Rare genetic diseases affect millions worldwide, but most have no effective treatment. Around 95% lack an approved therapy or validated drug target, leaving patients with limited options¹. Advances in genome and exome sequencing have accelerated the rate at which new pathogenic variants are identified, but functional studies and therapeutic development lag far behind. This gap is especially acute for disorders affecting the nervous system, which make up an estimated 74% of rare diseases and often present with complex, variable symptoms.
Most rare conditions are too uncommon to attract sustained commercial investment, so progress often relies on academic groups and public funding. Without approaches that scale across many disorders, a large number of variants remain uncharacterized. Progress requires experimental systems that can be applied broadly, not on a case-by-case basis.
Model organisms offer one way to close this gap. The nematode, Caenorhabditis elegans, shares many conserved genes with humans, can be genetically edited with precision, and is amenable to large-scale experiments. These features make C. elegans a useful model to study the functional impact of variants and run drug screens more quickly and at lower cost than vertebrate models.
Previous work has shown that high-throughput behavioral profiling in C. elegans can systematically detect disease-relevant phenotypes and even identify compounds that rescue mutant strains2. A new study, by O’Brien et al. (2025)3, builds on this, extending the approach to patient-specific mutations, making the models more clinically representative.
The authors created 25 C. elegans strains carrying mutations linked to human genetic disorders, including complete loss-of-function alleles and single amino acid substitutions identified in patients. Each strain was tracked in multiwell plates under a standardized 16-minute protocol that recorded baseline behavior, responses to blue light, and recovery afterwards. Automated image analysis extracted more than 8,000 features per strain, covering morphology, posture, and locomotion.
All 25 strains differed from wild-type worms. Loss-of-function mutations in genes affecting complexes and regulators like BORC, FLCN, and FNIP2 produced strong, reproducible behavioral phenotypes, making them suitable for high-throughput drug screening. Patient-specific variants showed a range of effects. For example, a missense mutation in smc-3 produced viable worms with distinct behavioral and developmental differences, despite the complete loss of the gene being lethal. In contrast, a variant in tnpo-2 showed only subtle changes under normal conditions, but its phenotype became detectable after chemical sensitization with aldicarb. The authors also found that mutations in related cellular processes often led to similar behavioral profiles, suggesting that worm phenotyping can capture disease-relevant pathways.
The study shows that high-throughput behavioral profiling of C. elegans can capture a wide spectrum of variant effects, from severe to subtle. Strong phenotypes in loss-of-function mutants confirm that the assay is sensitive and reproducible, while the ability to detect and enhance weaker phenotypes demonstrates flexibility. This means that even variants with modest effects can still be associated with behavioral changes under the right conditions.
The clustering of phenotypes across genes with related functions indicates that the approach does not only pick up arbitrary behavioral noise but also reflects underlying biology. This strengthens the case for using worms as avatars of human disease, where phenotypic similarity can point to conserved pathways relevant to pathology.
The work also shows how patient-specific mutations can be studied in living organisms without requiring a detailed mechanistic hypothesis in advance. By focusing on measurable behavioral outcomes, researchers can generate data that can be used to prioritize targets for drug screening.
Along with previous work, the results suggest that worm models could serve as an intermediate platform between genetic diagnosis and therapeutic testing, aligning functional modelling more closely with the pace of new variant discovery.
Worms & Rare Disease Research
C. elegans has been a workhorse of genetics and developmental biology for decades, with a well-annotated genome and established use in modelling disease processes. In this work, however, our old friends are put to work in a new way. The authors apply high-throughput, automated phenotyping to a panel of patient-specific mutations, creating a standardized assay that can be scaled across many variants. This moves the worm from being a model for basic biology to a potential platform for systematic, clinically relevant functional testing.
Each year, many new rare disease genes are added to clinical databases, but only a fraction will be investigated in detail. Most individual conditions are too uncommon to attract sustained commercial investment, leaving academic groups and public funding programs to take the lead. Without new scalable models, many of these variants will remain uncharacterized. Automated behavioral profiling in worms may help reduce this bottleneck. Strains can be engineered and phenotyped quickly, and the same assay can be applied across diverse pathways. Comparing behavioral profiles also helps identify conserved mechanisms that may connect seemingly unrelated conditions.
There are limits to what worms can achieve. Behavioral fingerprints are not clinical endpoints, and translation requires careful validation in vertebrate systems and patient-derived cells. Their value lies in generating reproducible, disease-relevant signals that can prioritize genes and compounds for further testing.
Progress will depend on sustained infrastructure and funding. Initiatives in Europe and the USA have identified rare disease research as a priority, but resources remain fragmented. Connecting patient registries, sequencing programs, and functional model systems will be essential to ensure new genetic findings can move towards clinical practice.
By showing that patient-specific variants can be modelled and screened at scale, this study suggests a way to align functional testing with the pace of gene discovery. It illustrates how long-standing model organisms can be repurposed with new tools to address one of the central challenges in rare disease research.