Yves A. Lussier, MD, FAMCI, is the Chair of Biomedical Informatics at University of Utah School of Medicine. As a professional engineer and physician-scientist, he is an international expert in translational bioinformatics and a pioneer in research informatics techniques including systems biology, data representation through ontologies, and high-throughput methods in personalized medicine.
Dr. Lussier comes to the University Utah from the University of Arizona, where he was the Associate Vice President for Information Science and Chief Knowledge Officer of the UArizona Health Sciences (UAHS), Founding Director of the Center for Biomedical Informatics and Biostatistics, and Professor of Medicine. During his time at UArizona, he developed novel programs in biomedical informatics, computational genomics, and precision health, as well as provided critical leadership to advance precision health approaches to health outcomes and healthcare delivery and in the development of big data analytical tools and resource services. Prior to his tenure at UArizona, Dr. Lussier was professor of medicine, bioengineering and biopharmaceutical sciences at University of Illinois at Chicago (UIC), and assistant vice president for health affairs and chief research information officer for the University of Illinois Hospital and Health Sciences System (2011-13). From 2006-2011, he was the associate director of informatics for the University of Chicago Comprehensive Cancer Center as well as co-director of biomedical informatics for the Clinical and Translational Science Award (CTSA)-funded Institute for Translational Medicine. From 2001-2006, Dr. Lussier was an assistant professor in the Departments of Biomedical Informatics and Medicine at Columbia University in New York.
Lussier’s research group conducts pioneering hypothesis-driven computational modeling predictions in precision medicine that are then validated in vitro, in vivo and in clinical trials. As a leader of the fields of translational bioinformatics and of Data Science-augmented precision medicine, he has launched successful companies and international conferences, authored 185 publications, and delivered more than 100 invited presentations in precision medicine, systems medicine, and translational bioinformatics, including 28 opening keynotes at international conferences. He has been awarded $190,000,000 in grants as principal, core leader, or co-investigator, and mentored or co-mentored over 90 graduates, post graduate fellows, and junior faculty members, of which twelve are faculty members, seven obtained K-awards, and five obtained R awards. Dr. Lussier’s honors include three IBM Faculty Awards, inducted Fellow of the American College of Medical Informatics (ACMI), 1st recipient of the Columbia University Faculty Mentoring Award, “Ambassador for Health Sciences” at the University of Sherbrooke (Canada), and 16 outstanding publication awards from the American Medical Informatics Association (AMIA), the International Society for Computational Biology (ISCB), and the Translational Bioinformatics Conference (TBC). In 2016, Dr. Lussier was invited among ten USA academic leaders invited by the White House for its Precision Medicine Summit.
Jianrong Li has worked in the field of Biomedical Informatics for over 22 years, with several years of experience in the banking industry. With a wealth of expertise in Machine Learning, I2B2, Bioinformatics, Natural Language Processing, Data Mining, Artificial Intelligence, Biotechnology, Text Mining, Information Retrieval, and Statistics, he has been at the forefront of the field's evolution. He has hands-on skills in technologies such as DB2, MySQL, Microsoft SQL Server, Solaris, Linux, FileMaker, and Cytoscape. He is proficient in programming languages such as PERL, Python, Java, C, R, and C#, which have enabled him to solve complex problems in the field. His commitment to the field is reflected in his certification as a CLARITY DATA MODEL - PROFESSIONAL BILLING expert. He is an expert in DAG-anchored terminology mapping methods for new terms to any target, and his exceptional ability to provide instant high-quality clinical NLP and coding without training sets using expert-system based NLP over clinical data is highly regarded.
Liam Wilson is a software developer with degrees in computer science and mathematics from the University of Arizona. His career experience includes working with various data science research groups, contributing to distributed software orchestration tools, and developing optimization engines in the manufacturing industry. While with the Lussier group, he has contributed to a variety of projects, from validating large-scale environmental exposure/disease predictions to extending single-subject methods developed for the transcriptome to other ‘omics. He currently develops software and tools for analyzing clinical and ‘omics data, contributes to the writing of grant proposals and scientific papers, and creates effective development plans and quality assurance procedures to the ultimate end of furthering translational bioinformatics research.
Driven by an unwavering dedication to enhancing patient health, she serves as an AI Data Scientist at the Biomedical Informatics Department at the University of Utah. She is an alum of the University of Tennessee Health Science Center, where she specialized in Biomedical Engineering. With over 5 years of experience in pediatric medical imaging, she has collaborated with renowned institutions including St. Jude Children's Hospital, Le Bonheur Children's Hospital, and Cincinnati Children's Hospital – the latter being recognized as the #1 pediatric hospital in the nation in 2023. As she delves into her PhD, her focus sharpens on devising pioneering deep neural network models. These models are tailor-made to meticulously analyze intricate gene expression datasets, aiming to diagnose complex diseases in their nascent stages, notably cancer. Outside the realm of academia, she channels her artistic flair into canvas paintings and holds an equal passion for traveling and woodworking.
Colleen’s main role is to bridge the gap between research and administration and to foster collaborative efforts between multiple units across campus and with external stakeholders. She currently serves as the Director of Strategic Operations for the Department of Biomedical Informatics as well as manages the Lussier Research Group. She works across traditional boundaries, and is well-versed in translating research prerogatives into action and operationalizing strategic plans. She received her Bachelor's Degree in Business Administration (2007) and Master's Degree in Human Resource Development (2013) from Northeastern Illinois University. She received her Doctorate of Education in Interdisciplinary Leadership, with a concentration in non-profit social entrepreneurship, at Governors State University in 2016. She recently completed a Master of Public Health degree with a concentration in Health Services Administration from The University of Arizona (2019). Prior to this, she worked with Dr. Lussier at the University of Arizona from 2013 to 2020 and the University of Illinois at Chicago from 2011–2013.
Nima’s primary research interest is to better understand the underlying molecular mechanisms of complex diseases and ultimately translate the results into clinical practice. I therefore utilize various analytical and computational methods developed in evolutionary biology, epigenetics, genetics, and bioinformatics for analyzing the data derived from distinctive high-throughput assays. However, most of the currently available analytical methods lack the power to uncover the mechanisms that their alterations lead to development of diseases for them the large cohort of patients are not available or hard to obtain such as rare diseases. To address this issue, he is currently working in the Lussier Research Group on developing, expanding, and implementing single-subject analytical methods which infuse and anchor the knowledge from various sources of omics’ data with novel statistics to further our insights into the biology that underpins the development and progression of rare diseases.
|Dillon Aberasturi, PhD
|Ikbel Achour, PhD
|Lead Scientist, Translational Medicine
|Joanne Berghout, PhD
|Senior Computational Geneticist
|New York University School of Medicine
|Director of Clinical Research Informatics and Associate Professor
|James L. Chen
|The Ohio State University
|Assistant Professor, Internal Medicine & Biomedical Informatics
|Jungwei Fan, PhD
|EPFL Laboratory of Systems Biology & Genetics
|Young Ji Lee
|University of Pittsburgh
|University of Utah
|Assistant Professor, Biomedical Informatics Research
|Haiquan Li, PhD
|The University of Arizona
|Assistant Professor, Biosystems Informatics
|Qike Li, PhD
|University of Illinois at Chicago
|David J. Mann
|NorthShore University HealthSystem
|Dept of Psychiatry at Columbia University
|Assistant Professor of Clinical Neurobiology
|AIM Specialty Health
|Business Information Analyst 2
|University of Illinois at Chicago
|MD/PhD Graduate Student
|The Ohio State University
|NIH National Library of Medicine Biomedical Informatics Research Training Program Fellow
|University of Michigan
|Indra Neil Sarkar
|University of Vermont
|Director of Biomedical Informatics and Assistant Professor of Microbiology and Molecular Genetics
|A. Grant Schissler, PhD
|University of Nevada, Reno
|Francesca Vitali, PhD
|The University of Arizona
|Research Assistant Professor
|University of Chicago
|The University of Chicago
|Samir Rachid Zaim, PhD
|Code for Venezuela
|Biostatistician and Data Scientist
In response to the national Precision Medicine Initiative (PMI), UAHS has committed significant resources to expand the clinical utility of its open-source, patient-centric analytic methods, such as the N-of-1-pathways software, which aids physicians in interpreting the dynamic changes of disease-associated gene expression arising from patients’ own DNA blueprints. As part of the initiative, UAHS will translate large-scale clinical and genomic data into actionable individual outcomes through two of its centers: the UA Center for Biomedical Informatics and Biostatistics (CB2) and the UA Center for Applied Genetics and Genomic Medicine (TCAG2M). Both centers bring together physicians, scientists, patients and other key stakeholders to develop strategies that advance understanding of the factors contributing to individual health and disease and personalized approaches to disease prevention, early detection and treatment.
Yves Lussier, MD, FACMI, will lead the UAHS patient-centric analytical methods and was invited to attend the Precision Medicine Initiative Summit held Feb 25th in Washington, D.C. UAHS’ involvement in the PMI was initiated and facilitated by Ikbel Achour, PhD, who serves as CB2’s director for precision health. Dr. Lussier collaborates closely with Kenneth S. Ramos, MD, PhD, PharmB, associate vice president for precision health sciences, director of the UA TCAG2M and an elected member of the National Academy of Medicine.
In this era of precision medicine, accurate personal transcriptome interpretation and N-of-1 (single-subject) efficacy trials remain unmet challenges. We therefore developed a method, “N-of-1-pathways,” that translates gene expression data profiles into disease mechanism significance for a pair of samples - one patient at the time.
The emergence of precision medicine ushered in the opportunity to incorporate individual molecular data into patient care. In contrast to personal DNA sequencing profiling increasingly pursued in clinical practice, genome-wide transcriptome profiling has often provided biological information at the gene and pathway levels that are common and applicable only to a larger cohort. The N-of-1-pathways method, a global framework, relies on three principles: i) the statistical universe is a single patient/sample; ii) significance is derived from genesets/biomodules; and iii) similarity metric of inter-mechanisms’ relationships. N-of-1-pathways provides a unique and novel framework for N-of-1-studies (e.g. patients, cell-lines, tissues, etc.) aimed at predicting individual response to therapy and biomarker discovery. N-of-1-pathways offers opportunities to include patient-centered “omics” reports into electronic medical records for individualized clinical interpretation and precise treatment.
'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine. Gardeux V*, Achour I*, Li J, Maienschein-Cline M, Li H, Pesce L, Parinandi G, Bahroos N, Winn R, Foster I, Garcia JG, Lussier YA. - J Am Med Inform Assoc. 2014
JAMIA Editor Pick 2014 - AWARD Best TBC Research Paper 2013; Presentation at Translational Bioinformatics Conference (TBC) - TBI AMIA 2013 Joint Summits on Translational Science
Presentation at Translational Bioinformatics Conference (TBC)
Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival. Schissler AG*, Gardeux V*, Li Q*, Achour I*, Li H, Piegorsch WW, Lussier YA. - Bioinformatics. 2015
Presentation at Intelligent Systems for Molecular Biology, ISMB 2015
Towards a PBMC "virogram assay" for precision medicine: Concordance between ex vivo and in vivo viral infection transcriptomes. Gardeux V, Bosco A, Li J, Halonen MJ, Jackson D, Martinez FD, Lussier YA. - J Biomed Inform. 2015
* These authors contributed equally to the work
Haiquan Li*, Ikbel Achour*, Lisa Bastarache*, Joanne Berghout, Vincent Gardeux, Jianrong Li,Younghee Lee, Lorenzo Pesce7, Xinan Yang, Kenneth S Ramos, Ian Foster, Joshua C Denny, Jason H Moore and Yves A Lussier.
* These authors contributed equally to this work
Functionally altered biological mechanisms arising from disease-associated polymorphisms, remain difficult to characterise when those variants are intergenic, or, fall between genes. We sought to identify shared downstream mechanisms by which inter- and intragenic single-nucleotide polymorphisms (SNPs) contribute to a specific physiopathology. Using computational modelling of 2 million pairs of disease-associated SNPs drawn from genome-wide association studies (GWAS), integrated with expression Quantitative Trait Loci (eQTL) and Gene Ontology functional annotations, we predicted 3,870 inter–intra and inter–intra SNP pairs with convergent biological mechanisms (FDR 0.05). These prioritised SNP pairs with overlapping messenger RNA targets or similar functional annotations were more likely to be associated with the same disease than unrelated pathologies (OR412). We additionally confirmed synergistic and antagonistic genetic interactions for a subset of prioritised SNP pairs in independent studies of Alzheimer’s disease (entropy P = 0.046), bladder cancer (entropy P = 0.039), and rheumatoid arthritis (PheWAS case–control Po10− 4). Using ENCODE data sets, we further statistically validated that the biological mechanisms shared within prioritised SNP pairs are frequently governed by matching transcription factor binding sites and long-range chromatin interactions. These results provide a ‘roadmap’ of disease mechanisms emerging from GWAS and further identify candidate therapeutic targets among downstream effectors of intergenic SNPs.
npj Genomic Medicine (2016) 1, 16006; doi:10.1038/npjgenmed.2016.6; published online 27 April 2016