Medial Temporal Lobe Subfields Correlate with Alzheimer's Cognitive Domains; Insights from High-Resolution T2 MRI of ADNI Database

doi:10.21203/rs.3.rs-4892557/v1

Download PDF

Article

Medial Temporal Lobe Subfields Correlate with Alzheimer's Cognitive Domains; Insights from High-Resolution T2 MRI of ADNI Database

https://doi.org/10.21203/rs.3.rs-4892557/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Alzheimer's Disease (AD) causes multi-domain cognitive decline. Brain imaging biomarkers and neuropsychiatric testing detect difficulties, although it is unclear how cognitive processes and medial temporal lobe subregions relate. High-resolution T2 MRIs of AD patients' medial temporal lobes were compared to composite scores for memory, language, executive function, and visuospatial ability.

Methods

156 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants provided data. Composite cognitive scores and high-resolution T2 MRI volumetric assessments of medial temporal lobe subregions were obtained. Multiple linear regression was used to account for factors and analyze composite scores and regional volumes.

Results

In AD patients, left cornu ammonis (CA), subiculum (SUB), perirhinal cortices (BA35), and bilateral parahippocampal cortex (PHC) size positively linked with memory performance. Language was strongly connected with hippocampi and cortical volumes in moderate cognitive impairment, and right entorhinal cortex (ERC) volume in AD patients. The bilateral SUB in normal cognitive function and the right SUB in AD positively linked with executive ability. Cognitively normal people with bilateral SUB had better visual-spatial skills.

Conclusion

Across AD stages, medial temporal subregions and cognitive composites had unique structure-function patterns, with left hemisphere effects preceding bilateral participation, underlining their combined value for early disease identification and monitoring.

Biological sciences/Neuroscience

Health sciences/Neurology

Alzheimer’s disease

Magnetic Resonance Imaging

Hippocampus

Entorhinal Cortex

Alzheimer's Disease Neuroimaging Initiative

Medial temporal lobes

Alzheimer's disease (AD) is a kind of neurodegenerative dementia that progressively affects most everyday cognitive functions and is the sixth cause of death and the third most common disease after cardiovascular disease and cancer (1, 2). Its symptoms consist of loss of memory, a lack of communication with others, and an inability to recognize acquaintance (3). While patients with AD constitute 2% of the population at the age of 65 years, this increases to 30% at the age of 85 years (4). Additionally, the total number of people with AD is expected to double over the next 20 years, with approximately 1 in 85 people affected by 2050 (5). Neuropsychiatric assessments play a crucial role in the evaluation and diagnosis of various mental health and neurological disorders, including AD (6). These assessments typically encompass a range of cognitive, behavioral, and emotional evaluations designed to detect changes in memory, executive function, language, and visuospatial abilities (7).

Although former studies have well proven the accuracy of neuropsychiatric assessments for AD diagnosis, the recently proposed composite cognitive scores have yet not been comprehensively studied (8). Using composite scores instead of single criteria can be more useful for two reasons. First, by including several indicators in one score and by reducing the number of potential comparisons, it preserves statistical power and thus reduces measurement error. Second, by summarizing all data into a single score, it allows for comparison with other variables such as neuroimaging summaries and biomarkers without having to address the challenges posed by separate measures (9). There is also evidence for combining cognitive assessments and MRI markers which increase the detection of future dementia (10).

In addition to composite cognitive scores, neuroimaging biomarkers have shown promise in enhancing the early detection and monitoring of AD (11, 12). Neuroimaging biomarkers, particularly those reflecting medial temporal lobe atrophy, show promise for early detection and monitoring of AD (13, 14). However, the specific associations between medial temporal subregions and different cognitive domains across the AD spectrum remain incompletely characterized. High-resolution T2-weighted MRI allows for detailed volumetric measurements of hippocampal subfields and adjacent cortical regions in the medial temporal lobe (15, 16). Differential vulnerability of these regions has been reported in AD, with early changes seen in entorhinal cortex and CA1, followed by involvement of other subfields, perirhinal cortex, and para hippocampal gyrus (17, 18). However, the cognitive correlates of these subregional volumetric changes, especially in preclinical and prodromal AD, have not been fully elucidated.

Therefore, the aim of this study was to comprehensively examine the associations of high-resolution T2 MRI metrics of medial temporal subregions with composite scores for memory, language, executive function and visuospatial abilities in older adults across the cognitive spectrum from normal to Mild cognitive impairment (MCI) to AD dementia. We hypothesized that poorer performance in each cognitive domain would be associated with smaller volumes of specific medial temporal subregions, and that these structure-function relationships would vary by stage of disease.

2.1. Participants and data source

This study analyzed data from the ADNI database ( https://adni.loni.usc.edu/ ). The ADNI was launched in 2003 by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, the Food and Drug Administration, private pharmaceutical companies, and non-profit organizations as a $60 million, 5-year public-private partnership. The primary goal of ADNI has been to test whether serial MRI, positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessments could be combined to measure the progression of MCI and early AD. For up-to-date information, see www.adni-info.org . After data cleaning, we reached 156 cases that had both baseline cognitive composite scores and high-resolution T2 MRI volumes of medial temporal subfields. Cognitive composite scores were derived from the phenotype harmonization consortium for memory function (ADNI-MEM), executive function (ADNI-EF), visuospatial function (ADNI-VSP), and language function (ADNI-LAN). Additional inclusion and exclusion criteria are detailed in ADNI. The ADNI categorized CN subjects as healthy persons matched in age to the MCI group with no substantial cognitive impairment. CN individuals were defined by an MMSE score of 24–30, a CDR score of 0, and delayed recall scores from Logical Memory II (Wechsler Memory Scale-Revised) of ≥ 9 for 16 years of education, ≥ 5 for 8–15 years, and ≥ 3 for 0–7 years (Petersen et al. 2010). ADNI defines MCI as individuals with memory complaints, MMSE score 24–30, CDR score 0.5, memory box score 0.5+, and delayed recall scores ≤ 8 for 16 + years, ≤ 4 for 8–15 years, and ≤ 2 for 0–7 years. Individuals must not have dementia and have mostly intact general cognition and functional performance (Petersen et al. 2010). ADNI excluded subjects who used antidepressants with anticholinergic properties, regular narcotics over two doses per week, or neuroleptics or other anticholinergic drugs within four weeks of screening. Exclusion criteria included using antiparkinsonian medications within four weeks after screening, participating in other experimental drug studies, and starting or stopping diuretic meds within four weeks. Cholinesterase inhibitors and memantine were allowed for MCI patients if the dose was stable for four weeks before screening (19). estrogen, estrogen-like substances, and vitamin E were authorized if the dose was steady for four weeks before screening. Once registered, research participants were to notify site investigators of medication changes (19).

2.2. Cognitive and clinical measures

Co-calibrated composite scores computed using recent psychometric methodologies allowed direct comparison of research participants in different cohorts who were tested with distinct test batteries. The ADNI website (www.adni-info.org) details the construction of each cognitive composite score. Briefly, the ADNI-MEM includes RAVLT, ADAS-Cog, logical memory, and some Mini-Mental State Examination (MMSE) sub-scores. The ADNI-EF was calculated using category fluency—animals, vegetables, trails A and B, digit span backward, WAIS-R digit symbol substitution, and 5 clock drawing items (circle, symbol, numbers, hands, time). ADNI-LAN includes neuropsychological battery language-related tests, and Alzheimer's Disease Assessment Scale–cognitive subscale (ADAS-Cog) language Finally, ADNI-VSP was established utilizing clock-copy-based Neuropsychological Battery exam, ADAS-Cog's constructional praxis score, and MMSE's copy design score.

2.3. Medial temporal lobe high-resolution T2 MRI

Medial temporal lobe subregion high -resolution T2 MRI volumetric measurements obtained from ADNI database. Regions of interest were hippocampal subfields (CA1, CA2, CA3), dentate gyrus, Subicular Complex, and extrahippocampal cortical regions of entorhinal, perirhinal, and para-hippocampal cortex. The perirhinal cortex is divided into BA35 and BA36 segments. More details on image processing are available at www.adni-info.org. Based on the manual provided by ADNI, we omitted those cases with image quality ≤ 1. Moreover, as it was recommended, we created the CA sum variable (CA1 + CA2 + CA3) due to the often low image quality of CA2 and CA3 because of their small size. For extrahippocampal cortical regions (ERC, PHC, BA35, and BA36) normalized volume variables were created by dividing the raw volumes by the number of slices in which the ROI appears. Figure 1 illustrates the medial temporal lobe subfields on sagittal and coronal view of brain.

2.4. Statistical analyses

One-way ANOVA and Kruskal-Wallis analyses were performed to compare baseline cognitive, and imaging variables between groups. Bonferroni correction was used for between-group comparisons. Multiple linear regression was applied for the association between composite scores and medial temporal subregion T2 MRI metrics with age, education, and baseline MMSE as covariates. False discovery rate applied to address multiple comparison effects. Statistical significance was set at the P < 0.05 level. All the statistical analyses were performed using the R program software version 4.3.3.

Table 1 displays the initial characteristics of the study's participants. We conducted a study on a total of 156 individuals, consisting of 93 cognitively normal (CN) individuals, 46 patients with MCI, and 17 patients diagnosed with AD. The three groups exhibited comparable age and education levels, with no statistically significant difference (p > 0.05). CDRSB and ADAS-13 scores increase with cognitive decline across all groups, but MMSE rating reduces whenever cognitive declines (All P values <0.001). Notable differences in ADNI composite scores were noted, with scores rising as cognitive state improved (ADNI-MEM, ADNI-EF, ADNI-LAN P values <0.001, ADNI-VSP P value < 0.05).

The T2 MRI measurements for individuals with normal CN, MCI, and AD are displayed in Figure 2 Measurements were taken of bilateral CA, DG, MISC, SUB, ERC, BA35, BA36, PHC, and SULCUS. Figure 1 shows that the AD group generally had smaller bilateral T2 MRI volumes in most subregions compared to the CN and MCI groups (P value <0.05). There exist certain deviations from this regularity. Among the AD, the volumes of the left hemisphere MISC are significantly greater compared to the CN group (P value <0.05) while insignificantly greater than the MCI (Figure 1C). Similarly, AD subjects represented higher left and right sulcus volumes than both CN and MCI, though the differences were insignificant.

The ADNI composite scores were correlated with the volumetric measures of the medial temporal subregions, as seen in Tables 2-5. The results of the ADNI-MEM indicate that there were significant negative associations seen in the left DG and right MISC regions in the CN group and bilateral MISC regions in the MCI group. On the other hand, significant positive association were noted among left CA, SUB, and bilateral BA35 and PHC regions in individuals with AD, as shown in Table 2. Regarding ADNI-EF, Table 3 shows that among the CN group, the cognitive score displayed statistically significant positive correlations with bilateral SUB, while for the AD group there was no correlation except for a significant negative relationship with right SUB (P values < 0.05). The ADNI-LAN (Table 4) did not find any significant connections in the AD group, except a positive correlation in the right ERC region (P value < 0.05). However, the MCI group exhibited strong positive correlations in several locations, including bilateral CA, DG, BA36, and left BA35. The analysis conducted using ADNI-VSP (Table 5) did not reveal any statistically significant correlations in individuals with AD and MCI, but the bilateral SUB showed a significant positive correlation with the metric among the CN group (P value < 0.01).

Our study examined the relationship between high-resolution T2 MRI scans of the medial temporal lobe and memory, language, executive function, and visuospatial abilities in normal-aging CN, MCI, and AD patients. Most importantly, smaller medial temporal subregions, especially in the left hemisphere, were associated with worse composite cognitive scores across multiple categories. However, cognitive area and disease stage affected the structure-function association of these entities. In AD, left CA, SUB, BA35, and both sides of the PHC were positively associated with memory function (ADNI-MEM). ADNI-LAN showed positive relationships between mild MCI patients' bilateral hippocampus (CA, DG) and cortical areas (BA35, BA36) size and language skills. In AD patients, only right ERC volume was positively correlated with the language skills. In the CN group, executive function (ADNI-EF) and visuospatial ability (ADNI-VSP) were positively correlated with bilateral subiculum and right ERC volumes.

Language changes in AD can manifest as difficulties in recalling vocabulary, reduced ability to name familiar objects, decreased precision in expressing meaning, paraphasia (substituting words or sounds), increased pauses and slower speech rate (indicating problems with language production), decreased amount and quality of speech content, lexical disorders (repeating words and using pronouns instead of names), and syntactic disorders (20, 21). Severe AD can lead to echolalia, aphasia, and restricted language (22). Language difficulties can have an impact on social connections, particularly in instances when the obstacles are moderate or severe (23–25). Notably, language difficulties often appear in the first and preclinical stages of AD, making them useful for detecting the disease early (26). Detecting language impairments may accelerate the beginning of medication therapy and the adoption of tactics to stabilize or restrict the advancement of the condition. In addition, the surveillance of language abnormalities might direct the creation of alternative communication strategies to enhance interpersonal connections. Our findings indicate that there is a connection between the size of the medial temporal lobe and language abilities. It appears that language skills may start to decline slightly later than memory skills as the disease progresses (27). Within the MCI group, we found that there were positive connections between ADNI-LAN and the volumes of both hippocampal regions (CA, DG) and cortical regions (BA35, BA36). This suggests that language difficulties during the early stage of the disease may be associated with shrinkage in both sides of the medial temporal lobe (28). However, it was observed that only the volume of the right ERC had a significant positive correlation with ADNI-LAN in the group with AD dementia. This suggests that language impairments in the later stages of the disease may be more dependent on the spread of pathology to neocortical language regions, as indicated by the association with the volume of the right ERC. Chauveau et al. conducted a study that focuses on the ERC and its role in language function (29). They also explored how the ERC may be related to the language abnormalities reported in AD. The ERC, a component of the anterior temporal lobe system, plays a crucial role in semantic processing, language comprehension, and verbal fluency (30). The ERC's early engagement in the AD progression may interfere with the neuronal networks that are accountable for language processing, resulting in a deterioration of semantic memory, naming proficiency, and verbal fluency (31). Chauveau and colleagues proposed that the participation of the ERC in language function may be connected to its role in retrieving and processing semantic information, which is crucial for activities involving the production of words (29).

Memory deficits are one of the first and most noticeable characteristics of AD, frequently manifesting in the preclinical and early phases (32). The disease's progression leads to increasingly severe impairments in the ability to encode and retrieve new information, impacting both episodic and semantic memory (33). The medial temporal lobe, specifically the hippocampus and ERC, is a crucial brain area involved in the memory impairments seen in AD (34). Neuroimaging studies have repeatedly shown that people with AD have considerable shrinkage of the hippocampus and entorhinal cortex (35, 36). This shrinkage is linked to the buildup of neurofibrillary tangles and amyloid plaques (37). The damage caused by this impairs the process of forming, strengthening, and recalling specific memories, resulting in the severe memory deficits that are characteristic of AD. The initial and substantial participation of the medial temporal lobe in AD emphasizes its potential as a biomarker for early identification and monitoring of the condition, as well as a target for therapeutic approaches focused on protecting memory function. In terms of memory performance, our findings indicate that there are substantial positive associations between the ADNI-MEM composite and volumes of the left CA, SUB, BA35, and bilateral PHC in AD. These findings support prior research that suggests the left medial temporal lobe play a vital role in the encoding and retrieval of spoken memory. The strong associations identified between ADNI-MEM and these regional volumes confirm the effectiveness of this new composite as a reliable indicator of memory impairment in the initial phases of AD. In line with our research, Mortamais et al. have shown that AD is characterized by early cognitive impairments, namely in episodic memory, which can be identified during the preclinical phase (38). Their review emphasized the crucial significance of the medial temporal lobe, particularly the hippocampus and ERC, in the memory deficits reported in AD. It also acknowledged the link between the shrinkage of these areas and the buildup of neurofibrillary tangles and amyloid plaques. While Mortamais et al. did not explicitly utilize the memory composite, their results provide evidence for the possibility of employing cognitive evaluations and neuroimaging biomarkers to identify and track the progression of AD by detecting and monitoring atrophy in the medial temporal lobe. This is consistent with our strategy of using the ADNI-MEM composite, which shows significant connections with the sizes of certain regions in the medial temporal lobe, as a dependable indication of memory decline in the early stages of AD.

Executive function impairments, which manifest as challenges in tasks including as planning, organizing, problem-solving, and adapting to unfamiliar circumstances (39). They frequently encounter difficulties in organizing work in a specific order, comprehending complex situations, and adapting their techniques (39). Impairments in inhibition control and working memory lead to heightened impulsivity and difficulties in retaining information in the short-term (40). Visuospatial anomalies result in difficulties with spatial orientation, leading to patients being disoriented in familiar environments and inaccurately perceiving distances (41). Perceptual-motor skills are impaired, leading to difficulties in hand-eye coordination and recognizing familiar faces or objects (42). We found positive relationships between executive function and visuospatial ability, as measured by ADNI-EF and ADNI-VSP composites, respectively, and the volumes of the bilateral SUB and right ERC in the CN group. The results indicate that non-memory activities are susceptible to early impairment and rely on shared posteromedial cortical hubs. The connections correspond to prior findings that link the subiculum to spatial processing, and the ERC to executive processes such as cognitive flexibility (43, 44). However, these correlations were not detected in the group of individuals with AD, indicating that the condition may interfere with the usual connections between structure and function that are observed in healthy persons. Possible reasons for the absence of correlation in the AD group include disruptions in the normal relationship between structure and function, the activation of alternative neural networks as a compensatory mechanism, the variability in how AD is presented and progresses, a limitation in detecting changes in advanced stages of the disease, and the impact of other brain regions outside of the medial temporal lobe (45, 46). These findings emphasize the significance of examining the distinct connections between brain structure and cognitive function in both healthy aging and AD. By comprehending these changes, we can gain insights into the underlying disease mechanisms and use this knowledge to develop specific interventions that can help preserve cognitive function in affected individuals.

The limitations of this study include the cross-sectional design, modest sample size for the AD group, and lack of longitudinal follow-up. Larger, prospective studies are needed to track the evolution of medial temporal morphology and cognitive profiles over time. Incorporation of other imaging modalities and biomarkers could further elucidate the complex interplay of structural, functional and pathologic changes driving cognitive decline in AD.

In conclusion, using composite cognitive scores and high-resolution T2 MRI of medial temporal lobe subregions, this study identified distinct structure-function patterns across Alzheimer's disease stages. The relationships between medial temporal subfields volume and composite scores for memory, language, executive function, and visuospatial abilities dynamically changed as the disease progressed, with initial left hemisphere effects preceding bilateral involvement. The results underscore the value of comprehensive cognitive assessment combined with neuroimaging for early Alzheimer's detection and monitoring.

Ethical approval
The study adhered to the ethical principles outlined in the Helsinki declarations. Data was collected from the ADNI database, and the co-authors ensured that no personally identifiable information of the patients was accessed. For more information on ADNI's ethical protocols, please visit adni.loni.usc.edu.

Informed consent
Informed consent was obtained from the study participants.

Author Contribution

M.Ma. conceptualized and designed the study. M.S. arranged the manuscript structure. P.S. and M.Mo. critically revised and refined the article. A.D., A.R., A.A., F.E-C., M.S-R., S.S., R.R., P.T., A.K., and F.A. contributed to manuscript writing and data collection. All authors reviewed the manuscript.

Acknowledgement

Data collection and sharing for this study was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol- Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. Data used in this study were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.ucla.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

Data Availability

Data AvailabilityThe data used in this study are not publicly available as they were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The ADNI data are available to qualified researchers upon request and approval from ADNI. Interested researchers can apply for access to the ADNI data through the ADNI website (http://adni.loni.usc.edu/data-samples/access-data/). The authors of this study do not have permission to redistribute the ADNI data directly.

Association As. Alzheimer's disease facts and figures. Alzheimer's & Dementia. 2017;13(4):325 – 73. (2017).
Zvěřová, M. Clinical aspects of Alzheimer's disease. Clin. Biochem. 72, 3–6 (2019).
Jahn, H. Memory loss in Alzheimer's disease. Dialog. Clin. Neurosci. 15 (4), 445–454 (2013).
Association As, Thies, W. & Bleiler, L. Alzheimer's disease facts and figures. Alzheimer's & dementia. 2013;9(2):208 – 45. (2013).
Scheltens, P. et al. Alzheimer's disease. Lancet. 397 (10284), 1577–1590 (2021).
Cummings, J. The role of neuropsychiatric symptoms in research diagnostic criteria for neurodegenerative diseases. Am. J. Geriatric Psychiatry. 29 (4), 375–383 (2021).
Lü, W., Duan, J., Zhang, W., Yang, W. & Yu, W. Relationship between neuropsychiatric symptoms and cognitive functions in patients with cognitive impairment. Psychogeriatrics. 21 (5), 773–782 (2021).
Belleville, S., Fouquet, C., Hudon, C., Zomahoun, H. T. V. & Croteau, J. Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis. Neuropsychol. Rev. 27 (4), 328–353 (2017).
Crane, P. K. et al. Development and assessment of a composite score for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Brain Imaging Behav. 6 (4), 502–516 (2012).
Eckerström, C. et al. A combination of neuropsychological, neuroimaging, and cerebrospinal fluid markers predicts conversion from mild cognitive impairment to dementia. J. Alzheimers Dis. 36 (3), 421–431 (2013).
Veitch, D. P. et al. Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease. Alzheimer's Dement. 18 (4), 824–857 (2022).
Akram, A. S. et al. Advancing the Frontier: Neuroimaging Techniques in the Early Detection and Management of Neurodegenerative Diseases. Cureus ;16(5). (2024).
Battineni, G. et al. Improved Alzheimer’s disease detection by MRI using multimodal machine learning algorithms. Diagnostics. 11 (11), 2103 (2021).
de Flores, R. et al. Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer's disease. Alzheimer's Dement. 16 (6), 843–852 (2020).
Bussy, A. et al. Hippocampal subfield volumes across the healthy lifespan and the effects of MR sequence on estimates. NeuroImage. 233, 117931 (2021).
Lenhart, L. et al. Anatomically Standardized Detection of MRI Atrophy Patterns in Early-Stage Alzheimer’s Disease. Brain Sci. 11 (11), 1491 (2021).
Stark, S. M., Frithsen, A. & Stark, C. E. Age-related alterations in functional connectivity along the longitudinal axis of the hippocampus and its subfields. Hippocampus. 31 (1), 11–27 (2021).
Karimani, F., Asgari Taei, A., Abolghasemi-Dehaghani, M-R., Safari, M-S. & Dargahi, L. Impairment of entorhinal cortex network activity in Alzheimer’s disease. Front. Aging Neurosci. 16, 1402573 (2024).
Petersen, R. C. et al. Alzheimer's disease Neuroimaging Initiative (ADNI) clinical characterization. Neurology. 74 (3), 201–209 (2010).
Fraser, K. C., Meltzer, J. A. & Rudzicz, F. Linguistic features identify Alzheimer’s disease in narrative speech. J. Alzheimers Dis. 49 (2), 407–422 (2016).
Szatloczki, G., Hoffmann, I., Vincze, V., Kalman, J. & Pakaski, M. Speaking in Alzheimer’s disease, is that an early sign? Importance of changes in language abilities in Alzheimer’s disease. Front. Aging Neurosci. 7, 195 (2015).
Ferris, S. H. & Farlow, M. Language impairment in Alzheimer’s disease and benefits of acetylcholinesterase inhibitors. Clin. Interv. Aging :1007–1014. (2013).
Vigo, I., Coelho, L. & Reis, S. Speech-and language-based classification of Alzheimer’s disease: a systematic review. Bioengineering. 9 (1), 27 (2022).
Mueller, K. D., Hermann, B., Mecollari, J. & Turkstra, L. S. Connected speech and language in mild cognitive impairment and Alzheimer’s disease: A review of picture description tasks. J. Clin. Exp. Neuropsychol. 40 (9), 917–939 (2018).
Petti, U., Baker, S. & Korhonen, A. A systematic literature review of automatic Alzheimer’s disease detection from speech and language. J. Am. Med. Inform. Assoc. 27 (11), 1784–1797 (2020).
Mistur, R. et al. Current challenges for the early detection of Alzheimer's disease: brain imaging and CSF studies. J. Clin. Neurol. 5 (4), 153–166 (2009).
Verma, M. & Howard, R. J. Semantic memory and language dysfunction in early Alzheimer's disease: a review. Int. J. Geriatr. Psychiatry. 27 (12), 1209–1217 (2012).
Visser, P., Verhey, F., Hofman, P., Scheltens, P. & Jolles, J. Medial temporal lobe atrophy predicts Alzheimer's disease in patients with minor cognitive impairment. J. Neurol. Neurosurg. Psychiatry. 72 (4), 491–497 (2002).
Chauveau, L. et al. Medial temporal lobe subregional atrophy in aging and Alzheimer's disease: a longitudinal study. Front. Aging Neurosci. 13, 750154 (2021).
Brickman, A. M. & Stern, Y. Aging and memory in humans. (2009).
Ranganath, C. & Ritchey, M. Two cortical systems for memory-guided behaviour. Nat. Rev. Neurosci. 13 (10), 713–726 (2012).
Salmon, D. P. Neuropsychological features of mild cognitive impairment and preclinical Alzheimer’s disease. Behav. Neurobiol. aging :187–212. (2012).
Perry, R. J., Watson, P. & Hodges, J. R. The nature and staging of attention dysfunction in early (minimal and mild) Alzheimer’s disease: relationship to episodic and semantic memory impairment. Neuropsychologia. 38 (3), 252–271 (2000).
Pennanen, C. et al. Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol. Aging. 25 (3), 303–310 (2004).
Killiany, R. et al. MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology. 58 (8), 1188–1196 (2002).
Aël Chetelat, G. & Baron, J-C. Early diagnosis of Alzheimer’s disease: contribution of structural neuroimaging. Neuroimage. 18 (2), 525–541 (2003).
Norfray, J. F. & Provenzale, J. M. Alzheimer's disease: neuropathologic findings and recent advances in imaging. Am. J. Roentgenol. 182 (1), 3–13 (2004).
Mortamais, M. et al. Detecting cognitive changes in preclinical Alzheimer's disease: A review of its feasibility. Alzheimer's Dement. 13 (4), 468–492 (2017).
Vasudev, L. Executive function in high functioning individuals with age-associated memory impairment or Alzheimer's disease (University of Ottawa (Canada), 2000).
Stopford, C. L., Thompson, J. C., Neary, D., Richardson, A. M. & Snowden, J. S. Working memory, attention, and executive function in Alzheimer’s disease and frontotemporal dementia. Cortex. 48 (4), 429–446 (2012).
O'Brien, H. L. et al. Visual mechanisms of spatial disorientation in Alzheimer's disease. Cereb. Cortex. 11 (11), 1083–1092 (2001).
Domico, M. & Hill, V. What You Need to Know about Alzheimer's Disease (Bloomsbury Publishing USA, 2022).
Izzo, J., Andreassen, O. A., Westlye, L. T. & van der Meer, D. The association between hippocampal subfield volumes in mild cognitive impairment and conversion to Alzheimer’s disease. Brain Res. 1728, 146591 (2020).
Gong, L., Liu, D., Zhang, B., Yu, S. & Xi, C. Sex-Specific Entorhinal Cortex Functional Connectivity in Cognitively Normal Older Adults with Amyloid-β Pathology. Mol. Neurobiol. :1–10. (2024).
Cai, S. et al. Altered functional brain networks in amnestic mild cognitive impairment: a resting-state fMRI study. Brain imaging Behav. 11, 619–631 (2017).
Maass, A. et al. Alzheimer’s pathology targets distinct memory networks in the ageing brain. brain. 142 (8), 2492–2509 (2019).

Table 1 to 5 are available in the Supplementary Files section.

No competing interests reported.

Table15.docx

Download PDF

Editorial decision: Revision requested
21 Nov, 2024
Reviews received at journal
18 Nov, 2024
Reviewers agreed at journal
12 Nov, 2024
Reviews received at journal
31 Oct, 2024
Reviewers agreed at journal
21 Oct, 2024
Reviewers invited by journal
28 Aug, 2024
Editor assigned by journal
27 Aug, 2024
Editor invited by journal
26 Aug, 2024
Submission checks completed at journal
22 Aug, 2024
First submitted to journal
10 Aug, 2024

You are reading this latest preprint version

Medial Temporal Lobe Subfields Correlate with Alzheimer's Cognitive Domains; Insights from High-Resolution T2 MRI of ADNI Database

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1. Introduction

2. Methods

2.1. Participants and data source

2.2. Cognitive and clinical measures

2.3. Medial temporal lobe high-resolution T2 MRI

2.4. Statistical analyses

3. Results

4. Discussion

5. Conclusion

Declarations

Informed consent
Informed consent was obtained from the study participants.

Author Contribution

Acknowledgement

Data Availability

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Medial Temporal Lobe Subfields Correlate with Alzheimer's Cognitive Domains; Insights from High-Resolution T2 MRI of ADNI Database

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1. Introduction

2. Methods

2.1. Participants and data source

2.2. Cognitive and clinical measures

2.3. Medial temporal lobe high-resolution T2 MRI

2.4. Statistical analyses

3. Results

4. Discussion

5. Conclusion

Declarations

Informed consent Informed consent was obtained from the study participants.

Author Contribution

Acknowledgement

Data Availability

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Informed consent
Informed consent was obtained from the study participants.