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Cognitive profiles in persons with depressive disorder and Alzheimer's disease.

ABSTRACT: Alzheimer's disease and depressive disorder are frequent in old age. Both may be associated with depressed mood and cognitive impairment. Therefore, finding a strategy to clarify the diagnosis underlying subjective complaints of impaired cognition and depressed mood in older persons is of utmost interest. We conducted a cross-sectional retrospective observational clinical cohort study using patient records from 2014 to 2018. From 3758 patients, we included patients aged 60 years and older with a Mini-Mental-Status Examination score of 24 and above. Final analysis included all patients in whom Alzheimer's disease biomarker analysis was performed (cerebrospinal fluid markers of Alzheimer's disease or positron emission tomography imaging; n = 179) and patients with depressive disorder in whom Alzheimer's disease was ruled out by analysis of biomarkers suggestive of Alzheimer's disease (n = 70). With case-control matching for age, education and gender, performance of patients with Alzheimer's disease was worse in acquisition, consolidation and recall of verbal information and false-positive answers. None of the results, however, sufficed to differentially diagnose individual patients with Alzheimer's disease or depressive disorder. With more severe symptoms of depression, patients with biomarker-verified Alzheimer's disease performed worse in executive testing but were not additionally impaired in verbal episodic memory performance. We conclude that distinguishing between Alzheimer's disease and depressive disorder is unreliable on clinical grounds and behavioural testing alone. Diagnosing the cause of subjective complaints about deteriorating cognitive function or depressed mood requires additional biomarker assessment, whereas cognitive assessment is needed to define appropriate targets of symptomatic treatment in patients with Alzheimer's disease and depressive disorder.

SUBMITTER: Lanza C

PROVIDER: S-EPMC7772098 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAlzheimer's disease (AD), type 2 diabetes mellitus (T2DM), and Major Depressive Disorder (MDD) have a higher incidence rate in modern society. Although increasing evidence supports close associations between the three, the mechanisms underlying their interrelationships remain elucidated.ObjectiveThe primary purpose is to explore the shared pathogenesis and the potential peripheral blood biomarkers for AD, MDD, and T2DM.MethodsWe downloaded the microarray data of AD, MDD, and T2DM from the Gene Expression Omnibus database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis to identify differentially expressed genes. We took the intersection of differentially expressed genes to obtain co-DEGs. Then, we performed GO and KEGG enrichment analysis on the common genes in the AD, MDD, and T2DM-related modules. Next, we utilized the STRING database to find the hub genes in the protein-protein interaction network. ROC curves were constructed for co-DEGs to obtain the most diagnostic valuable genes and to make drug predictions against the target genes. Finally, we conducted a present condition survey to verify the correlation between T2DM, MDD and AD.ResultsOur findings indicated 127 diff co-DEGs, 19 upregulated co-DEGs, and 25 down-regulated co-DEGs. Functional enrichment analysis showed co-DEGs were mainly enriched in signaling pathways such as metabolic diseases and some neurodegeneration. Protein-protein interaction network construction identified hub genes in AD, MDD and T2DM shared genes. We identified seven hub genes of co-DEGs, namely, SMC4, CDC27, HNF1A, RHOD, CUX1, PDLIM5, and TTR. The current survey results suggest a correlation between T2DM, MDD and dementia. Moreover, logistic regression analysis showed that T2DM and depression increased the risk of dementia.ConclusionOur work identified common pathogenesis of AD, T2DM, and MDD. These shared pathways might provide novel ideas for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosing and treating.

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Project description:BACKGROUND:Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders. METHODS:Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted. RESULTS:Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10- 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10- 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p = 1.5 × 10- 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different. CONCLUSIONS:Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.

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Cognitive profiles in persons with depressive disorder and Alzheimer's disease.

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