Yuping Ning

Increased suicide attempts in young depressed patients with abnormal temporal–parietal–limbic gray matter volume

BACKGROUND Suicide is a major cause of death throughout the world. Approximately 60% of all suicides have a history of depression. Previous studies of structural brain imaging have shown that suicide is often associated with abnormal fronto-limbic networks. However, the mechanism underlying suicide in depression remains poorly understood. METHOD Twenty sex- and age-matched suicidal unipolar patients were compared with 18 non-suicidal unipolar patients and 28 healthy controls. High-resolution T1-weighted 3T magnetic resonance imaging (MRI) scans were acquired. Hamilton Depressive Rating Scale (HAMD) and Self-Rating Depression scale (SDS) were evaluated. The criterion for suicidality was one or more documented lifetime suicide attempts. A whole-brain optimized voxel-based morphometry (VBM) approach was applied. The Dysfunctional Attitude Scale (DAS) was used to measure cognitive scheme in depressive patients. RESULTS Compared with controls, patients without suicide history showed significant decreased gray matter volume in the left insula lobe [-35 18 9], whereas patients with suicide history showed significantly decreased gray matter volume in the right middle temporal gyrus [60 -53 -8] and increased gray matter volume in the right parietal lobe [39 -39 60]. Compared with the non-suicidal depressed patient group, the suicidal group showed significant decreased gray matter volume in left limbic cingulated gyrus [-2 -21 28]. Moreover, the gray matter volume values in this significantly different brain region were negatively correlated with dysfunctional attitude scores in suicidal depressed patients. LIMITATIONS This study needs replication and further clarification in a larger patient population. CONCLUSIONS Suicide attempts in young depressed patients may be related to abnormal gray matter volumes in temporal-parietal-limbic networks. Specifically, small left limbic cingulate gyrus volumes may be a candidate for the prediction of suicide in young depressed patients.

Psychometric properties of the Chinese (Mandarin) TEMPS-A: A population study of 985 non-clinical subjects in China

BACKGROUND The TEMPS-A (Temperament Evaluation of Memphis, Pisa, Paris and San Diego) is a 110-item auto-questionnaire (self-rated) which consists of five temperament scales: depressive, cyclothymic, hyperthymic, irritable and anxious temperaments. It has been translated into over 25 languages and validated in at least 12, with broad cross-cultural cogency. This is a first attempt to validate the TEMPS-A in a very large Chinese population speaking Mandarin. METHODS The Chinese TEMPS-A was adapted from the original English version following a rigorous process of forward translation and backward translation (after the approval of the English back translation by H.S.A. and K.K.A.), it was administered to 985 non-clinical Chinese subjects aged between 18-60 years (53.8% female) in four communities in Guangzhou City, China. A subset of 105 subjects was retested approximately six weeks later. Standard psychometric tests of reliability and validation were performed. RESULTS The test-retest reliability for depressive (0.74), cyclothymic (0.71), hyperthymic (0.67), irritable (0.66) and anxious (0.83) were respectively as shown in the parentheses. For internal consistency, Chronbach alphas coefficients were 0.68, 0.85, 0.82, 0.83 and 0.87, respectively. Exploratory factor analysis revealed 2 super factors, Factor I loading on anxious, cyclothymic, irritable, and depressive temperaments; and Factor II loading on hyperthymic. Depressive, cyclothymic, irritable and anxious temperaments were correlated with each other. Males had significantly higher scores than females for the hyperthymic and irritable temperaments. The prevalence of the dominant depressive (2.9%), cyclothymic (5.6%), hyperthymic (1.3%), irritable (7.0%) and anxious (5.3%) temperaments were respectively as shown in the parentheses. LIMITATIONS Although it is likely that generalizability of our scale is good for the entire Mandarin-speaking ethnic composition of China today, future research is needed to establish this conclusively. CONCLUSION The Chinese TEMPS-A standardized on one of the largest non-clinical samples in any of the other national studies to date, has good internal consistency, coheres well with validated versions in other languages. The findings suggest that it is a psychometrically sound instrument to assess affective temperaments in clinical and biological studies in China.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

AbstractStructural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Gray Matter Volume Abnormalities in Depressive Patients With and Without Anxiety Disorders

AbstractComorbidity with anxiety disorder is a relatively common occurrence in major depressive disorder. However, the unique and shared neuroanatomical characteristics of depression and anxiety disorders have not been fully identified. The aim of this study was to identify gray matter abnormalities and their clinical correlates in depressive patients with and without anxiety disorders.We applied voxel-based morphometry and region-of-interest analyses of gray matter volume (GMV) in normal controls (NC group, n = 28), depressive patients without anxiety disorder (DP group, n = 18), and depressive patients with anxiety disorder (DPA group, n = 20). The correlations between regional GMV and clinical data were analyzed.The DP group showed decreased GMV in the left insula (INS) and left triangular part of the inferior frontal gyrus when compared to the NC group. The DPA group showed greater GMV in the midbrain, medial prefrontal cortex, and primary motor/somatosensory cortex when compared to the NC group. Moreover, the DPA group showed greater GMV than the DP group in the frontal, INS, and temporal lobes. Most gray matter anomalies were significantly correlated with depression severity or anxiety symptoms. These correlations were categorized into 4 trend models, of which 3 trend models (ie, Models I, II, and IV) revealed the direction of the correlation between regional GMV and depression severity to be the opposite of that between regional GMV and anxiety symptoms. Importantly, the left INS showed a trend Model I, which might be critically important for distinguishing depressive patients with and without anxiety disorder.Our findings of gray matter abnormalities, their correlations with clinical data, and the trend models showing opposite direction may reflect disorder-specific symptom characteristics and help explain the neurobiological differences between depression and anxiety disorder.

Neuropsychiatric Features of Neurosyphilis: Frequency, Relationship with the Severity of Cognitive Impairment and Comparison with Alzheimer Disease

Background: The pattern of neuropsychiatric features of patients with neurosyphilis and the impact of the severity of cognitive impairment on neuropsychiatric syndromes are unknown. Objective: We aim to assess the neuropsychiatric features of patients with neurosyphilis, and compare the impact of the severity of cognitive impairment on the neuropsychiatric syndromes between neurosyphilis and Alzheimer disease (AD). Methods: Neuropsychiatric symptoms and the degree of cognitive impairment were assessed in a case-control study of 91 neurosyphilis, 162 AD, 157 mild cognitive impairment, and 139 normal controls by the Neuropsychiatric Inventory (NPI) scale and Clinical Dementia Rating scale, respectively. Factor analysis was performed on the 12 NPI items. Results: Factor analysis showed that patients with neurosyphilis showed more severe neuropsychiatric syndromes at the dementia stage than those neurosyphilis patients at the mild cognitive impairment stage, while neuropsychiatric manifestations were equally common among the different stages of dementia (all p < 0.05). Frontal lobe syndrome was more severe in patients with neurosyphilis than in patients with AD from the early mild cognitive impairment stage to the moderate dementia stage (all p < 0.01). Conclusions: Patients with neurosyphilis show different patterns of neuropsychiatric syndromes at the mild cognitive impairment and dementia stages, and differ from patients with AD.

Using Support Vector Machine to Identify Imaging Biomarkers of Major Depressive Disorder and Anxious Depression

Comorbidity with anxiety disorders is a relatively common occurrence in major depressive disorder. However, there are no objective, neurological markers which can be used to identify depressive disorder with and without anxiety disorders. The aim of this study was to examine the diagnostic value of structural MRI to distinguish depressive patients with and without ss using support vector machine. In this paper, we applied voxel-based morphometry of gray matter volume (GMV), then choose discriminative features to classify different group using linear support vector machine (SVM) classifier. The experimental results showed that specific structural brain regions may be a potential biomarkers for disease diagnosis.

Cognitive Impairment and Structural Abnormalities in Late Life Depression with Olfactory Identification Impairment: an Alzheimer’s Disease-Like Pattern

Abstract Background Late-life depression patients are at a high risk of developing Alzheimer’s disease, and diminished olfactory identification is an indicator in early screening for Alzheimer’s disease in the elderly. However, whether diminished olfactory identification is associated with risk of developing Alzheimer’s disease in late-life depression patients remains unclear. Methods One hundred and twenty-five late-life depression patients, 50 Alzheimer’s disease patients, and 60 normal controls were continuously recruited. The participants underwent a clinical evaluation, olfactory test, neuropsychological assessment, and neuroimaging assessment. Results The olfactory identification impairment in late-life depression patients was milder than that in Alzheimer’s disease patients. Diminished olfactory identification was significantly correlated with worse cognitive performance (global function, memory language, executive function, and attention) and reduced grey matter volume (olfactory bulb and hippocampus) in the late-life depression patients. According to a multiple linear regression analysis, olfactory identification was significantly associated with the memory scores in late-life depression group (B=1.623, P<.001). The late-life depression with olfactory identification impairment group had worse cognitive performance (global, memory, language, and executive function) and more structural abnormalities in Alzheimer’s disease-related regions than the late-life depression without olfactory identification impairment group, and global cognitive function and logical memory in the late-life depression without olfactory identification impairment group was intact. Reduced volume observed in many areas (hippocampus, precuneus, etc.) in the Alzheimer’s disease group was also observed in late-life depression with olfactory identification impairment group but not in the late-life depression without olfactory identification impairment group. Conclusion The patterns of cognitive impairment and structural abnormalities in late-life depression with olfactory identification impairment patients were similar to those in Alzheimer’s disease; olfactory identification may help identify late-life depression patients who are at a high risk of developing Alzheimer’s disease.

Kynurenine pathway changes in late-life depression with memory deficit

Kynurenine pathway (KP) activation is associated with many neuropsychiatric diseases, such as major depressive disorder (MDD) and Alzheimers disease (AD). Investigations conducted on MDD seldom shed light on KP changes in late-life depression (LLD), though memory deficit (MD) in patients with LLD is a predictable sign of AD. Thus, we aimed to investigate whether tryptophan (TRP) metabolism and kynurenine (KYN) metabolism were imbalanced in patients with LLD with MD and in patients with LLD without MD. We explored KP characteristics between LLD with MD and LLD without MD groups. We investigated 85 patients with LLD and MD, 71 patients with LLD without MD, and 129 healthy controls (HCs). Serum concentrations of TRP, KYN, and kynurenic acid (KYNA) were detected by liquid chromatography-tandem mass spectrometry. Cognition performance was assessed by the Mini-Mental State Examination (MMSE). Language ability was assessed by the Boston Naming Test (BNT). Depressive symptoms were assessed by the 17-item Hamilton Depression Scale (HAMD-17). Lower TRP and KYNA levels, a lower KYNA/KYN ratio and a higher KYN/TRP ratio were found in patients with LLD and MD compared to those in HC. Low levels of TRP and KYN, in the absence of a changed KYN/TRP ratio, were found in patients with LLD without MD. The KYNA/TRP ratio and MMSE, BNT, and HAMD-17 scores were associated with the presence of LLD. MMSE scores and a trend for the KYN/TRP ratio were associated with the presence of MD in patients with LLD. Aside from MMSE scores, there was a trend toward an association between the KYN/TRP ratio and the presence of MD in patients with LLD. In conclusion, profound shifts in TRP metabolism and KYN metabolism were found in patients with LLD and MD but not in patients with LLD without MD.

A reliable global cognitive decline and cortisol as an associated risk factor for patients with late-life depression in the short term: A 1-year prospective study

BACKGROUND Late-life depression is a risk factor of dementia. It may increase the risk of reliable cognitive decline in the short term, and its associated risk factors remain unclear. Cortisol level may be one of the important predictors. OBJECTIVES To estimate whether patients with late-life depression are at an increased risk for reliable global cognitive declines in 1 year, and explore associated risk factors predicting cognitive declines. METHODS This prospective 1-year follow-up study involved 148 participants (67 with late-life depression and 81 normal elderly). Global cognitive function was assessed by the Mini-Mental State Examination (MMSE). The reliable global cognitive decline was defined by the reliable change index (RCI) of the MMSE. Factors related to cognitive function (e.g., age, gender, education, duration of depression and severity of depression) were obtained. Serum cortisol levels were measured at baseline. RESULTS At the 1-year follow-up assessment, 19 patients with late-life depression (28.4%) showed reliable global cognitive declines, a risk that was 6.4 times (95% CIs = 1.3-31.1, p = 0.021) higher than that of normal elderly. Elevated serum cortisol levels and older age were associated with the risk of cognitive decline that was 1.6- and 1.2-times higher (95% CIs = 1.07-2.5, p = 0.02, and 95% CIs = 1.04-1.4, p = 0.01 respectively). LIMITATIONS Serum cortisol levels were measured only in the morning. CONCLUSIONS Late-life depression is associated with a greatly increased risk of reliable cognitive decline in short term. Cortisol dysregulation may contribute to the pathology of cognitive decline.