Biomarker identification and effect estimation on schizophrenia - a high dimensional data analysis

Modified climbing fiber/Purkinje cell synaptic connectivity in the cerebellum of the neonatal phencyclidine model of schizophrenia

Synaptogenesis and neural network remodeling are at their maximum during the perinatal period of human brain development. Perturbations of this highly sensitive stage might underlie the etiology of neurodevelopmental disorders. Subchronic neonatal administration of phencyclidine, a drug of abuse, has been used to model schizophrenia in rodents. In this model, we found specific long-term synaptic changes in Purkinje cells and transient gene expression changes in the cerebellum. While transient increased neuronal activity in the cerebellum, induced using chemogenetics, reproduces some phencyclidine-induced molecular changes, it is insufficient to reproduce the long-term synaptic effects. Our results show the complex mechanism of action of phencyclidine on the development of neuronal connectivity and further highlight the potential contribution of cerebellar defects in psychiatric diseases.

Environmental perturbations during the first years of life are a major factor in psychiatric diseases. Phencyclidine (PCP), a drug of abuse, has psychomimetic effects, and neonatal subchronic administration of PCP in rodents leads to long-term behavioral changes relevant for schizophrenia. The cerebellum is increasingly recognized for its role in diverse cognitive functions. However, little is known about potential cerebellar changes in models of schizophrenia. Here, we analyzed the characteristics of the cerebellum in the neonatal subchronic PCP model. We found that, while the global cerebellar cytoarchitecture and Purkinje cell spontaneous spiking properties are unchanged, climbing fiber/Purkinje cell synaptic connectivity is increased in juvenile mice. Neonatal subchronic administration of PCP is accompanied by increased cFos expression, a marker of neuronal activity, and transient modification of the neuronal surfaceome in the cerebellum. The largest change observed is the overexpression of Ctgf, a gene previously suggested as a biomarker for schizophrenia. This neonatal increase in Ctgf can be reproduced by increasing neuronal activity in the cerebellum during the second postnatal week using chemogenetics. However, it does not lead to increased climbing fiber/Purkinje cell connectivity in juvenile mice, showing the complexity of PCP action. Overall, our study shows that administration of the drug of abuse PCP during the developmental period of intense cerebellar synaptogenesis and circuit remodeling has long-term and specific effects on Purkinje cell connectivity and warrants the search for this type of synaptic changes in psychiatric diseases.

Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders

Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection methods, such as the Lasso, tend to select one of them and eliminate the others, although some of the eliminated ones are still scientifically valuable. To alleviate this drawback, we propose a feature selection method based on covariate space decomposition, referred herein as the "Decomposition Feature Selection" (DFS), and show that this method can lead to scientifically meaningful results in studies with correlated high dimensional data. The DFS consists of two steps: (i) decomposing the covariate space into disjoint subsets such that each of the subsets contains only uncorrelated covariates and (ii) identifying significant predictors by traditional feature selection within each covariate subset. We demonstrate through simulation studies that the DFS has superior practical performance over the Lasso type methods when multiple highly correlated covariates need to be retained. Application of the DFS is demonstrated through a study of bipolar disorders with correlated biomarkers.

Associations between SNPs and immune-related circulating proteins in schizophrenia

Genome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis.

Cancer Immune Equilibrium and Schizophrenia Have Similar Interferon-γ, Tumor Necrosis Factor-α, and Interleukin Expression: A Tumor Model of Schizophrenia

For at least a century, a debate has continued as to whether cancer risk is reduced in schizophrenia. Genetic studies have also suggested the 2 conditions may share protein transcriptional pathways. The author predicted that if the pathophysiology of schizophrenia confers protection from cancer, then the immunology of schizophrenia should reflect a state of tumor suppression, ie, the opposite of tumor escape. To examine this possibility, the author performed a literature search for measurements of cytokines in drug-naïve first episode subjects with schizophrenia for comparison with cytokine expression in tumor escape vs tumor suppression. The comparison showed that instead of either tumor suppression or escape, schizophrenia appears to be in a state of tumor equilibrium. Based on this finding, the author hypothesized that the clinical presentation of schizophrenia may involve cell transformation similar to an early stage of cancer initiation or an attenuated tumorigenesis. While this condition could reflect the presence of an actual tumor such as an ovarian teratoma causing anti-NMDA receptor encephalitis, it would only explain a small percentage of cases. To find a more likely tumor model, the author then compared the cytokine profile of schizophrenia to individual cancers and found the best match was melanoma. To demonstrate the viability of the theory, the author compared the hallmarks, emerging hallmarks, and enabling characteristics of melanoma to schizophrenia and found that many findings in schizophrenia are understood if schizophrenia is a condition of attenuated tumorigenesis.