Publications by authors named "Brian Mangilog"

Tubulinopathies encompass a wide spectrum of disorders resulting from variants in genes encoding α- and β-tubulins, the key components of microtubules. While previous studies have linked or dominantly inherited missense variants to neurodegenerative phenotypes, including amyotrophic lateral sclerosis, frontotemporal dementia, hereditary spastic ataxia, and more recently, an isolated report of congenital myopathy, the full phenotypic and genotypic spectrum of -related disorders remains incompletely characterised. In this multi-centre study, we identified 13 novel missense variants in 31 individuals from 19 unrelated families.

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More than 50% of families with suspected rare monogenic diseases remain unsolved after whole-genome analysis by short-read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare-disease cohort of 98 samples from 41 families, using nanopore sequencing, achieving per sample ∼36× average coverage and 32-kb read N50 from a single flow cell.

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Article Synopsis
  • Rigid spine syndrome is a rare condition in children marked by progressive scoliosis, neck and spine stiffness, muscle weakness, and breathing issues, primarily linked to genetic variations in the SELENON gene.
  • Recent research identified additional genetic variants in the HMGCS1 gene in five patients, suggesting it plays a role in this syndrome, despite it not being previously linked to any diseases.
  • Functional studies of the HMGCS1 variants showed altered protein stability and activity, and experiments in zebrafish indicated that these mutations severely impact development, but can be rescued by introducing healthy HMGCS1 mRNA.
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  • * Long-read sequencing (LRS) offers a promising solution by providing more comprehensive data, including better long-range mapping and methylation profiling, which can help identify variants not detectable by SRS.
  • * In a study involving 98 samples, LRS successfully identified additional rare variants in 11 cases, enhancing diagnostic accuracy for rare monogenic diseases and suggesting its future importance in clinical genomics.
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  • Researchers sequenced the genomes of 822 families with suspected rare monogenic diseases that were previously undiagnosed through standard genetic tests, including exome sequencing.
  • They found that genome sequencing provided a molecular diagnosis for 29.3% of the initial families, with 8.2% requiring genome sequencing to identify variants that exome sequencing missed.
  • The study showed that both research and clinical approaches could benefit from genome sequencing, demonstrating its importance in uncovering previously undetected genetic variations.
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Background: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating.

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Background: Causal variants underlying rare disorders may remain elusive even after expansive gene panels or exome sequencing (ES). Clinicians and researchers may then turn to genome sequencing (GS), though the added value of this technique and its optimal use remain poorly defined. We therefore investigated the advantages of GS within a phenotypically diverse cohort.

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Background: A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery.

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Purpose: Advances in genomic research have facilitated rare disease diagnosis for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other health care contexts. Quantifying and describing inequities in genetic diagnostic yield is inherently challenging due to barriers to both clinical and research genetic testing.

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