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Kynurenine is correlated with IL-1β in plasma of schizophrenia patients

Overview of attention for article published in Journal of Neural Transmission, January 2018
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Title
Kynurenine is correlated with IL-1β in plasma of schizophrenia patients
Published in
Journal of Neural Transmission, January 2018
DOI 10.1007/s00702-018-1838-8
Pubmed ID
Authors

Helena P. G. Joaquim, Alana C. Costa, Wagner F. Gattaz, Leda Leme Talib

Abstract

The etiology of schizophrenia is still unclear. It is well-known that pro-inflammatory cytokines are higher in schizophrenia patients since the first episode psychosis comparing to healthy controls. Inflammatory downstream cascades influence different cellular pathways, like the displacement of the tryptophan (TRP) metabolism to the production of kynurenine (KYN) instead of serotonin, which results in the generation of several neuro and immunoactive metabolites. The aim of this study was to determine TRP, KYN and IL-1β plasma levels in first-onset schizophrenia (n = 28) and healthy controls (n = 30). The plasmatic levels of TRP and KYN were decreased in schizophrenic patients (p = 0.004 and p = 0.002, respectively), but there was no difference in the ratio of KYN/TRP (p = 0.554) or either in IL-1β (p = 0.101). Positive correlation was observed between KYN and IL-1β only in the schizophrenia group (r = 0.461, p = 0.021). And, there was also positive correlation between KYN and Positive and Negative Symptoms Scale (PANSS) (r = 0.395, p = 0.037). There is no correlation between the other analytes and other parameters of PANSS. Although our results of KYN have been different than expected and there was no difference in the KYN/TRP ratio, we observed a positive correlation between IL-1β and KYN, corroborating findings that pro-inflammatory agents hold up the KYN pathway.

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Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 20%
Student > Doctoral Student 4 11%
Student > Ph. D. Student 3 9%
Professor 2 6%
Other 2 6%
Other 5 14%
Unknown 12 34%
Readers by discipline Count As %
Medicine and Dentistry 5 14%
Psychology 4 11%
Neuroscience 3 9%
Social Sciences 2 6%
Computer Science 1 3%
Other 2 6%
Unknown 18 51%