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Record W4381125374 · doi:10.1136/gutjnl-2023-bsg.134

P62 African-specific IBD susceptibility loci previously identified in African Americans are reflected in patients with IBD in Zambia

2023· article· en· W4381125374 on OpenAlexaboutno aff
Phoebe Hodges, Monica Mweetwa, Joyce Sibwani, Emebet Mengesha, Talin Haritunians, Dermot McGovern, Paul Kelly

Bibliographic record

VenuePoster presentations · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsGenotypingSingle-nucleotide polymorphismPopulationUlcerative colitisAllele frequencyGenotypeMedicineLogistic regressionGeneticsBiologyInternal medicineDiseaseGeneEnvironmental health

Abstract

fetched live from OpenAlex

Introduction Scarcity of IBD in sub-Saharan Africa may reflect both differing population genetic disposition and exposure to environmental factors, however, little data relating to this has been published to date. Our aim was to perform genetic analyses of IBD in Zambian subjects. Methods Saliva was collected in Oragene DNA collection tubes (DNAGenotek, Ottawa, Canada) from IBD cases and controls in the GI clinic of a tertiary hospital in Zambia and stored at 4C. DNA was extracted using the NucleoSpin Tissue kit (Macherey-Nagel) and genotyped using the H3Africa Consortium Array (Illumina). Genetic association for genotyped and imputed SNPs case-control binary variable was performed using logistic regression including principal components for population sub-structure as covariates (PLINKv1.9). Variant effect prediction and functional analysis were performed using the Ensembl platform and ClueGO software. Results Genotyping was performed on 16 cases (14 UC, 2 Crohn’s) and 29 controls. Variants were present on LSAMP and ELMO1 which have previously been described as novel risk loci for UC and IBD respectively in African American cohorts.1 2 A variant on IL23R (rs790631:G>A, allele frequency 8.6% cases and 25% controls, (p=3.44 x10-2, OR 0.283)) has previously been associated with increased risk of Crohn’s in a Caucasian population.3 No variants on NOD2, ATG16L1 or CARD9 were present. The SNP with the strongest association with IBD (OR 9.51) was rs3763236:G>A (allele frequency 63.8% cases and 15.6% controls), an intron variant on CNPY3, which encodes a toll-like receptor-specific chaperone protein and has not previously been identified as a risk locus for IBD. Functional pathway analysis (figure 1) shows pathways with significant enrichment which included Type 1 diabetes and the extra-cellular matrix which have previously been implicated in IBD. Conclusions IBD risk loci that have previously been identified as African specific in African American cohorts are reflected in this small cohort of sub-Saharan African patients. These findings suggest that additional and larger studies are needed to determine the genetic architecture of under researched populations in which IBD is emerging. References Brant SR, Okou DT, Simpson CL, Cutler DJ, Haritunians T, Bradfield JP, et al. Genome-wide association study identifies African-specific susceptibility loci in African Americans with inflammatory bowel disease. Gastroenterology. 2017;152(1):206–17.e2. Cordero RY, Cordero JB, Stiemke AB, Datta LW, Buyske S, Kugathasan S, et al. Trans-ancestry, bayesian meta-analysis discovers 20 novel risk loci for inflammatory bowel disease in an African American, East Asian, and European cohort. Hum Mol Genet. 2022. Taylor KD, Targan SR, Mei L, Ippoliti AF, McGovern D, Mengesha E, et al. IL23R haplotypes provide a large population attributable risk for Crohn’s disease. Inflamm Bowel Dis. 2008;14(9):1185–91.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.018
GPT teacher head0.273
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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