NPJ Genomic Medicine最新文献

Rapid genomic diagnostics in the Neonatal Intensive Care Unit represents a paradigm shift in medicine with increasing evidence of the utility of early diagnosis, impacting management. The goal of the Utah NeoSeq Project was to implement and evaluate a multidisciplinary and longitudinal rapid sequencing program while transitioning to CLIA-certified sequencing. Enrollment of 65 infants resulted in 26 (40%) with a diagnostic variant(s) and 7 (11%) harboring a strong candidate. This includes re-analyses resulting in four additional diagnoses. Parental surveys indicated that 7% (4/59) of parents had a decisional conflict after consent, and 3% (2/59) experienced decisional regret after the results. Fifty-two provider surveys were conducted. Seventy-nine percent (41/52) of results and 86% (19/22) of diagnostic results were "very useful" or "useful" and associated with management changes. The NeoSeq Project demonstrates that a multidisciplinary collaborative approach to diagnosis is feasible. We have developed a generalizable, collaborative protocol that addresses the need for expedited genetic evaluation with emerging technologies.

Individuals with heritable thoracic aortic disease (HTAD) face a high risk of deadly aortic dissections, but genetic testing identifies causative variants in only a minority of cases. We explored the contribution of non-canonical splice variants (NCVAS) to thoracic aortic disease (TAD) using SpliceAI and sequencing data from diverse cohorts, including 551 early-onset sporadic dissection cases and 437 HTAD probands with exome sequencing, 57 HTAD pedigrees with whole genome sequencing, and select sporadic cases with clinical panel testing. NCVAS were identified in syndromic HTAD genes such as FBN1, SMAD3, and COL3A1, including intronic variants in FBN1 in two Marfan syndrome (MFS) families. Validation in the Penn Medicine BioBank and UK Biobank showed enrichment of NCVAS in HTAD-associated genes among dissections. These findings suggest NCVAS are an underrecognized contributor to TAD, particularly in sporadic dissection and unsolved MFS cases, highlighting the potential of advanced splice prediction tools in genetic diagnostics.

In immunocompromised pediatric patients, diagnosing invasive pulmonary aspergillosis (IPA) poses a significant challenge. Next-Generation Sequencing (NGS) shows promise for detecting fungal DNA but lacks standardization. This study aims to advance towards clinical evaluation of liquid biopsy NGS for Aspergillus detection, through an evaluation of wet-lab procedures and computational analysis. Our findings support using both CHM13v2.0 and GRCh38.p14 in host-read mapping to reduce fungal false-positives. We demonstrate the sensitivity of our custom kraken2 database, cRE.21, in detecting Aspergillus species. Additionally, cell-free DNA sequencing shows superior performance to whole-cell DNA sequencing by recovering higher fractions of fungal DNA in lung fluid (bronchoalveolar lavage [BAL] fluid) and plasma samples from pediatric patients with probable IPA. In a proof-of-principle, A. fumigatus was identified in 5 out of 7 BAL fluid samples and 3 out of 5 plasma samples. This optimized workflow can advance fungal-NGS research and represents a step towards enhancing diagnostic certainty by enabling more sensitive and accurate species-level diagnosis of IPA in immunocompromised patients.

Rett syndrome (RTT) is a severe neurodevelopmental disorder, with MECP2 mutations accounting for 90-95% of classic and 50-70% of atypical cases. However, many clinically diagnosed RTT patients remain without molecular diagnoses. While point mutations and large rearrangements in MECP2 are well studied, the role of small-intermediate structural variants (SVs) remains mostly elusive. Using standard short-read whole genome sequencing, we identified novel de novo SVs in three out of three previously unresolved RTT cases: a complex SV with two deletions ( ~ 5Kbp and ~60Kbp) and a ~105Kbp inversion; a ~200Kbp translocation; and a ~3Kbp deletion. These findings suggest that such elusive SVs might be a common cause for "MECP2-negative" RTT. Incorporating SV detection into routine genetic testing through bioinformatic analysis of short-read sequencing or manual review using IGV could improve diagnostic rates and expand our understanding of RTT and similar disorders.

Programmed cell death protein 1 (PD-1) is a critical immune checkpoint receptor and a target for cancer immune checkpoint inhibitors (ICI). We investigated PD-1 transcript expression across cancer types and its correlations to clinical outcomes. Using a reference population, PD-1 expression was calculated as percentiles in 489 of 514 patients (31 cancer types) with advanced/metastatic disease. PD-1 RNA expression varied across and within cancer types; pancreatic and liver/bile duct malignancies displayed the highest rates of high PD-1 (21.82% and 21.05%, respectively). Elevated CTLA-4, LAG-3, and TIGIT RNA expression were independently correlated with high PD-1. Although high PD-1 was not associated with outcome in immunotherapy-naïve patients (n = 272), in patients who received ICIs (n = 217), high PD-1 transcript expression was independently correlated with prolonged survival (hazard ratio 0.40; 95%CI, 0.18-0.92). This study identifies PD-1 as an important biomarker in predicting ICI outcomes, and advocates for comprehensive immunogenomic profiling in cancer management.

Genetic diagnosis of ADPKD has been challenging due to the variant heterogeneity, presence of duplicated segments, and high GC content of exon 1 in PKD1. In our reproductive center, 40 patients were still genetically undiagnosed or diagnosed without single-nucleotide resolution after testing with a short-read sequencing panel in 312 patients with ADPKD phenotype. A combination of long-range PCR and long-read sequencing approach for PKD1 was performed on these 40 patients. LRS additionally identified 10 pathogenic or likely pathogenic PKD1 variants, including four patients with microgene conversion (c.160_166dup, c.2180T>C, and c.8161+1G>A) between PKD1 and its pseudogenes, three with indels (c.-49_43del, c.2985+2_2985+4del, and c.10709_10760dup), one with likely pathogenic deep intronic variant (c.2908-107G>A) and two with large deletions. LRS also identified nine PKD1 CNVs and precisely determined the breakpoints, while SRS failed to identify two of these CNVs. Therefore, LRS enables higher diagnostic yield of ADPKD and provides significant benefits for genetic counseling.

High on-treatment platelet reactivity (HTPR) with clopidogrel predicts ischemic events in adults with coronary artery disease, and while HTPR varies by ethnicity, no genome-wide association study (GWAS) of clopidogrel response has been conducted in Caribbean Hispanics. This study aimed to identify genetic predictors of HTPR in a cohort of 511 Puerto Rican cardiovascular patients treated with clopidogrel, stratified by P2Y12 reaction units (PRU) into responders and non-responders (HTPR). Local ancestry inference (LAI) and traditional GWAS identified variants in the CYP2C19 region associated with HTPR, primarily in individuals with European ancestry. Three variants (OSBPL10 rs1376606, DERL3 rs5030613, RGS6 rs9323567) showed suggestive significance, and a variant in UNC5C was linked to increased HTPR risk. These findings highlight the unique genetic landscape of Caribbean Hispanics and challenge the significance of CYP2C19*2 in predicting clopidogrel response in patients with high non-European ancestry. Further studies are needed to replicate these results in other diverse cohorts.

An integrated approach combining whole exome sequencing (WES) and autozygosity mapping was used to molecularly diagnose inherited retinal disease (IRD) in 192 unrelated Iranian families, 76.1% of which originate from a consanguineous background. Data analysis was performed using an in-house pipeline to detect single-nucleotide variants (SNVs), small insertions and deletions, copy number variants (CNVs) and runs of homozygosity (ROHs). Using this approach, we obtained a molecular diagnosis for 72.9% of the cohort. In total, 209 variants were identified in 78 IRD-associated genes. The majority occurred only once (81.8%) and 52.9% were novel. Variants in ROHs were found in 82.8% of patients from consanguineous backgrounds. The importance of structural variation (SV) was demonstrated, with CNVs identified in 5.3%, including several novel CNVs. Multilocus genomic variation was observed in two families. This integrated study using WES and in-depth variant assessment significantly expanded the molecular spectrum of IRD in Iran, an understudied population.

Duchenne and Becker Muscular Dystrophy are dystrophinopathies with a prevalence of 1:5000-6000 males, caused by pathogenic variants in DMD. These conditions are often accompanied by neurodevelopmental disorders (NDDs) like autism (ASD; ~20%) and intellectual disability (ID; ~30%). However, their low penetrance in dystrophinopathies suggests additional contributing factors. In our study, 83 individuals with dystrophinopathies were clinically evaluated and categorized based on ASD (36 individuals), ID risk (12 individuals), or controls (35 individuals). Exome sequencing analysis revealed an enrichment of risk de novo variants (DNVs) in ASD-DMD individuals (adjusted p value = 0.0356), with the number of DNVs correlating with paternal age (p value = 0.0133). Additionally, DMD-ASD individuals showed a higher average of rare risk variants (RRVs) compared to DMD-Controls (adjusted p value = 0.0285). Gene ontology analysis revealed an enrichment of extracellular matrix-related genes, especially collagens, and Ehlers-Danlos syndrome genes in ASD-DMD and DMD-ID groups. These findings support an oligogenic model for ASD in dystrophinopathies, highlighting the importance of investigating homogenized samples to elucidate ASD's genetic architecture.

Genetic testing is essential for diagnosing and managing clinical conditions, particularly rare Mendelian diseases. Although efforts to identify rare phenotype-associated variants have focused on protein-truncating variants, interpreting missense variants remains challenging. Deep learning algorithms excel in various biomedical tasks^1,2, yet distinguishing pathogenic from benign missense variants remains elusive^3-5. Our investigation of AlphaMissense (AM)⁵, a deep learning tool for predicting the potential functional impact of missense variants and assessing gene essentiality, reveals limitations in identifying pathogenic missense variants over 45 rare diseases, including very early onset inflammatory bowel disease. For the expert-curated pathogenic variants identified in our cohort, AM's precision was 32.9%, and recall was 57.6%. Notably, AM struggles to evaluate pathogenicity in intrinsically disordered regions (IDRs), resulting in unreliable gene-level essentiality scores for genes containing IDRs. This observation underscores ongoing challenges in clinical genetics, highlighting the need for continued refinement of computational methods in variant pathogenicity prediction.