# 1/2 Cross modal integration of molecular and physiological networks in ASD

> **NIH NIH U01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $1,031,274

## Abstract

Genetic approaches have been successful in identifying causal genetic factors, both common and rare, that
contribute to risk for autism spectrum disorder (ASD), providing a crucial starting point for mechanistic
neurobiological investigations. However, moving towards an integrated mechanistic understanding of ASD at
a molecular, cellular, and circuit level faces substantial challenges, such as extreme genetic heterogeneity
and the lack of causal frameworks with which to connect different levels of analysis of nervous system
function in model systems or patients. Nearly a decade ago, we reasoned that gene and protein networks
would provide an organizing framework for understanding heterogeneous psychiatric disease genetic risk in a
unified context and inform disease modeling; indeed there is now substantial evidence supporting
convergence of major effect risk genes during mid-fetal cortical development. Furthermore, related functional
genomic studies, including in those with a major gene form of ASD (dup)15q11-13, show shared patterns of
transcriptional and chromatin dysregulation in post-mortem ASD brain, further supporting biological
convergence. Where and how this occurs, and what biological mechanism(s) it reflects is not known. To
address this, we propose an ambitious project that addresses several major challenges in establishing causal
linkages between genetic risk and CNS structure and function in ASD. The work proposed in this multi-PI U01
involves a team of four principal investigators and co-investigators from UCLA and Stanford with the expertise
necessary to perform this work using state of the art methodologies, ranging from developing and
characterizing in vitro models of human brain development, stem cells, physiology, genomics, physics, and
behavior. Through close collaboration, we will develop and analyze in vitro human stem cell based models
that are differentiated from induced pluripotent stem cells and assembled into organized 3D brain cultures
called human forebrain spheroids (hFS). These hFS contain the major cell classes of the developing
forebrain, including progenitors, radial glia, cortical interneurons, glutamatergic neurons, and non-reactive
astrocytes, and form functional synapses. We will model the effects of six major effect ASD risk loci in hFS
with molecular, genomic, and physiological analyses to assess convergence at each level of analysis. We will
also conduct comparisons of physiology using three rodent models based on the same genes modeled in vitro
with the aim of integrating phenotypes to develop predictive models and compare with in vivo rodent models.
We will analyze the relationship of molecular alterations and basic cellular and synaptic features with potential
emergent or dynamic network features in control-derived hFS and compare these features with hFS harboring
ASD risk mutations and test a subset of causal relationships based on network model predictions. Completion
of these aims will lead to a more...

## Key facts

- **NIH application ID:** 9995576
- **Project number:** 5U01MH115746-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** DANIEL H GESCHWIND
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,031,274
- **Award type:** 5
- **Project period:** 2017-09-21 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9995576

## Citation

> US National Institutes of Health, RePORTER application 9995576, 1/2 Cross modal integration of molecular and physiological networks in ASD (5U01MH115746-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9995576. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*