At follow-up, 8 out of 41 patients (19.5%) with MCI had progressed to dementia, 8 patients (19.5%) had improved to normal levels of cognitive functioning, 25 patients (61%) had remained stable within the MCI group.
Nine adults with DS and dementia plus four who are exhibiting declines in cognition analogous to mild cognitive impairment in the general population (MCI-DS) were compared to their pair-matched peers with DS but without dementia or MCI-DS.
Pre-MCI subjects showed accelerated rates of progression to MCI as compared to NCI subjects, but slower rates of progression to dementia than MCI subjects.
Among 200 outpatients with dementia and MCI whose NGF SNP rs6330 genotype was identified, those with A-MCI (n = 35) and early-stage AD (n = 67) were recruited and divided into three groups according to genotype (C/C: n = 58, C/T: n = 39, T/T: n = 5).
Among 200 outpatients with dementia and MCI, 146 outpatients with mild AD or A-MCI were recruited and divided into two genotypic groups, valine homozygosity (Val/Val) and methionine (Met) carriers, based on the representative BDNF functional polymorphism Val66Met.
Among 215 outpatients with dementia and MCI, 155 with mild AD (n = 108) or A-MCI (n = 47) were recruited and divided into three genotypic groups based on the representative NT-3 functional polymorphisms rs6332 and rs6489630.
CSF Apo-E levels were associated with longitudinal cognitive decline, MCI conversion to dementia, and gray matter atrophy rate in total tau/Aβ1-42 ratio and APOE genotype-adjusted analyses.
Although PD-MCI is a risk factor for developing Parkinson's disease dementia there is evidence to suggest that PD-MCI might consist of distinct subtypes with different pathophysiologies and prognoses.
Further comparisons with our previous cross-sectional findings indicated that telomere lengths prior to clinical decline were similar to those of other adults with Down syndrome (DS) who have not experienced clinical decline while telomere lengths following transition to MCI-DS or dementia in the current study were comparable to those of other adults with DS who have developed MCI-DS or dementia.
Relationships between normalized EEG measures and time to clinical progression (conversion from SCD to MCI/dementia or from MCI to dementia) were analyzed using Cox proportional hazard models.
FADD forms were quantified by western blot analysis in dorsolateral prefrontal cortex (DLPFC) samples from a large cohort of participants in a community-based aging study (Memory and Aging Project, MAP), experiencing no-(NCI, n = 51) or mild-(MCI, n = 42) cognitive impairment, or dementia (n = 57).
Higher stride time variability was associated with falls in older adults without dementia (CHI and each MCI subgroup) and mild non-AD dementia, whereas lower gait speed was associated with falls in all participant groups, except in mild AD dementia.
150 individuals with ET (109 Normal Cognition (ET-NC group), and 30 with MCI and 11 dementia (ET-CI group)) completed self-ratings and objective assessments of memory, language, and executive functioning.
Determination of YKL-40 CSF concentration may be also helpful in differentiation between types of dementia and in the distinction of patients in the stable phase of MCI from those who progressed to dementia.
According to cognitive function, the patients were divided into a group of normal cognitive function, a mild cognitive impairment group (MCI group) and a dementia group.
Cognitive function was assessed using two computer-based questionnaires (touch panel-type dementia assessment scale [TDAS] and mild cognitive impairment [MCI] screen).
In study 1, REST levels were compared across the following four well-characterized groups: healthy elderly (n=65), mild cognitive impairment who remained stable (stable MCI, n=36), MCI who later converted to dementia (converter MCI, n=29) and AD (n=65) from the AddNeuroMed cohort.
In the absence of a specific phenotype, the diagnosis of MCI might identify PSP patients at greatest risk of developing dementia and should be considered further in the diagnostic assessment.
The presented approach is a valuable tool for identifying patients with dementia or MCI and for supporting the clinician in the diagnostic process, by providing an outstanding support decision tool in the diagnostics of neurodegenerative diseases.