Multiscale genetic architecture of donor-recipient differences reveals intronic LIMS1 locus mismatches associated with long-term renal transplant survival
Bibliographic record
Abstract
Abstract Background Long-term kidney allograft survival remains suboptimal. Emerging evidence indicates donor-recipient (D-R) mismatches outside of human leukocyte antigens (HLA) contribute to graft survival but mechanisms remain unclear, specifically for those mismatches within intronic regions. Methods We analyzed genome-wide SNP data of D-R pairs from two well-phenotyped kidney transplant cohorts (median follow-up ~1800 days), Genomics of Chronic Allograft Rejection (GoCAR; n=385) and Clinical Trials in Organ Transplantation 1/17 (CTOT1/17; n=146), quantifying genetic mismatches outside of HLA for every D-R pair at variant, gene, and genome-wide scales. Results Unbiased genome-wide screen of GoCAR D-R pairs uncovered the LIMS1 locus as the topranked candidate where D-R mismatches associated with death censored graft loss (DCGL). Independent of HLA, a previously unreported relationship between mismatches at a highly linked, intronic haplotype of 30 SNPs was seen as associated with DCGL, with confirmatory association in intra-ancestry D-Rs. Validation testing within the CTOT-01/17 showed similar associations with DCGL. Haplotype D-R mismatches showed a dosage effect, and the introduction of minor alleles in the donor to major allele-carrying recipients showed a greater risk of DCGL. Both the new LIMS1 haplotype and the previously reported LIMS1 SNP rs893403 are expression quantitative trait loci (eQTL) for the gene GCC2 in recipient immune cells, without alterations in GCC2 or LIMS1 coding sequences. Transcriptome enrichment analyses performed on whole blood and within multiple T cell subsets demonstrated significant associations of GCC2 gene, and of either allelic locus, with regulation of TGF-beta-SMAD signaling, implying a role in Treg function and association with rejection. Conclusions Our analysis unravels intronic non-HLA SNP mismatches within LIMS1 that do not induce protein sequence variation but associate with DCGL. By acting as cis-eQTLs for GCC2 expression, these SNPs modulates TGF-beta signaling and T cell function, associating with immune events and graft outcomes. The findings have clinical implications for risk assessment and individualized therapy in kidney transplant recipients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".