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Record W2143417044 · doi:10.1371/journal.pgen.1002491

A Meta-Analysis and Genome-Wide Association Study of Platelet Count and Mean Platelet Volume in African Americans

2012· review· en· W2143417044 on OpenAlexaff
Rehan Qayyum, Beverly M. Snively, Elad Ziv, Michael A. Nalls, Ching‐Ti Liu, Weihong Tang, Lisa R. Yanek, Leslie A. Lange, Michele K. Evans, Santhi K. Ganesh, Melissa A. Austin, Guillaume Lettre, Diane M. Becker, Alan B. Zonderman, Andrew B. Singleton, Tamara B. Harris, Emile R. Mohler, Benjamin A. Logsdon, Charles Kooperberg, Aaron R. Folsom, James G. Wilson, Lewis C. Becker, Alex P. Reiner

Bibliographic record

VenuePLoS Genetics · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Institute on Minority Health and Health DisparitiesNational Center for Research ResourcesNational Cancer InstituteNational Center on Minority Health and Health DisparitiesNational Human Genome Research InstituteNational Institute on AgingUniversity of California, IrvineWake Forest UniversityKaiser Foundation Research InstituteNational Institutes of HealthBroad InstituteWomen's Health InitiativeJackson State UniversityJohns Hopkins UniversityNational Heart, Lung, and Blood InstituteNorthwestern UniversityUniversity of Minnesota
KeywordsGenome-wide association studyMean platelet volumeBiologyGenetic associationPlateletGeneticsPopulationPopulation stratificationSingle-nucleotide polymorphismInternal medicineImmunologyGeneGenotypeMedicine

Abstract

fetched live from OpenAlex

Several genetic variants associated with platelet count and mean platelet volume (MPV) were recently reported in people of European ancestry. In this meta-analysis of 7 genome-wide association studies (GWAS) enrolling African Americans, our aim was to identify novel genetic variants associated with platelet count and MPV. For all cohorts, GWAS analysis was performed using additive models after adjusting for age, sex, and population stratification. For both platelet phenotypes, meta-analyses were conducted using inverse-variance weighted fixed-effect models. Platelet aggregation assays in whole blood were performed in the participants of the GeneSTAR cohort. Genetic variants in ten independent regions were associated with platelet count (N = 16,388) with p<5×10(-8) of which 5 have not been associated with platelet count in previous GWAS. The novel genetic variants associated with platelet count were in the following regions (the most significant SNP, closest gene, and p-value): 6p22 (rs12526480, LRRC16A, p = 9.1×10(-9)), 7q11 (rs13236689, CD36, p = 2.8×10(-9)), 10q21 (rs7896518, JMJD1C, p = 2.3×10(-12)), 11q13 (rs477895, BAD, p = 4.9×10(-8)), and 20q13 (rs151361, SLMO2, p = 9.4×10(-9)). Three of these loci (10q21, 11q13, and 20q13) were replicated in European Americans (N = 14,909) and one (11q13) in Hispanic Americans (N = 3,462). For MPV (N = 4,531), genetic variants in 3 regions were significant at p<5×10(-8), two of which were also associated with platelet count. Previously reported regions that were also significant in this study were 6p21, 6q23, 7q22, 12q24, and 19p13 for platelet count and 7q22, 17q11, and 19p13 for MPV. The most significant SNP in 1 region was also associated with ADP-induced maximal platelet aggregation in whole blood (12q24). Thus through a meta-analysis of GWAS enrolling African Americans, we have identified 5 novel regions associated with platelet count of which 3 were replicated in other ethnic groups. In addition, we also found one region associated with platelet aggregation that may play a potential role in atherothrombosis.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.021
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.091
GPT teacher head0.311
Teacher spread0.220 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations110
Published2012
Admission routes1
Has abstractyes

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