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Record W3044689135 · doi:10.1111/cge.13817

Spectrum of genes for inherited hearing loss in the Israeli Jewish population, including the novel human deafness gene <scp> <i>ATOH1</i> </scp>

2020· article· en· W3044689135 on OpenAlexfundno aff
Zippora Brownstein, Süleyman Gülsüner, Tom Walsh, Fábio Tadeu Arrojo Martins, Shahar Taiber, Ofer Isakov, Ming K. Lee, Mor Bordeynik‐Cohen, Maria Birkan, Weise Chang, Silvia Casadei, Nada Danial‐Farran, Amal Abu Rayyan, Ryan J. Carlson, Asgeir Ö. Arnthórsson, Meirav Sokolov, Dror Gilony, Noga Lipschitz, Moshe Frydman, Bella Davidov, Michal Macarov, Michal Sagi, Chana Vinkler, Hana Poran, Reuven Sharony, Nadra Nasser Samra, Naama Zvi, Hagit Baris Feldman, Amihood Singer, Ophir Handzel, Ronna Hertzano, Doaa Ali‐Naffaa, Noa Ruhrman‐Shahar, Ory Madgar, Efrat Sofrin‐Drucker, Amir Peleg, Morad Khayat, Mordechai Shohat, Lina Basel‐Vanagaite, Elon Pras, Dorit Lev, Michael Wolf, Eirı́kur Steingrı́msson, Noam Shomron, Matthew W. Kelley, Moien Kanaan, Stavit A. Shalev, Mary‐Claire King, Karen B. Avraham

Bibliographic record

VenueClinical Genetics · 2020
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersNational Institutes of HealthSavoy FoundationIsrael Science FoundationUniversity of Washington
KeywordsHearing lossGeneticsPopulationBiologyGenetic counselingAlleleGeneGenotypeMedicineAudiology

Abstract

fetched live from OpenAlex

Mutations in more than 150 genes are responsible for inherited hearing loss, with thousands of different, severe causal alleles that vary among populations. The Israeli Jewish population includes communities of diverse geographic origins, revealing a wide range of deafness-associated variants and enabling clinical characterization of the associated phenotypes. Our goal was to identify the genetic causes of inherited hearing loss in this population, and to determine relationships among genotype, phenotype, and ethnicity. Genomic DNA samples from informative relatives of 88 multiplex families, all of self-identified Jewish ancestry, with either non-syndromic or syndromic hearing loss, were sequenced for known and candidate deafness genes using the HEar-Seq gene panel. The genetic causes of hearing loss were identified for 60% of the families. One gene was encountered for the first time in human hearing loss: ATOH1 (Atonal), a basic helix-loop-helix transcription factor responsible for autosomal dominant progressive hearing loss in a five-generation family. Our results show that genomic sequencing with a gene panel dedicated to hearing loss is effective for genetic diagnoses in a diverse population. Comprehensive sequencing enables well-informed genetic counseling and clinical management by medical geneticists, otolaryngologists, audiologists, and speech therapists and can be integrated into newborn screening for deafness.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.283
GPT teacher head0.406
Teacher spread0.122 · 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 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

Citations29
Published2020
Admission routes1
Has abstractyes

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