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Updated: Aug 20, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Sex-Specific Heterogeneity of Mild Cognitive Impairment Identified Based on Multi-Modal Data Analysis
Sreevani Katabathula1, Pamela B Davis2, Rong Xu1
1Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
Background:
Mild cognitive impairment (MCI), a prodromal phase of Alzheimer's disease (AD), is heterogeneous with different rates and risks of progression to AD. There are significant gender disparities in the susceptibility, prognosis, and outcomes in patients with MCI, with female being disproportionately negatively impacted.
Objective:
The aim of this study was to identify sex-specific heterogeneity of MCI using multi-modality data and examine the differences in the respective MCI subtypes with different prognostic outcomes or different risks for MCI to AD conversion.
Methods:
A total of 325 MCI subjects (146 women, 179 men) and 30 relevant features were considered. Mixed-data clustering was applied to women and men separately to discover gender-specific MCI subtypes. Gender differences were compared in the respective subtypes of MCI by examining their MCI to AD disease prognosis, descriptive statistics, and conversion rates.
Results:
We identified three MCI subtypes: poor-, good-, and best-prognosis for women and for men, separately. The subtype-wise comparison (for example, poor-prognosis subtype in women versus poor-prognosis subtype in men) showed significantly different means for brain volumetric, cognitive test-related, also for the proportion of comorbidities. Also, there were substantial gender differences in the proportions of participants who reverted to normal function, remained stable, or converted to AD.
Conclusion:
Analyzing sex-specific heterogeneity of MCI offers the opportunity to advance the understanding of the pathophysiology of both MCI and AD, allows stratification of risk in clinical trials of interventions, and suggests gender-based early intervention with targeted treatment for patients at risk of developing AD.
Insights
This study reveals distinct subtypes of mild cognitive impairment (MCI) in men and women, highlighting significant gender differences in prognosis and progression to Alzheimer's disease (AD). Understanding these sex-specific patterns is crucial for targeted interventions.
Area of Science:
- Neurology
- Gerontology
- Biostatistics
Background:
- Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease (AD) and exhibits significant heterogeneity.
- Women with MCI face disproportionately negative outcomes compared to men, indicating gender-based disparities in susceptibility and prognosis.
Purpose of the Study:
- To identify sex-specific subtypes of MCI using multi-modality data.
- To investigate gender differences in MCI subtypes concerning prognosis and conversion rates to AD.
Main Methods:
- Applied mixed-data clustering to 325 MCI subjects (146 women, 179 men) with 30 features, analyzing data separately for each gender.
- Compared gender-specific MCI subtypes based on disease prognosis, descriptive statistics, and conversion rates to AD.
Main Results:
- Identified three distinct MCI subtypes (poor-, good-, and best-prognosis) separately for women and men.
- Found significant differences between male and female MCI subtypes in brain volume, cognitive test performance, and comorbidity prevalence.
- Observed substantial gender disparities in the rates of reversion to normal function, disease stability, and conversion to AD.
Conclusions:
- Analyzing sex-specific MCI heterogeneity advances understanding of MCI and AD pathophysiology.
- Enables risk stratification in clinical trials and suggests the need for gender-based early interventions for individuals at risk of AD.
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