# Uncovering the genetic architecture of extremely treatment-resistant schizophrenia using whole genome sequencing

> **NIH NIH K23** · BAYLOR COLLEGE OF MEDICINE · 2021 · $196,646

## Abstract

Schizophrenia (SCZ) is a severely disabling and highly heritable condition that afflicts ~1% of the global
population. Despite the advances in genetics that have shed light on the biology of so many diseases and led to
groundbreaking new treatments for conditions from blindness to cancer, genetic studies in SCZ have been
hindered by its genetic complexity and phenotypic heterogeneity: two patients who do not share a single
symptom can both receive the same diagnosis. One way forward is to define molecular subtypes, an approach
that has been successful in oncology and other realms of medicine, but which often requires identifying distinct
phenotypic subtypes. We therefore propose to study the most severe form of the disorder—extremely
treatment-resistant SCZ (ETRS)—because rare genetic variants of large effects are likely to be enriched in this
population. ETRS patients are the top 1% most severely affected patients, often remain hospitalized for
decades, and are not usually included in genetic studies, in part because they are not accessible to most
researchers. We will recruit 400 subjects with ETRS from the New York State inpatient system, thoroughly
characterize their phenotype, and perform whole genome sequencing (WGS). Our preliminary data from 75
ETRS patients revealed a higher-than-expected prevalence of seizures, dysmorphic features, and cognitive
impairment, which suggest the presence of one of the 60 Mendelian diseases known to mimic SCZ.
Furthermore, prior research and our preliminary data indicate that SCZ severity, cognitive impairment, and
treatment resistance are associated with a greater burden of rare single nucleotide variants (SNVs), copy
number variants (CNVs), and common variant polygenic risk. Therefore, in Aim 1, we will use diagnostic WGS
to identify (a) Mendelian conditions that mimic SCZ, such as Niemann-Pick disease type C, and (b)
pharmacogenetic variants that reduce the efficacy of antipsychotic treatments. Patients with either type of
mutation may be treatable. In Aim 2, we will (a) evaluate the burden of rare SNVs and rare CNVs. Since
extreme phenotypes can also be due to an excess of common variant risk, we will (b) determine the common
variant burden by calculating SCZ polygenic risk scores. We will use 6,500 individuals with typical SCZ and
165,000 healthy individuals as controls for Aims 1 and 2. The project will be conducted at Columbia University
Medical Center by Anthony Zoghbi, MD, a psychiatrist with clinical expertise and a career goal of becoming an
independent investigator in psychiatric genetics, focusing on SCZ. Dr. Zoghbi's comprehensive five-year
training plan will enable him to develop expertise in statistical genetics and genomics, cognitive assessment of
SCZ, and clinical research methods under the mentorship of David Goldstein, PhD (Director, Institute for
Genomic Medicine), statistical geneticist Suzanne Leal, PhD, and neuropsychologist Terry Goldberg, PhD. The
proposed aims align with his train...

## Key facts

- **NIH application ID:** 10409189
- **Project number:** 7K23MH121669-02
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Anthony Zoghbi
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $196,646
- **Award type:** 7
- **Project period:** 2020-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10409189

## Citation

> US National Institutes of Health, RePORTER application 10409189, Uncovering the genetic architecture of extremely treatment-resistant schizophrenia using whole genome sequencing (7K23MH121669-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10409189. Licensed CC0.

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