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Key takeaways:
- Large-scale genomic and clinical datasets can help researchers uncover genetic patterns that may be missed in smaller studies.
- The analysis identified ETF1 and IGF2BP1 as candidate genes for further investigation into microcephaly; additional validation is needed before these associations can be considered established causes of disease.
- The analysis also identified established microcephaly-associated genes, supporting the research approach.
- The approach could potentially support investigation of other rare diseases and emerging gene-disease relationships.
Understanding gaps in microcephaly genetics
For patients with rare diseases, identifying an underlying genetic cause can be life changing. Yet even with advances in exome and genome sequencing, many patients remain without a molecular diagnosis.
One reason is that our understanding of the relationship between genes and disease is still evolving.
While thousands of gene-disease associations have been established, many others remain unknown or insufficiently understood. Even when a genetic variant is detected, the available scientific evidence may not be enough to determine whether it contributes to a patient's condition.
Closing these knowledge gaps requires more than the ability to sequence DNA. It requires comprehensive genomic data, detailed clinical information, and the ability to identify meaningful patterns across large patient populations.
That's where the scale and depth of genomic data become particularly valuable.
Investigating microcephaly genetics at scale
At the 2026 American Society of Human Genetics (ASHG) Annual Meeting, GeneDx presented research demonstrating how large-scale clinical genomic data can support systematic gene discovery.
The study, Large-Scale Gene-Based Burden Analysis Reveals the Genetic Architecture of Microcephaly in 25,000 Individuals, was selected as a Reviewers' Choice poster.
Microcephaly, a condition characterized by a smaller-than-expected head size, can be associated with a wide range of genetic and neurodevelopmental disorders. Although numerous disease-associated genes have been identified, many affected patients still lack a definitive molecular diagnosis.
To investigate potential additional gene-disease associations, GeneDx researchers leveraged GeneDx Infinity™, the world's largest rare disease genomic dataset, to conduct a large-scale gene-based burden analysis.
The research included:
- 25,779 individuals with microcephaly
- 19,529 genes analyzed
- 476,448 unrelated parents and 418,542 non-microcephaly probands serving as comparison groups
Researchers evaluated whether qualifying rare variants in specific genes were enriched among patients with microcephaly compared with control populations.
By using two different control groups, the researchers could examine the robustness and specificity of the observed associations.
What the research revealed about microcephaly-associated genes
The analysis successfully recovered several established microcephaly-associated genes, including DYRK1A, KIF11, ASPM, FOXG1, DDX3X, TUBA1A, and WDR62.
Importantly, the analysis also identified two promising candidate genes, ETF1 and IGF2BP1, that demonstrated strong statistical associations across both control comparisons.
By identifying both established disease-associated genes and promising new candidates, the research demonstrates how the scale of Infinity can help scientists distinguish meaningful genetic patterns from background variation and prioritize new avenues for investigation.
While the candidate associations require additional validation before they can be considered established causes of disease, the study provides proof of concept for using Infinity to systematically investigate gene-disease associations at scale.
And the opportunity extends beyond microcephaly. The same analytical approach could potentially be applied to other clinical phenotypes, creating new avenues for rare disease research.
How genomic data can advance rare disease gene discovery
Sequencing technology continues to advance, allowing laboratories to detect an increasingly broad range of genetic variation. But identifying variants is only part of the challenge.
Understanding what those variants mean, and uncovering the gene-disease relationships that remain unknown, requires a continually evolving body of scientific evidence.
With more than one million exomes and genomes, Infinity provides GeneDx researchers with an extensive resource for identifying patterns across patient populations, investigating emerging gene-disease associations, and expanding our understanding of rare disease.
The microcephaly study demonstrates the potential of this approach. By combining the scale and depth of Infinity with advanced analytical methods and scientific expertise, GeneDx can pursue discoveries that may ultimately contribute to more definitive answers for patients.
