Genomics and Rare Diseases

Clinical exome sequencing for stroke evaluation uncovers a high frequency of Mendelian disorders: a retrospective analysis.

This study evaluates the use of clinical exome sequencing in stroke patients, finding a high frequency of Mendelian disorders in a retrospective cohort.

Var I Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data

Var I Decrypt is a web-based tool for analyzing whole-exome sequencing data, enabling variant prioritization and functional analysis in clinical settings.

Phasing of de novo mutations using a scaled-up multiple amplicon long-read sequencing approach

This study phases de novo mutations using a combined long-read and short-read sequencing approach, successfully determining parent-of-origin for 71% of analyzed mutations.

Contribution of Mendelian disorders in a population-based pediatric neurodegeneration cohort

The paper evaluates Mendelian causes of pediatric neurodegenerative disorders in a cohort of 69 patients, finding 42 genetic diagnoses and 32 unique disorders.

Endophenotype Effect Sizes Provide Evidence Supporting Variant Pathogenicity in Monogenic Disease Susceptibility Genes

The paper shows that variant effect sizes on quantitative endophenotypes support pathogenicity in monogenic disease genes.

Genome-wide prediction of disease variants with a deep protein language model

This paper uses a deep protein language model to predict the functional impact of all human missense variants, outperforming existing methods and providing isoform-specific annotations.

Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes

The paper identifies biological properties of ion channel residues associated with variant pathogenicity and links them to clinical phenotypes and functional assays.

AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

AnFiSA is an open-source platform for analyzing sequencing data in rare genetic disease, addressing reproducibility, adaptability, and explainability in genomic analysis.

DeepGenePrior: A deep learning model to prioritize genes affected by copy number variants

DeepGenePrior uses deep learning to prioritize genes affected by copy number variants in neurodevelopmental disorders, identifying common genes across autism, schizophrenia, and developmental delay.

Improved diagnosis of rare disease patients through application of constrained coding region annotation and de novo status.

This paper evaluates the diagnostic utility of incorporating de novo variants and constrained coding regions in rare disease patients, showing improved diagnostic rates.

A proposed general variant classification framework using chronic pancreatitis as a disease model

The paper proposes a new variant classification framework for chronic pancreatitis, introducing new categories to better classify variants in disease-causing and predisposing genes.

Performance Comparison Of Agilent New SureSelect All Exon v8 Probes With v7 Probes For Exome Sequencing

This study compares Agilent SureSelect All Exon v8 and v7 probes for exome sequencing, finding v8 improves SNV and indel detection with the same read count.

A framework evaluating the utility of multi-gene, multi-disease population-based panel testing that accounts for uncertainty in penetrance estimates

The paper presents a framework to evaluate the clinical utility of multi-gene, multi-disease panel testing by incorporating variant frequency, penetrance estimates, and disutilities, while accounting for uncertainty in penetrance.

MvPPT: a highly efficient and sensitive pathogenicity prediction tool for missense variants

The paper introduces mvPPT, a missense variant pathogenicity predictor that outperforms existing tools in sensitivity and accuracy using gradient boosting and diverse feature sets.

Estimating diagnostic noise in panel-based genomic analysis

The paper estimates diagnostic noise in genomic analysis using gene panels by analyzing variant prioritization rates in different panel sizes and disease categories.

Characterizing the genetic polymorphisms in 370 challenging medically relevant genes using long-read sequencing data from 41 human individuals among 19 global populations

The paper uses long-read sequencing to analyze genetic polymorphisms in 370 medically relevant genes across 41 individuals from 19 populations, identifying CNVs and variants missed by short-read sequencing.

Activating mutations in FGFR3 are associated with clonal expansion events and high de novo rates in the male germline

The paper investigates FGFR3 mutations in the male germline, finding some mutations increase with age and lead to clonal expansions and higher mutation rates.

Objective evaluation of clinical actionability for genes involved in myopathies: 63 genes with a medical value for patient care

The paper evaluates the clinical actionability of 63 myopathy-related genes using ClinGen criteria, finding that only 8 of the top 36 genes had prior ClinGen scores.

Aggregated genomic data as cohort-specific allelic frequencies can boost variants and genes prioritization in non-solved cases of inherited retinal dystrophies

The paper builds a cohort-specific allelic frequency database to prioritize variants and genes in non-solved inherited retinal dystrophies, identifying 8 potential causative variants and 18 genes for further study.

A power-based sliding window approach to evaluate the clinical impact of rare genetic variants

The paper introduces Power Window, a method to identify clinically impactful regions of genes using population-scale datasets, showing improved accuracy in variant effect prediction.

Genomic ascertainment for UBA1 variants and VEXAS syndrome: a population-based study

This study uses genomic ascertainment to determine the prevalence and clinical features of pathogenic UBA1 variants in a population-based cohort, finding higher prevalence and expressivity than previously reported.

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project.

This study analyzes splicing variants in whole-genome sequencing data to identify new diagnoses in rare diseases.

The PREGCARE study: Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation

The paper presents a method to assess recurrence risk of de novo mutations in families using deep-sequencing and haplotyping, finding that 59% of DNMs had reduced risk below 0.1%.

Optimising diagnostic yield in highly penetrant genomic disease

The paper reports diagnostic outcomes from a large-scale genomic study of developmental disorders, identifying factors that influence diagnostic success.

Recommendations for clinical interpretation of variants found in non-coding regions of the genome

This paper provides recommendations for interpreting non-coding variants in clinical settings, adapting existing guidelines to account for their role in disease.

Deciphering the consequence of deep intronic variants: a progeroid syndrome caused by a TAPT1 mutation is revealed by combined RNA/SI-NET sequencing

The paper identifies a deep intronic TAPT1 mutation causing progeroid syndrome using RNA-seq and homozygosity mapping, showing it leads to exon skipping and protein-null allele.

Updated Variant Curation Expert Panel Criteria and Pathogenicity Classifications for 251 Variants for RYR1-related Malignant Hyperthermia Susceptibility

The paper updates ACMG/AMP criteria for RYR1-related MHS and classifies 251 variants, finding that many VUS classifications lack sufficient evidence and suggesting functional studies are needed.

Missense variants in ANKRD11 cause KBG syndrome by impairment of stability or transcriptional activity of the encoded protein

This study identifies ANKRD11 missense variants as a cause of KBG syndrome by impairing protein stability or transcriptional activity, supporting haploinsufficiency as the underlying mechanism.

StabilitySort: assessment of protein stability changes on a genome-wide scale to prioritise potentially pathogenic genetic variation

StabilitySort prioritizes pathogenic genetic variants by assessing their impact on protein stability using AlphaFold2 predictions.

Accuracy of a machine learning method based on structural and locational information from AlphaFold2 for predicting the pathogenicity of TARDBP and FUS gene variants in ALS

The paper develops MOVA, a machine learning method using AlphaFold2 structural data to predict pathogenicity of ALS-related gene variants, showing good accuracy for TARDBP and FUS.