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Record W2801932994 · doi:10.1186/s12882-018-0890-9

Assessing known chronic kidney disease associated genetic variants in Saudi Arabian populations

2018· article· en· W2801932994 on OpenAlexaff
Cyril Cyrus, Samir Al-Mueilo, Chittibabu Vatte, Shahanas Chathoth, Leslie A. Lange, Hatem Qutub, Rudaynah Al Ali, Fahad Al‐Muhanna, Matthew B. Lanktree, Khaled R. Alkharsah, Abdullah M. Al‐Rubaish, Brian Kim-Mozeleski, Brendan J. Keating, Amein Al Ali

Bibliographic record

VenueBMC Nephrology · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsKidney diseaseMedicineInternal medicineRenal functionMinor allele frequencyGenetic associationNephrologyGenome-wide association studyLogistic regressionGenetic variationCohortAlleleGenotypeAllele frequencyGeneticsPopulationSingle-nucleotide polymorphismBiologyGeneEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Genome wide association studies of patients with European descent have identified common variants associated with risk of reduced estimated glomerular filtration rate (eGFR). A panel of eight variants were selected to evaluate their association and prevalence in a Saudi Arabian patient cohort with chronic kidney disease (CKD). METHODS: ) and effects were compared with results obtained from 133,413 participants in the CKD genetics consortium. Multivariable regression was used to evaluate the role of these eight variants in improving prediction of CKD development. RESULTS: All eight variants were present in Saudi populations with minor allele frequency ranging from 16 to 46%. The risk variant in all four genes demonstrated the same direction of effect as observed in European populations. One variant, rs4821480, in MYH9 was significantly associated with increased risk of development of CKD (OR = 1.69, 95% CI 1.22-2.36, P = 0.002), but the additional variants were not statistically significant given our modest sample size. CONCLUSIONS: CKD risk variants identified in European populations are present in Saudis. We did not find evidence to suggest heterogeneity of effect size compared to previously published estimates in European populations. Multivariable logistic regression analysis showed a statistically significant improvement in predicting the CKD using models with either FGF23 and vitamin D or FGF23, vitamin D level, and MYH9 genotypes (AUC = 0.93, 95% CI 0.90-0.95, P < 0.0001).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.319
Teacher spread0.284 · 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 teacher head, not a consensus.

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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