|Our research goals
are to identify genetic determinants and environmental risks underlying
selected human diseases (including developing new analytic approaches),
and determine how these risks contribute to disease etiology, with the
ultimate goal to inform diagnosis, treatment, disease risk prediction,
early intervention, and prevention. We
plan to develop three directions: bioinformatics development, disease
risk discovery, and translational genomics. Below are representative projects for each category.|
- Develop new platform to genotype ERVs using long reads sequencing:
We will use Pacific Biosciences and Nanopore long read sequencing to
further improve our current algorithm for ERV detection (ERVcaller ver1 was
published in Bioinformatics).
Our new platform (ERVcaller ver2) will identify ERV and other
transposable element variants that are not detectable by Illumina short
- Develop new platform to detect mosaic viral integrations for brain disorders: We will improve our current algorithm for viral integration detection (VIcaller ver1 was published in Genome Research).
Our new platform (VIcaller ver2) aims to detect mosaic viral
integration events on the human virome level in blood and brain samples using ultra-deep
sequencing and/or long reads. I will then use it to test whether viral infections/integrations are involved in certain brain
behavioral disorders. This platform can be
further extended to the human bacteriome.
Disease risk discovery (selected pilot projects)
- Identify ERV variants and ERV expression in alcohol use disorder (AUD): We
have collected WGS data from AUD samples and RNA-Seq data from AUD
brain PFC, ethanol treated human embryonic stem cell-derived neurons,
and alcohol use mouse brains. We showed that ethanol induced ERV
activation and expression in neurons; AUD brains exhibited elevated ERV
expression than controls; and ERV genotypes were associated with AUD.
We will conduct systematic analyses to study the “ERV-immune
response-neuroinflammation-disease” link. We will also examine
developmental and environmental modulators, such as stress, childhood
maltreatment, nutrients, which may be ERV activators. This analytic
platform can be applied to ME/CFS and other neuroinflammatory diseases.
The fact that addiction treatment medications (such as Naltrexone) are
used to “treat” ME/CFS patients in current clinical practice
support that the two diseases may share some biology and pathogenesis in
- Identify multi-omics risks in ME/CFS: We
will integrate multi-omics data (genome, transcriptome, epigenome,
microbiome, and brain images) from patients with ME/CFS. We will use
various in-house pipelines to examine SNV, Indel, DNA methylation,
pathogens, and other factors, particularly ERVs. ERVs may explain both
familial inheritance and altered immune response/inflammation observed
Translational medicine (selected pilot projects)
- Identify AUD early stage risks:
AUD is a progressive, lifetime disease. AUD is hard to cure but is
preventable. The best period for prevention is adolescence. Identifying
behavioral, brain, and genetic markers and elucidating the
developmental pathways from early onset symptoms to AUD will help
at-risk children for early intervention. We will use a lifespan
approach to identify AUD developmental pathways using phenome-genome
data of over 12000 individuals who have struggled with AUD. This study
may generate actionable data that can guide intervention and prevention
for AUD and related deaths.
- Potential treatment to reverse ERV effects:
There are already anti-retroviral clinical trials to suppress ERV
expression in multiple sclerosis and amyotrophic lateral sclerosis.
ME/CFS share symptoms with multiple sclerosis (e.g., chronic fatigue
and pain). If our analyses prove that ERVs are risk in ME/CFS,
substance use disorders, or other neuroinflammatory diseases, the
existing FDA-approved anti-retroviral or anti-inflammatory drugs can be
repurposed to reverse ERV effects in these diseases. Indeed, some
ME/CFS patients’ symptoms improved after self-use of these drugs.