Background: Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by the abnormal expansion of CAG triplet repeat. We aimed to reappraise HD epidemiology in a northern Italian population, in relation to introduction of genetic testing.
Methods: Through ICD-9M code 333.4 and medical fare exemption code RF0080, HD cases were identified from administrative health data and medical records from the Units of Neurology and Genetics, Ferrara University Hospital, and from other provincial neurological structures.
Results: HD mean annual incidence rate in 1990-2009 was 0.3 per 100,000 (95% CI 0.2-0.5). All incident cases were found to have symptoms of the disease's classic form, and neither juvenile nor the rigid Westphal variant was detected. The mean (SD) age at onset was 50.2 (12.7 years; range 32-82 years), 54.9 (14.6) for men and 45.8 (9.4) for women. On prevalence day, December 31, 2014, HD prevalence was 4.2 per 100,000 (95% CI 2.4-7.0), with a male:female ratio of 1:2.
Conclusions: The prevalence and incidence of HD in our population were lower than the prevalence and incidence reported for other European and Italian populations, but higher compared to those of Asia, Africa, and Eastern Europe. Compared to previous studies, HD incidence and prevalence did not change significantly.
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http://dx.doi.org/10.1159/000479697 | DOI Listing |
Molecules
January 2025
Chair and Department of Biochemistry and Pharmacogenomics, Medical University of Warsaw, 1 Banacha Str., 02-097 Warsaw, Poland.
Vitamin B (thiamine) plays an important role in human metabolism. It is essential for the proper growth and development of the body and has a positive effect on the functioning of the digestive, cardiovascular, and nervous systems. Additionally, it stimulates the brain and improves the psycho-emotional state.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Chair and Department of General Biology and Parasitology, Medical University of Warsaw, Chałubińskiego 5, 02-004 Warsaw, Poland.
Diabetes mellitus (DM) and neurodegenerative diseases/disturbances are worldwide health problems. The most common chronic conditions diagnosed in persons 60 years and older are type 2 diabetes mellitus (T2DM) and cognitive impairment. It was found that diabetes mellitus is a major risk for cognitive decline, dementia, Parkinson's disease (PD), Alzheimer's disease (AD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS) and other neurodegenerative disorders.
View Article and Find Full Text PDFGenes (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.
Antioxidants (Basel)
January 2025
Laboratory of Molecular, Cellular and Genomic Biomedicine, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain.
Lipid metabolism plays a critical role in maintaining cellular integrity, especially within the nervous system, where lipids support neuronal structure, function, and synaptic plasticity. However, this essential metabolic pathway is highly susceptible to oxidative stress, which can lead to lipid peroxidation, a damaging process induced by reactive oxygen species. Lipid peroxidation generates by-products that disrupt many cellular functions, with a strong impact on proteostasis.
View Article and Find Full Text PDFSci Rep
January 2025
Cognition and Brain Plasticity Unit, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain.
One of the principal goals of Precision Medicine is to stratify patients by accounting for individual variability. However, extracting meaningful information from Real-World Data, such as Electronic Health Records, still remains challenging due to methodological and computational issues. A Dynamic Time Warping-based unsupervised-clustering methodology is presented in this paper for the clustering of patient trajectories of multi-modal health data on the basis of shared temporal characteristics.
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