A brainnetome atlas-based methamphetamine dependence identification using neighborhood component analysis and machine learning on functional MRI data.

Addiction to methamphetamine (MA) is a major public health concern. Developing a predictive model that can classify and characterize the brain-based biomarkers predicting MA addicts may directly lead to improved treatment outcomes. In the current study, we applied the support vector machine (SVM)-based classification method to resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from individuals with methamphetamine use disorder (MUD) and healthy controls (HCs) to identify brain-based features predictive of MUD. Brain connectivity analyses were conducted for 36 individuals with MUD as well as 37 HCs based on the brainnetome atlas, and the neighborhood component analysis was applied for feature selection. Eighteen most relevant features were screened out and fed into the SVM to classify the data. The classifier was able to differentiate individuals with MUD from HCs with a high prediction accuracy, sensitivity, specificity, and AUC of 88.00, 86.84, 89.19, and 0.94, respectively. The top six discriminative features associated with changes in the functional activity of key nodes in the default mode network (DMN), all the remaining discriminative features are related to the thalamic connections within the cortico-striato-thalamo-cortical (CSTC) loop. In addition, the functional connectivity (FC) between the bilateral inferior parietal lobule (IPL) and right cingulate gyrus (CG) was significantly correlated with the duration of methamphetamine use. The results of this study not only indicated that MUD-related FC alterations were predictive of group membership, but also suggested that machine learning techniques could be used for the identification of MUD-related imaging biomarkers.

Association between childhood trauma and accelerated telomere erosion in adulthood: A meta-analytic study.

BACKGROUND: Childhood trauma has long-term sequelae on health status and contributes to numbers of somatic and mental disorders in later life. Findings from experimental studies in animals suggest that telomere erosion may be a mediator of this relationship. However, results from human studies are heterogeneous. To address these inconsistencies, we performed a meta-analysis regarding the association between childhood trauma and telomere length in adulthood. METHOD: Articles were identified by systematically searching the Medline, EMBASE and Web of Science databases. Twenty four studies, which include twenty six sample sets and 30,919 participants, met the inclusion criteria for meta-analyses. RESULTS: This meta-analyses revealed that individuals experienced childhood trauma have accelerated telomere erosion in adulthood, with a small effect size (r = -0.05, 95% CI = -0.08-0.03, p < 0.001). Subgroup analyses by type of childhood trauma revealed a trend in difference between groups (Q = 5.24, p = 0.07). Analyses for individual trauma types revealed a significant association between childhood separation and telomere erosion (r = -0.09, p < 0.001), but not for physical abuse, sexual abuse and loss of a parent. CONCLUSION: This meta-analysis demonstrated a significant association between childhood trauma and accelerated telomere erosion in adulthood, and further revealed that different trauma types have various impacts on telomere. Additional research on the mechanism that links the individual types of childhood trauma with telomere is needed in the future.

Decreased left middle temporal gyrus volume in antipsychotic drug-naive, first-episode schizophrenia patients and their healthy unaffected siblings.

BACKGROUND: The shared neuropathological characteristics of patients with schizophrenia and their siblings might represent intermediate phenotypes that could be used to investigate genetic susceptibility to the illness. We sought to discover gray matter volume differences in patients with schizophrenia and their unaffected siblings with voxel-based morphometry (VBM). METHODS: We recruited antipsychotic drug-naive, first-episode schizophrenia (FES) patients, their unaffected siblings and age-, sex- and handedness-matched healthy controls. We used VBM to investigate differences in gray matter volume among the 3 groups. RESULTS: There were significant gray matter volumetric differences among the 3 groups in bilateral hippocampal and parahippocampal gyri, bilateral middle temporal gyri, and superior temporal gyri (FDR p<0.05). Patients had significant regional gray matter reduction in all regions listed above compared with healthy volunteers, and their gray matter volume in the right hippocampus and parahippocampus was also lower than the sibling group. The sibling group had significantly lower volumes compared to healthy individuals only in the left middle temporal gyrus, and volume of this region was not different between siblings and patients. CONCLUSIONS: Our findings confirm and extend previous VBM analyses in schizophrenia and it indicate that schizophrenia may be characterized by an abnormal development of cerebral lateralization. Furthermore, these data argue that patients and their unaffected siblings might share decreases in the gray matter volume of the left middle temporal gyrus, and this regional reduction might be a potential endophenotype for schizophrenia.

A family with radio-ulnar synostosis, scoliosis, and thick vermilion of lips: a novel syndrome or variant of Giuffrè-Tsukahara syndrome?

We report on a three-generation Chinese family presenting with a recognizable condition consisting of radio-ulnar synostosis, short stature, scoliosis, distinctive craniofacial features (thick vermilion to the lips, prominent eyes, and flat malar region), and a shortened and thickened femur neck. The inheritance of the trait was presumably autosomal dominant. The lack of microcephaly in the family suggested a variant of Giuffè-Tsukahara syndrome but could represent variability

Effects of typical and atypical antipsychotics on glucose-insulin homeostasis and lipid metabolism in first-episode schizophrenia.

RATIONALE: Glucose and lipid metabolism dysfunction is a significant side effect associated with antipsychotics. Although there are many studies about the linkages between drugs and metabolic dysfunction, most of these studies have compared the effects of two antipsychotics on only one metabolic measure: either glucose or lipid metabolism. OBJECTIVES: The present study aimed to investigate the effects of clozapine, olanzapine, risperidone, and sulpiride on glucose and lipid metabolism in first-episode schizophrenia. MATERIALS AND METHODS: One hundred twelve schizophrenics were assigned randomly to receive clozapine, olanzapine, risperidone, or sulpiride for 8 weeks. Planned assessments included body mass index (BMI), waist-to-hip ratio, fasting glucose, insulin, C-peptide, insulin resistance index (IRI), cholesterol, and triglyceride. All measures were collected at baseline and at the end of the 8-week treatment. RESULTS: After treatment, insulin, C-peptide, and IRI were significantly increased in the four groups, but not fasting glucose levels. Cholesterol and triglyceride levels were significantly increased in the clozapine and olanzapine groups. Patients treated with clozapine and olanzapine had higher fasting insulin, C-peptide, and IRI levels than those treated with risperidone and sulpiride. Among the four antipsychotics, the increases of mean BMI from high to low were as follows: clozapine, olanzapine, sulpiride, and risperidone. CONCLUSIONS: This study confirmed that the four antipsychotic drugs were associated with an increase of insulin, C-peptide, and IRI. It was found that clozapine and olanzapine were associated with an increase in cholesterol and triglyceride levels. The effects of clozapine and olanzapine on the glucose and lipid metabolism outweighed those of risperidone and sulpiride.