Assessing Genetic Overlap and Causality Between Blood Plasma Proteins and Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Blood plasma proteins have been associated with Alzheimer's disease (AD), but understanding which proteins are on the causal pathway remains challenging. OBJECTIVE: Investigate the genetic overlap between candidate proteins and AD using polygenic risk scores (PRS) and interrogate their causal relationship using bi-directional Mendelian randomization (MR). METHODS: Following a literature review, 31 proteins were selected for PRS analysis. PRS were constructed for prioritized proteins with and without the apolipoprotein E region (APOE+/-PRS) and tested for association with AD status across three cohorts (n = 6,244). An AD PRS was also tested for association with protein levels in one cohort (n = 410). Proteins showing association with AD were taken forward for MR. RESULTS: For APOE ɛ3, apolipoprotein B-100, and C-reactive protein (CRP), protein APOE+ PRS were associated with AD below Bonferroni significance (pBonf, p < 0.00017). No protein APOE- PRS or AD PRS (APOE+/-) passed pBonf. However, vitamin D-binding protein (protein PRS APOE-, p = 0.009) and insulin-like growth factor-binding protein 2 (AD APOE- PRS p = 0.025, protein APOE- PRS p = 0.045) displayed suggestive signals and were selected for MR. In bi-directional MR, none of the five proteins demonstrated a causal association (p < 0.05) in either direction. CONCLUSION: Apolipoproteins and CRP PRS are associated with AD and provide a genetic signal linked to a specific, accessible risk factor. While evidence of causality was limited, this study was conducted in a moderate sample size and provides a framework for larger samples with greater statistical power.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".