Dataset Information

Enhanced Molecular Aging in Late-Life Depression: the Senescent-Associated Secretory Phenotype.

ABSTRACT:

Objective

This study aims to investigate whether a systemic molecular pattern associated with aging (senescent-associated secretory phenotype [SASP]) is elevated in adults with late-life depression (LLD), compared with never-depressed elderly comparison participants.

Design

Cross-sectional study.

Participants

We included 111 older adults (80 with LLD and 31 comparison participants) in this study.

Measurement

A panel of 22 SASP-related proteins was extracted from a previous multiplex protein panel performed in these participants. We conducted a principal component analysis to create the SASP index based on individual weights of each of protein.

Results

Participants with LLD showed a significantly increased SASP index compared with comparison participants, after controlling for age, depressive symptoms, medical comorbidity (CIRS-G) scores, sex, and cognitive performance (F_(1,98) = 7.3, p = 0.008). Correlation analyses revealed that the SASP index was positively correlated with age (r = 0.2, p = 0.03) and CIRS score (r = 0.27, p = 0.005), and negatively correlated with information processing speed (r = -0.34, p = 0.001), executive function (r = -0.27, p = 0.004) and global cognitive performance (r = -0.28, p = 0.007).

Conclusions

To the best of our knowledge, this is the first study to show that a set of proteins (i.e., SASP index) primarily associated with cellular aging is abnormally regulated and elevated in LLD. These results suggest that individuals with LLD display enhanced aging-related molecular patterns that are associated with higher medical comorbidity and worse cognitive function. Finally, we provide a set of proteins that can serve as potential therapeutic targets and biomarkers to monitor the effects of therapeutic or preventative interventions in LLD.

SUBMITTER: Diniz BS

PROVIDER: S-EPMC5164865 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Enhanced Molecular Aging in Late-Life Depression: the Senescent-Associated Secretory Phenotype.

Diniz Breno Satler BS Reynolds Charles F CF Sibille Etienne E Lin Chien-Wei CW Tseng George G Lotrich Francis F Aizenstein Howard J HJ Butters Meryl A MA

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry 20160831 1

<h4>Objective</h4>This study aims to investigate whether a systemic molecular pattern associated with aging (senescent-associated secretory phenotype [SASP]) is elevated in adults with late-life depression (LLD), compared with never-depressed elderly comparison participants.<h4>Design</h4>Cross-sectional study.<h4>Participants</h4>We included 111 older adults (80 with LLD and 31 comparison participants) in this study.<h4>Measurement</h4>A panel of 22 SASP-related proteins was extracted from a pr ...[more]

PMID: 27856124

Similar Datasets

Project description:Late-life depression (LLD), compared to depression at a young age, is more likely to have poor prognosis and high risk of progression to dementia. A recent systemic review and meta-analysis of the present antidepressants for LLD showed that the treatment response rate was 48% and the remission rate was only 33.7%, thus implying the need to improve the treatment with other approaches in the future. Recently, agents modulating the glutamatergic system have been tested for mental disorders such as schizophrenia, dementia, and depressive disorder. Ketamine, a noncompetitive NMDA receptor (NMDAR) antagonist, requires more evidence from randomized clinical trials (RCTs) to prove its efficacy and safety in treating LLD. The metabotropic receptors (mGluRs) of the glutamatergic system are family G-protein-coupled receptors, and inhibition of the Group II mGluRs subtypes (mGlu2 and mGlu3) was found to be as effective as ketamine in exerting rapid antidepressant activity in some animal studies. Inflammation has been thought to contribute to depression for a long time. The cytokine levels not only increase with age but also decrease serotonin. Regarding LLD, interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α) released in vivo are likely to contribute to the reduced serotonin level. Brain-derived neurotrophic factor (BDNF), a growth factor and a modulator in the tropomyosin receptor kinase (Trk) family of tyrosine kinase receptors, probably declines quantitatively with age. Recent studies suggest that BDNF/TrkB decrement may contribute to learning deficits and memory impairment. In the process of aging, physiological changes in combination with geriatric diseases such as vascular diseases result in poorer prognosis of LLD in comparison with that of young-age depression. Treatments with present antidepressants have been generally unsatisfactory. Novel treatments such as anti-inflammatory agents or NMDAR agonists/antagonists require more studies in LLD. Last but not least, LLD and dementia, which share common pathways and interrelate reciprocally, are a great concern. If it is possible to enhance the treatment of LDD, dementia can be prevented or delated.

Project description:BackgroundThere is limited research examining the impact of risk and protective factors on late-life depression using large population-based datasets, particularly those examining differences among older migrants and non-migrants in Europe countries. Thus, the first aim was to analyze differences between migrants and non-migrants regarding socioeconomic status, depression, multimorbidity, healthy aging, and lifestyle behaviors. The second aim was to examine the impact of healthy aging on late-life depression in older migrants compared to their counterparts without a history of international migration in extensive and harmonized data from different population-based cohort studies.Materials and methodsWe analyzed cross-sectional, predominantly nationally representative, community-based data from European participants in the Aging Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) cohort. The descriptive analyses included sociodemographic variables, somatic comorbidities, multimorbidity, healthy aging, and lifestyle behaviors according to migration status. The effects of these variables on late-life depression were examined in a multivariate logistic regression model, including migration status and years since migration as predictors.ResultsData of 122,571 individuals aged ≥ 50 years were analyzed, of which 11,799 (9.60%) were migrants. The descriptive analyses indicated that compared to non-migrants, migrants showed a higher prevalence of diabetes (25.6%), hypertension (38.0%), coronary artery disease (49.4%), stroke (4.9%), and depression (31.1%). Healthy aging was also better in non-migrants (51.7; SD = 9.7) than in migrants (39.6; SD = 18.2). The results of the logistic regression showed that migration status [OR = 1.231 (CIs: 0.914-1.547)] and increased number of years since migration in the host country [OR = 0.003 (CIs: 0.001-0.005)] were associated with greater levels of depressive symptoms. Concerning health variables, multimorbidity was associated with higher levels of depressive symptoms [OR = 0.244 (CIs: 0.211-0.278)], whereas better healthy aging was associated with fewer depressive symptoms [OR = -0.100 (CIs: -0.102 to -0.098)]. The interaction between migration and healthy aging status was also significant [OR. = -0.019 (CIs: -0.025 to -0.014)].ConclusionMigrants reported higher risks for worse health outcomes compared to non-migrants. Significantly, worse healthy aging was associated with a greater risk of depressive symptoms in migrants than in non-migrants. Shedding light on migration and aging processes is essential for promoting a cross-cultural understanding of late-life depression in Europe.

Dataset Information

Enhanced Molecular Aging in Late-Life Depression: the Senescent-Associated Secretory Phenotype.

Objective

Design

Participants

Measurement

Results

Conclusions

Publications

Enhanced Molecular Aging in Late-Life Depression: the Senescent-Associated Secretory Phenotype.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets