Longitudinal associations between alcohol use, smoking, genetic risk scoring and symptoms of depression in the general population: a prospective 6-year cohort study.

BACKGROUND: Alcohol consumption, smoking and mood disorders are leading contributors to the global burden of disease and are highly comorbid. Yet, their interrelationships have remained elusive. The aim of this study was to examine the multi-cross-sectional and longitudinal associations between (change in) smoking and alcohol use and (change in) number of depressive symptoms. METHODS: In this prospective, longitudinal study, 6646 adults from the general population were included with follow-up measurements after 3 and 6 years. Linear mixed-effects models were used to test multi-cross-sectional and longitudinal associations, with smoking behaviour, alcohol use and genetic risk scores for smoking and alcohol use as independent variables and depressive symptoms as dependent variables. RESULTS: In the multi-cross-sectional analysis, smoking status and number of cigarettes per day were positively associated with depressive symptoms (p < 0.001). Moderate drinking was associated with less symptoms of depression compared to non-use (p = 0.011). Longitudinally, decreases in the numbers of cigarettes per day and alcoholic drinks per week as well as alcohol cessation were associated with a reduction of depressive symptoms (p = 0.001-0.028). Results of genetic risk score analyses aligned with these findings. CONCLUSIONS: While cross-sectionally smoking and moderate alcohol use show opposing associations with depressive symptoms, decreases in smoking behaviour as well as alcohol consumption are associated with improvements in depressive symptoms over time. Although we cannot infer causality, these results open avenues to further investigate interventions targeting smoking and alcohol behaviours in people suffering from depressive symptoms.

Application of network methods for understanding mental disorders: pitfalls and promise.

Galvanized with the availability of sophisticated statistical techniques and large datasets, network medicine has emerged as an active area of investigation. Following this trend, network methods have been utilized to understand the interplay between symptoms of mental disorders. This realistic approach that may provide an improved framework into understanding mental conditions and underlying mechanisms is certainly to be welcomed. However, we have noticed that symptom network studies tend to lose sight of the fundamentals, overlook major limitations embedded in study designs, and make inferences that are difficult to justify with current findings. There is concern that disregarding these flaws may halt the progress of the network approach in psychiatry. Therefore, in this paper, we first attempt to identify the pitfalls: (1) a reductionist understanding of medicine and psychiatry, thereby inadvertently reintroducing the dichotomy of medicine (lung cancer) and psychiatry (depression), (2) a shortsighted view of signs and symptoms, (3) overlooking the limitations of available datasets based on scales with embedded latent class structures, (4) overestimating the importance of the current findings beyond what is supported by the study design. By addressing current issues, the hope is to navigate this rapidly growing field to a more methodologically sound and reproducible path that will contribute to our understanding of mental disorders and its underlying mechanisms.

Rabies virus vaccine as an immune adjuvant against cancers and glioblastoma: new studies may resurrect a neglected potential.

To review the literature about the use of Rabies Virus-Vaccine (RV-V) as an anticancer immunotherapeutic modality in the light of recent findings. The literature search in relevant databases with the following key words: Rabies virus, cancer, remission. Remissions occured following RV-V injections in patients with cervical cancer and melanoma. Pilot clinical studies showed that RV-V injections enhanced survival in glioblastoma patients, which is supported by findings in GL261 mouse glioma model. If public health studies demonstrate protective role of RV-V against certain types of cancers, it can be benefitted as a novel immune adjuvant in clinic.