Adult-Onset Dystonia with Late-Onset Epilepsy in TUBB4A-Related Hypomyelinating Leukodystrophy—A New Intermediate Phenotype

Mukherjee, Adreesh; Sarkar, Peyalee; Sarkar, Sumanta; Agrawal, Raju; Dubey, Souvik; Pandit, Alak

doi:10.4103/aian.aian_952_21

Annals of Indian Academy of Neurology

2022

DOI: 10.4103/aian.aian_952_21

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Adult-Onset Dystonia with Late-Onset Epilepsy in TUBB4A-Related Hypomyelinating Leukodystrophy—A New Intermediate Phenotype

Adreesh Mukherjee¹,

Peyalee Sarkar²,

Sumanta Sarkar³

et al.

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Cited by 4 publications

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References 11 publications

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“…[ 12 ] An intermediate phenotype between H-ABC and DYT-TUBB4A has been previously reported from India. [ 13 ] TUBB4A encodes for beta-tubulin 4A protein, which is a contributor to microtubule polymerization and stability. Laryngeal involvement is seen in patients with generalized and segmental dystonia, including DYT1, DYT6, DYT25, and DYT28, although it is rarely a presenting feature in these patients, unlike DYT4.…”

mentioning

confidence: 99%

Dyt-Tubb4a

Garg¹,

Aggarwal²

2023

Annals of Indian Academy of Neurology

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mentioning

confidence: 99%

Dyt-Tubb4a

Garg¹,

Aggarwal²

2023

Annals of Indian Academy of Neurology

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Expanding the phenotypic and genotypic spectrum of DYT-TUBB4A with seven patients from India

Garg,

Holla,

Ganguly

et al. 2024

Parkinsonism & Related Disorders

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Evaluation of input data modality choices on functional gene embeddings

Brechtmann,

Bechtler,

Londhe

et al. 2023

NAR Genomics and Bioinformatics

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Functional gene embeddings, numerical vectors capturing gene function, provide a promising way to integrate functional gene information into machine learning models. These embeddings are learnt by applying self-supervised machine-learning algorithms on various data types including quantitative omics measurements, protein–protein interaction networks and literature. However, downstream evaluations comparing alternative data modalities used to construct functional gene embeddings have been lacking. Here we benchmarked functional gene embeddings obtained from various data modalities for predicting disease-gene lists, cancer drivers, phenotype–gene associations and scores from genome-wide association studies. Off-the-shelf predictors trained on precomputed embeddings matched or outperformed dedicated state-of-the-art predictors, demonstrating their high utility. Embeddings based on literature and protein–protein interactions inferred from low-throughput experiments outperformed embeddings derived from genome-wide experimental data (transcriptomics, deletion screens and protein sequence) when predicting curated gene lists. In contrast, they did not perform better when predicting genome-wide association signals and were biased towards highly-studied genes. These results indicate that embeddings derived from literature and low-throughput experiments appear favourable in many existing benchmarks because they are biased towards well-studied genes and should therefore be considered with caution. Altogether, our study and precomputed embeddings will facilitate the development of machine-learning models in genetics and related fields.

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Adult-Onset Dystonia with Late-Onset Epilepsy in TUBB4A-Related Hypomyelinating Leukodystrophy—A New Intermediate Phenotype

Cited by 4 publications

References 11 publications

Dyt-Tubb4a

Dyt-Tubb4a

Expanding the phenotypic and genotypic spectrum of DYT-TUBB4A with seven patients from India

Evaluation of input data modality choices on functional gene embeddings

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