Alzheimer's disease and cerebrovascular disease biomarkers in older adults with mild cognitive impairment or major depressive disorder
Bibliographic record
Abstract
Abstract Background Mild Cognitive Impairment (MCI) and Major Depressive Disorder (MDD) are independently associated with increased risk of dementia. Cerebrospinal fluid (CSF) and neuroimaging biomarkers can help to elucidate the etiology of cognitive impairment. We compared CSF biomarker profiles of Alzheimer’s disease (AD) and white matter hyperintensities (WMH) across three groups: MCI, MDD, or comorbid MCI+MDD. Method We measured CSF total tau, p‐tau, amyloid‐β42, using a sandwich ELISA method (Innotest, Fujirebio), and calculated p‐tau/amyloid‐β42 ratio in 31 participants diagnosed with MCI (N=13), MDD (N=7), or both MCI and MDD (N=11) enrolled in the Preventing Alzheimer’s dementia with cognitive remediation plus transcranial direct current stimulation in mild cognitive impairment and depression (PACt‐MD) study. All diagnoses were made in accordance with NIA‐AA and DSM 5 criteria. Participants with p‐tau > 68 pg/mL and ATI < 0.8 were considered AD (+). WMH were quantified on T2‐weighted magnetic resonance images in 27 of the participants. We compared CSF AD biomarkers across diagnostic groups. We then compared cognitive performance and WMH in those with AD (+) versus AD (‐) CSF biomarkers. Result 9/31 participants exhibited AD (+) CSF: 7/13 with MCI and 2/11 with MCI+MDD. Participants with AD (+) CSF showed more impairment in verbal memory, working memory, language, and overall cognition than those with AD (‐) CSF (p=0.02, p=0.04, p=0.04, and p=0.03, respectively). 26/27 (96%) participants exhibited moderate to severe WMH irrespective of diagnosis or AD biomarker status. Conclusion Few participants in our sample with MDD had an AD (+) CSF biomarker profile, despite a neurocognitive profile of MCI. All participants with AD (‐) CSF had moderate to severe WMH, including those with MDD alone. Further investigation should determine whether volume or distribution of WMH contribute to cognitive impairment or depression in MCI patients who have an AD (‐) CSF biomarker profile.
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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) | 0.001 | 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) | 0.001 | 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".