Using advanced data analysis to understand autism and its symptoms
Official title: A Modular Framework for Data-Driven Neurogenetics to Predict Complex and Multidimensional Autistic Phenotypes
Funded at Boston University (Charles River Campus) · NIH-10847527 · Data updated 2026-11-12
This study is looking at how brain images and genetic information can help us understand the different symptoms of Autism Spectrum Disorder (ASD) better, so we can create more personalized treatment options for children with ASD.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Boston University (Charles River Campus) NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | June 1, 2023 |
| Project end | May 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $438,718 |
| NIH project number | 5R01HD108790-03 |
| Project ID | NIH-10847527 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children aged 0-11 years who exhibit symptoms of Autism Spectrum Disorder.
✕Less likely to help
Patients who do not have symptoms of Autism Spectrum Disorder or are older than 11 years may not benefit from this research.
What this research studies
This research investigates Autism Spectrum Disorder (ASD) by integrating brain imaging and genetic data to better understand the diverse symptoms associated with the condition. By developing advanced deep learning models, the project aims to link genetic variations with brain structure and function, providing a more comprehensive view of ASD. The goal is to create a modular platform that can help personalize treatment options based on individual patient profiles. This approach seeks to improve the accuracy of diagnoses and the effectiveness of interventions for children with ASD.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective treatment options for children with autism.
How similar studies have gone: Previous research in imaging-genetics has shown promise in linking neuroimaging features with genetic data, suggesting potential for success in this innovative approach.
Where this research is happening
-
Boston University (Charles River Campus)
Boston, United States Active
Researchers
- Principal investigator: Venkataraman, Archana — Boston University (Charles River Campus)
- Study coordinator: Venkataraman, Archana
Related research
Other NIH-funded projects on the same topics.
-
How Arousal Changes How We See the World
This grant studies how moments of alertness or mood changes alter how the brain processes what we see.
-
NGF Metabolism as a biomarker for cognitive decline in familial Alzheimer's disease
Researchers are studying whether patterns in nerve growth factor pathways in blood and CSF can signal early, preclinical stages of Alzheimer's in people with genetic risk.
-
NGF metabolism as an early biomarker for cognitive decline in familial Alzheimer's disease
This project tests whether NGF pathway proteins in blood and CSF can signal early, preclinical changes in people with familial Alzheimer’s disease.
-
Ultra-High Density wearable brain monitoring in real life
Aims to make advanced wearable brain sensors that work in daily life to track brain activity alongside movement, perception, and communication.
-
A new method to image brain activity noninvasively using speckle contrast spectroscopy
A new, noninvasive imaging technique called speckle contrast optical spectroscopy (SCOS) could help measure brain blood flow in people, including those with brain injuries or neurodegenerative conditions.
-
NGF Metabolic Dysfunction as a Marker of Cognitive Decline in Autosomal Dominant Alzheimer's Disease
This project looks at nerve growth factor pathways in people with a genetic form of Alzheimer's to see if blood and spinal fluid markers can identify early brain changes before symptoms appear.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.