650 research outputs found
The Methylenetetrahydrofolate Reductase C677T Polymorphism and Risk for Late-Onset Alzheimer's disease: Further Evidence in an Italian Multicenter Study
No full textBackground: A functional polymorphism in the methylenetetrahydrofolate reductase (MTHFR) gene, namely C677T (rs1801133), results in increased Hcy levels and has been associated with risk of late-onset Alzheimer's disease (LOAD). Many investigators reported association between rs1801133 and LOAD risk in Asian populations and in carriers of the apolipoprotein E (APOE) ε4 allele, but recent meta-analyses suggest a contribution also in other populations, including Caucasians and/or northern Africans. Objective: To further address this issue, we performed a relatively large case-control study, including 581 LOAD patients and 468 matched controls of Italian origin. APOE data were available for a subgroup of almost 600 subjects. Methods: Genotyping for rs1801133 was performed with PCR-RFLP techniques. Results: In the total population, the MTHFR 677T allele (OR=1.20; 95 CI=1.01-1.43) and carriers of the MTHFR 677T allele (CTTT versus CC: OR=1.34; 95 CI=1.03-1.73) resulted in increased LOAD risk. Similarly, in APOE ε4 carriers, we observed an increased frequency of MTHFR 677CT carriers (CT versus CC: OR=2.82; 95 CI=1.25-6.32). Very interestingly, also in non-APOE ε4 carriers, both MTHFR 677T allele (OR=1.38; 95 CI=1.03-1.85) and MTHFR 677TT genotype (OR=2.08; 95 CI=1.11-3.90) were associated with LOAD. All these associations survived after corrections for age, gender, and multiple testing. Conclusions: The present results suggest that the MTHFR C677T polymorphism is likely a LOAD risk factor in our cohort, either in APOE ε4 or in non-APOE ε4 carriers
The implication of BDNF Val66Met polymorphism in progression from subjective cognitive decline to mild cognitive impairment and Alzheimer's disease: a 9-year follow-up study
No full textBrain-derived natriuretic factor (BDNF) Val66Met polymorphism has been frequently reported to be associated with Alzheimer's disease (AD) with contrasting results. Numerous studies showed that Met allele increased the risk of AD only in women, while other studies have found worse cognitive performance in Val/Val carriers. We aimed to inquire the effects of Val66Met polymorphism on the progression from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and from MCI to AD and to ascertain if this effect is modulated by demographic and cognitive variables. For this purpose, we followed up 74 subjects (48 SCD, 26 MCI) for a mean time of 9 years. All participants underwent extensive neuropsychological assessment, cognitive reserve estimation, BDNF and apolipoprotein E (ApoE) genotype analysis at baseline. Personality traits and leisure activities were assessed in a subgroup. Each patient underwent clinical-neuropsychological follow-up, during which 18 out of 48 SCD subjects progressed to MCI and 14 out of 26 MCI subjects progressed to AD. We found that Val66Met increased the risk of progression from SCD to MCI and from MCI to AD only in women. Nevertheless, Val/Val carriers who progressed from SCD to MCI had a shorter conversion time compared to Met carriers. We concluded that Val66Met polymorphism might play different roles depending on sex and stage of the disease
Common Variants in PLD3 and Correlation to Amyloid-Related Phenotypes in Alzheimer’s Disease
No full textThe phospholipase D3 (PLD3) gene has shown association with Alzheimer's disease (AD). However, the role of PLD3 common variants in amyloid-β (Aβ) pathology remains unclear. We examined the association of thirteen common single nucleotide polymorphisms (SNPs) with cerebrospinal fluid (CSF) Aβ(1- 42) levels and florbetapir retention on florbetapir 18F amyloid positron emission tomography (AV45-PET) in a large population. We found that one SNP (rs11667768) was significantly associated with CSF Aβ(1- 42) levels in the normal cognition group. We did not observe an association of any SNP with florbetapir retention. Our study predicted the potential role of PLD3 variants in Aβ pathology
Genomic Copy Number Analysis in Alzheimer's Disease and Mild Cognitive Impairment: An ADNI Study
No full textCopy number variants (CNVs) are DNA sequence alterations, resulting in gains (duplications) and losses (deletions) of genomic segments. They often overlap genes and may play important roles in disease. Only one published study has examined CNVs in late-onset Alzheimer's disease (AD), and none have examined mild cognitive impairment (MCI). CNV calls were generated in 288 AD, 183 MCI, and 184 healthy control (HC) non-Hispanic Caucasian Alzheimer's Disease Neuroimaging Initiative participants. After quality control, 222 AD, 136 MCI, and 143 HC participants were entered into case/control association analyses, including candidate gene and whole genome approaches. Although no excess CNV burden was observed in cases (AD and/or MCI) relative to controls (HC), gene-based analyses revealed CNVs overlapping the candidate geneCHRFAM7A, as well asCSMD1,SLC35F2,HNRNPCL1,NRXN1,andERBB4regions, only in cases. Replication in larger samples is important, after which regions detected here may be promising targets for resequencing.</jats:p
Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting
No full textBackground: Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder worldwide. People suffering from PD exhibit motor symptoms that affect the control of upper and lower limb movement. Among daily activities that depend on proper upper limb control is the handwriting process, which has been studied in state-of-the-art research, mainly considering non-semantic drawings like spirals, geometric figures, cursive lines, and others. Objectives: This paper analyzes the suitability of modeling the handwriting process of digits from 0 to 9 to automatically discriminate between PD patients and healthy control subjects. The main hypothesis is that modeling these numbers allows a more natural evaluation of upper limb control. Methods: Two approaches are considered: modeling of the images resulting from the strokes collected by the digital tablet and modeling of the time series yielded by the digital tablet while performing the strokes, i.e., time-dependent signals. The first approach is implemented by fine-tuning a CNN-based architecture, while the second approach is based on hand-crafted features measured upon the time series, namely pressure and kinematic measurements. Features extracted from time-dependent signals are represented following two strategies, one based on statistical functionals and the other one based on creating Gaussian Mixture Models (GMMs). Results: The experiments indicate that pressure-based features modeled with functionals are the ones that yield the highest accuracy, indicating that PD-related symptoms are better modeled with dynamic approaches than those based on images. Conclusions: The dynamic approach outperformed the image-based model, indicating that the writing process, modeled with signals collected over time, reveals motor symptoms more clearly than images resulting from handwriting. This finding is in line with previous results in the state-of-the-art research and constitutes a step forward to create more accurate and informative methods to detect and monitor PD symptoms.This work has been funded by the School of Engineering at UdeA and Pratech Group S.A.S. grants # IAPFI23-1-01 and # PI2023-58010. Adolfo M. García is an Atlantic Fellow at the Global Brain Health Institute (GBHI) and is partially supported by the National Institute On Aging of the National Institutes of Health (R01AG075775, 2P01AG019724); ANID (FONDECYT Regular 1210176, 1210195); DICYT-USACH (032351G-DAS); Agencia Nacional de Promoción Científica y Tecnológica (01-PICTE-2022-05-00103); Agencia Nacional de Investigación e Innovación (EI-X-2023-1-176993); and the Multi-partner Consortium to Expand Dementia Research in Latin America (ReDLat), which is supported by the Fogarty International Center and the National Institutes of Health, the National Institute on Aging (R01AG057234, R01AG075775, R01AG21051, and CARDS-NIH), Alzheimer’s Association (SG-20- 725707), Rainwater Charitable Foundation’s Tau Consortium, the Bluefield Project to Cure Frontotemporal Dementia, and the Global Brain Health Institute.School of Engineering at UdeA and Pratech Group S.A.S.National Institute On Aging of the National Institutes of HealthANIDDICYT-USACHAgencia Nacional de Promoción Científica y TecnológicaAgencia Nacional de Investigación e InnovaciónMulti-partner Consortium to Expand Dementia Research in Latin America (ReDLat)Fogarty International Center and the National Institutes of HealthNational Institute on AgingAlzheimer’s AssociationRainwater Charitable Foundation’s Tau ConsortiumBluefield Project to Cure Frontotemporal DementiaGlobal Brain Health Institut
Effect of BDNF Val66Met polymorphism on hippocampal subfields in multiple sclerosis patients
No full textBrain-derived neurotrophic factor (BDNF) Val66Met polymorphism was shown to strongly affect BDNF function, but its role in modulating gray matter damage in multiple sclerosis (MS) patients is still not clear. Given BDNF relevance on the hippocampus, we aimed to explore BDNF Val66Met polymorphism effect on hippocampal subfield volumes and its role in cognitive functioning in MS patients. Using a 3T scanner, we obtained dual-echo and 3DT1-weighted sequences from 50 MS patients and 15 healthy controls (HC) consecutively enrolled. MS patients also underwent genotype analysis of BDNF, neurological and neuropsychological evaluation. Hippocampal subfields were segmented by using Freesurfer. The BDNF Val66Met polymorphism was found in 22 MS patients (44%). Compared to HC, MS patients had lower volume in: bilateral hippocampus-amygdala transition area (HATA); cornus ammonis (CA)1, granule cell layer of dentate gyrus (GCL-DG), CA4 and CA3 of the left hippocampal head; molecular layer (ML) of the left hippocampal body; presubiculum of right hippocampal body and right fimbria. Compared to BDNF Val66Val, Val66Met MS patients had higher volume in bilateral hippocampal tail; CA1, ML, CA3, CA4, and GCL-DG of left hippocampal head; CA1, ML, and CA3 of the left hippocampal body; left HATA and presubiculum of the right hippocampal head. In MS patients, higher lesion burden was associated with lower volume of presubiculum of right hippocampal body; lower volume of left hippocampal tail was associated with worse visuospatial memory performance; lower volume of left hippocampal head with worse performance in semantic fluency. Our findings suggest the BNDF Val66Met polymorphism may have a protective role in MS patients against both hippocampal atrophy and cognitive impairment. BDNF genotype might be a potential biomarker for predicting cognitive prognosis, and an interesting target to study for neuroprotective strategies. © 2021, The Author(s), under exclusive licence to Springer Nature Limited
Neurofilaments as Decay Rate Biomarker in Spinocerebellar Ataxia Type 1: Highlighting Key Questions of Application and Future Challenges
No full textAssociation of Rare APOE Missense Variants V236E and R251G With Risk of Alzheimer Disease
No full text- …
