Rare inherited renal disorders, or RIRD, are a genetically diverse group of conditions that include Alport syndrome, nephrotic syndrome, Dent disease, Lowe syndrome, nephrogenic diabetes insipidus and congenital anomalies of the kidney and urinary tract. Individually each is uncommon, but together they contribute substantially to illness and death, particularly among children and young adults. Many patients progress to end-stage renal disease, requiring dialysis or transplantation. Because these diseases are hereditary, a precise molecular diagnosis matters enormously: it can guide treatment, inform family planning, and identify relatives who may carry the same risk.

Next-generation sequencing has transformed the diagnostic landscape for such conditions. Whole-exome sequencing, which reads the protein-coding portions of the genome, can reveal the causative mutation in a substantial fraction of cases. Yet the technology has also created a new bottleneck. Sequencing routinely flags variants of uncertain significance, DNA changes whose effect on protein function is unknown. Under current classification frameworks such as those of the American College of Medical Genetics and Genomics, these variants cannot be used alone to make a diagnosis. Functional evidence, showing that a variant actually disrupts a gene or protein, is often the decisive factor in reclassifying them as pathogenic or benign.

That evidence is scarce for populations that are underrepresented in global genetic databases, and Sri Lankans are a prime example. Variants that are rare or absent in European and East Asian reference cohorts are frequently classified as uncertain simply because nobody has studied them. The Sri Lankan population, with its complex history and distinct genetic architecture, carries variants that may be unique to the island or shared with South Asian neighbors but poorly documented elsewhere. Building population-specific functional data is therefore not an academic luxury; it directly determines whether a family in Colombo receives a definitive diagnosis or an ambiguous report.

The research team, led by K. M. Fathima Rizna and corresponding author Dineshani Hettiarachchi under the senior authorship of Vajira H. W. Dissanayake, set out to functionally characterize variants previously identified through whole-exome sequencing in Sri Lankan patients with clinically diagnosed rare inherited renal disorders. Their strategy had two complementary arms. The first was real-time quantitative polymerase chain reaction, or RT-qPCR, a laboratory technique that measures how actively a gene is transcribed into messenger RNA in patient samples compared with controls. The second was in silico protein modeling, computational methods that predict the three-dimensional structure of a protein and estimate how a specific amino acid change or truncation might destabilize it.

The gene expression results were striking. Several genes showed reduced expression in patient samples: AVPR2, which carries a missense change and encodes the arginine vasopressin receptor 2 central to water balance in the kidney; DAAM2, a gene involved in actin regulation within kidney filter cells; OCRL, mutated in Lowe syndrome and Dent disease; and CLCN5, a chloride channel gene also implicated in Dent disease. In contrast, NPHS2, which encodes the podocin protein essential for the glomerular filtration barrier, and COL4A5, the collagen gene behind X-linked Alport syndrome, showed increased expression. Most notably, DAAM2 expression was strongly downregulated, pointing to a potential functional relevance for the variant of uncertain significance associated with it. DAAM2 variants have previously been shown to cause nephrotic syndrome through disruption of the actin cytoskeleton, making this finding particularly compelling.

The computational modeling told a consistent story. Truncating variants in COL4A5, OCRL and AVPR2 were predicted to cause significant structural disruption, either by removing essential functional domains or by introducing premature stop signals that terminate protein synthesis early. A missense variant in AVPR2 was predicted to affect a transmembrane region of the receptor, the segment that spans the cell membrane and is critical for the receptor to sit correctly in its cellular location and transmit the vasopressin signal. When the team compared these predictions with their laboratory measurements, the two lines of evidence converged: genes whose proteins were predicted to be severely damaged showed absent or reduced expression in patient samples, a pattern consistent with the modeling results.

This convergence is the methodological heart of the study. Neither approach alone is conclusive. Gene expression changes can be secondary consequences of disease rather than causes, and structural predictions depend on the quality of available templates and the assumptions built into tools such as homology modeling and AlphaFold-based structure prediction. But when a predicted structural catastrophe in a protein aligns with measurably reduced transcription of its gene in the tissue of an affected patient, the case for pathogenicity becomes far stronger. Integrating protein modeling with gene expression analysis, the authors argue, provides functional insights that neither method delivers on its own, and supports the potential reclassification of selected variants of uncertain significance.

The clinical implications reach beyond Sri Lanka. For the families enrolled in the study, functional evidence may convert an uncertain result into an actionable diagnosis, enabling cascade testing of relatives, more accurate recurrence risk counseling, and in some cases access to targeted management. For the wider field, the study demonstrates a practical, relatively low-cost workflow, RT-qPCR plus computational modeling, that laboratories in resource-limited settings can deploy to add functional evidence where expensive experimental systems are unavailable. It also adds Sri Lankan variant data to the global pool, gradually correcting the Eurocentric bias that still distorts variant interpretation worldwide.

Limitations remain, and the authors are careful about what their data can and cannot show. Expression measurements were performed on available patient samples rather than in purpose-built disease models, and computational predictions, however sophisticated, ultimately require experimental validation through approaches such as model organism studies or cellular assays before variants can be definitively reclassified. Patient data could not be deposited in public repositories for ethical and privacy reasons, though it is available from the corresponding author on reasonable request. Nevertheless, the study marks a meaningful step toward diagnostic precision for rare inherited kidney disease in a population that has long waited for its genomes to be read on their own terms, and it offers a template other underrepresented populations can follow.

Subject of Research: Functional characterization of genetic variants associated with rare inherited renal disorders in the Sri Lankan population

Article Title: Functional characterization of genetic variants associated with rare inherited renal disorders in the Sri Lankan population

Article References: Rizna, K. M. F., Noordeen, N., Bandara, W. M. M. S., Hewavitharana, H., Hendalage, B., Neththikumara, N., Hettiarachchi, D., & Dissanayake, V. H. W. (2026). Functional characterization of genetic variants associated with rare inherited renal disorders in the Sri Lankan population. Molecular Genetics and Genomics, 301(1), Article 201. https://doi.org/10.1007/s00438-026-02524-x

Image Credits: AI Generated

DOI: 10.1007/s00438-026-02524-x

Keywords: rare inherited renal disorders, whole-exome sequencing, variants of uncertain significance, RT-qPCR, in silico protein modeling, Sri Lanka, kidney genetics, Alport syndrome, nephrotic syndrome, DAAM2, AVPR2, COL4A5