Adenosine, Schizophrenia and Cancer: Does the Purinergic System Offer a Pathway to Treatment?

Adenosine Metabolism Pathway Alterations in Frontal Cortical Neurons in Schizophrenia

Schizophrenia is a neuropsychiatric illness characterized by altered neurotransmission, in which adenosine, a modulator of glutamate and dopamine, plays a critical role that is relatively unexplored in the human brain. In the present study, postmortem human brain tissue from the anterior cingulate cortex (ACC) of individuals with schizophrenia (n = 20) and sex- and age-matched control subjects without psychiatric illness (n = 20) was obtained from the Bronx-Mount Sinai NIH Brain and Tissue Repository. Enriched populations of ACC pyramidal neurons were isolated using laser microdissection (LMD). The mRNA expression levels of six key adenosine pathway components-adenosine kinase (ADK), equilibrative nucleoside transporters 1 and 2 (ENT1 and ENT2), ectonucleoside triphosphate diphosphohydrolases 1 and 3 (ENTPD1 and ENTPD3), and ecto-5'-nucleotidase (NT5E)-were quantified using real-time PCR (qPCR) in neurons from these individuals. No significant mRNA expression differences were observed between the schizophrenia and control groups (p > 0.05). However, a significant sex difference was found in ADK mRNA expression, with higher levels in male compared with female subjects (Mann-Whitney U = 86; p < 0.05), a finding significantly driven by disease (t(17) = 3.289; p < 0.05). Correlation analyses also demonstrated significant associations (n = 12) between the expression of several adenosine pathway components (p < 0.05). In our dementia severity analysis, ENTPD1 mRNA expression was significantly higher in males in the "mild" clinical dementia rating (CDR) bin compared with males in the "none" CDR bin (F(2, 13) = 5.212; p < 0.05). Lastly, antipsychotic analysis revealed no significant impact on the expression of adenosine pathway components between medicated and non-medicated schizophrenia subjects (p > 0.05). The observed sex-specific variations and inter-component correlations highlight the value of investigating sex differences in disease and contribute to the molecular basis of schizophrenia's pathology.

Genetic prediction of the causal relationship between schizophrenia and tumors: a Mendelian randomized study

Background

Patients with schizophrenia are at a higher risk of developing cancer. However, the causal relationship between schizophrenia and different tumor types remains unclear.

Methods

Using a two-sample, two-way Mendelian randomization method, we used publicly available genome-wide association analysis (GWAS) aggregate data to study the causal relationship between schizophrenia and different cancer risk factors. These tumors included lung adenocarcinoma, lung squamous cell carcinoma, small-cell lung cancer, gastric cancer, alcohol-related hepatocellular cancer, tumors involving the lungs, breast, thyroid gland, pancreas, prostate, ovaries and cervix, endometrium, colon and colorectum, and bladder. We used the inverse variance weighting (IVW) method to determine the causal relationship between schizophrenia and different tumor risk factors. In addition, we conducted a sensitivity test to evaluate the effectiveness of the causality.

Results

After adjusting for heterogeneity, evidence of a causal relationship between schizophrenia and lung cancer risk was observed (odds ratio [OR]=1.001, 95% confidence interval [CI], 1.000-1.001; P=0.0155). In the sensitivity analysis, the causal effect of schizophrenia on the risk of lung cancer was consistent in both direction and degree. However, no evidence of causality or reverse causality between schizophrenia and other tumors was found.

Conclusion

This study elucidated a causal relationship between the genetic predictors of schizophrenia and the risk of lung cancer, thereby providing a basis for the prevention, pathogenesis, and treatment of schizophrenia in patients with lung cancer.

Glucose dysregulation in antipsychotic-naive first-episode psychosis: in silico exploration of gene expression signatures

Antipsychotic (AP)-naive first-episode psychosis (FEP) patients display early dysglycemia, including insulin resistance and prediabetes. Metabolic dysregulation may therefore be intrinsic to psychosis spectrum disorders (PSDs), independent of the metabolic effects of APs. However, the potential biological pathways that overlap between PSDs and dysglycemic states remain to be identified. Using meta-analytic approaches of transcriptomic datasets, we investigated whether AP-naive FEP patients share overlapping gene expression signatures with non-psychiatrically ill early dysglycemia individuals. We meta-analyzed peripheral transcriptomic datasets of AP-naive FEP patients and non-psychiatrically ill early dysglycemia subjects to identify common gene expression signatures. Common signatures underwent pathway enrichment analysis and were then used to identify potential new pharmacological compounds via Integrative Library of Integrated Network-Based Cellular Signatures (iLINCS). Our search results yielded 5 AP-naive FEP studies and 4 early dysglycemia studies which met inclusion criteria. We discovered that AP-naive FEP and non-psychiatrically ill subjects exhibiting early dysglycemia shared 221 common signatures, which were enriched for pathways related to endoplasmic reticulum stress and abnormal brain energetics. Nine FDA-approved drugs were identified as potential drug treatments, of which the antidiabetic metformin, the first-line treatment for type 2 diabetes, has evidence to attenuate metabolic dysfunction in PSDs. Taken together, our findings support shared gene expression changes and biological pathways associating PSDs with dysglycemic disorders. These data suggest that the pathobiology of PSDs overlaps and potentially contributes to dysglycemia. Finally, we find that metformin may be a potential treatment for early metabolic dysfunction intrinsic to PSDs.

Purinergic Signalling in Physiology and Pathophysiology

Since its inception by the late Geoffrey Burnstock in the early 1970s [...].