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Record W2122186098 · doi:10.1371/journal.pgen.1003247

Genetic Determinants of Trabecular and Cortical Volumetric Bone Mineral Densities and Bone Microstructure

2013· review· en· W2122186098 on OpenAlexaff
Lavinia Paternoster, Mattias Lorentzon, Terho Lehtimäki, Joel Eriksson, Mika Kähönen, Olli T. Raitakari, Marika Laaksonen, Harri Sievänen, Jorma Viikari, Leo‐Pekka Lyytikäinen, Dan Mellström, Magnus K. Karlsson, Östen Ljunggren, Elin Grundberg, John P. Kemp, Adrian Sayers, Maria Nethander, David M. Evans, Liesbeth Vandenput, Jonathan H. Tobias, Claes Ohlsson

Bibliographic record

VenuePLoS Genetics · 2013
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcGill UniversityMcGill University and Génome Québec Innovation Centre
FundersMedical Research CouncilTurun Yliopistollinen KeskussairaalaEmil Aaltosen SäätiöVetenskapsrådetTampereen TuberkuloosisäätiöNovo NordiskJuho Vainion SäätiöSuomen KulttuurirahastoNovo Nordisk FondenAcademy of FinlandPaavo Nurmen SäätiöUniversity of BristolKelaStiftelsen för Strategisk ForskningEuropean CommissionSahlgrenska UniversitetssjukhusetWellcome Trust
KeywordsQuantitative computed tomographyGenome-wide association studyBone mineralBiologyOsteoporosisBone densityGenetic epidemiologyQuantitative trait locusInternal medicineCortical boneGeneticsEndocrinologyMedicineAnatomySingle-nucleotide polymorphismGenotypeGene

Abstract

fetched live from OpenAlex

Most previous genetic epidemiology studies within the field of osteoporosis have focused on the genetics of the complex trait areal bone mineral density (aBMD), not being able to differentiate genetic determinants of cortical volumetric BMD (vBMD), trabecular vBMD, and bone microstructural traits. The objective of this study was to separately identify genetic determinants of these bone traits as analysed by peripheral quantitative computed tomography (pQCT). Separate GWA meta-analyses for cortical and trabecular vBMDs were performed. The cortical vBMD GWA meta-analysis (n = 5,878) followed by replication (n = 1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, p = 3.6×10⁻¹⁴; LOC285735, rs271170, p = 2.7×10⁻¹²; OPG, rs7839059, p = 1.2×10⁻¹⁰; and ESR1/C6orf97, rs6909279, p = 1.1×10⁻⁹). The trabecular vBMD GWA meta-analysis (n = 2,500) followed by replication (n = 1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, p = 1.9×10⁻⁹). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (n = 729). rs1021188 was significantly associated with cortical porosity while rs9287237 was significantly associated with trabecular bone fraction. The genetic variant in the FMN2/GREM2 locus was associated with fracture risk in the MrOS Sweden cohort (HR per extra T allele 0.75, 95% confidence interval 0.60-0.93) and GREM2 expression in human osteoblasts. In conclusion, five genetic loci associated with trabecular or cortical vBMD were identified. Two of these (FMN2/GREM2 and LOC285735) are novel bone-related loci, while the other three have previously been reported to be associated with aBMD. The genetic variants associated with cortical and trabecular bone parameters differed, underscoring the complexity of the genetics of bone parameters. We propose that a genetic variant in the RANKL locus influences cortical vBMD, at least partly, via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences GREM2 expression in osteoblasts and thereby trabecular number and thickness as well as fracture risk.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.344
Teacher spread0.290 · 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 designOther design
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

Citations116
Published2013
Admission routes1
Has abstractyes

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