Poster M7 - Assessing Progression Patterns of Alzheimer’s Disease: The Impact of Age, Sex, and Volumetric Changes in Brain Regions

Introduction: Alzheimer’s disease (AD) is a neurodegenerative condition marked by a gradual decline in cognitive abilities and memory, posing significant challenges to affected individuals, their families, and society. The pathophysiological process of AD begins years before its clinical symptoms appear. In research and clinical settings, the MCI (mild cognitive impairment) is considered as the risk state that may progress to AD. MCI is divided into two stages: early MCI (EMCI) and late MCI (LMCI). Despite extensive research dedicated to understanding AD, its diverse progression patterns present a significant challenge for developing effective diagnostic and therapeutic strategies. The impact of age on AD progression is widely acknowledged, with increasing age serving as the primary risk factor for the disease's development. Recent findings suggest that gender-specific factors may play a role in the onset and progression of AD, highlighting the importance of considering gender as a significant variable in understanding disease mechanisms. Furthermore, recent advancements in neuroimaging techniques have enabled the identification of structural changes in specific brain regions associated with AD pathology. Investigating the volumetric alterations in these regions may offer valuable insights into the underlying neurobiology of the disease and its progression over time. Therefore, this study aimed to examine how age, sex, and volumetric changes in brain regions influence the progression of Alzheimer's disease aiding in distinguishing between early and later stages of clinical symptoms, facilitating earlier detection of Alzheimer's disease progression.

Materials and

Methods: We acquired T1-weighted structural MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, comprising 1,000 participants divided evenly across five categories, each containing 200 subjects (100 female and 100 male) aged from 50 to 90 years. We subsequently conducted several preprocessing steps on the data, including brain extraction, bias field correction, image registration, and brain parcellation. We used the Automated Anatomical Labeling-3 (AAL-3) brain atlas for brain region mapping and volume measurements of brain areas such as hippocampus, amygdala, ventral posterolateral, and lateral pulvinar. We standardized the volumetric data by normalizing it with respect to the total brain volume. Additionally, we identified and removed 40 outliers to ensure the reliability of the data. We conducted statistical analyses (analysis of covariance (ANCOVA)) to identify significant differences in volumetric changes between male and female participants, considering age, and categories as key variables. The Bonferroni post hoc test was used to adjust for multiple comparisons and minimize Type I errors by adjusting the significance threshold, ensuring more reliable results. We also conducted the analysis of variance (ANOVA) to determine the relationship between the categories and volumetric changes and also considered the post hoc test (multi compare test).

Results, Conclusions, and Discussions:

Results: The ANCOVA analysis found significant findings in both the CSF segment of the hippocampus (p < 0.039) and the amygdala's white matter (p < 0.013), considering age, sex, and categories based on volumetric changes. Significance levels were notable for sex ( < 0.037) and categories ( < 0.013) based on these changes. Females consistently exhibited higher significance, notably in the hippocampus, where significant differences were found across multiple categories: CN, AD (p < 0.001), MCI, AD (p < 0.001), and LMCI, AD (p < 0.007). For males, significance primarily lay in the MCI, AD category (p < 0.021). In the amygdala, females demonstrated notable significance in the EMCI, LMCI category (p = 0.020) and the AD, EMCI category (p < 0.001), while for males, it was in the MCI, LMCI category (p = 0.003). The pulvinar lateral region exhibited significance concerning both sex and age (p = 0.048). In the ventral posterolateral and pulvinar lateral regions, significance below 8.33e-16 (in Gray matter) and 2.45e-07 (in CSF) respectively was observed, differentiating the MCI and AD category from others, as per the ANOVA. The Gray matter exhibited prominent significance in categorizing for ventral posterolateral and pulvinar lateral regions, while the white matter showed significance in the hippocampus and amygdala. The hippocampus was most significant in categorizing AD, whereas the amygdala was significant in differentiating EMCI.

Discussion: This study assessed the significance of age, sex and categories of AD based on the volumetric brain regions extracted from parcellated AAL-3 brain atlas data. The hypothesis showed that the white matter of amygdala region and CSF of hippocampus region could be a novel biomarker in identifying the stages of AD. Also, it was evident from the results that progression pattern indicated volumetric changes (reduction) was higher in female than male with the progression of age.

Conclusion: The hypothesis-based study offers an effective means of assessing the significance of age, sex, and cognitive categories in relation to AD based on volumetric changes within four brain regions. By utilizing this statistical approach, clinicians can acquire valuable insights to guide targeted therapeutic interventions for individuals at risk.

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