Genomics and Rare Diseases

Mode of inheritance needs to be accounted for in interpreting genotype-phenotype links in monogenic disorders

The paper re-analyzes genetic variants in POI patients, finding that the claimed diagnostic yield is overestimated due to incorrect assumptions about inheritance modes.

The effect of ascertainment on penetrance estimates for rare variants: implications for establishing pathogenicity and for genetic counselling

The paper shows that penetrance estimates for rare variants can be unreliable due to ascertainment bias and introduces PenEst, an app to analyze this effect, along with LOD score corrections for pathogenicity assessment.

Gaps in the phenotype descriptions of ultra-rare genetic conditions: review and multi-center consensus reporting guidelines

The paper reviews phenotype reporting in genetic disorders and proposes guidelines to improve clinical relevance.

Systematic identification of disease-causing promoter and untranslated region variants in 8,040 undiagnosed individuals with rare disease

This study identifies disease-causing promoter and untranslated region variants in 8,040 undiagnosed rare disease patients using a new framework and finds 12 variants with potential pathogenicity.

A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction

The paper curates a high-confidence set of pathogenic and likely pathogenic UTR variants and evaluates deep learning models for predicting their functional impact.

GENETIC COUNSELING IN THE MIDDLE EAST

This study surveys healthcare professionals in the Middle East to understand challenges and perspectives on genetic counseling and testing, finding cultural and resource-related barriers and positive patient attitudes.

SNPred outperforms other ensemble-based SNV pathogenicity predictors and elucidates the challenges of using ClinVar for evaluation of variant classification quality.

The functional impact of rare variation across the regulatory cascade

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

Defining the single base importance of human mRNAs and lncRNAs

The paper introduces BIC, a tool to measure single base importance in human mRNAs and lncRNAs, showing its utility in pathogenicity assessment, cancer prognosis, and SARS-CoV-2 transmissibility prediction.

aenmd: Annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

aenmd annotates PTC-containing transcript-variant pairs for predicted NMD escape, identifying variants that may cause dominant-negative or gain-of-function effects.

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

DosaCNV predicts gene haploinsufficiency and deletion pathogenicity using deep multiple-instance learning, outperforming existing methods by integrating gene-level features.

Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

This paper presents a framework to reduce false positives in predicted loss-of-function variants by analyzing LoF evasion mechanisms and adjusting ACMG/AMP guidelines.

Pathogenic paralogous variants can be used to apply the ACMG PS1 and PM5 variant interpretation criteria

The paper introduces para-PS1/PM5 criteria by incorporating pathogenic paralogous variants to improve variant classification under ACMG guidelines, increasing classifiable amino acids 3.6-fold.

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

APOGEE 2 improves pathogenicity prediction for mitochondrial missense variants using a machine learning model based on ACMG/AMP guidelines and provides region-wise genome fragility assessments.

A Weights-based variant ranking pipeline for familial complex disorders

The paper introduces WARP, a variant ranking pipeline for familial complex disorders, which identifies potential disease-predisposing genes in pedigrees by combining multiple weighted factors.

VelosGT: An App for Variant Analysis and Rare Disease Discovery

VelosGT is a MacOS app for analyzing human genomes to find genetic mutations and rare diseases, offering faster and more efficient variant analysis than standard pipelines.

VarSCAT: A computational tool for sequence context annotations of genomic variants

VarSCAT annotates genomic variant sequence contexts, revealing that over 75% of human indels have breakpoint ambiguities and over 80% of STR region variants are indels.

Unique Capabilities of Genome Sequencing for Rare Disease Diagnosis

This study evaluates genome sequencing's diagnostic yield in a cohort of undiagnosed rare disease patients, finding it solves 29.3% of cases with specific variant types not detectable by exome sequencing.

Cross-protein transfer learning substantially improves disease variant prediction

This paper introduces a cross-protein transfer learning framework that improves disease variant prediction using deep mutational scanning data from few proteins, achieving better specificity than existing models.

Variant annotation across homologous proteins (Paralogue Annotation) identifies disease-causing missense variants with high precision, and is widely applicable across protein families

This paper introduces Paralogue Annotation, a method using homologous protein variants to predict disease-causing missense variants with high precision.

Genetic Dependence and Genetic Diseases

The paper examines genetic dependence features of genes and their role in determining pathogenicity and clinical features of genetic diseases.

Genome Sequencing and Comprehensive Rare Variant Analysis of 465 Families with Neurodevelopmental Disorders

This study uses genome sequencing to identify causal variants in families with neurodevelopmental disorders, finding 36% of affected individuals have causal variants and 26% have variants of uncertain significance.

Advancing Understanding of Inequities in Rare Disease Genomics

This paper describes the Rare Genomes Project's efforts to address inequities in rare disease genomics by diversifying enrollment and understanding barriers to access.

The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change

The paper analyzes VUS rates in genetic testing and finds lower rates in exome/genome sequencing compared to multi-gene panels, suggesting improvements in variant reporting practices.

Choosing variant interpretation tools for clinical applications: context matters

The paper introduces cost models to compare pathogenicity predictors in clinical contexts, showing no optimal predictor exists for all scenarios and highlighting the importance of rejection classifiers.

Federated analysis of the contribution of recessive coding variants to 29,745 developmental disorder patients from diverse populations

The paper quantifies the contribution of recessive coding variants to developmental disorders in diverse populations, identifying novel genes and highlighting challenges in interpreting missense variants.

Comparing the diagnostic and clinical utility of WGS and WES with standard genetic testing (SGT) in children with suspected genetic diseases: A systematic review and meta-analysis

This study compares the diagnostic and clinical utility of whole-genome sequencing (WGS), whole-exome sequencing (WES), and standard genetic testing (SGT) in children with suspected genetic diseases, finding WGS and WES to be more effective than SGT.

Re-evaluation and Re-analysis of 152 research exomes five years after the initial report reveals clinically relevant changes in 20%

The paper re-analyzes 152 exomes from developmental disorder families five years later, finding 20% clinically relevant changes and reclassifying variants.

Lost in translation: the pitfalls of Ensembl Gene annotations between human genome assemblies and their impact on diagnostics

The paper identifies 267 genes reclassified as protein-coding in GRCh38 that were previously labeled as non-protein-coding in GRCh37, highlighting the impact of outdated annotations on variant prioritization and clinical diagnostics.

Prevalence and Clinical Significance of Commonly Diagnosed Genetic Disorders in Preterm Infants

This study finds that 1.3% of preterm infants have genetic disorders, with higher rates in those who died or had severe morbidity, and identifies specific disorders linked to increased morbidity and mortality.