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Record W2919929114 · doi:10.3389/fgene.2019.00136

Using Whole Genome Sequencing in an African Subphenotype of Myasthenia Gravis to Generate a Pathogenetic Hypothesis

2019· article· en· W2919929114 on OpenAlexfundno aff
Melissa Nel, Nicola Mulder, Tarin A. Europa, Jeannine M. Heckmann

Bibliographic record

VenueFrontiers in Genetics · 2019
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFrench Muscular Dystrophy AssociationUniversity of Cape TownNational Research FoundationRare Disease FoundationBC Children's HospitalChildren's Hospital FoundationAssociation Française contre les MyopathiesMuscular Dystrophy Association
KeywordsMyasthenia gravisWhole genome sequencingBiologyGenomeComputational biologyGeneticsVirologyGeneImmunology

Abstract

fetched live from OpenAlex

Myasthenia gravis (MG) is a rare, treatable antibody-mediated disease which is characterised by muscle weakness. The pathogenic antibodies are most frequently directed at the acetylcholine receptors (AChRs) at the skeletal muscle endplate. An ophthalmoplegic subphenotype of MG (OP-MG), which is characterised by treatment resistant weakness of the extraocular muscles (EOMs), occurs in a proportion of myasthenics with juvenile symptom onset and African genetic ancestry. Since the pathogenetic mechanism(s) underlying OP-MG is unknown, the aim of this study was to use a hypothesis-generating genome-wide analysis to identify candidate OP-MG susceptibility genes and pathways. Whole genome sequencing (WGS) was performed on 25 AChR-antibody positive myasthenic individuals of African genetic ancestry sampled from the phenotypic extremes: 15 with OP-MG and 10 individuals with control MG (EOM treatment-responsive). Variants were called according to the Genome Analysis Toolkit (GATK) best practice guidelines using the hg38 reference genome. In addition to single variant association analysis, variants were mapped to genes (+/- 200kb) using VEGAS2 to calculate gene-based test statistics and HLA allele group assignment was inferred through “best-match” alignment of reads against the IMGT/HLA database. While there were no single variant associations that reached genome-wide significance in this exploratory sample, several genes with significant gene-based test statistics and known to be expressed in skeletal muscle had biological functions which converge on muscle atrophy signalling and myosin II function. The closely linked HLA-DPA1 and HLA-DPB1 genes were associated with OP-MG subjects (gene-based pG SNP (rs9277534) in the HLA-DPB1 3’UTR, which increases HLA-DPB1 expression, differed between the two groups (G-allele 0.30 in OP-MG vs 0.60 in control MG; p=0.04). Furthermore, we show that rs9277534 is an HLA-DBP1 expression quantitative trait locus in patient-derived myocytes (p<1x10-3). The application of a SNP to gene to pathway approach to this exploratory WGS dataset of African myasthenic individuals, and comparing dichotomous subphenotypes, resulted in the identification of candidate genes and pathways that may contribute to OP-MG susceptibility. Overall, the hypotheses generated by this work remain to be verified by interrogating candidate gene and pathway expression in patient-derived extraocular muscle.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.038
GPT teacher head0.261
Teacher spread0.223 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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