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Record W4391881533 · doi:10.3389/fpsyt.2024.1375509

Editorial: New insights on the relationship between neuroplasticity, genetic endophenotypes, and psychiatric disorders throughout aging and in the elderly population

2024· editorial· en· W4391881533 on OpenAlexaffabout
Felipe Kenji Sudo, Viola Oertel, Sanjeev Kumar, Gilberto Sousa Alves

Bibliographic record

VenueFrontiers in Psychiatry · 2024
Typeeditorial
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsEndophenotypeNeuroplasticityPopulationPsychologyPsychiatryPsychiatric geneticsClinical psychologyMedicineSchizophrenia (object-oriented programming)Cognition

Abstract

fetched live from OpenAlex

Beyond genetic predispositions, the notion that people’s illness profile and clinical outcomes may be driven by the degree of stress throughout their lifespan has become increasingly accepted. Allostatic load (AL), the wear and tear on organic systems due to chronic overactivity or inactivity of physiological processes in response to stress, has emerged as a popular concept to explain different phenotypes within groups with similar chronological ages(1). High AL has been linked to an array of clinical consequences consistently associated with aging, including metabolic diseases, neurodegenerative conditions, mood disorders, and mortality(2). However, the mechanisms underpinning the relationships between age-related changes and stress are still matter of debate. In this issue, authors sought to explore these shortcomings through different approaches. For instance, De Oliveira et al. investigated the impact of aging on neurophysiological reactions to acute stress, namely the startle reflex(3). In normal conditions, the startle reflex is reduced when the pulse is preceded by a weaker sensory stimulus (prepulse), characterizing the physiological phenomenon named “prepulse inhibition” (PPI). Previous evidence suggested that aging is associated with decreased startle reflex and increased startle latency(4). Moreover, a U-shaped function relationship was found between PPI and age(4). Given that other data indicated a positive correlation between PPI and cognitive performance in young adults(5), the authors hypothesized that PPI alterations could function as a biomarker of cognitive decline in normal aging. The results demonstrated a reduced PPI in healthy older subjects (n=14) in comparison with a younger group (n=14). Although no significant correlation was detected between PPI and scores in neuropsychological tasks in older participants, the study provides new insights into the aging-related brain changes affecting the sensorimotor functional integration. Other studies addressed the issue of cognitive changes in older subjects by analyzing the relationships across mood disorders, executive function deficits, and markers of neural dysfunction. Chu et al conducted a cross-sectional design in subjects with late-life depression (LLD, n=50) and Alzheimer’s disease (AD, n=50) and showed greater executive dysfunction in AD than in LLD, and greater accuracy of Trail Making Test A and B and Medial Temporal Atrophy (MTA) measurements to discriminate between these clinical groups(6). The study emphasizes the relevance of employing standard cognitive assessment tools to screen and detect dementia, which may be useful in the context of less economic resources, where advanced (CSF, blood) biomarkers are of high cost or not available(6). As for Ma et al., the topic was approached through a pilot randomized trial in a community of 28 individuals in Hong Kong investigating the impact of computerized cognitive training (CCT) on executive dysfunction of LLD subjects. The intervention included 2 sessions per week, one hour each, along 6 weeks and the experimental group reached significant improvement in global cognitive function assessed using Montreal Cognitive Assessment (MoCA). Correlations between Hamilton depression scale improvement and increase in BDNF levels were also reported. Although results are limited by its reduced sample size and small statistical power, findings may encourage upcoming investigations on the effect of CCT on mood and BDNF, possibly establishing this intervention as effective for cognition in LLD(7). Finally, stress related to medical conditions may also exert significant influence on mood states. In this perspective, Guo et al. analyzed the prevalence of depression and anxiety in adults who underwent dacryocystorhinostomy (DCR) due to nasolacrimal duct obstruction (NLDO)(8). This condition can cause epiphora, blurred vision, and dry eye, which have been related to mental health disorders. Consistently, the authors found a positive association among dry eye, anxiety, and depressive symptoms(8). The articles presented in this issue may add to our understanding on how cognitive and mood disorders through the life cycle could be prevented, diagnosed, or treated. Future studies about the role of stress and AL on age-related neural changes ought to be ignited by this evidence, providing important advances in the knowledge of the processes implicated in late life mental health disorders.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.290
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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