Jessica Dennis

Assistant Professor

Research Classification

Bioinformatics
Genetic medicine

Research Interests

Administrative health data
Complex Trait Genetics
Electronic health records
Epidemiology
genetic epidemiology
Genetics of Neurological and Psychiatric Diseases
Machine Learning
Mental Health and Psychopathology in Children and Youth
Precision Health
statistical genetics

Relevant Thesis-Based Degree Programs

View all programs

Affiliations to Research Centres, Institutes & Clusters

BC Children's Hospital Research Institute
The Social Exposome Cluster

Research Options

I am interested in and conduct interdisciplinary research.
 
 

Open All

Recruitment

Master's students
Doctoral students
Postdoctoral Fellows
Any time / year round

The last decade has seen an unprecedented explosion of data. In medicine, data are increasingly being generated and linked across electronic health records, administrative databases, and biobanked samples. These resources hold tremendous promise for improving human health and achieving precision medicine, which will only be realized by thoughtful study designs and innovative analyses.

My lab uses novel computational methods grounded in genetic epidemiology and statistical genetics to capitalize on today’s big data resources. We aim to understand how genetic and epigenetic differences between people contribute to variation in disease susceptibility, response to treatment, and recovery. A primary goal of our research is to reduce the suffering associated with psychiatric disorders, many of which first manifest in childhood and adolescence. We conduct studies in large population datasets, with a major interest in electronic health records and biobanks, and we work at the intersection of genetics, epidemiology, statistics, bioinformatics, and computer science.

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).
I am interested in hiring Co-op students for research placements.

Complete these steps before you reach out to a faculty member!

Check requirements
  • Familiarize yourself with program requirements. You want to learn as much as possible from the information available to you before you reach out to a faculty member. Be sure to visit the graduate degree program listing and program-specific websites.
  • Check whether the program requires you to seek commitment from a supervisor prior to submitting an application. For some programs this is an essential step while others match successful applicants with faculty members within the first year of study. This is either indicated in the program profile under "Admission Information & Requirements" - "Prepare Application" - "Supervision" or on the program website.
Focus your search
  • Identify specific faculty members who are conducting research in your specific area of interest.
  • Establish that your research interests align with the faculty member’s research interests.
    • Read up on the faculty members in the program and the research being conducted in the department.
    • Familiarize yourself with their work, read their recent publications and past theses/dissertations that they supervised. Be certain that their research is indeed what you are hoping to study.
Make a good impression
  • Compose an error-free and grammatically correct email addressed to your specifically targeted faculty member, and remember to use their correct titles.
    • Do not send non-specific, mass emails to everyone in the department hoping for a match.
    • Address the faculty members by name. Your contact should be genuine rather than generic.
  • Include a brief outline of your academic background, why you are interested in working with the faculty member, and what experience you could bring to the department. The supervision enquiry form guides you with targeted questions. Ensure to craft compelling answers to these questions.
  • Highlight your achievements and why you are a top student. Faculty members receive dozens of requests from prospective students and you may have less than 30 seconds to pique someone’s interest.
  • Demonstrate that you are familiar with their research:
    • Convey the specific ways you are a good fit for the program.
    • Convey the specific ways the program/lab/faculty member is a good fit for the research you are interested in/already conducting.
  • Be enthusiastic, but don’t overdo it.
Attend an information session

G+PS regularly provides virtual sessions that focus on admission requirements and procedures and tips how to improve your application.

 

ADVICE AND INSIGHTS FROM UBC FACULTY ON REACHING OUT TO SUPERVISORS

These videos contain some general advice from faculty across UBC on finding and reaching out to a potential thesis supervisor.

View More Advice Videos

Supervision Enquiry

If you have reviewed some of this faculty member's publications, understand their research interests and have reviewed the admission requirements, you may submit a contact request to this supervisor.

Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Finding the functional consequences of genetic risk loci on gene expression and DNA methylation by integrating contextual information (2023)

The majority of genetic loci that influence complex traits are non-coding. Roughly half of these loci affect gene expression in one or more tissues, despite making up less than 10% of common genetic variants. However, it is increasingly unlikely that genetic effects on gene expression will be sufficient to assign a function to all non-coding risk loci. This thesis splits the problem of assigning new functions to complex trait loci into two steps.First, I aim to increase the number of non-coding loci with a known function without requiring new molecular datasets. In my thesis, I explore context-dependent genetic regulation of molecular traits, where the context that affects this process is either inferred from data or a common phenotypic measure like sex. I then advocate for associating genetic variation with molecular data other than gene expression, primarily on DNA methylation.Second, I outline how to tie these novel molecular functions to genetic risk for complex traits. Importantly, this requires methods and workflows that summarize genetic effects at individual loci across interpretable functional units (genes) and genome-wide genetic risk for complex traits.In my scholarship chapters, I first show that environments inferred from global gene expression can correlate with various phenotypic and environmental variables. These inferred contexts are replicated across samples and can subsequently be used to identify novel context-specific genetic regulation of gene expression. I then show that novel context-specific genetic regulation can be approached in DNA methylation using sex, measured in virtually all genetic and molecular datasets.My later chapters demonstrate how to summarize genetic effects to learn which traits are particularly relevant to these novel regulatory relationships. I start with effects and individual loci and then explore methods to interpret the gene-level influence of genetic effects on DNA methylation. Then I demonstrate how cumulative, genome-wide risk for complex traits can provide new insight into the biological functions underlying complex traits beyond the effects I observe at individual loci.Overall this thesis shows that we require various approaches to discover disease-relevant molecular functions of non-coding genetic loci.

View record

Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Investigating sex differences in the polygenic risk of major depressive disorder and shared associations with cardiovascular disease (2022)

Major depressive disorder (MDD) is a leading cause of morbidity and disability worldwide, with approximately twice as many women reported to have a lifetime occurrence of MDD than men. MDD is a polygenic trait, wherein hundreds to thousands of common genetic variants with small effect sizes contribute to risk of disease. This study investigated sex differences in the risk factor comorbidity and genetic architecture of MDD in over 16,000 people aged 45-85 from the Canadian Longitudinal Study on Aging (CLSA), with 21% of females (n=1,741) and 12% of males (n=1,055) coded with MDD. Polygenic risk scores (PRS) for individuals were made using sex-stratified and non-sex-specific (“both-sexes”) UK Biobank genome-wide association study summary statistics data. The female sex-specific PRS had higher associations with MDD in females in the top decile of PRS risk (OR = 1.68 (1.32-2.14), p = 2.8E-05) than the male-specific PRS in males (OR = 1.43 (1.07-1.93), p = 0.017) and the both-sexes PRS applied to both sexes (OR = 1.51 (1.25-1.83), p = 2.5E-05). Odds of MDD for the sex-specific PRSs, socioeconomic, lifestyle and clinical risk factors were assessed using a multivariable logistic regression model for each sex. Sex-specific risk factor associations with odds of MDD were found in females (hypothyroidism (OR = 1.42 (1.25-1.63), p = 1.74E-07), not being partnered (OR = 1.34 (1.17-1.52), p = 1.26E-05), having diabetes (OR = 1.30 (1.11-1.52), p = 1.03E-03), higher sex-specific autosomal PRS (OR = 1.10 (1.04-1.16), p = 6.15E-04) and a history of ischemic heart disease (OR = 1.52 (1.14-2.01), p = 3.39E-03)) and males (high blood pressure, OR = 1.35 (1.04-1.47), p = 4.55E-05). Significant differences were observed in the proportion of variables that contributed to the most to each model, evaluated by relative pseudo-R2 values. Age contributed the most to the model for both sexes (73% for females, 57% for males), wherein younger age was associated with higher odds of MDD. The results of this thesis underscore the relevance for sex-disaggregating analyses of complex traits, like MDD, and the incorporation of clinical variables into models of MDD, in applications such as early detection and primary prevention.

View record

Publications

Current Students & Alumni

This is a small sample of students and/or alumni that have been supervised by this researcher. It is not meant as a comprehensive list.

Emilie Théberge

Master of Science in Medical Genetics (MSc)

Research Topic
Investigating sex differences in the polygenic risk of major depressive disorder and shared associations with cardiovascular disease
 
Jessica Dennis's Profile
ORCID Profile
Other link
Supervision Enquiry

Membership Status

Member of G+PS
View explanation of statuses

Location

BC Children's Hospital

Program Affiliations

Medical Genetics
Bioinformatics
Genome Science and Technology

Academic Unit(s)

Department of Medical Genetics
 

If this is your researcher profile you can log in to the Faculty & Staff portal to update your details and provide recruitment preferences.

 
 

Follow these steps to apply to UBC Graduate School!

Review Application Steps