Clinical utility of comprehensive gene panel testing for common and rare causes of skeletal dysplasia and other skeletal disorders: Results from the largest cohort to date.

Molecular genetics enables more precise diagnoses of skeletal dysplasia and other skeletal disorders (SDs). We investigated the clinical utility of multigene panel testing for 5011 unrelated individuals with SD in the United States (December 2019-April 2022). Median (range) age was 8 (0-90) years, 70.5% had short stature and/or disproportionate growth, 27.4% had a positive molecular diagnosis (MDx), and 30 individuals received two MDx. Genes most commonly contributing to MDx were FGFR3 (16.9%), ALPL (13.0%), and COL1A1 (10.3%). Most of the 112 genes associated with ≥1 MDx were primarily involved in signal transduction (n = 35), metabolism (n = 23), or extracellular matrix organization (n = 17). There were implications associated with specific care/treatment options for 84.4% (1158/1372) of MDx-positive individuals; >50% were linked to conditions with targeted therapy approved or in clinical development, including osteogenesis imperfecta, achondroplasia, hypophosphatasia, and mucopolysaccharidosis. Forty individuals with initially inconclusive results became MDx-positive following family testing. Follow-up mucopolysaccharidosis enzyme activity testing was positive in 14 individuals (10 of these were not MDx-positive). Our findings showed that inclusion of metabolic genes associated with SD increased the clinical utility of a gene panel and confirmed that integrated use of comprehensive gene panel testing with orthogonal testing reduced the burden of inconclusive results.

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

BACKGROUND: Blood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer. METHODS: Whole-genome sequencing was performed on cfDNA extracted from plasma samples (N = 546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validations to assess generalization performance. RESULTS: In a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance. CONCLUSIONS: A machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

Mutation update: Review of TPP1 gene variants associated with neuronal ceroid lipofuscinosis CLN2 disease.

Neuronal ceroid lipofuscinosis type 2 (CLN2 disease) is an autosomal recessive condition caused by variants in the TPP1 gene, leading to deficient activity of the lysosomal enzyme tripeptidyl peptidase I (TPP1). We update on the spectrum of TPP1 variants associated with CLN2 disease, comprising 131 unique variants from 389 individuals (717 alleles) collected from the literature review, public databases, and laboratory communications. Previously unrecorded individuals were added to the UCL TPP1-specific database. Two known pathogenic variants, c.509-1 G>C and c.622 C>T (p.(Arg208*)), collectively occur in 60% of affected individuals in the sample, and account for 50% of disease-associated alleles. At least 86 variants (66%) are private to single families. Homozygosity occurs in 45% of individuals where both alleles are known (87% of reported individuals). Atypical CLN2 disease, TPP1 enzyme deficiency with disease onset and/or progression distinct from classic late-infantile CLN2, represents 13% of individuals recorded with associated phenotype. NCBI ClinVar currently holds records for 37% of variants collected here. Effective CLN2 disease management requires early diagnosis; however, irreversible neurodegeneration occurs before a diagnosis is typically reached at age 5. Timely classification and public reporting of TPP1 variants is essential as molecular testing increases in use as a first-line diagnostic test for pediatric-onset neurological disease.

Mucopolysaccharidosis type VI (MPS VI) and molecular analysis: Review and classification of published variants in the ARSB gene.

Maroteaux-Lamy syndrome (MPS VI) is an autosomal recessive lysosomal storage disorder caused by pathogenic ARSB gene variants, commonly diagnosed through clinical findings and deficiency of the arylsulfatase B (ASB) enzyme. Detection of ARSB pathogenic variants can independently confirm diagnosis and render genetic counseling possible. In this review, we collect and summarize 908 alleles (201 distinct variants, including 3 polymorphisms previously considered as disease-causing variants) from 478 individuals diagnosed with MPS VI, identified from literature and public databases. Each variant is further analyzed for clinical classification according to American College of Medical Genetics and Genomics (ACMG) guidelines. Results highlight the heterogeneity of ARSB alleles, with most unique variants (59.5%) identified as missense and 31.7% of unique alleles appearing once. Only 18% of distinct variants were previously recorded in public databases with supporting evidence and clinical significance. ACMG recommends publishing clinical and biochemical data that accurately characterize pathogenicity of new variants in association with reporting specific alleles. Variants analyzed were sent to ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), and MPS VI locus-specific database (http://mps6-database.org) where they will be available. High clinical suspicion coupled with diagnostic testing for deficient ASB activity and timely submission and classification of ARSB variants with biochemical and clinical data in public databases is essential for timely diagnosis of MPS VI.