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Record W1981020155 · doi:10.1371/journal.pgen.1002718

Meta-Analysis of Genome-Wide Scans for Total Body BMD in Children and Adults Reveals Allelic Heterogeneity and Age-Specific Effects at the WNT16 Locus

2012· review· en· W1981020155 on OpenAlexaff
Carolina Medina‐Gómez, John P. Kemp, Karol Estrada, Joel Eriksson, Jeff Liu, Sjur Reppe, David M. Evans, Denise H. M. Heppe, Liesbeth Vandenput, Lizbeth Herrera, Susan M. Ring, Claudia J. Kruithof, Nicholas J. Timpson, M. Carola Zillikens, Ole Kristoffer Olstad, Hou‐Feng Zheng, J. Brent Richards, Beaté St Pourcain, Albert Hofman, Vincent W. V. Jaddoe, George Davey Smith, Mattias Lorentzon, Kaare M. Gautvik, André G. Uitterlinden, Robert Brommage, Claes Ohlsson, Jonathan H. Tobias, Fernando Rivadeneira

Bibliographic record

VenuePLoS Genetics · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsJewish General HospitalMcGill University
FundersErasmus+Education, Audiovisual and Culture Executive AgencyMedical Research CouncilNovo Nordisk FondenVetenskapsrådetNovo NordiskUniversity of BristolErasmus Medisch CentrumZonMwStiftelsen för Strategisk ForskningErasmus Universiteit RotterdamGöteborgs UniversitetEuropean CommissionNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome Trust
KeywordsBiologyLocus (genetics)Minor allele frequencyGenome-wide association studyLinkage disequilibriumBone mineralGeneticsQuantitative trait locusSingle-nucleotide polymorphismGenotypingAllelePopulationBone densityEndocrinologyInternal medicineAllele frequencyGenotypeGeneMedicineOsteoporosis

Abstract

fetched live from OpenAlex

To identify genetic loci influencing bone accrual, we performed a genome-wide association scan for total-body bone mineral density (TB-BMD) variation in 2,660 children of different ethnicities. We discovered variants in 7q31.31 associated with BMD measurements, with the lowest P = 4.1 × 10(-11) observed for rs917727 with minor allele frequency of 0.37. We sought replication for all SNPs located ± 500 kb from rs917727 in 11,052 additional individuals from five independent studies including children and adults, together with de novo genotyping of rs3801387 (in perfect linkage disequilibrium (LD) with rs917727) in 1,014 mothers of children from the discovery cohort. The top signal mapping in the surroundings of WNT16 was replicated across studies with a meta-analysis P = 2.6 × 10(-31) and an effect size explaining between 0.6%-1.8% of TB-BMD variance. Conditional analyses on this signal revealed a secondary signal for total body BMD (P = 1.42 × 10(-10)) for rs4609139 and mapping to C7orf58. We also examined the genomic region for association with skull BMD to test if the associations were independent of skeletal loading. We identified two signals influencing skull BMD variation, including rs917727 (P = 1.9 × 10(-16)) and rs7801723 (P = 8.9 × 10(-28)), also mapping to C7orf58 (r(2) = 0.50 with rs4609139). Wnt16 knockout (KO) mice with reduced total body BMD and gene expression profiles in human bone biopsies support a role of C7orf58 and WNT16 on the BMD phenotypes observed at the human population level. In summary, we detected two independent signals influencing total body and skull BMD variation in children and adults, thus demonstrating the presence of allelic heterogeneity at the WNT16 locus. One of the skull BMD signals mapping to C7orf58 is mostly driven by children, suggesting temporal determination on peak bone mass acquisition. Our life-course approach postulates that these genetic effects influencing peak bone mass accrual may impact the risk of osteoporosis later in life.

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)0.012
metaresearch head score (Gemma)0.018
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.016
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
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 head0.062
GPT teacher head0.303
Teacher spread0.241 · 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
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

Citations168
Published2012
Admission routes1
Has abstractyes

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