STAGE ISSS: Suzanne M. Leal

Join us for the next instalment of the STAGE International Speaker Seminar Series (ISSS) with

Dr. Suzanne M. Leal

Sergievsky Family Professor of Neurological Sciences (in Neurology and in the Gertrude H. Sergievsky Center)
Director, Center for Statistical Genetics
Columbia University

Free Hybrid (In-person/Online) Event | Registration Optional

Talk Title:

Leveraging cis and trans variants to improve protein expression level prediction and the power of complex trait proteome-wide association studies.

Abstract:

Since genetic effects are often mediated through proteins, the analysis of proteomic data can provide insights into disease etiology. However, most studies lack proteomic data. Although protein-expression levels can be predicted, most methods only use cis-variants. Therefore, TransCisPredict was developed to perform proteome-wide association studies (PWAS) at biobank scale using cis- and trans-variants. It reduces computational burden through selecting a subset of trans-variants. To account for differences in protein regulatory architecture, four prediction methods are used for weight-estimation, i.e., BayesR, Elastic Net, LASSO, and SuSiE and five-fold cross-validation (CV) is used to select the optimal method for each protein. Lastly TransCisPredict also performs protein-phenotype association analyses. TransCisPredict was implemented to estimate weights using White British UK Biobank study subjects (N=42,644) with proteomic and genotype-array data. These weights were then used to predict protein-expression levels for White British UK Biobank study subjects without proteomic data (N=364,132) followed by a PWAS for type 2 diabetes (T2D). Significant association results were validated using two-sample Mendelian randomization that controls for horizontal pleiotropy. Of the 2,920 available protein-expression levels, 2,339 (80%) could be predicted with a CV-R2>0.05 when cis- and trans-variants were used. The PWAS yielded 40 proteins associated with T2D that were validated. When analysis was limited to cis-variation, expression levels could only be predicted for 466 proteins (16%) of which three were associated with T2D and validated. Measured protein-expression levels were also analyzed by performing a direct PWAS (dPWAS) for T2D. The PWAS had a higher percent of associated and validated proteins (48.2%) compared to the dPWAS (33.2%). Additionally, PWAS identified five validated T2D associated proteins that were not detected in the dPWAS. Incorporating both cis- and trans-variants facilitates the prediction of more proteins compared to using cis-only variants thereby increasing the power of PWAS.

Speaker Profile:

Suzanne M. Leal, Ph.D. is a statistical geneticist who since 2019 is the Sergievsky Family Professor of Neurological Sciences and Director of the Center for Statistical Genetics at Columbia University. Her primary interest lies in understanding the genetic etiology of complex and Mendelian traits, with an emphasis on developing and applying statistical and epidemiological methods to tackle this complex problem. She has worked extensively on method development to elucidate complex trait disease etiology using various omics data. She developed the first rare-variant aggregate associations test, the Combined Multivariate and Collapsing (CMC) method. Most recently she has developed methods to perform 1) proteome-wide association studies (PWAS) using both cis and trans variants and 2) rare-variant aggregate association testing in admixed populations. Additionally, Dr. Leal studies a variety of complex and Mendelian traits that include Alzheimer’s disease, early-and late-onset hearing loss, neurodevelopmental disorders, skeletal disorders, and tinnitus. For the study of Mendelian traits, e.g. nonsyndromic hearing impairment and polydactyly she has ascertained >2,000 families internationally including from Finland, Mali, and Pakistan. Her research which is funded by several National Institute of Health grants has led to over 300 publications. Additionally, Dr. Leal mentors predoctoral and postdoctoral trainees and organizes and teaches statistical genetics courses nationally and internationally.

Sponsors:

ISSS events are made possible through the generous support of our partner organizations. For a complete list of sponsors, please see here.

CANSSI STAGE is supported by partner institutions across the country, including financial and in-kind support from CANSSI Ontario—an extra-departmental unit within the University of Toronto Faculty of Arts & Science. CANSSI Ontario is the Ontario Regional Centre of the Canadian Statistical Sciences Institute (CANSSI).

Photography Disclosure:

Photographs and/or video may be taken of participants at STAGE events. These photos/videos are for the Program’s use only and may appear on its website, in printed brochures, or in other promotional or reporting materials. By attending STAGE events, you accept the possibility that you may be videotaped or photographed. If you have any concerns, please inform us by sending an e-mail to esther.berzunza@utoronto.ca

Poster