# Functional genomics of the human connectome in psychiatric illness

> **NIH NIH R01** · YALE UNIVERSITY · 2021 · $669,224

## Abstract

PROJECT SUMMARY/ABSTRACT
Converging evidence indicates that the boundaries separating nominally distinct psychiatric diagnoses are not
sharp or discontinuous with normal behavioral traits and brain function. In healthy populations, individual
differences in behavior are reflected in variability across the collective set of functional brain connections
(functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in
patient populations may arise through detectable patterns of network function. The intrinsic connectivity of the
functional connectome is under strong genetic influence. Spatial patterns of gene transcription recapitulate the
topography of large-scale brain networks, potentially driving comorbidity between symptomatically related
disorders. However, most of what we currently know about the human connectome comes from the study of
healthy populations, impeding the development of fully dimensional models of brain function and obscuring the
interactions through which genetic and neurobiological variation might coalesce to support suites of behaviors
and illness risk within an individual. To address the disconnect between mechanism and nosology, the NIMH
strategic plan calls for a bottom-up reappraisal of psychopathology across multiple levels of analysis;
facilitating the study of relationships from genes to neural circuits and networks through behavior, cutting
across disorders as traditionally defined. Directly addressing these objectives, our proposal will link individual
variation in functional connectomes with symptom profiles across unipolar depression, bipolar depression, and
schizophrenia through the combined application of neuroimaging, behavioral, and genomic methods. We will
establish key biological and clinical features of the functional connectome in three stages. First, we recently
established that disruptions within the frontoparietal network (spanning aspects of dorsolateral and
dorsomedial prefrontal, lateral parietal, and posterior temporal cortices) reflect a shared feature of
schizophrenia and psychotic bipolar disorder. Building upon this work, we will quantify the extent to which
frontoparietal connectivity may reflect a disorder-general marker of symptom severity across both affective and
psychotic illnesses, validating the key psychological features (Aim 1). Second, we will map transdiagnostic
functional connectome variability to the diversity of clinical presentations, extending our analyses across cortex
to develop predictive models of multidimensional symptom profiles (Aim 2). Third, we will identify novel
patterns of gene expression that follow the spatial organization of large-scale brain networks, establish the
impact of contributing loci on in vivo connectome functioning, and assess co-heritability with illness risk (Aim
3). Completion of these aims will yield insights into the neural, behavioral, and genetic basis of affective and
psychotic illnesses, providing a ...

## Key facts

- **NIH application ID:** 10187655
- **Project number:** 5R01MH120080-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** AVRAM J HOLMES
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $669,224
- **Award type:** 5
- **Project period:** 2019-08-15 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10187655

## Citation

> US National Institutes of Health, RePORTER application 10187655, Functional genomics of the human connectome in psychiatric illness (5R01MH120080-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10187655. Licensed CC0.

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