Influence of PLEK Genetic Variants on Brain Glucose Metabolism
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder shaped by genetic factors. Expression quantitative trait loci (eQTL) mapping identifies how genetic variants regulate gene expression, offering a powerful tool for uncovering the mechanisms underlying the disease. In this study, we adopted a data-driven approach to explore the relationships between genetic variants, blood gene expression, and FDG-PET imaging using the ADNI dataset. We hypothesized that regulatory effects revealed through eQTL mapping are associated with changes in brain FDG-PET imaging. METHODS: We analyzed genomic and blood transcriptomic data from 746 individuals across the AD continuum in the ADNI dataset. eQTL mapping of gene-single nucleotide polymorphism (SNP) pairs was performed using the MatrixEQTL package in the R statistical environment, accounting for age and sex covariates. Significance was defined as an FDR-adjusted p-value < 0.01 and an absolute beta value > 0.5. Subsequently, voxel-wise regression analyses on FDG-PET imaging data were conducted with the RMINC package to evaluate associations between gene-SNP interactions and brain glucose metabolism. RESULTS: Out of 10,558 genes and 477,532 SNPs analyzed, 5,278 SNPs were significantly associated with changes in the expression of 217 genes. We analyzed the 11 SNP pairs with the strongest effects on expression patterns for each gene, including both upregulation and downregulation. Voxel-wise regression analysis assessed the interaction between SNP carriership and gene expression on FDG-PET. This revealed that carriers of the PLEK SNP rs8761, associated with PLEK gene downregulation (Figure 1A), exhibited FDG-PET hypermetabolism in the frontal and temporal cortices. In contrast, the PLEK SNP rs1063479, linked to PLEK gene upregulation, did not show significant changes in the FDG-PET signal (Figure 1B). CONCLUSION: The PLEK gene encodes pleckstrin, a plasma protein involved in the innate immune response and expressed in glial cells. Variants of PLEK associated with FDG-PET imaging suggest a potential link between a plasma protein related to immune cells and brain glucose metabolism. To our knowledge, the role of PLEK in brain glucose metabolism has not been previously reported. Therefore, future studies should explore these associations to better understand the underlying mechanisms and their implications for AD pathology.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".