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Objective Genetic variations in the gene encoding zinc finger protein 804A gene (ZNF804A) have been associated with major depression and bipolar disorder. In this work we focused on the potential influence of ZNF804A variations on the risk of developing specific sub-phenotypes as well as the individual response to available treatments. Methods We used two samples of different ethnic origin: a Korean sample, composed by 242 patients diagnosed with major depression and 132 patients diagnosed with bipolar disorder and 326 healthy controls; an Italian sample composed 151 major depression subjects, 189 bipolar disorder subjects and 38 outpatients diagnosed for a primary anxiety disorder. Results Our analyses reported an association of rs1344706 with psychotic phenotype in the cross-diagnostic pooled sample (geno p = 4.15 × 10-4, allelic p = 1.06 × 10-4). In the cross-diagnosis Italian sample but not in the Korean one, rs7597593 was involved with depressive symptoms improvement after treatment (geno p = 0.025, allelic p = 0.007). Conclusion The present study evidenced the role of ZNF804A alterations in symptoms improvement after treatment. Both manic and depressive symptoms seem to be modulated by ZNF804A, though the latter was observed in the bipolar pooled sample only. The role of this factor is likely related to synaptic development and maintenance; however, further analyses will be needed to better understand the molecular mechanics involved with ZNF804A.

Depression affects 7% of the elderly population, and it often remains misdiagnosed or untreated. Peripheral biomarkers might aid clinicians by allowing more accurate and well-timed recognition of the disease. We sought to determine if plasma protein levels predict the severity of depressive symptomatology or distinguish patients from healthy individuals. The severity of depressive symptoms and global cognitive functioning were assessed by the Geriatric Depression Scale (GDS) and Mini-Mental State Examination (MMSE) in 152 elderly subjects, 76 of which with major depressive disorder (MDD). Plasma levels of 24 proteins were measured by multiplexing and analyzed as continuous predictors or dichotomized using the median value. The association between individual plasma proteins and MDD risk or depressive symptoms severity was investigated using multiple logistic and linear regressions including relevant covariates. Sensitivity analyses were performed excluding cognitively impaired individuals or non-acute patients with MDD. After adjusting for possible confounders and false discovery rate (FDR) correction, we found lower Fetuin-A levels in MDD patients vs. controls (pFDR = 1.95 × 10–6). This result was confirmed by the sensitivity and dichotomized analyses. Lower prolactin (PRL) levels predicted more severe depressive symptoms in acute MDD patients (pFDR = 0.024). Fetuin-A is a promising biomarker of MDD in the elderly as this protein was negatively associated with the disorder in our sample, regardless of the global cognitive functioning. Lower PRL levels may be a peripheral signature of impaired neuroprotective processes and serotoninergic neurotransmission in more severely depressed patients.

Objective Genetics factors are likely to play a role in the risk, clinical presentation and treatment outcome in major depressive disorder (MDD). In this study, we investigated the role of three candidate genes for MDD; calcium voltage- gated channel subunit alpha1 C ( CACNA1C ), cholinergic receptor nicotinic alpha 7 subunit ( CHRNA7 ), and mitogen- activated protein kinase 1 ( MAPK1 ). Methods Two-hundred forty-two MDD patients and 326 healthy controls of Korean ancestry served as samples for the analyses. Thirty-nine single nucleotide polymorphisms (SNPs) within CACNA1C , CHRNA7 , and MAPK1 genes were genotyped and subsequently tested for association with MDD (primary analysis) and other clinical features (symptoms' severity, age of onset, history of suicide attempt, treatment outcome) (secondary analyses). Single SNPs, haplotypes and epistatic analyses were performed. Results Single SNPs were not associated with disease risk and clinical features. However, a combination of alleles (haplotype) within MAPK1 was found associated with MDD-status. Secondary analyses detected a possible involvement of CACNA1C haplotype in resistance to antidepressant treatment. Conclusion These data suggest a role for MAPK1 and CACNA1C in MDD risk and treatment resistance, respectively. However, since many limitations characterize the analysis, the results must be considered with great caution and verified.