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Variability in tau‐atrophy relationships reveals underlying phenotypes in individuals on the Alzheimer’s disease continuum
Author(s) -
Das Sandhitsu R,
Xie Long,
McCollum Lauren,
de Flores Robin,
Irwin David J,
Nasrallah Ilya M,
Dickerson Brad C,
Yushkevich Paul,
Wolk David A
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.047272
Subject(s) - precuneus , atrophy , psychology , neurodegeneration , alzheimer's disease , neuroscience , medicine , white matter , audiology , pathology , cognition , disease , magnetic resonance imaging , radiology
Background Tau neurofibrillary tangles (T) are thought to be the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in AD. However, there is substantial variability in the T‐N relationship – manifested in higher or lower atrophy than expected for the level of tau in a given brain region. We quantitatively describe and categorize source(s) of variability using region‐based measures of T and N to gain insight into underlying modulatory factors, including polypathology. Method Regional cortical thickness and 18 F‐Flortaucipir SUVR were computed in 108 gray matter ROIs from cognitively‐impaired, amyloid‐positive individuals (n=137) in ADNI. ROI‐specific residuals from a robust linear fit between SUVR and cortical thickness were computed. Using a threshold of +/‐ 1.5 standard deviation (S.D.), ROIs were categorized into “positive”, “negative”, or “neutral” residual (Fig 1). The residual signs for all ROIs were used in a hierarchical clustering framework to partition the dataset. Result Six groups appear to represent different phenotypes summarized in Table 1. Overall, the groups differed in age, burden of white matter hyperintensity (WMH), clinical status, and MMSE. However, they did not differ in tau burden in key brain ROIs (e.g. inferotemporal cortex, precuneus, angular gyrus). Group 1 is largest, consisting of individuals with low residuals described as having a canonical “T‐N” relationship. Group 2 has significantly higher temporolimbic atrophy relative to tau with many cases having a pattern of atrophy suggestive of TDP‐43 copathology. Group 3 appears to be a resilient phenotype with less atrophy relative to tau in lateral cortical regions. Group 4 is similar to Group 2 with high temporal atrophy, but also more diffuse atrophy. Group 5 also displays resilience, particularly in the temporal lobe. Group 6 shows widespread higher atrophy relative to tau, has the lowest MMSE and highest WMH. Conclusion We demonstrate that a measure of deviation from a normative relationship between tau burden and neurodegeneration across brain regions in individuals on the AD continuum captures variability due to multiple underlying factors, and can reveal phenotypes, which if validated, may be helpful for identifying possible contributors to neurodegeneration in addition to tau, which may ultimately be useful for cohort selection in clinical trials.