Longitudinal Changes in Temporal Variability in AD and MCI: Implications for Targeted Interventions
Poster No:
195
Submission Type:
Abstract Submission
Authors:
Yue Gu1, Tatia Lee2
Institutions:
1The University of Hong Kong, Hong Kong, N/A, 2University of Hong Kong, Hong Kong, Hong Kong SAR
First Author:
Co-Author:
Introduction:
Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC) represent critical stages in cognitive decline (Rostamzadeh et al., 2022; Troisi et al., 2024). Understanding the differences in functional connectivity (FC) changes across groups can not only provide insights into the progression of neurodegenerative diseases, but also help identify targeted regions for interventions, facilitating more effective treatment and diagnostic strategies. This study aims to elucidate the alterations in FC both across and within these groups over two temporal intervals (90 days and 300 days) to uncover potential answers to these critical questions.
Methods:
All fMRI data were sourced from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We chose two temporal variabilities of both whole brain states (Deco et al., 2017) and regional level (Zhang et al., 2016) were used. Statistical methods including ANOVA and t-tests were employed to compare the rate of changes in FC across both time intervals, assessing inter-group differences at each stage.
Results:
For the 90-day interval, ANOVA comparisons revealed no significant changes between T1-T2 (p = 0.1341) or T2- T3 (p = 0.5442). However, significant differences were found between the AD and HC groups for T1-T2 (p = 0.0447, Figure 1). In the 300-day interval, similar trends were observed, with no significant differences detected in ANOVA (T1-T2: p = 0.1528; T2-T3: p = 0.6278). T-tests indicated marginal significance between AD and HC for the T1-T2 interval (p = 0.0658). When comparing the 90-day and 300-day intervals, no significant results were found within each group. Notably, in both the 90-day and 300-day intervals, the average rate of changes in metastability showed that AD exhibited the most alterations, followed by MCI, while the HC group displayed relatively smaller changes (Figure 2). In the analysis of nodal temporal variability among three groups during the T1-T2 interval, several nodes exhibited statistically significant differences. Comparisons between AD and HC revealed significant differences in nine nodes, including left inferior orbital frontal gyrus (t(93) = 2.2910, 0.0242), right superior temporal gyrus (t(93) = -2.5077, p = 0.0139), and right precuneus (t(93) = -2.1780; p = 0.0319). Additionally, significant distinctions were observed between AD and MCI in left superior orbital frontal gyrus (t(104) = 2.2005; p = 0.0299), left inferior orbital frontal gyrus (t(104) = 2.4548; p = 0.0158), right precuneus (t(104) = -2.2508, p = 0.0265). Furthermore, comparisons between HC and MCI indicated significant alterations in six nodes, such as the right fusiform gyrus (t(189) = 2.1381, p = 0.0338), and the right inferior triangular frontal gyrus (t(189) = 2.0115, p = 0.0457), right middle frontal gyrus gyrus (t(189) = 2.2794, p = 0.0238), and right inferior orbital frontal cortex (t(189) = 2.5753, p = 0.0108). For the T2-T3, significant differences were observed between AD/MCI and HC in left middle frontal gyrus (|t| > 2.2004, p < 0.0303). Additionally, significant differences were found between AD and HC/MCI in the regions of right precuneus (t > 3.1748, p < 0.0020) and left superior occipital gyrus (t > 2.1315, p < 0.0405), with a threshold of t > -2.5435 and p < 0.0204 for left middle temporal gyrus. In the comparison of nodal temporal variability within each group across intervals, a significant difference was observed in the supramarginal gyrus, which is associated with the auditory network (t(23) = 2.2335, p = 0.0334). These findings underscore critical changes in functional connectivity across specific brain regions.
·Figure 1 Comparison of rates of metastability (T1-T2) among different groups (AD, HC, MCI) over a 90-day interval. Asterisks indicate statistically significant results, with p-values shown for each co
·Figure 2 Comparison of metastability between different groups for 90-day interval and 300-day interval. The light blue bars represent the mean values for 90-day interval, while the dark blue bars repr
Conclusions:
The rate of changes in FC over long intervals was not significantly greater, but there were distinct differences in nodal temporal variability across different intervals. Nodes exhibiting significant short-term changes may warrant greater focus, potentially helping to avoid long-term changes and control disease progression.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Novel Imaging Acquisition Methods:
BOLD fMRI 2
Keywords:
Aging
MRI
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
Petersen, R.C., Aisen, P.S., Beckett, L.A., Donohue, M.C., Gamst, A.C., Harvey, D.J., Jack, C.R., Jagust, W.J., Shaw, L.M., Toga, A.W., Trojanowski, J.Q., Weiner, M.W., 2010. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Clinical characterization. Neurology 74, 201–209. https://doi.org/10.1212/WNL.0b013e3181cb3e25
Rostamzadeh, A., Bohr, L., Wagner, M., Baethge, C., Jessen, F., 2022. Progression of Subjective Cognitive Decline to MCI or Dementia in Relation to Biomarkers for Alzheimer Disease. Neurology 99, e1866–e1874. https://doi.org/10.1212/WNL.0000000000201072
Troisi, G., Marotta, A., Lupiañez, J., Casagrande, M., 2024. Does personality affect the cognitive decline in aging? A systematic review. Ageing Research Reviews 100, 102455. https://doi.org/10.1016/j.arr.2024.102455
Zhang, J., Cheng, W., Liu, Z., Zhang, K., Lei, X., Yao, Y., Becker, B., Liu, Y., Kendrick, K.M., Lu, G., Feng, J., 2016. Neural, electrophysiological and anatomical basis of brain- network variability and its characteristic changes in mental disorders. Brain 139, 2307–2321. https://doi.org/10.1093/aww143