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Record W3019182562 · doi:10.1053/j.ajkd.2020.01.006

Association of Genetic Polymorphisms of TGF-β1, HMOX1, and APOL1 With CKD in Nigerian Patients With and Without HIV

2020· article· en· W3019182562 on OpenAlexaff
Udeme E. Ekrikpo, Khuthala Mnika, Emmanuel Effa, Samuel Ajayi, Chimezie Okwuonu, Bala Waziri, Aminu K. Bello, Collet Dandara, André Pascal Kengne, Ambroise Wonkam, Ikechi G. Okpechi

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsUniversity of Alberta
FundersNational Human Genome Research InstituteNational Heart, Lung, and Blood Institute
KeywordsSingle-nucleotide polymorphismMinor allele frequencyMedicineKidney diseaseContext (archaeology)GenotypeOdds ratioAlleleInternal medicineAllele frequencyGenotypingImmunologyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

RATIONALE & OBJECTIVE: Recent studies in the human immunodeficiency virus (HIV)-infected population have suggested that there are genetic predispositions to the development of chronic kidney disease (CKD) in this context. We investigated the association of genetic polymorphisms of the genes encoding apolipoprotein L1 (APOL1), transforming growth factor β1 (TGF-β1; a profibrotic cytokine), and heme oxygenase 1 (HMOX1) with prevalent CKD among adults with and without HIV infection. STUDY DESIGN: Case-control study. SETTING & PARTICIPANTS: group). EXPOSURE: The genetic polymorphisms with reference single-nucleotide polymorphism (rs) identification numbers rs1800469 (TGF-β1), rs1800470 (TGF-β1), rs121918282 (TGF-β1); rs60910145 (APOL1 G1 risk allele), rs73885319 (APOL1 G1 risk allele), rs71785313 (APOL1 G2 risk allele), and rs743811 (HMOX1); HIV. OUTCOME: CKD. ANALYTICAL APPROACH: Single-nucleotide polymorphism (SNP) genotyping of rs1800469 (TGF-β1), rs1800470 (TGF-β1), rs121918282 (TGF-β1); rs60910145 (APOL1), rs73885319 (APOL1), rs71785313 (APOL1), and rs743811 (HMOX1) was performed. Hardy-Weinberg equilibrium was evaluated for all SNPs, and minor allele frequencies were reported. A case-control analysis was performed, and multivariable logistic regression was used to control for potential confounders. RESULTS: Minor allele frequencies for TGF-β1 (rs1800469, rs1800470, and rs1800471), APOL1 (rs60910145, rs73885319, and rs71785313), and HMOX1 (rs743811) were 0.25, 0.46, 0.46, 0.44, 0.45, 0.17, and 0.14, respectively. Among HIV-positive individuals, only TGF-β1 rs1800470 (GG vs AA), APOL1 (in the recessive model), and hypertension were associated with prevalent CKD (adjusted ORs of 0.44 [95% CI, 0.20-0.97], 2.54 [95% CI, 1.44-4.51], and 2.17 [95% CI, 1.35-3.48], respectively). No SNP polymorphisms were associated with prevalent CKD among HIV-negative individuals. LIMITATIONS: The lack of histopathology data for proper categorization of the type of HIV-related nephropathy. CONCLUSIONS: APOL1 polymorphisms were highly prevalent in this population and among adult patients infected with HIV and were associated with increased CKD risk. The TGF-β1 (rs1800470) polymorphism was associated with reduced risk, and HMOX1 polymorphisms were unassociated with CKD.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.002
GPT teacher head0.176
Teacher spread0.173 · 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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Citations23
Published2020
Admission routes1
Has abstractyes

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