Back

From dysphoria to anhedonia: Age-related shift in the link between cognitive and affective symptoms

Harlev, D.; Vituri, A.; Shahar, M.; Wolpe, N.

2025-03-27 psychiatry and clinical psychology
10.1101/2025.03.26.25324666 medRxiv
Show abstract

BackgroundDepression in aging shows heterogeneous symptoms across cognitive, affective, and neurobiological domains. Traditional categorical diagnoses may not capture these complex patterns, prompting a shift toward dimensional or domain-based approaches. We examined whether the symptoms that bridge cognition and affect differ by age, and explored their associations with brain structure. MethodsData from 756 young ([≤]45 years) and 1230 older ([≥]65 years) adults from the Cambridge Centre for Ageing and Neuroscience were analysed. Cognition was assessed using the Addenbrookes Cognitive Examination Revised, and depressive and anxiety symptoms with the Hospital Anxiety and Depression Scale. Graphical LASSO was used to construct cognitive-affective networks, testing for age-related differences in strength and bridging centrality measures. Building on these findings, we further examined the association between bridging symptoms, cognition, and gray matter volume (GMV). ResultsSymptom strength centrality was similar across groups. However, in older but not in younger adults, depressive symptoms were more strongly connected to cognitive symptoms than anxiety symptoms. The primary bridging symptom shifted with age, from dysphoria in young adults to anhedonia in older adults. Follow-up analyses indicated that the anhedonia-to-dysphoria difference was associated with the relationship between GMV and cognition, particularly in older adults. ConclusionsCognitive-affective bridging symptoms differ with age, with anhedonia replacing dysphoria as the key bridge in older adults. This shift was linked to differences in how GMV relates to cognition in late life. These results highlight the need to target different symptoms to alleviate cognitive-affective manifestations across the lifespan.

Published in The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.