Cluster-based Cognitive Profiles and Their Relationship with Neurofilament Light Chain in Patients with Severe Mental Disorders of the Elderly
Abstract
Objective: Old adult patients with severe mental disorders (SMD) face remarkable cognitive decline, yet differentiating psychiatric progression from neurodegenerative onset remains challenging. In this study, we intended to evaluate cognitive deficits in old adult patients with SMD and their association with neurofilament light chain (NfL), a marker of axonal injury. Methods: We recruited 45-year-old adult patient participants: 15 with schizophrenia, 15 with bipolar disorder (BD), and 15 Mini–Mental State Examination (MMSE)-matched patients with mild or major neurocognitive disorders. We collected their demographic data, clinical variables, MMSE scores, depression scales, and blood NfL levels. We compared cognitive profiles across diagnostic groups and used cluster analysis to identify cognitive subgroups, exploring correlations between NfL levels and specific cognitive domains. Results: No significant associations between NfL levels and cognition were found within traditional diagnostic categories. But cluster analysis identified a distinct subgroup (Cluster A) comprising schizophrenia and BD patients with cognitive deficits resembling neurocognitive disorders. Cluster A exhibited significantly lower scores in orientation, attention/calculation, and memory. In this subgroup, NfL levels were significantly and negatively correlated with orientation (r = −0.452, p < 0.05), attention/calculation (r = −0.435, p < 0.05), memory (r = −0.352, p < 0.05), and comprehension (r = −0.486, p < 0.01). Conclusion: A subset of old adult patients with SMD shares a cognitive profile with neurocognitive disorders, where NfL levels are correlated with impairment severity. These findings underscore the heterogeneity of aging in old adult patients with SMD and suggest that biomarker-informed, cluster-based approaches may help the identification and personalized intervention for those at higher neurodegenerative risk.
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BibTeX
@article{chutingyang2026clusterbased,
title = {{Cluster-based Cognitive Profiles and Their Relationship with Neurofilament Light Chain in Patients with Severe Mental Disorders of the Elderly}},
author = {Chu Ting Yang, M.D. and Cho-Yin Huang, M.D. and Chih Chiang Chiu, M.D., Ph.D. and Ming-Chyi Huang, M.D., Ph.D. and Chian-Jue Kuo, M.D., Ph.D. and Po-Yu Chen, M.D., Ph.D. and Wen-Yin Chen, M.D., Ph.D.},
journal = {Taiwanese Journal of Psychiatry},
year = {2026},
month = jul,
doi = {10.4103/tpsy.tpsy_29_26},
url = {https://doi.org/10.4103/tpsy.tpsy_29_26},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Cluster-based Cognitive Profiles and Their Relationship with Neurofilament Light Chain in Patients with Severe Mental Disorders of the Elderly
AU - Chu Ting Yang, M.D.
AU - Cho-Yin Huang, M.D.
AU - Chih Chiang Chiu, M.D., Ph.D.
AU - Ming-Chyi Huang, M.D., Ph.D.
AU - Chian-Jue Kuo, M.D., Ph.D.
AU - Po-Yu Chen, M.D., Ph.D.
AU - Wen-Yin Chen, M.D., Ph.D.
PY - 2026
DA - 2026/07/01
JO - Taiwanese Journal of Psychiatry
DO - 10.4103/tpsy.tpsy_29_26
UR - https://doi.org/10.4103/tpsy.tpsy_29_26
AB - Objective: Old adult patients with severe mental disorders (SMD) face remarkable cognitive decline, yet differentiating psychiatric progression from neurodegenerative onset remains challenging. In this study, we intended to evaluate cognitive deficits in old adult patients with SMD and their association with neurofilament light chain (NfL), a marker of axonal injury. Methods: We recruited 45-year-old adult patient participants: 15 with schizophrenia, 15 with bipolar disorder (BD), and 15 Mini–Mental State Examination (MMSE)-matched patients with mild or major neurocognitive disorders. We collected their demographic data, clinical variables, MMSE scores, depression scales, and blood NfL levels. We compared cognitive profiles across diagnostic groups and used cluster analysis to identify cognitive subgroups, exploring correlations between NfL levels and specific cognitive domains. Results: No significant associations between NfL levels and cognition were found within traditional diagnostic categories. But cluster analysis identified a distinct subgroup (Cluster A) comprising schizophrenia and BD patients with cognitive deficits resembling neurocognitive disorders. Cluster A exhibited significantly lower scores in orientation, attention/calculation, and memory. In this subgroup, NfL levels were significantly and negatively correlated with orientation (r = −0.452, p < 0.05), attention/calculation (r = −0.435, p < 0.05), memory (r = −0.352, p < 0.05), and comprehension (r = −0.486, p < 0.01). Conclusion: A subset of old adult patients with SMD shares a cognitive profile with neurocognitive disorders, where NfL levels are correlated with impairment severity. These findings underscore the heterogeneity of aging in old adult patients with SMD and suggest that biomarker-informed, cluster-based approaches may help the identification and personalized intervention for those at higher neurodegenerative risk.
SN - 1028-3684
SN - 2666-2078
ER -