MétaCan
Menu
Back to cohort
Record W4415450719 · doi:10.1210/jendso/bvaf149.1764

SAT-195 Exome Sequencing of Patients with Syndromic Tall Stature Reveals Novel Candidate Genes

2025· article· en· W4415450719 on OpenAlexaff
Edoarda Vasco de Albuquerque Albuquerque, Raíssa Rezende, Laurana de Polli Cellin, Lucas Santos de Santana, Antônio Marcondes Lerário, Vinicius de Souza, Renata Da Cunha Scalco, Alexander A.L. Jorge

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsCandidate geneShort statureExome sequencingExomeGenome-wide association studyGenetic associationDNA sequencingCohort

Abstract

fetched live from OpenAlex

Abstract Disclosure: G.J. Kim: None. E.V. de Albuquerque Albuquerque: None. R.C. Rezende: None. L.D. Cellin: None. L.S. de Santana: None. A.M. Lerario: None. V. de Souza: None. R.D. Scalco: None. A.A. Jorge: Novo Nordisk. Background: Monogenic causes of syndromic tall stature result in a recognizable pattern of clinical characteristics that include dysmorphisms, malformations, and/or neurodevelopmental disorders. Thus far, few articles have been published regarding the diagnosis of syndromic tall stature by genetic testing. The purpose of this study was to use whole exome sequencing (WES) to evaluate a cohort of patients with syndromic tall stature, with the aim of describing genetic causes of and new candidate genes for tall stature. Methods: We included 37 patients referred to a single, tertiary academic center specialized in growth disorders for the evaluation of tall stature from January 2017 to February 2024. Patients included both novel cases and cases being reanalyzed. Trio analysis was performed for four patients, and WES was performed for only the index cases for the remaining patients. Variants were prioritized based on minor allele frequency, prediction to be loss-of-function, inheritance pattern compatibility, and prior reports. Copy number variations (CNVs) were further prioritized based on involved protein-coding genes displaying haploinsufficiency. If diagnosis of a known tall stature disorder could not be achieved, analysis for candidate genes was performed, taking into account the above criteria as well as GWAS catalog associations with height and weight phenotypes, DECIPHER catalog listings of overlapping CNVs, medical literature on our candidate genes, recurrence of rare variants with similar phenotypes, and animal models consistent with the proposed phenotype. Results: Of the 37 patients included in this study, genetic diagnosis was achieved in 11 patients, for a diagnostic yield of 29.7%. Pathogenic or likely pathogenic variants were identified in FBN1 (3x), PTEN, NSD1, SUZ12, CDH8, and DEPDC5, with some of these results having been previously described in other papers. One patient carried significant variants in two genes, FBN2 and COL5A1. Furthermore, we identified two patients with pathogenic deletions confirmed by chromosomal microarray analysis. Through analysis of the gene content compromised by these deletions, description of other cases with overlapping CNVs, biological plausibility, and data from the literature, two candidate genes for tall stature were identified: PTCH1 and SST. Additionally, three genes (KDM4A, RAP1GAP2 and GRB10) were identified via WES based on gene constraints, recurrence in our cohort (KDM4A), biological plausibility, and additional cases in literature (GRB10). Conclusions: These findings indicate a diagnostic yield of syndromic tall stature by WES that is comparable to those found in studies of other syndromic growth disorders. We also present five new candidate genes for tall stature. Further work is required to continue characterizing the impact of these genes on adult height, as well as to describe novel candidate genes for height. Presentation: Saturday, July 12, 2025

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Endocrine SocietySame topicGenetic factors in colorectal cancerFrench-language works237,207