# Genetic Topography of Brain Morphology in Relation to Language in Large N Study of Schizophrenia

> **NIH NIH R03** · HARVARD MEDICAL SCHOOL · 2021 · $64,750

## Abstract

This RO3 application proposes to investigate the genetic topography (GT) of the cortex in a large cohort of
schizophrenia, familial high risk to develop psychosis and healthy control subjects (3257 subjects) from the
GENUS Consortium. GT offers a novel perspective by delineating the cortex according to genetic influences
instead of traditional anatomical boundaries. Our preliminary data indicate that in healthy controls, cortical
clusters obtained by GT exhibit better discoverability and higher heritability, i.e. are superior endophenotypes
compared to cortical units obtained with other commonly used atlases, such as the Desikan-Killiany, the
Glasser and the Yeo. Thus, genetic clusters obtained according to GT in healthy controls associate with a
significantly higher number of common genetic variants. GT has shown as well that there is significant
overlapping between genetic clusters of surface area and traditionally defined anatomical surface area regions,
while GT clusters of cortical thickness do not necessarily follow anatomical boundaries. For example, there is
shared genetic influence between the non-adjacent temporal and prefrontal cortexes, regions that are
commonly affected in SZ, and that together contribute to important cognitive functions such as language, an
important clue in the study of mental illnesses. By applying a novel software tool compatible with the commonly
used and anatomically based FreeSurfer segmentation, we will determine for the first time the genetic mapping
of the cortex in schizophrenia and in subjects at familial risk to develop schizophrenia. We will also examine SZ
polygenic risk score for genetic association with GT clusters and compare to Yeo and Glasser atlases in SZ.
Indeed, the genetic mapping of the cortex has not been carried out before in any mental disease. Cognitive
measures, in particular cognitive measures of language, available for the full cohort of subjects will be used for
correlation with genetically defined cortical regions as well as with anatomically defined ones, and correlations
compared. Ultimately, the present proposal aims at establishing cortical genetic clusters as highly discoverable
and highly heritable discreet units to be used in future GWAS of mental disease.

## Key facts

- **NIH application ID:** 10128096
- **Project number:** 1R03MH122759-01A1
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Elisabetta C. del Re
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $64,750
- **Award type:** 1
- **Project period:** 2020-12-18 → 2022-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10128096

## Citation

> US National Institutes of Health, RePORTER application 10128096, Genetic Topography of Brain Morphology in Relation to Language in Large N Study of Schizophrenia (1R03MH122759-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10128096. Licensed CC0.

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