Effect of EPHA1 Genetic Variation on Cerebrospinal Fluid and Neuroimaging Biomarkers in Healthy, Mild Cognitive Impairment and Alzheimer's Disease Cohorts
Bibliographic record
Abstract
Ephrin type-A receptor 1 (EPHA1) (11771145) was documented to be one of the most strongly associated locus with Alzheimer's disease (AD) in a recent meta-analysis of five genome wide association studies. However, its contribution to the pathogenesis of AD remains unclear to date. Here, we addressed the role of EPHA1 in AD by investigating the influence of EPHA1 on cerebrospinal fluid and neuroimaging biomarkers in three clinical stages from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We did not detect significant association of EPHA1 with amyloid-β deposition or tau protein. However, the A-allele in the mild cognitive impairment group remarkably prevented hippocampal atrophy (partial correlation coefficient 2.812, 95% CI 0.651 to 4.973) at two-year follow-up. Additionally, AD subjects with the A-allele displayed less atrophy and greater cerebral metabolic rate for glucose (CMRgl) in the right lateral occipitotemporal gyrus (volume: partial correlation coefficient 540.10, 95% CI 247.26 to 832.95; CMRgl: partial correlation coefficient 0.056, 95% CI 0.024 to 0.087) and inferior temporal gyrus (volume: partial correlation coefficient 327.98, 95% CI 11.65 to 644.31; CMRgl: partial correlation coefficient 0.055, 95% CI 0.019 to 0.091) at baseline. This study suggests EPHA1 (rs11771145) interferes with the pathological alteration of the hippocampus and the lateral occipitotemporal and inferior temporal gyri throughout the AD process, leading to a lower risk of AD. However, the limited sample size and follow-up as well as the diversity across ethnicities precluded explanation of these findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".