Mapping of PARK2 and PACRG Overlapping Regulatory Region Reveals LD Structure and Functional Variants in Association with Leprosy in Unrelated Indian Population Groups
Bibliographic record
Abstract
Leprosy is a chronic infectious disease caused by Mycobacterium Leprae, where the host genetic background plays an important role toward the disease pathogenesis. Various studies have identified a number of human genes in association with leprosy or its clinical forms. However, non-replication of results has hinted at the heterogeneity among associations between different population groups, which could be due to differently evolved LD structures and differential frequencies of SNPs within the studied regions of the genome. A need for systematic and saturated mapping of the associated regions with the disease is warranted to unravel the observed heterogeneity in different populations. Mapping of the PARK2 and PACRG gene regulatory region with 96 SNPs, with a resolution of 1 SNP per 1 Kb for PARK2 gene regulatory region in a North Indian population, showed an involvement of 11 SNPs in determining the susceptibility towards leprosy. The association was replicated in a geographically distinct and unrelated population from Orissa in eastern India. In vitro reporter assays revealed that the two significantly associated SNPs, located 63.8 kb upstream of PARK2 gene and represented in a single BIN of 8 SNPs, influenced the gene expression. A comparison of BINs between Indian and Vietnamese populations revealed differences in the BIN structures, explaining the heterogeneity and also the reason for non-replication of the associated genomic region in different populations.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".