3)was used to define whether there was a suicidal ideation. Participants were subsequently grouped according to endorsement of presence (HAM-D3 score ≥1, n=46) versus absence (HAM-D3 score=0, n=31) of suicidal ideation symptoms. The sleep efficiency, total sleep time, wakefulness after sleep onset, rapid eye movement percent/latency, and non-rapid eye movement sleep stages 1-3 (N1-N3) were assessed. ANOVA analyses were conducted to explore the correlation of sleep parameters with suicidal ideation between the groups with and without suicidal ideation. In model 1, the HAM-D3 constituted the independent variable in separate ANOVA tests; in model 2 the impact of depressive symptoms were assessed as a covariate with sleep parameters. RESULTS: There was less stage N3 [(55±41)min, t=-4.731, P<0.05] and the reduced percentage of N3 [(15±11)%, t=-4.194, P<0.05] in LLD patients with suicidal ideation, compared with the LLD patients without suicidal ideation [(104±49) min, (26±11)%]. Correlation analyses revealed that there was a significant correlation between the suicidal ideation and the percentage of stage N3 and sleep time of stage N3 (both P<0.05). CONCLUSIONS: Suicidal ideation is associated with less N3 sleep in LLD patients.

Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder.

Neuroimaging studies have shown topological disruptions of both functional and structural whole-brain networks in major depressive disorder (MDD). This study examined common and specific alterations between these two types of networks and whether the alterations were differentially involved in the two hemispheres. Multimodal MRI data were collected from 35 MDD patients and 35 healthy controls, whose functional and structural hemispheric networks were constructed, characterized, and compared. We found that functional brain networks were profoundly altered at multiple levels, while structural brain networks were largely intact in patients with MDD. Specifically, the functional alterations included decreases in intra-hemispheric (left and right) and inter-hemispheric (heterotopic) functional connectivity; decreases in local, global and normalized global efficiency for both hemispheric networks; increases in normalized local efficiency for the left hemispheric networks; and decreases in intra-hemispheric integration and inter-hemispheric communication in the dorsolateral superior frontal gyrus, anterior cingulate gyrus and hippocampus. Regarding hemispheric asymmetry, largely similar patterns were observed between the functional and structural networks: the right hemisphere was over-connected and more efficient than the left hemisphere globally; the occipital and partial regions exhibited leftward asymmetry, and the frontal and temporal sites showed rightward lateralization with regard to regional connectivity profiles locally. Finally, the functional-structural coupling of intra-hemispheric connections was significantly decreased and correlated with the disease severity in the patients. Overall, this study demonstrates modality- and hemisphere-dependent and invariant network alterations in MDD, which are helpful for understanding elaborate and characteristic patterns of integrative dysfunction in this disease.

Relationship of Mean Platelet Volume To MDD: A Retrospective Study.

BACKGROUND: Results of numerous studies show that major depressive disorder (MDD) is associated with a chronic low-grade inflammation, but the underlying mechanism remains unclear. AIM: To compare the results of blood cell analysis of MDD patients with healthy controls, and explore the potential value of it as an indicator of immune-inflammation in MDD, especially the mean platelet volume. METHODS: 103 MDD patients and 106 healthy controls with matched age and gender were recruited. We collected peripheral blood samples from both groups and gathered basic data. For comparison of normally distributed data (age, body mass index, lymphocyte count, white blood cell count, red blood cell count, hematocrit, platelet count and mean corpuscular volume) between groups, single t-test were used; and for comparison of non-normally distributed data (Neutrophil count, neutrophil count, platelet/ lymphocyte ratio, hemoglobin, red blood cell distribution width, mean platelet volume, mean hemoglobin concentration, mean hemoglobin and platelet distribution width), we used Mann-Whitney U-test. RESULTS: Compared with healthy controls, the MDD groups showed significantly higher white blood cell count (F=0.443, p=0.004), plateletcrit (F=8.3, p<0.001), neutrophil and lymphocyte ratio (Z=-6.063, p<0.001), neutrophil count (Z=-5.062, p<0.001), platelet/lymphocyte ratio (Z=-2.469, p=0.014), red blood cell distribution width (Z=-2.481, p=0.013) and mean platelet volume (Z=-2.668, p=0.008). In addition they had significantly lower hemoglobin (Z=-3.876, p<0.001), mean hemoglobin amount (Z=-3.005, p=0.003), red blood cell count (F=0.248, p<0.001), lymphocyte count (F=3.826, p=0.004) and hematocrit (F=0.000, p>0.001). CONCLUSIONS: The results suggest that serum inflammatory response probably exists in people with MDD, and indicators of blood analysis especially mean platelet volume have a potential value as biomarker for inflammation.

Evaluation of the risk factors of depressive disorders comorbid with obstructive sleep apnea.

OBJECTIVE: Overlap of obstructive sleep apnea (OSA) complicates diagnosis of depressive disorder and renders antidepressant treatment challenging. Previous studies have reported that the incidence of OSA is higher in patients with depression than in the general population. The purpose of this article was to investigate clinical risk factors to predict OSA in depression disorders. METHODS: A total of 115 patients diagnosed with major depressive disorder (MDD) and bipolar disorder (in a major depressive episode), who underwent overnight polysomnography, were studied retrospectively. They were divided into two groups: non-OSA and OSA. The patients who had apnea-hypopnea index (AHI) <5 were defined as the non-OSA group, whereas the OSA group was defined as those with an AHI ≥5. Logistic regression was used to analyze the association among AHI and clinical factors, including sex, age, body mass index (BMI), Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale, Pittsburgh Sleep Quality Index (PSQI), and diagnosis (MDD or bipolar disorder [in a major depressive episode]). RESULTS: In 115 patients, 51.3% had OSA. Logistic regression analysis showed significant associations between AHI and diagnosis (MDD or bipolar disorder [in a major depressive episode]), BMI, HAMD, and PSQI (P<0.05). CONCLUSION: The findings of our study suggested that the rate of depression being comorbid with OSA is remarkably high and revealed that there is a high rate of undetected OSA among depressive disorder patients and untreated OSA among mood disorder patients. The clinical risk factors (diagnosis [MDD or bipolar disorder {in a major depressive episode}], BMI, HAMD, and PSQI) could predict AHI or OSA diagnosis and contribute to OSA screening in depressive disorder patients.

Sympathetic skin response and R-R interval variation in the assessment of clinical remission of bipolar disorder.

For our retrospective study, we chose patients who met the inclusion criteria for bipolar disorder (BD) according to the ICD-10. We conducted correlation analyses between scale scores and SSR and RRIV values before and after 1 year ±1 month of treatment. Our results suggest that the feet SSR latency and R% can be used as an indicator of clinical BD remission. The scales have high sensitivity and low specificity in assessing BD remission.

Sub-hubs of baseline functional brain networks are related to early improvement following two-week pharmacological therapy for major depressive disorder.

Accumulating evidence suggests that early improvement after two-week antidepressant treatment is predictive of later outcomes of patients with major depressive disorder (MDD); however, whether this early improvement is associated with baseline neural architecture remains largely unknown. Utilizing resting-state functional MRI data and graph-based network approaches, this study calculated voxel-wise degree centrality maps for 24 MDD patients at baseline and linked them with changes in the Hamilton Rating Scale for Depression (HAMD) scores after two weeks of medication. Six clusters exhibited significant correlations of their baseline degree centrality with treatment-induced HAMD changes for the patients, which were mainly categorized into the posterior default-mode network (i.e., the left precuneus, supramarginal gyrus, middle temporal gyrus, and right angular gyrus) and frontal regions. Receiver operating characteristic curve and logistic regression analyses convergently revealed excellent performance of these regions in discriminating the early improvement status for the patients, especially the angular gyrus (sensitivity and specificity of 100%). Moreover, the angular gyrus was identified as the optimal regressor as determined by stepwise regression. Interestingly, these regions possessed higher centrality than others in the brain (P < 10(-3)) although they were not the most highly connected hubs. Finally, we demonstrate a high reproducibility of our findings across several factors (e.g., threshold choice, anatomical distance, and temporal cutting) in our analyses. Together, these preliminary exploratory analyses demonstrate the potential of neuroimaging-based network analysis in predicting the early therapeutic improvement of MDD patients and have important implications in guiding earlier personalized therapeutic regimens for possible treatment-refractory depression.

Recognition of facial expressions of emotion in panic disorder.

BACKGROUND: Whether patients with panic disorder behave differently or not when recognizing the facial expressions of emotion remains unsettled. SAMPLING AND METHODS: We tested 21 outpatients with panic disorder and 34 healthy subjects, with a photo set from the Matsumoto and Ekman Japanese and Caucasian facial expressions of emotion, which includes anger, contempt, disgust, fear, happiness, sadness, and surprise. RESULTS: Compared to the healthy subjects, patients showed lower accuracies when recognizing disgust and fear, but a higher accuracy when recognizing surprise. CONCLUSIONS: These results suggest that the altered specificity to these emotions leads tso self-awareness mechanisms to prevent further emotional reactions in panic disorder patients.