A Multi-Omics Epidemiologic Study of Alzheimer’s disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alzheimer’s disease (AD) is a devastating neurodegenerative disease that accounts for more than 70% of worldwide dementia cases. The rising AD prevalence in aging populations is posing a substantial economic and health challenge. Unfolding the events leading to the development of AD may guide drug and preventive treatment research. Recent advances in multi-omics technology enable us to disentangle the molecular mechanism underlying AD pathophysiology. I have used multi-omics layers to enhance further our understanding of the molecular pathways underlying AD risk and pathophysiology. In this thesis, I identified biological pathways that may contribute to early AD pathology. I also evaluated the role of proteins and metabolites in the circulation and their interaction with AD risk genes. I found elevated levels of the HAGH and CDH6 proteins in blood in pre-dementia cases in the Rotterdam Study, and findings were replicated in an independent cohort. Findings from this thesis also underscore the role of signaling lipids in the pathophysiology of AD. Finally, this thesis provides new insight into the determinants of the gut-liver-brain axis in AD.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it