Heidi L. Rehm

This study explores equitable strategies for participant engagement in rare disease genomic research through interviews with underrepresented individuals and clinicians.

The paper evaluates incomplete penetrance in 4,325 rare disease families, finding 1.6% of diagnosed cases involve inherited variants from unaffected parents and showing divergent transcriptional effects in CHD8-related cases.

AlphaGenome Atlas predicts regulatory effects of non-coding variants across the human genome, improving their prioritization and interpretation.

The Rare Genomes Project provides remote genomic sequencing to rare disease families, achieving a 23.3% diagnostic solve rate and highlighting the role of research in overcoming clinical diagnostic barriers.

The paper identifies novel spliceosome-related genes and pseudogenes associated with rare diseases using variant analysis and prioritization methods.

This study evaluates the diagnostic yield of short-read and long-read sequencing in rare diseases, finding limited added value from long-read sequencing despite increased variant discovery.

The paper estimates penetrance of disease variants in genes prioritized for genomic newborn screening using adult biobank data, finding higher penetrance than ICD codes suggest.

PFES quantifies the protein context of missense variants, enabling mechanistically transparent interpretation and reclassification of variants of uncertain significance.

The Evidence Aggregator (EvAgg) uses generative AI to streamline rare disease diagnostics by extracting and summarizing genetic variant and clinical information from literature, improving efficiency and accuracy.

The paper introduces a data model and dataset for rare disease research, enabling interoperable multi-omic data integration across clinical sites.

The paper describes international workshops training variant scientists on the ClinGen Variant Curation Interface (VCI) and reports on its usage and costs.

The paper estimates genetic prevalence for 22 autosomal recessive conditions using gnomAD data and develops a tool to democratize these calculations, highlighting the dynamic nature of prevalence estimates.

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

The paper develops a comprehensive list of genetic conditions for genomic newborn screening, including 777 conditions associated with 743 genes, for implementation across multiple U.S. states and territories.

The paper evaluates challenges in genomic variant representation across resources and develops normalization methods to improve clinical outcome associations.

This paper improves allele frequency estimates in gnomAD by applying local ancestry inference to admixed populations, revealing significant frequency differences that could affect clinical interpretation.

The paper develops an automated tool for reanalyzing genomic data in rare disease cohorts, showing improved diagnostic yields through iterative reanalysis.

The paper identifies mitochondrial DNA variants in undiagnosed rare disease families using exome and genome sequencing data, leading to diagnoses in 0.4% of cases.

STRchive provides a dynamic resource for interpreting TR variants at disease loci, showing most TR diseases affect children and pathogenic genotypes exist in gnomAD without known disease prevalence.

The paper calibrates three new computational tools for clinical variant classification, finding they provide evidence strength comparable to previously recommended tools.

The paper examines how variants of uncertain significance (VUS) are reclassified based on subclassification evidence levels across four clinical laboratories.

The paper develops and validates SMA Finder, a tool to diagnose spinal muscular atrophy in genome, exome, and panel sequencing data, identifying known and novel cases with high accuracy.

The paper introduces a new TR catalog, TRExplorer v1.0, containing 4.86 million loci, designed for both short-read and long-read analyses and includes variation clusters identified using long-read HiFi data.

The paper assesses rare missense variants in genome sequences using PP3/BP4 evidence strength classifications and finds few variants meet strong or moderate criteria.

Mostly de novo variants in an 18 bp constrained region of U4 snRNA gene RNU4-2 cause a syndromic neurodevelopmental disorder, estimated to explain 0.41% of cases.

The paper harmonizes diverse human genomes from multiple datasets to create a new reference panel with improved variant coverage and population structure analysis.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

The paper quantifies regional missense mutational intolerance using 730,947 exomes to identify constrained gene regions and improve variant interpretation.

The paper detects and classifies copy number variants in exome data from 6,633 families, identifying causal CNVs in 173 families and improving classification standards.

The paper analyzes pathogenic variant frequencies in the All of Us cohort by ancestry, revealing disparities and potential biases in genomic data.