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Record W2042573312 · doi:10.1089/gte.2008.0013

Ethnic Differences in the Frequency of the Cardioprotective C679X PCSK9 Mutation in a West African Population

2008· article· en· W2042573312 on OpenAlexaff
Francine Sirois, Elias Gbeha, Ambaliou Sanni, Michel Chrétien, Damian Labuda, Majambu Mbikay

Bibliographic record

VenueGenetic Testing · 2008
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversité de MontréalOttawa Hospital
Fundersnot available
KeywordsPCSK9Allele frequencyMutationEthnic groupPopulationGeneticsLoss of heterozygosityBiologyApolipoprotein BInternal medicineAlleleLDL receptorEndocrinologyGeneCholesterolMedicineLipoproteinEnvironmental health

Abstract

fetched live from OpenAlex

PCSK9 is a liver-secreted blood protein that promotes the degradation of low-density lipoprotein receptors, leading to reduced hepatic uptake of plasma cholesterol. Nucleotide variations in its gene have been linked to hypo- and hyper-cholesterolemia. Two nonsense mutations, Y142X and C679X, are associated to lifelong hypocholesterolemia and a remarkable protection against coronary heart disease (CHD) in African Americans. The aim of this study was to determine the frequency of these cardioprotective mutations in West Africans. Subjects (n = 520) from different ethnic groups were recruited in Burkina-Faso, Benin, and Togo. Only the C679X mutation was detected. All carriers were heterozygous. The overall heterozygosity frequency was 3.3%. It varied significantly among ethnic groups, ranging from 0% to 6.9%. The overall high frequency of the cardioprotective C679X mutation in Africa may contribute to the lower incidence of CHD on this continent. The interethnic frequency differences may reflect historical settlement and migration patterns in the region, possibly combined with positive selection for the mutation driven by yet-unknown environmental factors.

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 score0.006

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)0.0020.000

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 head0.062
GPT teacher head0.271
Teacher spread0.209 · 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".

Quick stats

Citations18
Published2008
Admission routes1
Has abstractyes

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