Pathologic correlates of aging-related tau astrogliopathy: ARTAG is associated with LATE-NC and cerebrovascular pathologies, but not with ADNC
Bibliographic record
Abstract
Age-related tau astrogliopathy (ARTAG) is detectable in the brains of over one-third of autopsied persons beyond age 80, but the pathoetiology of ARTAG is poorly understood. Insights can be gained by analyzing risk factors and comorbid pathologies. Here we addressed the question of which prevalent co-pathologies are observed with increased frequency in brains with ARTAG. The study sample was the National Alzheimer's Coordinating Center (NACC) data set, derived from multiple Alzheimer's disease research centers (ADRCs) in the United States. Data from persons with unusual conditions (e.g. frontotemporal dementia) were excluded leaving 504 individual autopsied research participants, clustering from 20 different ADRCs, autopsied since 2020; ARTAG was reported in 222 (44.0%) of included participants. As has been shown previously, ARTAG was increasingly frequent with older age and in males. The presence and severity of other common subtypes of pathology that were previously linked to dementia were analyzed, stratifying for the presence of ARTAG. In logistical regression-based statistical models that included age and sex as covariates, ARTAG was relatively more likely to be found in brains with limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), and in brains with comorbid cerebrovascular pathology (arteriolosclerosis and/or brain infarcts). However, ARTAG was not associated with severe Alzheimer's disease neuropathologic change (ADNC), or primary age-related tauopathy (PART). In a subset analysis of 167 participants with neurocognitive testing data, there was a marginal trend for ARTAG pathology to be associated with cognitive impairment as assessed with MMSE scores (P = 0.07, adjusting for age, sex, interval between final clinic visit and death, and ADNC severity). A limitation of the study was that there were missing data about ARTAG pathologies, with incomplete operationalization of ARTAG according to anatomic region and pathologic subtypes (e.g., thorn-shaped or granular-fuzzy astrocytes). In summary, ARTAG was not associated with ADNC, whereas prior observations about ARTAG occurring with increased frequency in aging, males, and brains with LATE-NC were replicated. It remains to be determined whether the increased frequency of ARTAG in brains with comorbid cerebrovascular pathology is related to local infarctions or neuroinflammatory signaling, or with some other set of correlated factors including blood-brain barrier dysfunction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".