# Estimating the genetic and environmental architecture of psychiatric disorders

> **NIH NIH R01** · UNIVERSITY OF COLORADO · 2020 · $639,536

## Abstract

PROJECT SUMMARY
Understanding the genetic and environmental architecture of traits has been one of the central goals of
behavioral genetics over the last fifty years. Traditional approaches using twins and families have shown that
most traits, including psychiatric disorders, are highly heritable. More recently, methods that estimate
heritability (h2) from single nucleotide polymorphisms (SNPs) in unrelated individuals (h2SNP) have
demonstrated the importance of common variants to the genetic variation underlying complex traits. In turn,
the realization that common variants are responsible for substantial trait heritability has motivated continued
investment in large whole-genome datasets, which have allowed the discovery of thousands of SNPs reliably
associated with complex traits. In the midst of this deluge of data, however, fundamental questions about the
genetic and environmental architecture of traits remain unanswered, and new methodological approaches that
leverage increasingly large whole-genome datasets are needed to answer them.
In this Renewal application, we build on our previous methodological work to answer four high-level questions
about the genetic and environmental architecture of complex traits. First, estimates of h2SNP for psychiatric
disorders remain lower than estimates of h2 from twin and family studies. How much of this “still missing”
heritability is due to rare risk variants? Using methods developed during the previous period of our grant, we
will provide the best estimates to date of the importance of rare versus common risk variants of schizophrenia,
bipolar disorder, and major depression. Second, there appears to be substantial overlap between common risk
alleles for psychiatric disorders such as schizophrenia and bipolar disorder. Do rare risk alleles overlap to the
same degree, or do they tend to be disorder-specific? We will use extensions of our previously developed
methods to help answer this question. Third, the availability of large whole-genome datasets is growing at an
unprecedented rate. Can this data be leveraged to answer fundamental questions about the importance of
genes and the environment, traditionally the domain of twin and family designs? We propose the development
of methodological approaches that use measured genetic data among relatives that exist in large datasets to
help answer old questions in new ways that bypass earlier limitations. Finally, it is crucial to understand factors
that can bias estimates and lead to incorrect conclusions. We show how assortative mating and gene-by-
environment interactions bias existing estimates of h2SNP, and we propose the development of models and
software tools that mitigate these biases. By project's end, we anticipate having tools that open up new vistas to
behavioral genetics research, allowing for a clearer understanding of the genetic and environmental
architecture of psychiatric disorders and other complex traits. Doing so will help guide future analy...

## Key facts

- **NIH application ID:** 9900864
- **Project number:** 5R01MH100141-08
- **Recipient organization:** UNIVERSITY OF COLORADO
- **Principal Investigator:** Matthew Charles Keller
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $639,536
- **Award type:** 5
- **Project period:** 2013-02-04 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9900864

## Citation

> US National Institutes of Health, RePORTER application 9900864, Estimating the genetic and environmental architecture of psychiatric disorders (5R01MH100141-08). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9900864. Licensed CC0.

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