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Risk Factors for the Progression of Mild Cognitive Impairment in Different Types of Neurodegenerative Disorders.

ABSTRACT: Objective:Mild cognitive impairment (MCI) is a transitional state between normal aging and early dementia. It has a heterogeneous etiology and clinical course. This study aimed to examine the factors associated with the progression of MCI in different types of dementia disorders. Method:A retrospective, longitudinal, observational study of outpatients with MCI was conducted at a medical center in northern Taiwan. Patient medical records were reviewed, and risk factors were analyzed by multivariate analysis. Results:Among 279 patients with MCI, 163 (58.4%), 68 (24.4%), and 48 (17.2%) were diagnosed with Alzheimer's disease, vascular cognitive impairment, and Lewy body diseases, respectively. During the observation period, 37.2% of patients progressed to dementia. Older age and a higher Clinical Dementia Rating Scale-Sum of Boxes were associated with the risk of progression. Hyperlipidemia was associated with a decreased risk. Converters were more likely to receive an antidementia prescription. Conclusion:Our study suggests the importance of comprehensive clinical profiling, risk factor assessment, and detailed drug history evaluations in improving our understanding and management of dementia subtypes.

SUBMITTER: Chen PH

PROVIDER: S-EPMC6008817 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Risk Factors for the Progression of Mild Cognitive Impairment in Different Types of Neurodegenerative Disorders.

Chen Pei-Hao PH Cheng Shih-Jung SJ Lin Hui-Chi HC Lee Chuo-Yu CY Chou Chih-Ho CH

Behavioural neurology 20180605

<h4>Objective</h4>Mild cognitive impairment (MCI) is a transitional state between normal aging and early dementia. It has a heterogeneous etiology and clinical course. This study aimed to examine the factors associated with the progression of MCI in different types of dementia disorders.<h4>Method</h4>A retrospective, longitudinal, observational study of outpatients with MCI was conducted at a medical center in northern Taiwan. Patient medical records were reviewed, and risk factors were analyze ...[more]

PMID: 29971138

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Project description:BackgroundOptimization of vascular risk factor control is emerging as an alternative approach to improve cognitive outcomes in Alzheimer's disease, although its efficacy is still under debate. We aimed to investigate the contribution of vascular risk factors on Alzheimer's biomarkers and conversion rate to dementia in subjects with mild cognitive impairment (MCI) with low cerebral small vessel disease burden.MethodsTwo hundred ninety-five newly diagnosed MCI subjects were enrolled from March 2005 to May 2017 for a cross-sectional assessment of vascular risk factors and Alzheimer's plasma and imaging biomarkers, followed by a cognitive outcome assessment 24 months after enrollment. The association between vascular risk factors and Alzheimer's biomarkers were tested using multivariable linear regression models adjusted with age, gender, education, and APOE ε4 allele. The association between vascular risk factors and conversion to dementia was tested using multivariable logistic regression models adjusted with age, gender, education, and baseline Mini-Mental State Examination (MMSE) score.ResultsAt baseline, higher low-density lipoprotein (LDL) cholesterol level was associated with more advanced plasma biomarkers, including Aβ42/Aβ40 ratio (P = 0.012) and tau level (P = 0.001). A history of hypertension was associated with more advanced white matter hyperintensity (P = 0.011), while statin therapy for dyslipidemia was associated with less advanced white matter hyperintensity (P = 0.002). At 24 months, individual vascular risk factor was not significantly associated with cognitive outcome. By contrast, statin therapy for dyslipidemia was associated with reduced conversion to dementia (adjusted OR = 0.191, 95% CI = 0.062~0.586, P = 0.004).ConclusionsFor MCI subjects, dyslipidemia may contribute to AD-related neurodegeneration while hypertension may contribute to vascular pathology. The association between statin therapy for dyslipidemia and reduced conversion to dementia supports further interventional study to evaluate the potential beneficial effect of statin in MCI subjects.

Project description:IntroductionHeterogeneity in risk of conversion to Alzheimer's disease (AD) among individuals with mild cognitive impairment (MCI) is well known. Novel statistical methods that are based on partially ordered set (poset) models can be used to create models that provide detailed and accurate information about performance with specific cognitive functions. This approach allows for the study of direct links between specific cognitive functions and risk of conversion to AD from MCI. It also allows for further delineation of multi-domain amnestic MCI, in relation to specific non-amnestic cognitive deficits, and the modeling of a range of episodic memory functioning levels.MethodsFrom the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, conversion at 24 months of 268 MCI subjects was analyzed. It was found that 101 of those subjects (37.7%) converted to AD within that time frame. Poset models were then used to classify cognitive performance for MCI subjects. Respective observed conversion rates to AD were calculated for various cognitive subgroups, and by APOE e4 allele status. These rates were then compared across subgroups.ResultsThe observed conversion rate for MCI subjects with a relatively lower functioning with a high level of episodic memory at baseline was 61.2%. In MCI subjects who additionally also had relatively lower perceptual motor speed functioning and at least one APOE e4 allele, the conversion rate was 84.2%. In contrast, the observed conversion rate was 9.8% for MCI subjects with a relatively higher episodic memory functioning level and no APOE e4 allele. Relatively lower functioning with cognitive flexibility and perceptual motor speed by itself also appears to be associated with higher conversion rates.ConclusionsAmong MCI subjects, specific baseline cognitive profiles that were derived through poset modeling methods, are clearly associated with differential rates of conversion to AD. More precise delineation of MCI by such cognitive functioning profiles, including notions such as multidomain amnestic MCI, can help in gaining further insight into how heterogeneity arises in outcomes. Poset-based modeling methods may be useful for providing more precise classification of cognitive subgroups among MCI for imaging and genetics studies, and for developing more efficient and focused cognitive test batteries.

Dataset Information

Risk Factors for the Progression of Mild Cognitive Impairment in Different Types of Neurodegenerative Disorders.

Publications

Risk Factors for the Progression of Mild Cognitive Impairment in Different Types of Neurodegenerative Disorders.

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