Serum placental growth factor as a biomarker of cerebrovascular changes in Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: While Alzheimer's disease (AD) biomarkers are now widely used, those focusing on vascular etiologies remain underdeveloped. Among candidates, angiogenesis markers appear particularly promising. Placental growth factor (PlGF) plays a key role in tissue vascularization and regulation of vascular permeability, in addition to being reactive to cerebral ischemia. Here, we aimed to establish the role of PIGF in AD by examining its association with selected MRI markers of cerebrovascular disease (CVD). METHOD: We measured serum concentrations of PIGF (U-PLEX Human PIGF Assay, Meso Scale Discovery) in elderly individuals with subjective cognitive impairment (n = 114), mild cognitive impairment (n = 86), early AD (n = 29) and controls (n = 55) from the CIMA-Q cohort. MRI CVD markers included regional white matter hyperintensity (WMH) volumes and microbleeds acquired through validated segmentation tools. PlGF levels were compared across groups using one-way ANOVA, while associations with age, sex, vascular risk factors, cognition, and AD biomarkers were analyzed using Pearson/Spearman tests. Linear regression models adjusted for age, sex, and ApoE4 examined the link between PlGF and MRI CVD markers. RESULT: Serum PlGF was found to be higher in men than women (p = .02) and to increase with age (p = .003) but did not differ between clinical groups. Among vascular and metabolic parameters, PlGF levels correlated positively with waist size, weight and triglycerides levels (p <.005). There was also a trend between PlGF levels and diastolic, but not systolic, blood pressure (p = .05). Serum pTau217 was the only AD biomarker associated with PlGF (p <.05). We could not find any direct association between PlGF and cognition. PlGF levels correlated with total (r=0.19, p = .03) and deep cerebellar (r=0.18, p = .04) microbleeds, but not WMH. In regression models, the association between PlGF and microbleeds remain consistent in APOE4 carriers (b=2.1, p = .04) and in men (b=1.8, p = .03) only. CONCLUSION: Serum PlGF is a promising biomarker of CVD, especially cerebral microbleeds, in AD. Our results suggest that its role may specifically apply to certain subpopulations such as APOE4 carriers. In the era of anti-amyloid therapies, understanding mechanisms linking PlGF to CVD is of utmost importance to evaluate its potential for safety and monitoring purposes.
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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 | 0.000 | 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".