# Characterizing a spectrum of mosaic variation in the population and across neurological disorders

> **NIH NIH F31** · HARVARD MEDICAL SCHOOL · 2020 · $38,996

## Abstract

Project Summary
Post-zygotic mutations, both those arising early in life (mosaic) and acquired in somatic tissues throughout life,
are present in a sub-population of cells and have been implicated in a variety of disorders, but the prevalence of
these mutations in the general population is largely unknown due to limitations in tools and reference datasets.
Recent studies have suggested that post-zygotic mutations can have a profound impact on disease, particularly
neuropsychiatric and neurodegenerative disorders. From these prior studies, it is clear that post-zygotic
mutations are prevalent in the population and could represent a significant contribution to human disease, but
systematic analyses in very large reference sets using tightly benchmarked tools are needed. Prior studies have
been limited in scope, focusing solely on single nucleotide variants (SNVs) and small indels, or a narrow class
of mega-base scale structural variation (SV). The emergence of population-scale whole-genome sequencing
(WGS) in controls, and tens of thousands of case cohorts, offers the first opportunities to interrogate a mutational
spectrum of mosaic variation including SV, SNVs, and indels at WGS-resolution. In this fellowship, I propose
that post-zygotic mutations are abundant in the population across the size spectrum, increase with age, and can
have a measurable impact on gene function. To further describe this cryptic class of variation in the population,
across ages, and in disease cohorts, I plan to first optimize and benchmark recently developed mosaic SV
detection algorithms, then, using these tools, derive allelic fraction thresholds to distinguish mosaic variation
from somatic variation (Aim 1). I will then apply these tools and annotations to a population-scale WGS reference
dataset in the genome aggregation database (gnomAD). These analyses will determine the incidence and
prevalence of post-zygotic mutations at sequence resolution and determine the variance explained by age in the
accumulation of somatic mutations in the population (Aim 2). Finally, I will directly test prior hypotheses that
post-zygotic mutations influence disease risk from WGS data in an early onset neurodevelopmental disorder
(autism) cohort and a late onset neurodegenerative disorder (Alzheimer’s disease) cohort, as well as matched
controls, to determine the differential influence of early mosaic variation and the accumulation of somatic
variation on disease risk and brain function (Aim 3). Collectively, the aims outlined in this proposal will leverage
unique tools and resources to further characterize this underappreciated class of genomic variation and its
influence on human disease, as well as provide outstanding mentorship in each of my targeted areas of
development during my PhD training.

## Key facts

- **NIH application ID:** 10149166
- **Project number:** 5F31NS113414-02
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Elise Valkanas
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $38,996
- **Award type:** 5
- **Project period:** 2019-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10149166

## Citation

> US National Institutes of Health, RePORTER application 10149166, Characterizing a spectrum of mosaic variation in the population and across neurological disorders (5F31NS113414-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10149166. Licensed CC0.

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