Molecular correlates of autism-associated behavioral phenotypes

• Applicant: Hanna Hoernberg, Ph.D.
• Subject Area: Experimental Models for the Understanding of Nervous System Diseases ; Molecular Biology and Physiology of Neurons and Glial Cells
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 558807072

Autism is a group of heritable childhood-onset conditions characterized by alterations in social communication and interaction coupled with repetitive and restrictive behavior. There is a wide range and variability of symptoms that is matched by a complex genetic etiology, such that two individuals with autism may have vastly different support needs. In addition, autism shares many characteristics with other neurodevelopmental and psychiatric disorders, including overlapping clinical symptoms and shared genetic risk factors. This large variability between autistic individuals and overlap with other disorders has made the identification of new treatment approaches difficult. Therefore, there is a need to stratify patients into clinically and biologically meaningful subgroups for a personalized medicine approach. Different approaches for stratification have been suggested, including subdividing individuals based on shared behavioral symptoms, underlying genetic risk factors, or neurobiological biomarkers. However, a critical challenge not yet addressed is to what extent genetic or neurobiological biomarkers have predictive value for clinical symptoms. Furthermore, it is not known if similarities in behavioral symptoms are associated with common neurobiological mechanisms. Thus, the main objectives of this proposal are to examine how mutations in functionally similar autism-associated genes affect the prevalence and trajectory of behavioral phenotypes and, at the same time, identify convergent biological mechanisms that can be targeted for treatment. Mouse models with their genetic similarity, ease of genetic and neural manipulation, and range of socioemotional behaviors, provide a useful translational model to address this challenge. To examine the link between genotype and phenotype, we will employ a convergent approach that integrates behavioral phenotyping and mass-spectrometry-based molecular data. We will use a combination of radio-frequency identification and video tracking for detailed phenotyping of multiple behavioral domains throughout development to examine: (i) the phenotypic overlap and individual variability in multiple mouse models for autism, and (ii) how synaptic and neuronal protein networks and signaling pathways correlate with the animal’s behavioral phenotype and genotype. By using novel strategies for preclinical phenotyping that incorporate sex differences and developmental trajectories, this project will deliver fundamental insights into the core biological processes underlying autism-associated behavioral phenotypes, and has the potential to identify new mechanism-based diagnostics and treatment approaches.

• DFG Programme: Research Grants