We determined whether apolipoprotein E epsilon4 (ApoE4) or catechol-O-methyltransferase (COMT) genotypes were associated with dementia, hallucinations, Alzheimer's disease pathological findings (AP), or cortical Lewy bodies (CLBs) in autopsy-confirmed cases of Parkinson's disease (PD). Outcomes were obtained from medical records. Pathology reports identified AP and CLBs. Brain tissue was genotyped. A total of 47 subjects (33 men, 14 women) had PD onset at 62.4 +/- 8.7 years of age and died at 77.8 +/- 5.6 years of age. Demented and hallucinating patients did not differ in age at onset (AO) of PD or age at death, or the proportion ApoE4+, AP+, or CLB+ compared to nondemented patients or non-hallucinating patients. ApoE4 and COMT (low metabolizer [LH], intermediate metabolizer [HL], or high metabolizer [HH]) did not influence AO, death, or dementia- or hallucination-free survival, based on age or duration of treatment. All seven subjects with AP were demented and had hallucinations. CLBs were associated with dementia but not hallucinations. In Cox regression models adjusting for AO and duration of treatment, increased risk of dementia was associated with male sex but not significantly with ApoE4; inclusion of AP in the model did not affect the results; COMT was not a risk factor for dementia. Psychosis risk was not associated with ApoE4, COMT, or sex. The observation that males have increased dementia risk and the trend for ApoE4 requires confirmation in larger prospective autopsy studies.
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http://dx.doi.org/10.1002/mds.20481 | DOI Listing |
Genes (Basel)
December 2024
Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Background/objectives: Artificial intelligence and large language models like ChatGPT and Google's Gemini are promising tools with remarkable potential to assist healthcare professionals. This study explores ChatGPT and Gemini's potential utility in assisting clinicians during the first evaluation of patients with suspected neurogenetic disorders.
Methods: By analyzing the model's performance in identifying relevant clinical features, suggesting differential diagnoses, and providing insights into possible genetic testing, this research seeks to determine whether these AI tools could serve as a valuable adjunct in neurogenetic assessments.
J Psychiatr Pract
January 2025
Department of Psychiatry, Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
Charles Bonnet syndrome (CBS) is a clinical condition in which patients with visual impairment experience visual hallucinations (VH) in the presence of clear consciousness. It typically occurs in elderly people and confuses clinicians with multiple differential diagnoses due to VH, which can be present in a variety of clinical conditions ranging from psychosis to neurocognitive disorders (eg, neurocognitive disorder with Lewy bodies). In the latter, the concomitant presence of cognitive decline and parkinsonism aids the diagnosis.
View Article and Find Full Text PDFWorld J Psychiatry
January 2025
Division of Geriatric Psychiatry, Department of Psychiatry, Changhua Christian Hospital, Changhua 500, Taiwan.
This letter provides a concise review of the pertinent literature on visual and tactile hallucinations in elderly patients. The discussion addresses differential diagnoses and potential underlying mechanisms, as well as the psychopathology associated with tactile hallucinations, and emphasizes the necessity for investigation into the possibility of coexisting delusional infestation (parasitosis). These symptoms frequently manifest in patients with primary psychotic disorders, organic mental disorders, and substance use disorders.
View Article and Find Full Text PDFPsychiatry Clin Neurosci
January 2025
Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan.
Aim: Despite the clinical importance and significant social burden of neuropsychiatric symptoms (NPS) in dementia, the underlying neurobiological mechanism remains poorly understood. Recently, neuroimaging-derived brain-age estimation by machine-learning analysis has shown promise as an individual-level biomarker. We investigated the relationship between NPS and brain-age in amnestic mild cognitive impairment (MCI) and early dementia.
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