BDNF in antipsychotic naive first episode psychosis: Effects of risperidone and the immune-inflammatory response system.

Brain-derived neurotrophic factor (BDNF) and the immune-inflammatory response system (IRS) have been implicated in the pathophysiology of schizophrenia. However, no research examined the associations between BDNF and immune activation both before and after treatment in antipsychotic-naïve first episode psychosis (AN-FEP). This study aims to examine serum BDNF levels and their association with IRS and the compensatory immune-regulatory reflex system (CIRS) in AN-FEP before and after risperidone treatment. We included 31 AN-FEP and 22 healthy controls. AN-FEP showed reduced levels of BDNF as compared to controls, and BDNF levels normalized after treatment with risperidone. BDNF levels were inversely correlated with a greater IRS response. Higher levels of IRS/CIRS biomarkers were associated with lower levels of BDNF including M1 macrophage, T-helper (Th)-1, Th-2, and Th-17, and T-regulatory (Treg) cell responses. Our findings indicate that AN-FEP is characterized by decreased levels of BDNF, which are normalized after treatment with risperidone. BDNF levels were inversely associated with activated immune-inflammatory pathways. The findings support the hypothesis that, increased IRS is linked to neurotoxicity, and that a decrease in BDNF may be part of the IRS/CIRS responses in FEP and, thus, be involved in the development of psychosis.

Factors influencing insulin resistance in relation to atherogenicity in mood disorders, the metabolic syndrome and tobacco use disorder.

OBJECTIVE: This study examines the effects of malondialdehyde (MDA) and uric acid on insulin resistance and atherogenicity in subjects with and without mood disorders, the metabolic syndrome (MetS) and tobacco use disorder (TUD). METHODS: We included 314 subjects with depression and bipolar depression, with and without the MetS and TUD and computed insulin resistance using the updated homeostasis model assessment (HOMA2IR) and atherogenicity using the atherogenic index of plasma (AIP), that is log10 (triglycerides/high density lipoprotein (HDL) cholesterol. RESULTS: HOMA2IR is correlated with body mass index (BMI) and uric acid levels, but not with mood disorders and TUD, while the AIP is positively associated with BMI, mood disorders, TUD, uric acid, MDA and male sex. Uric acid is positively associated with insulin and triglycerides and negatively with HDL cholesterol. MDA is positively associated with triglyceride levels. Comorbid mood disorders and TUD further increase AIP but not insulin resistance. Glucose is positively associated with increasing age, male gender and BMI. DISCUSSION: The results show that mood disorders, TUD and BMI together with elevated levels of uric acid and MDA independently contribute to increased atherogenic potential, while BMI and uric acid are risk factors for insulin resistance. The findings show that mood disorders and TUD are closely related to an increased atherogenic potential but not to insulin resistance or the MetS. Increased uric acid is a highly significant risk factor for insulin resistance and increased atherogenic potential. MDA, a marker of lipid peroxidation, further contributes to different aspects of the atherogenic potential. Mood disorders and TUD increase triglyceride levels, lower HDL cholesterol and are strongly associated with the atherogenic, but not insulin resistance, component of the MetS.

N-acetylcysteine for therapy-resistant tobacco use disorder: a pilot study.

INTRODUCTION: N-Acetylcysteine (NAC) may have efficacy in treating tobacco use disorder (TUD) by reducing craving and smoking reward. This study examines whether treatment with NAC may have a clinical efficacy in the treatment of TUD. METHODS: A 12-week double blind randomized controlled trial was conducted to compare the clinical efficacy of NAC 3 g/day versus placebo. We recruited 34 outpatients with therapy resistant TUD concurrently treated with smoking-focused group behavioral therapy. Participants had assessments of daily cigarette use (primary outcome), exhaled carbon monoxide (CO(EXH)) (secondary outcome), and quit rates as defined by CO(EXH) < 6 ppm. Depression was measured with the Hamilton Depression Rating Scale (HDRS). Data were analyzed using conventional and modified intention-to-treat endpoint analyses. RESULTS: NAC treatment significantly reduced the daily number of cigarettes used (Δ mean ± SD = -10.9 ± 7.9 in the NAC-treated versus -3.2 ± 6.1 in the placebo group) and CO(EXH) (Δ mean ± SD = -10.4 ± 8.6 ppm in the NAC-treated versus -1.5 ± 4.5 ppm in the placebo group); 47.1% of those treated with NAC versus 21.4% of placebo-treated patients were able to quit smoking as defined by CO(EXH) < 6 ppm. NAC treatment significantly reduced the HDRS score in patients with tobacco use disorder. CONCLUSIONS: These data show that treatment with NAC may have a clinical efficacy in TUD. NAC combined with appropriate psychotherapy appears to be an efficient treatment option for TUD.

Association of paraoxonase (PON)1 activity, glutathione S-transferase GST T1/M1 and STin.2 polymorphisms with comorbidity of tobacco use disorder and mood disorders.

There is evidence that genetic factors influence the probability of comorbidity of tobacco use disorder (TUD) with mood disorders. This study was carried out to examine whether both TUD and mood disorders are associated with genetic biomarkers particularly paraoxonase 1 (PON1) status, polymorphisms of glutathione S-transferases (GSTs), such as GSTM1 and GSTT1, and the STIn 2 polymorphism of the serotonin transporter. PON1 status (Q192R polymorphism and PON1 plasmatic activity), GSTM1, GSTT1, and STin.2 genotypes and alleles were assayed in 4 mutually exclusive study groups, i.e., comorbid mood disorder and TUD (n=95); TUD without mood disorders (n=90); mood disorders but no TUD (n=62); and controls (never-smokers without mood disorders; n=113). Logistic regression analyses showed that comorbid mood disorders and TUD were associated with significantly lower PON1 activity, the STin2.10/10 genotype (protective) or the Stin2.12 allele (risk factor) and the GSTM1 and GSTT1 null genotypes (protective). These results show that comorbid mood disorders and TUD are associated with specific biomarkers related to oxidative stress and serotonin pathways.

STin2 VNTR polymorphism is associated with comorbid tobacco use and mood disorders.

BACKGROUND: There is a significant comorbidity between mood disorders and tobacco use disorder (TUD), which may be related to both genetic and environmental factors. Gene variants of the 5-HT transporter, such as STin2 VNTR (a variable number of tandem repeats in the functional serotonin transporter intron 2) may be associated with mood disorders and TUD. AIMS: This study aimed to delineate the association between the STin2 genetic polymorphism and comorbid TUD and mood disorders, including depression or bipolar disorder. METHODS: We examined the STin2 VNTR polymorphism in never-smokers (n=113); patients with mood disorders without TUD (n=62); patients with TUD without mood disorders (n=90); and patients with both disorders (n=95). RESULTS: We found a significant association between the STin2 genetic polymorphism and the above diagnostic groups whereby the STin2.12 allele shows a positive association with comorbid TUD and mood disorders (Odds ratio=3.07, 95% CI=1.41-6.68), while the STin2.10/10 homozygous genotype shows a negative association (Odds ratio=0.34, 95% CI=0.16-0.74). Adjusting for years of education, age, gender, marital status and ethnicity did not change these results, but showed that TUD was associated with lower education levels and less stable relationships, whereas mood disorders were related to female gender. A family history of TUD was significantly associated with TUD in subjects without mood disorders only. CONCLUSIONS: The STin2.12 allele is positively and the STin2.10/10 genotype is negatively associated with comorbid TUD and mood disorders, depression or bipolar depression, suggesting that biological endophenotypes, e.g. disorders in serotonin metabolism, may in part underpin this comorbidity.

Paraoxonase (PON)1 Q192R functional genotypes and PON1 Q192R genotype by smoking interactions are risk factors for the metabolic syndrome, but not overweight or obesity.

Background The metabolic syndrome (MetS) is a complex of multiple risk factors that contribute to the onset of cardiovascular disorder, including lowered levels of high-density lipoprotein (HDL) and abdominal obesity. Smoking, mood disorders, and oxidative stress are associated with the MetS. Paraoxonase (PON)1 is an antioxidant bound to HDL, that is under genetic control by functional polymorphisms in the PON1 Q192R coding sequence. Aims and methods This study aimed to delineate the associations of the MetS with plasma PON1 activity, PON1 Q192R genotypes, smoking, and mood disorders (major depression and bipolar disorder), while adjusting for HDL cholesterol, body mass index, age, gender, and sociodemographic data. We measured plasma PON1 activity and serum HDL cholesterol and determined PON1 Q192R genotypes through functional analysis in 335 subjects, consisting of 97 with and 238 without MetS. The severity of nicotine dependence was measured using the Fagerström Nicotine Dependence Scale. Results PON1 Q192R functional genotypes and PON1 Q192R genotypes by smoking interactions were associated with the MetS. The QQ and QR genotypes were protective against MetS while smoking increased metabolic risk in QQ carriers only. There were no significant associations between PON1 Q192R genotypes and smoking by genotype interactions and obesity or overweight, while body mass index significantly increased MetS risk. Smoking and especially severe nicotine dependence are significantly associated with the MetS although these effects were no longer significant after considering the effects of the smoking by PON1 Q192R genotype interaction. The MetS was not associated with mood disorders, major depression or bipolar disorder. Discussion PON1 Q192R genotypes and genotypes by smoking interactions are risk factors for the MetS that together with lowered HDL and increased body mass and age contribute to the MetS.