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Record W2973985024 · doi:10.1002/jbmr.3875

A Rare Mutation in <i>SMAD9</i> Associated With High Bone Mass Identifies the SMAD-Dependent BMP Signaling Pathway as a Potential Anabolic Target for Osteoporosis

2019· article· en· W2973985024 on OpenAlexfundno aff
Celia L. Gregson, Dylan J. M. Bergen, Paul Leo, Richard B. Sessions, Lawrie Wheeler, April Hartley, Scott E. Youlten, Peter I. Croucher, Aideen McInerney‐Leo, William D. Fraser, Jonathan Tang, Lisa K. Anderson, Mhairi Marshall, Leon Sergot, Lavinia Paternoster, George Davey Smith, Matthew A. Brown, Chrissy L. Hammond, John P. Kemp, Jonathan H. Tobias, Emma L. Duncan

Bibliographic record

VenueJournal of Bone and Mineral Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council CanadaUniversity of QueenslandUniversity of BristolHarold Hyam Wingate FoundationNational Institute for Health and Care ResearchFP7 HealthBritish Geriatrics SocietyElizabeth Blackwell Institute for Health Research, University of BristolSeventh Framework ProgrammeMedical Research CouncilNational Institute on Handicapped ResearchVersus ArthritisArthritis Research UKWellcome Trust
KeywordsSMADOsteoporosisAnabolismMutationBone morphogenetic proteinMedicineBone massSignal transductionCancer researchEndocrinologyInternal medicineBiologyGeneticsTransforming growth factor

Abstract

fetched live from OpenAlex

ABSTRACT Novel anabolic drug targets are needed to treat osteoporosis. Having established a large national cohort with unexplained high bone mass (HBM), we aimed to identify a novel monogenic cause of HBM and provide insight into a regulatory pathway potentially amenable to therapeutic intervention. We investigated a pedigree with unexplained HBM in whom previous sequencing had excluded known causes of monogenic HBM. Whole exome sequencing identified a rare (minor allele frequency 0.0023), highly evolutionarily conserved missense mutation in SMAD9 (c.65T>C, p.Leu22Pro) segregating with HBM in this autosomal dominant family. The same mutation was identified in another two unrelated individuals both with HBM. In silico protein modeling predicts the mutation severely disrupts the MH1 DNA-binding domain of SMAD9. Affected individuals have bone mineral density (BMD) Z-scores +3 to +5, mandible enlargement, a broad frame, torus palatinus/mandibularis, pes planus, increased shoe size, and a tendency to sink when swimming. Peripheral quantitative computed tomography (pQCT) measurement demonstrates increased trabecular volumetric BMD and increased cortical thickness conferring greater predicted bone strength; bone turnover markers are low/normal. Notably, fractures and nerve compression are not found. Both genome-wide and gene-based association testing involving estimated BMD measured at the heel in 362,924 white British subjects from the UK Biobank Study showed strong associations with SMAD9 (PGWAS = 6 × 10−16; PGENE = 8 × 10−17). Furthermore, we found Smad9 to be highly expressed in both murine cortical bone–derived osteocytes and skeletal elements of zebrafish larvae. Our findings support SMAD9 as a novel HBM gene and a potential novel osteoanabolic target for osteoporosis therapeutics. SMAD9 is thought to inhibit bone morphogenetic protein (BMP)-dependent target gene transcription to reduce osteoblast activity. Thus, we hypothesize SMAD9 c.65T>C is a loss-of-function mutation reducing BMP inhibition. Lowering SMAD9 as a potential novel anabolic mechanism for osteoporosis therapeutics warrants further investigation. © 2019 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.282
Teacher spread0.268 · 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 designBench or experimental
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

Citations43
Published2019
Admission routes1
Has abstractyes

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