Researchers at Dongguan Maternal and Child Health Care Hospital in China retrospectively analyzed 99 children born small for gestational age who had either failed to show catch-up growth, presented with multisystem anomalies, or both. Using trio-based whole-exome sequencing, in which the affected child and both parents are sequenced together, the team searched for the genetic roots of these children’s conditions. The results were striking: a confirmed molecular diagnosis was established in 59 of the 99 children, a diagnostic yield of 59.6 percent.

Trio-based whole-exome sequencing works by capturing and reading the protein-coding portions of the genome—the exome—in all three members of a family. Because the parents’ sequences are available for comparison, scientists can determine whether a suspicious variant was inherited from a carrier parent or arose spontaneously in the child. This segregation analysis is critical for interpreting variants correctly, since the same DNA change can be harmless in one context and disease-causing in another.

The study’s methodology went beyond simple sequence analysis. In addition to examining single-nucleotide and small insertion-deletion variants, the researchers mined the sequencing read-depth data to infer copy-number variants—large deletions or duplications of chunks of chromosomes that conventional exome pipelines often miss. Sequence variants were confirmed by Sanger sequencing, the older but highly accurate method of reading individual DNA fragments. Variants were then classified using the standards developed by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology for sequence variants, and the ACMG/ClinGen criteria for copy-number variants.

Only pathogenic or likely pathogenic findings whose inheritance pattern fit the family data were counted as molecular diagnoses. This conservative approach matters in clinical genetics, where over-interpretation of ambiguous variants can lead to false diagnoses. The team also identified four variants that remained classified as variants of uncertain significance—changes that could not be confidently labeled benign or disease-causing and therefore did not count toward the diagnostic yield.

Breaking down the 59 diagnoses, the researchers found considerable diversity in the underlying genetic architecture. Monogenic disorders—single-gene defects—accounted for the largest share, explaining 44 children, or 74.6 percent of the diagnosed cases. Copy-number variants explained 13 children, or 22.0 percent. Notably, two children received dual diagnoses, carrying both a disease-causing sequence variant and a pathogenic copy-number variant, a reminder that a single genetic explanation is not always sufficient.

The diagnostic yield differed meaningfully between the two clinical presentations. Among children with isolated failed catch-up growth—those born small who never caught up but had no other anomalies—trio-WES produced a diagnosis in 52.9 percent of cases, or 9 of 17 children. Among children with multisystem anomalies, the yield rose to 61.0 percent, or 50 of 82 children. The higher yield in the multisystem group aligns with genetic principles: when developmental disturbances affect multiple organ systems, a shared underlying genetic cause becomes more likely, and the genome search has more clinical features to anchor interpretations.

The clinical implications are considerable. A molecular diagnosis does more than attach a name to a condition. It can redirect management toward condition-specific surveillance and treatment, inform parents about recurrence risks for future pregnancies, and spare families a prolonged diagnostic odyssey of repetitive and often invasive testing. For children born small for gestational age, identifying a specific genetic syndrome may reveal risks—such as endocrine dysfunction, renal anomalies, or tumor predisposition—that would otherwise be missed. Genetic counselling grounded in an identified inheritance model allows clinicians to tell parents precisely whether the condition could recur in a subsequent child.

The authors are careful to draw boundaries around their conclusions. The 99 children in this study were not a random sample of all children born small for gestational age; they were a clinically selected, high-risk subgroup who had already raised concern because of persistent growth failure or anomalies affecting multiple systems. The researchers explicitly caution that the 59.6 percent diagnostic yield should not be generalized to the overall SGA population, most of whom are simply constitutionally small and healthy. Applying expensive genome-wide testing to every child born small, without clinical red flags, would produce far lower yields and risk incidental and ambiguous findings.

Still, the study adds to a growing body of evidence that trio-based genomic sequencing should be considered early rather than late in the evaluation of children with unexplained growth failure and congenital anomalies. As sequencing costs continue to fall and analytical tools improve—including methods that detect copy-number variants from exome data without separate chromosome microarray testing—the case for a single comprehensive genetic test at the start of the diagnostic journey grows stronger. For families facing the anxiety of a child who is not growing as expected, a faster path to answers may now be within reach.

Subject of Research: Use of trio-based whole-exome sequencing to diagnose genetic disorders in children born small for gestational age with failed catch-up growth or multisystem anomalies

Article Title: Clinical application of trio-based whole-exome sequencing in children born small for gestational age with failed catch-up growth or multisystem anomalies

Article References: Jiang, Z., Zhong, X., Lin, P., Yan, T., He, W., Guo, L., Xie, Y., Yuan, H., & Cheng, S. (2026). Clinical application of trio-based whole-exome sequencing in children born small for gestational age with failed catch-up growth or multisystem anomalies. BMC Pediatrics. https://doi.org/10.1186/s12887-026-07633-5

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07633-5

Keywords: small for gestational age, trio whole-exome sequencing, failed catch-up growth, multisystem anomalies, molecular diagnosis, copy-number variants, genetic counselling, pediatrics, next-generation sequencing, rare variants, clinical genetics, Clinical

The clinical problem the team set out to address is well known in genomic medicine. Molecular diagnosis of rare disease currently plateaus at roughly fifty percent of patients, even after whole exome or whole genome sequencing. A substantial share of those unresolved cases involves variants that alter splicing, the process by which RNA transcripts are cut and re-joined to produce mature messenger RNA. Predicting whether a DNA change actually disrupts splicing in a patient’s tissues remains notoriously difficult, and variants of uncertain significance accumulate in reports without a practical way to test their effects directly.

Short-read RNA sequencing, which fragments transcripts into small pieces before reading them, often cannot show how exons connect across a whole transcript. Long-read platforms from Oxford Nanopore Technologies solve this by reading RNA-derived molecules end to end, revealing full isoform structures. Until now, however, long-read RNA approaches have typically demanded large control cohorts, complex bioinformatics and tissue samples that are hard to obtain, keeping them confined to specialist research laboratories rather than routine diagnostics.

RAPID, short for RNA Analysis Pipeline for Integrated Diagnostics, was designed from the outset to be diagnostically deployable. It is fully modular, covering the entire sample-to-answer journey, from primer design targeting genes of interest through nanopore sequencing to reproducible single-sample interpretation. Cases entered the workflow after exome or genome sequencing and multidisciplinary team review had narrowed the search to five or fewer candidate genes, meaning the sequencing effort could be focused and fast. Crucially, the method relies on accessible tissues such as blood and does not require large control datasets for interpretation.

The study applied the workflow to six probands with suspected monogenic neurometabolic disease, and the outcomes illustrate three distinct diagnostic scenarios. In two cases, targeted long-read RNA sequencing confirmed pathogenic splice disruption at the transcript level, converting uncertainty into a resolved molecular diagnosis. In one case, the RNA evidence argued against a candidate gene, prompting its exclusion and redirecting the diagnostic search. In the remaining three cases, transcript-level findings prioritised further DNA investigation, refining how the variants of uncertain significance should be weighed.

Technically, the workflow captured amplicons spanning the relevant exons and splice junctions of each candidate gene, generating reads long enough to assemble near-full-length isoform structures. The team demonstrated reproducibility by showing consistent isoform composition for a control gene across commercial blood RNA samples and an independent public long-read dataset, and they characterised the minimum read depth needed to detect transcripts at low fractional abundance. Quality control metrics, including read length and depth, were achieved using standard long-read sequencing infrastructure within a clinically relevant timeframe.

The authors also mapped their RNA results onto the established variant interpretation framework used by clinical scientists, in which aberrant splicing leading to frameshifts or premature stop codons, particularly in transcripts subject to nonsense-mediated decay, can support pathogenic classifications. By providing direct, mechanism-level evidence rather than in silico predictions, the workflow strengthens this evidence hierarchy and gives diagnostic laboratories a practical route to resolving variants that would otherwise remain reportable only as uncertain.

The significance for patients and families is considerable. A definitive molecular diagnosis can end a diagnostic odyssey that sometimes lasts decades, inform prognosis, guide surveillance and treatment, enable accurate genetic counselling, and open doors to targeted therapies and clinical trials. For a field in which half of patients still leave the sequencing process without answers, a rapid, cost-effective test that interrogates RNA directly addresses one of the largest remaining diagnostic gaps.

The researchers argue that RAPID shows long-read RNA sequencing can be implemented within existing diagnostic infrastructure, offering a scalable path to routine transcript-level assessment in clinical genomics. As nanopore sequencing becomes more widespread in NHS and hospital laboratories, workflows of this kind could shift splicing variant interpretation from probabilistic prediction to direct functional measurement. Supported by funding from the charity Sparks and conducted with appropriate ethical approvals and participant consent, the study points toward a future in which reading the transcript itself becomes a standard step in solving rare disease.

The biological importance of splicing in human disease provides useful context for why this approach matters. Introns interrupt most human genes, and their precise removal depends on short sequence signals at exon boundaries that are frequently disrupted by single-nucleotide changes lying well outside protein-coding regions. Because such variants often sit in positions that protein-prediction tools ignore, they can be classified as benign or left as uncertain even when they silently abolish a transcript. Deep intronic changes can also activate cryptic exon inclusion, an effect essentially invisible to standard exome analysis, which is one reason splice-altering variation has been described as a substantial hidden burden within the undiagnosed fraction of rare disease cohorts.

The interpretation framework applied in the study reflects a broader international movement toward using RNA evidence in clinical classification. Guidelines from professional bodies now allow aberrant splicing demonstrated at the transcript level to contribute to pathogenic classifications, provided the altered transcript is shown to escape nonsense-mediated decay or to produce a clearly deleterious product. This matters because a large proportion of loss-of-function variants predicted to trigger nonsense-mediated decay are already treated as pathogenic by default; demonstrating experimentally that a variant of uncertain significance produces the same consequence effectively moves it into that well-established category. Conversely, showing that a candidate variant leaves splicing intact can be equally decisive, as the gene-exclusion case in this cohort illustrates.

Tissue choice is a central consideration for any transcript-based diagnostic test. Genes are not expressed uniformly across the body, and the reference resources that underpin transcript interpretation, such as population-scale tissue atlases, show that many disease-relevant genes have their highest expression in tissues that cannot ethically or practically be sampled. Blood, however, is accessible, and the workflow’s reliance on peripheral blood RNA, collected in standard preservation tubes and stored frozen, means the logistics resemble those of routine clinical phlebotomy rather than specialist tissue procurement. The supplementary analyses showing that isoform composition of a control gene is consistent across commercial RNA references and public datasets speak to the reproducibility that regulators and accreditation bodies would expect of a deployable assay.

The depth requirements characterised by the team address a practical question that any diagnostic laboratory must answer before adopting such a test: how much sequencing is enough. Because a deleterious transcript may represent only a small fraction of all transcripts from a given gene, particularly when nonsense-mediated decay degrades the abnormal product rapidly, sensitivity at low fractional abundance is essential. Mapping the relationship between transcript rarity and required read depth gives laboratories a principled basis for setting sequencing targets and quality thresholds rather than relying on ad hoc criteria.

The study also sits within a distinctive UK genomic infrastructure. Several participating families had previously been sequenced through national genome programmes, and the ethical frameworks governing those programmes permit recontact of participants for follow-up sampling, a mechanism that allowed the researchers to obtain fresh RNA from already-investigated patients. This recontact pathway, coordinated through clinical interpretation partnerships, represents a model for how long-read RNA follow-up could be layered onto existing genomic medicine services without requiring patients to restart the consent and recruitment process from scratch.

From a health-systems perspective, the economics of the approach deserve emphasis. Whole genome sequencing has become affordable at scale, but the interpretation bottleneck, not the sequencing itself, now limits diagnosis. A targeted assay that sequences only a handful of genes consumes modest sequencing capacity on instruments that many hospital laboratories already operate or can readily access, and the modular design means primer sets can be redesigned quickly for each new case. The near-full-length isoform output also reduces interpretive ambiguity, because the analyst sees the complete exon connectivity of each transcript rather than inferring it from fragmented short reads.

The neurometabolic focus of the cohort is itself informative. Leukodystrophies and related neurodegenerative conditions of childhood often present with nonspecific imaging findings and progressive symptoms, and several of the genes implicated in these disorders are known to harbour splice-disrupting variants that confound standard pipelines. For families facing such progressive conditions, the speed of the workflow is not merely convenient; an earlier molecular answer can determine eligibility for emerging therapies, some of which are most effective when started before irreversible neurological damage accumulates.

Looking forward, the study suggests a tiered model of genomic diagnosis in which short-read sequencing remains the first-line discovery tool, while targeted long-read RNA analysis serves as a rapid functional triage step for the subset of cases with splice-relevant candidates. The authors’ demonstration that results can be obtained within a clinically relevant timeframe, using standard infrastructure and single-sample interpretation without large control cohorts, positions transcript-level evidence to become a routine component of multidisciplinary review rather than a research exception reserved for specially funded projects.

Subject of Research: A targeted long-read RNA sequencing workflow for functionally resolving splicing variants in rare disease diagnosis

Article Title: RAPID: a targeted long-read RNA workflow for functional resolution of splicing variants in rare disease

Article References: Montgomery, K.-A., Macpherson, H., Anderson, C., Wade, C., Gustavsson, E. K., Lynch, D. S., Wilson, L. C., Davison, J., Wakeling, E., Tuschl, K., Houlden, H., Clement, E., Mills, P. B., & Ryten, M. (2026). RAPID: a targeted long-read RNA workflow for functional resolution of splicing variants in rare disease. Genome Medicine. https://doi.org/10.1186/s13073-026-01754-3

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01754-3

Keywords: long-read RNA sequencing, Oxford Nanopore Technologies, splicing variants, rare disease diagnostics, variants of uncertain significance, neurometabolic disease, transcriptomics, molecular diagnosis, clinical genomics, whole exome sequencing, RNA splicing, diagnostic workflow