While tau pathology is closely associated with neurodegeneration in Alzheimer’s disease (AD), our prior work using multi-modality imaging revealed that mismatch between tau (T) and neurodegeneration (N) may reflect contributions from non-AD processes. The medial temporal lobe (MTL), an early site of AD pathology, is also a common target of co-pathologies such as limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), often following an anterior–posterior atrophy gradient. Given the susceptibility of MTL to co-pathologies, here we explored T-N mismatch specifically within MTL using plasma ptau217 and MTL morphometry for identifying vulnerabilities and resilience in cognitively impaired or unimpaired AD patients.

We parcellated the MTL into 100 spatially contiguous segments and calculated their T-N mismatch using plasma ptau217 as a measure for T and thickness as a marker of N. Based on these mismatch profiles, we clustered 447 amyloid-positive individuals from ADNI cohort into data-driven T-N phenotypes. We characterized the T-N phenotypes by examining their cross-sectional and longitudinal atrophy both within the MTL and across the whole brain, as well as cognitive trajectories. This framework was replicated in an independent cohort and finally translated to a real-world clinical sample of 50 patients undergoing anti-amyloid therapy.

Clustering identified three T-N phenotypes with different MTL T-N mismatch profiles, atrophy patterns, and cognitive outcomes, despite comparable AD severity. The “canonical” group, characterized by low T-N residuals (N ∼ T), showed AD-like neurodegeneration patterns. The “vulnerable” group, characterized by disproportionately greater neurodegeneration than tau (N > T), showed atrophy primarily in the anterior MTL that extended into temporal-limbic regions, both in cross-sectional and longitudinal analyses. This group also exhibited neurodegeneration that preceded estimated tau onset and experienced faster cognitive decline across multiple domains, aligning with the typical characteristics of mixed LATE-NC with AD. In contrast, the “resilient” group (N < T) showed minimal atrophy and preserved cognitive function. These phenotypes were reproducible in an independent research cohort. Importantly, in a feasibility study applying the model developed from ADNI to a clinical cohort of patients receiving lecanemab, we identified vulnerable individuals with LATE-like atrophy patterns. This highlights its potential utility for identifying individuals with co-pathology in clinical settings.

Our findings demonstrate that T-N mismatch within MTL using MRI and plasma biomarkers can reveal AD groups with varying vulnerability/resilience, with the vulnerable group displaying structural and cognitive outcomes suggestive of LATE-NC. This approach offers a cost-effective strategy for clinical trial stratification and precision medicine for AD therapeutics.

The authors have declared no competing interest.

The study was supported by the funding R01 AG056014 and RF1 AG069474. LW is supported by National Institute on Aging grant R01AG070592, MultiPark - A Strategic Research Area at Lund University, the Bente Rexed Gerstedt Foundation and the Swedish Research Council (2022-00900). Data collection and sharing for this project 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).

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↵* Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.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 analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

All data produced in the present study are available upon reasonable request to the authors