Stanford Study Unveils Common Genetic Pathways in Autism

Research from Stanford University has revealed significant insights into autism, identifying shared genetic pathways linked to the condition. Published in the journal Nature in January 2023, the study shows that numerous mutations associated with autism converge on common biological pathways that influence brain development.

Autism has long been associated with mutations in over 100 genes. However, the findings from this study, which is among the largest of its kind, suggest that these mutations collectively impact specific biological mechanisms. The researchers utilized more than 90 patient-derived stem cell lines to create synthetic brain “organoids,” allowing them to model and observe these pathways during early brain development.

By analyzing dozens of genetic variants over the first 100 days of development, the team tracked how distinct mutations affect early brain formation and the points at which their impacts begin to overlap. “Rather than examining single genes in isolation, we systematically compared multiple high-confidence risk genes across defined developmental windows in a human stem cell-derived model of the cortex,” stated Sergiu Pasca, co-senior author and professor of psychiatry and behavioral sciences.

The research was a collaborative effort involving various institutions, including the Pasca Lab, the Broad Institute, and the Geschwind Lab at the University of California, Los Angeles (UCLA). Pasca’s team specializes in developing three-dimensional organoid models from reprogrammed stem cells, which mimic molecular changes occurring during fetal brain-like development. As direct study of the human brain during its development is not feasible, organoids offer a novel approach to investigating how genetic mutations influence neural function.

“We recognized very early on that to carry out something like this takes a multi-disciplinary team,” said Daniel Geschwind, co-senior author and UCLA human genetics professor. His lab has conducted genomic profiling of postmortem brains, revealing that individuals with autism share some molecular pathways. “By studying one mutation, you can’t really be sure that what you’re looking at isn’t specific to that particular mutation. So we’re trying to identify commonalities that could be involved,” he explained.

The researchers were surprised by the strong mutation-specific signatures observed during early developmental stages, followed by emerging convergence as development progressed. This insight may have important implications for the timing of clinical interventions. “A lot of work needs to be done to understand optimal timing for intervention for each different form of autism,” Geschwind noted. “But now that we have these models, we can actually test the question: Can we intervene early?”

Clinical geneticist Jon Bernstein of Stanford, who contributed to the study, pointed out that many patients with autism demonstrate differences in learning and behavior early in life, aligning with the early developmental variations identified in the research. Nevertheless, he cautioned that translating findings from organoids into effective therapies will require time and further investigation. “The results highlight that autism can have complex and varying origins and manifestations, so there is still more to learn.”

While autism remains genetically complex and highly variable, this study indicates that its underlying biology may be less fragmented than previously believed. Looking ahead, Pasca envisions organoid technologies as not only platforms for discovery but also as engines for therapeutic development. His lab has already employed similar stem cell-derived models to study Timothy syndrome, another rare neurodevelopmental disorder, identifying potential treatments for future clinical testing.

Geschwind aims to integrate computational methods with biology to create high-throughput tools capable of analyzing thousands of mutations simultaneously. “We need datasets across many different mutations,” he stated. “If done properly, those data can be used to train models for drug discovery.”

The collaborative nature of this research underscores the importance of interdisciplinary approaches in understanding complex conditions like autism. As scientists continue to delve into the genetic intricacies of autism, the potential for tailored interventions and improved therapeutic strategies becomes increasingly plausible.