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The disability and burden associated with major depression comes only in part from its affective symptoms; cognitive dysfunctions associated with depression also play a crucial role. Furthermore, these cognitive impairments during depression are manifold and multilevel affecting elementary and more complex cognitive processes equally. Several models from different directions tried to evaluate, conceptualize and understand the depth and magnitude of cognitive dysfunctions in depression and their bidirectional interactions with other types of depressive symptomatology including mood symptoms. In the current review, we briefly overview different types of cognitive symptoms and deficits related to major depression including hot and cold as well as trait- and state-like cognitive alterations and we also describe current knowledge related to the impact of cognitive impairments on the course and outcomes of depression including remission, residual symptoms, function, and response to treatment. We also emphasize shortcomings of currently available treatments for depression in sufficiently improving cognitive dysfunctions and point out the need for newer pharmacological approaches especially in cooperation with psychotherapeutic interventions. [ABSTRACT FROM AUTHOR]

Heterogeneous phenotypes of complex disorders pose a great challenge for genetic association studies and for the development of personalized treatment strategies. Cluster analysis of phenotypic data has been recently proposed as a reliable auxiliary method for such studies. A cohort of 236 treatment-seeking smokers was investigated after overnight nicotine abstinence. Alpha4 nicotinic acetylcholine receptor (nAChR) subunit-related phenotypes were assessed by the Fagerström Test for Nicotine Dependence (FTND), exhaled carbon monoxide (CO) measurements, the Minnesota Nicotine Withdrawal Scale (MNWS) and the Zung Self-Rating Depression Scale (ZSDS). Seven tag SNPs (single-nucleotide polymorphisms) across CHRNA4 (the gene encoding alpha4 subunit of the nicotinic acetylcholine receptor) were genotyped and two-step cluster analysis was used for phenotypic cluster characterization. Haplotype estimation was determined by HapStat module of R 2.0 software. Three different phenotypic clusters were identified and the C3 cluster was characterized by the highest ZSDS and MNWS scores compared to others. Furthermore, lifetime prevalence of major depression was significantly higher in the C3 cluster (p = 0.019). In genetic association tests, this cluster was also significantly associated with rs3787138 genotypes (p = 0.004) while haplotype analyses of three SNPs (rs3787138, rs1044396, rs3787140) revealed that the risk for C3 phenotype was almost three times higher in GCC haplotype carriers compared to others (pperm = 0.013). This is the first report on a significant association between CHRNA4 variants and a subgroup of smokers characterized by massive withdrawal symptoms and affective vulnerability. Identification of such a phenotypic cluster can be a pivotal step for further pharmacogenetic studies on ligands of the alpha4 nAChR subunit. Our results suggest that performing cluster analysis in genetic association studies can be proposed for complex disorders. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) is a leading cause of disability and premature mortality. This study compared the overall survival (OS) between patients with MDD and non-MDD controls stratified by gender, age, and comorbidities., Methods: This nationwide population-based cohort study utilized longitudinal patient data (01/01/2010 - 12/31/2020) from the Hungarian National Health Insurance Fund database, which contains healthcare service data for the Hungarian population. Patients with MDD were selected and matched 1:1 to those without MDD using exact matching. The rates of conversion from MDD to bipolar disorder (BD) or schizophrenia were also investigated., Results: Overall, 471,773 patients were included in each of the matched MDD and non-MDD groups. Patients with MDD had significantly worse OS than non-MDD controls (hazard ratio [HR] = 1.50; 95% CI: 1.48-1.51; males HR = 1.69, 95% CI: 1.66-1.72; females HR = 1.40, 95% CI: 1.38-1.42). The estimated life expectancy of patients with MDD was 7.8 and 6.0 years less than that of controls aged 20 and 45 years, respectively. Adjusted analyses based on the presence of baseline comorbidities also showed that patients with MDD had worse survival than non-MDD controls (adjusted HR = 1.29, 95% CI: 1.28-1.31). After 11 years of follow-up, the cumulative conversions from MDD to BD and schizophrenia were 6.8 and 3.4%, respectively. Converted patients had significantly worse OS than non-converted patients., Conclusions: Compared with the non-MDD controls, a higher mortality rate in patients with MDD, especially in those with comorbidities and/or who have converted to BD or schizophrenia, suggests that early detection and personalized treatment of MDD may reduce the mortality in patients diagnosed with MDD.