Dataset Information

Magnitude and correlates of cognitive impairment among major depressive disorder patients in Addis Ababa: institution based cross-sectional study.

ABSTRACT:

Objective

Cognitive impairments are now widely recognized and emerging as an important therapeutic target in a patient with a major depressive disorder (MDD). It associated with a more deteriorating course of illness among MDD patients. Therefore, understanding the level of cognitive impairment and associated factors is crucial to provide optimal care for MDD patients.

Result

The proportion of cognitive impairment among MDD patients was found to be 54.4% (95%, CI (49.6, 59.3). Factors significantly associated with having cognitive impairment were age adjusted odds ratio (AOR) = 3.00, 95%, confidence interval (CI): (1.49, 6.03), educational status, (AOR = 5.36, 95% CI 2.16, 13.26), employment status (AOR = 3.63, 95 CI 1.99, 6.62), duration of the illness (AOR = 3.16, 95% CI 1.31, 7.64), having co-morbid psychiatric illnesses (AOR = 2.16, 95% CI 1.26, 3.71), and illness relapse (AOR = 2.97, 95% CI 1.54, 5.73).

SUBMITTER: Ambaw A

PROVIDER: S-EPMC6416877 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

Magnitude and correlates of cognitive impairment among major depressive disorder patients in Addis Ababa: institution based cross-sectional study.

Ambaw Abebe A Desalegn Getachew Tesfaw GT

BMC research notes 20190314 1

<h4>Objective</h4>Cognitive impairments are now widely recognized and emerging as an important therapeutic target in a patient with a major depressive disorder (MDD). It associated with a more deteriorating course of illness among MDD patients. Therefore, understanding the level of cognitive impairment and associated factors is crucial to provide optimal care for MDD patients.<h4>Result</h4>The proportion of cognitive impairment among MDD patients was found to be 54.4% (95%, CI (49.6, 59.3). Fac ...[more]

PMID: 30871643

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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:Imaging techniques are a potentially powerful method of identifying phenotypes that are associated with, or are indicative of, a vulnerability to developing major depressive disorder (MDD). Here we identify seven promising MDD-associated traits identified by magnetic resonance imaging (MRI) or positron emission tomography (PET). We evaluate whether these traits are state-independent, heritable endophenotypes, or state-dependent phenotypes that may be useful markers of treatment efficacy. In MDD, increased activity of the amygdala in response to negative stimuli appears to be a mood-congruent phenomenon, and is likely moderated by the 5-HT transporter gene (SLC6A4) promoter polymorphism (5-HTTLPR). Hippocampal volume loss is characteristic of elderly or chronically-ill samples and may be impacted by the val66met brain-derived neurotrophic factor (BDNF) gene variant and the 5-HTTLPR SLC6A4 polymorphism. White matter pathology is salient in elderly MDD cohorts but is associated with cerebrovascular disease, and is unlikely to be a useful marker of a latent MDD diathesis. Increased blood flow or metabolism of the subgenual anterior cingulate cortex (sgACC), together with gray matter volume loss in this region, is a well-replicated finding in MDD. An attenuation of the usual pattern of fronto-limbic connectivity, particularly a decreased temporal correlation in amygdala-anterior cingulate cortex (ACC) activity, is another MDD-associated trait. Concerning neuroreceptor PET imaging, decreased 5-HT(1A) binding potential in the raphe, medial temporal lobe, and medial prefrontal cortex (mPFC) has been strongly associated with MDD, and may be impacted by a functional single nucleotide polymorphism in the promoter region of the 5-HT(1A) gene (HTR1A: -1019 C/G; rs6295). Potentially indicative of inter-study variation in MDD etiology or mood state, both increased and decreased binding potential of the 5-HT transporter has been reported. Challenges facing the field include the problem of phenotypic and etiological heterogeneity, technological limitations, the confounding effects of medication, and non-disease related inter-individual variation in brain morphology and function. Further advances are likely as epigenetic, copy-number variant, gene-gene interaction, and genome-wide association (GWA) approaches are brought to bear on imaging data.

Project description:BackgroundPatients diagnosed withmajor depressive disorder (MDD) usually experience impaired cognitive functioning, which might negatively impact their clinical and functional outcomes. This study aimed to investigate the association of specific clinical factors with cognitive dysfunction in a group of MDD patients.MethodsA total of 75 subjects diagnosed with recurrent MDD were evaluated during the acute stage. Their cognitive functions were assessed using the THINC-integrated tool (THINC-it) for attention/alertness, processing speed, executive function, and working memory. Clinical psychiatric evaluations, such as the Hamilton Anxiety Scale (HAM-A), the Young Mania Rating Scale (YMRS), the Hamilton Depression Scale (HAM-D), and the Pittsburgh Sleep Quality Index(PSQI), were used to assess patients' levels of anxiety, depression and sleeping problems. The investigated clinical variables were age, years of education, age at onset, number of depressive episodes, disease duration, presence of depressive and anxiety symptoms, sleep problems, and number of hospitalizations.ResultsThe results revealed that significant differences were observed between the two groups in the THINC-it total scores, Spotter, Codebreaker, Trails, and PDQ-5-D scores (P < 0.001). The THINC-it total scores, Spotter, Codebreaker, Trails, and Symbol Check were significantly associated with age and age at onset(P < 0.01). In addition, regression analysis found that years of education was positively associated with the Codebreaker total scores (P < 0.05). the THINC-it total scores, Symbol Check, Trails, and Codebreaker were correlated with the HAM-D total scores(P < 0.05). Additionally, the THINC-it total scores, Symbol Check, PDQ-5-D and Codebreaker significantly correlated with the PSQI total scores (P < 0.05).ConclusionWe found a significant statistical association between almost all cognitive domains and different clinical aspects in depressive disorder, such asage, age at onset, severity of depression, years of education, and sleep problems. Additionally, education was shown to be a protective factor against processing speed impairments. Special considerations of these factors might help outline better management strategies to improve cognitive functions in MDD patients.

Dataset Information

Magnitude and correlates of cognitive impairment among major depressive disorder patients in Addis Ababa: institution based cross-sectional study.

Objective

Result

Publications

Magnitude and correlates of cognitive impairment among major depressive disorder patients in Addis Ababa: institution based cross-sectional study.

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