NPJ Genomic Medicine最新文献

Personalized precision dosing remains an unmet clinical need. This study used population pharmacokinetic (PopPK) modeling to evaluate transitioning lacosamide (LCM) in children with epilepsy from body weight (BW)-based (mg/kg) to simplified BW-band or fixed-dose (mg) regimens. Real-world data from 190 patients were analyzed using nonlinear mixed-effects modeling program, comparing a BW-based model (Model I) and a genotype-guided model (Model II); the latter showed superior predictive performance. Monte Carlo simulations confirmed comparable LCM exposure across regimens, with >78% target attainment in external validation. A fixed 100 mg dose for patients ≥10 kg achieved equivalent exposure to BW-adjusted dosing, with consistent results in 1-4 years and obese patients. These findings enabled BW-band dosing as a clinically viable alternative to mg/kg regimens, while CYP2C19 genotyping further enhanced precision. This PopPK-based strategy simplifies LCM therapy without compromising efficacy, offering a practical approach to personalized epilepsy management in children.

Short-read genome sequencing (GS) is a powerful technique for investigating the genetic etiologies of rare diseases, capturing diverse genetic variations that are challenging to approach with exome sequencing (ES). We performed GS on 260 families with intellectual disability/developmental delay. GS detected potentially disease-related variants in 55 of the 260 families, with structural resolution by long-read sequencing or optical genome mapping, and functional assessment by RNA sequencing. Excluding 31 theoretically ES-resolvable cases, GS yielded likely pathogenic variants in 17 of 229 as well as variants of unknown significance in 7 of 229, totaling 10.5%. These variants implicated several new etiological mechanisms: a microduplication syndrome involving ATP6V0C; disturbed interactions of TBL1XR1 and NR2F1 with putative cis-regulatory elements by chromosomal rearrangements; and a CCG repeat expansion near the CHD3 transcription start site. This study highlights the critical role of GS in clinical diagnostics and its potential to advance understanding of genetic disorders.

Genotype plays a central role in the comprehensive management of pheochromocytomas and paragangliomas, highlighting the critical need for specific in vivo genetic models. Yet, animal models fall short of fully recapitulating the biological complexity of these tumours. We generated first-generation loss-of-function zebrafish models for sdhb, a canonical PPGL-associated gene, using CRISPR/Cas9. Sdhb-CRISPants exhibit increased heart rates, reduced swimming activity and premature death. In whole fish extracts, normetanephrine (NM), metanephrine (MN), and dopamine (DA) levels were about three times higher in sdhb CRISPants than in control larvae. In the bathing medium, NM and MN were also significantly elevated, along with 3-MT. Complementary metabolic and transcriptomic profiling revealed that sdhb CRISPants exhibit a clear signature of Complex II dysfunction and upregulation of genes involved in the hypoxia response, angiogenesis, stress response, and glycolysis. Our work validates the relevance of CRISPant zebrafish models to study the pathogenicity of PPGL-causing genetic variants in vivo.

Pathogenicity assessment of genetic variants is the cornerstone of genetic counselling. Copy gains of exons are challenging, as pathogenicity depends on the localization of the additional exons. Eight patients form six families carried copy gains of BRCA1 exons 8-20. For appropriate characterization, long-read sequencing aligned on three distinct reference genome assemblies, optical genomic mapping, short-read and long-read RNA sequencing were performed. All patients shared the same pathogenic structural variant, involving a large segment located downstream in the genome. One breakpoint occurred in a region incorrectly annotated in GRCh37/hg19 and GRCh38/hg38. Alignment to the T2T-CHM13/hs1 assembly was therefore necessary for accurate characterization. This rearrangement caused various BRCA1 transcriptomic abnormalities: back-splicing, forward genomic strand transcription by insertion of an ectopic promoter, fusion transcripts with the "Next to BRCA1" gene 1 (NBR1). Our findings underscore the need to combine advanced technologies with the latest genome references to resolve complex rearrangements with significant medical implications.

The German National Strategy for Genomic Medicine (genomDE) aims to integrate genome sequencing into standard healthcare. However, integrating genomics data from research and healthcare remains challenging. This study analyzed how the genomDE dataset could be mapped to international standards: the Genomics Reporting Fast Healthcare Interoperability Resources® (FHIR®) Implementation Guide (IG) 2.0.0, the Global Alliance for Genomics and Health (GA4GH)'s Phenopacket Schema, and the German national molecular genomics report IG of the Medical Informatics Initiative (MII). Sample FHIR® bundles and necessary search queries were created and validated. Most dataset elements could be represented using existing FHIR profiles, while unmapped elements were addressed through profiling and extensions. The study highlights that the genomDE dataset can largely be mapped to existing international standards, with the potential to extend these standards to accommodate missing elements, thereby improving genomic data interoperability in healthcare.

Despite advanced diagnostic tools, early detection of rare genetic conditions like Noonan syndrome (NS) remains challenging. We evaluated a deep learning model's real-world performance in identifying potential NS cases using electronic health record (EHR) data, validated through genetic sequencing and clinical assessment. The model analyzed 92,428 patients, identifying 171 high-risk individuals (score > 0.8) who underwent comprehensive review. Among these, 86 had prior genetic diagnoses, including three NS cases diagnosed during the study period. Genetic sequencing of remaining patients identified two additional NS cases with pathogenic variants. The model achieved 2.92% precision and 99.82% specificity. While precision was lower than prior validation (33.3%), this reflected expected differences in disease prevalence rather than model degradation. NS-associated phenotypes were enriched among high-risk patients, and trajectory analysis showed potential for earlier identification, highlighting both promise and limitations of EHR-based computational screening tools.

Asthma poses a significant public health burden. Despite identifying more than a hundred genetic risk loci in genome-wide association studies (GWAS), the underlying functional mechanisms remain poorly understood. Studying omics, especially microRNAs (miRNAs), is a promising approach to facilitate our understanding of the biological pathways of asthma. Here, we performed miRNA expression quantitative trait loci (miRNA-QTL) analyses using whole-genome sequencing and serum-based miRNA expression data from two independent cohorts of children with asthma (Genetic Epidemiology of Asthma in Costa Rica Study (GACRS), (NCT00021840, 2005-06-23) (N = 980, Discovery) and the Childhood Asthma Management Program (CAMP) (NCT00000575, 2005-06-23) (N = 354, Replication)). Our robust discovery analysis identified 28 significant cis-miRNA-QTL associations, where 12 were not reported in three independent miRNA-QTL studies. Three of these 12 signals were replicated in CAMP. The QTLs colocalize with expression and splicing QTL in asthma-relevant tissues and cells, and overlap with asthma-related and blood cell trait GWAS hits.

Pharmacogenetics can enhance cardiovascular disease (CVD) treatment by tailoring drug therapy to genetic profiles and minimising trial-and-error approaches. Genetic variability influences responses to common CVD drugs, including antiplatelet drugs (clopidogrel and aspirin), anticoagulants (warfarin), statins, and antihypertensives (ACE inhibitors and β-blockers). Understanding genetic polymorphisms can improve efficacy and safety. Despite this progress, further research is needed to optimise pharmacogenomic applications and advance personalised medicine to improve CVD treatment outcomes.

Variants affecting pre-mRNA splicing mechanisms are responsible for multiple monogenic disorders. However, their prioritization and interpretation remain challenging. Herein, we designed a strategy for the identification of likely spliceogenic variants in unsolved inherited retinal dystrophy (IRD) cases. We benchmarked thirteen splicing predictors on a curated training dataset, which revealed that the combination of SpliceAI and MaxEnt tools exhibited the best performance for the analysis of most splicing variants. However, for branch point variants, the BranchPoint tool (Alamut®-Batch) was the optimal choice. The proposed combination of tools was assessed using a validation cohort comprising 116 genetically diagnosed individuals with rare diseases, and subsequently applied for the analysis of 211 unsolved IRD families. The pipeline identified 30 likely pathogenic variants, 17 of which were predicted to alter splicing mechanisms. These results demonstrate an increase in diagnostic yield of up to 6.2%, reinforcing the importance of reanalysis strategies focused on identifying spliceogenic variants.

Limited information is available for TP53 pathogenic variants (PVs) in early-onset breast cancer patients in China. We investigated the prevalence and clinical relevance of TP53 PVs among 1492 BRCA1/2-negative early-onset breast cancer patients. Peripheral blood samples were collected for TP53 genetic testing through next-generation sequencing. Finally, TP53 PVs were identified in 7 patients (0.47%). The variants p.R248P, p.I251F, and p.G266R were identified for the first time in germline mutations. TP53 carriers exhibited significantly younger diagnosis age (p = 0.003) and higher prevalence of HER2-positive disease (p = 0.020). All carriers were diagnosed before age 35. In HER2-positive patients ≤35 years, the prevalence of TP53 PVs was 2.3%, significantly higher than others after adjusting for a family history of breast cancer and/or ovarian cancer and a personal history of bilateral breast cancer (OR = 13.57, p = 0.002). These results support TP53 genetic testing prioritization for HER2-positive patients under 35 years to guide clinical management, while validation in diverse populations remains essential.