Summary
Long-read sequencing, combined with transcriptomic profiling and functional assays, resolved six out of seven cases of unresolved inherited metabolic diseases, revealing pathogenic variations outside coding regions. This highlights the importance of considering non-coding variants in genetic diagnoses. Additionally, a study on diffuse large B-cell lymphoma (DLBCL) using single-cell RNA sequencing and ATAC-seq revealed extensive intratumoral heterogeneity and subtype-specific gene-expression programs, suggesting a dynamic ecosystem rather than a static diagnostic category.
Editors: Donna E. Hansel, MD, PhD, division head of pathology and laboratory medicine, MD Anderson Cancer Center, Houston; James Solomon, MD, PhD, assistant professor, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York; Erica Reinig, MD, assistant professor and medical director of molecular diagnostics, University of Wisconsin-Madison; Marcela Riveros Angel, MD, molecular genetic pathology fellow, Department of Pathology, Oregon Health and Science University, Portland; Maedeh Mohebnasab, MD, assistant professor of pathology, University of Pittsburgh; Alicia Dillard, MD, molecular pathologist, Sonic Healthcare USA, Rye Brook, NY; and Richard Wong, MD, PhD, assistant professor of pathology, University of California San Diego.
Use of long-read sequencing to monitor diagnostic blind spots of inherited metabolic diseases
April 2026—Inherited metabolic diseases are frequently suspected when biochemical testing reveals abnormal metabolites or disrupted metabolic pathways. Yet even when clinical suspicion is strong, standard genetic testing, particularly exome sequencing, often fails to identify a clear molecular diagnosis. The authors conducted a study to address the increasingly recognized problem of many pathogenic variants lying outside the regions reliably detected by conventional short-read sequencing. To overcome these diagnostic blind spots, the authors applied a combined strategy using targeted long-read sequencing, transcriptomic profiling, and functional assays in a group of patients with unresolved metabolic disease. Rather than identifying new disease genes, the study demonstrated that many unresolved cases involved known metabolic genes disrupted by previously undetectable mechanisms. In one patient, for example, an exon duplication that had been missed by earlier methods was detected by long-read sequencing. RNA sequencing confirmed altered gene expression, and functional validation showed that this alteration was sufficient to impair normal gene function. In another patient, long-read sequencing identified a deep intronic variant that generated a cryptic splice site. Other patients had alterations that required multiple additional studies to elucidate. These alterations included structural rearrangements causing exon duplication, transposable element insertions producing aberrant splicing, intronic variants generating pseudoexons, and regulatory alterations that reduced gene expression without affecting coding sequences. Across the study cohort of seven patients with unconfirmed metabolic diseases, a combined strategy of long-read sequencing, RNA profiling, and functional assays resolved six of the seven cases. The study demonstrated that pathogenic variation frequently lies outside coding regions assessed by routine testing. The findings emphasize that a negative exome does not rule out a genetic diagnosis, particularly when biochemical and clinical evidence strongly supports a metabolic disorder. In summary, this study illustrates a shift in clinical genetics by moving from sequence interpretation alone toward functional multi-omic analysis. Long-read sequencing, when guided by clinical phenotyping and RNA data, can uncover hidden pathogenic mechanisms and significantly increase diagnostic yield. As these technologies become more accessible, they may reshape diagnostic workflows for inherited metabolic disease by helping laboratories move beyond coding variants and toward a more complete understanding of genome structure and gene regulation.
Soriano-Sexto A, Sanchez-Lijarcio O, Beccari L, et al. Expanding the genetic landscape of inherited metabolic diseases using long-read sequencing and transcriptomic profiling. Eur J Hum Genet. 2026. doi.org/10.1038/s41431-025-01995-7
Correspondence: Dr. Belén Pérez at [email protected] or [email protected]