1H-MR spectroscopy biomarkers are associated with plasma-derived biomarkers of amyloid-β and tau in the early phase of AD continuum
Bibliographic record
Abstract
The objective of the study was to evaluate the relationship of plasma biomarkers of Alzheimer's disease (AD) with in vivo proton magnetic resonance spectroscopy (¹H-MRS) markers, and their association with cognitive function across the early stages of the AD continuum. Determining these associations may clarify the AD-related biological pathways and support the development of integrated AD blood and ¹H-MRS biomarkers for early detection of these pathways. Fifty-five older adults (40 cognitively unimpaired; 15 mild cognitive impairment) from the Mayo Clinic Study of Aging underwent single-voxel ¹H-MRS (sLASER) at 3T in the posterior cingulate gyrus (PCG) and left hippocampus (LH), along with plasma assays for Aβ42/40, phosphorylated tau (p-tau181), and the p-tau181/Aβ42 ratio. Associations between plasma biomarkers and ¹H-MRS metabolites (myo-inositol [mIns]/total creatine [tCr], total N-acetylaspartate [tNAA]/tCr, and tNAA/mIns) were examined using partial Spearman correlations (rho, ρ) adjusted for age and sex. Next, associations of the Mini-Mental State Examination with p-tau181/Aβ42 and tNAA/mIns were examined adjusting for the same covariates plus education. In both PCG and LH regions, lower tNAA/mIns was associated with higher p-tau181/Aβ42 (PCG:ρ=-0.59; LH:ρ=-0.54) and p-tau181 (PCG: ρ=-0.38; LH:ρ =-0.39), as well as with lower Aβ42/40 (PCG:ρ=0.40; LH:ρ=0.32). Higher mIns/tCr was associated with higher p-tau181/Aβ42 (PCG: ρ=0.56; LH:ρ=0.46) and p-tau181 (PCG:ρ=0.37; LH:ρ=0.31). Lower PCG and LH tNAA/mIns ratios were associated with lower MMSE (PCG:ρ=0.53; LH:ρ=0.46), while higher p-tau181/Aβ42 was associated with lower MMSE (ρ=-0.49). ¹H-MRS-derived gliosis and neuronal injury biomarkers are associated with early AD pathology, and cognitive performance, supporting their use as noninvasive biomarkers in early AD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".