2017 North Coast Conference on Precision Medicine Travel Awardees

Made possible by NIH/NHGRI R13HG009481


Basile, Anna Okula

Graduate student
Department of Biochemistry and Molecular Biology
The Pennsylvania State University
University Park, PA

Understanding the nature of genetic contribution to complex disease susceptibility has been at the heart of genetic research for the past decade. GWAS have largely driven the field and identified many SNPs associated with complex disease. Despite these successes, the inability of GWAS to explain more than a fraction of specific causal loci has led to the belief that many genetic and epigenetic factors likely contribute to complex diseases, including rare variants. Rare variants are believed to have larger effects than common variants, and studying their influence may add to our understanding of disease heritability. While the advent of next-generation technologies has presented an opportunity for discovering rare variants, multiple challenges exist. Because these variants are individually uncommon, there is low statistical power for detecting association with a trait. Large sample size requirements can often be prohibitive, especially when considering allele frequencies below 1%. Although multiple methods and statistical tests exist, few approaches provide an automated analysis framework. Also, the presence of genetic and phenotypic heterogeneity in complex disease presents a challenge in rare variant analysis. Heterogeneity has important implications in the discovery and replication of disease-causing genes as well as medical treatments appropriate for patients. My research aims to address challenges in rare variant analysis with 1) an automated biological approach for both collapsing and association testing of rare variants, and 2) the application of an advanced method for identifying phenotypic patterns present in clinical data for integration with sequence data to explore the genetic architecture of disease.

Butkiewicz, Mariusz

 Staff scientist, bioinformatics
Department of Biomedical and Translational Informatics
Geisinger Health Systems
Rockville, Maryland

Dr. Mariusz Butkiewicz is currently a Bioinformatics staff scientist in the Department of Biomedical and Translational Informatics at Geisinger Health Systems. His current research aims to bridge knowledge from WES/WGS sequencing data with phenotype data from Geisinger's electronic medical records system. Previously, Dr. Butkiewicz earned a Diploma in Computer Science (Master's equivalent) from Leipzig University in Germany, and later earned his PhD in computational Chemistry from Vanderbilt University working with Dr. Jens Meiler (www.meilerlab.org) on developing new cheminformatics approaches to applying machine learning approaches to aid drug discovery of novel small molecule therapeutics for Schizophrenia and Malaria. During his post-doctoral training with Dr. Jonathan Haines at Case Western Reserve University, his research centered on quantitative genetic and genomic studies with an emphasis on Alzheimer's disease, and other neurological disorders.

Clement, Tasmine

Undergraduate student
Department of Biochemistry
Virginia Tech
Blacksburg, Virginia

I have previously performed clinical-translational research at Notre Dame’s Center for Rare and Neglected Diseases. The goal was to develop therapies and outreach efforts for people suffering from various orphan diseases, like Niemann-Pick type C (NPC). NPC is a lysosomal storage disorder with a wide clinical spectrum that results in nervous system deterioration. NPC has a higher incidence in French Canadian (Nova Scotian) populations and Spanish-American (NM & CO) populations. As a researcher, I worked with health care practitioners and families to collect and summarize patient data electronically so that it would be easily shared between current and future parties; including researchers for clinical trials. I combed through a lifetime’s worth of medical records for patients with rare diseases in order to compile information on phenotypes, treatment plans and familial history. The information was then used to diagnose patients with rare diseases through clinical and biochemical biomarkers. With my work, patients were also able to enter clinical trials for potential drug treatments like cyclodextrin. I was also responsible for developing a disability scale for NPC to better evaluate clinical therapies and to find additional phenotypic correlations. In all, I spent two years identifying markers of disease progression within individuals and quality of life for each individual based on symptomology and individual treatment plans.

Hall, Jacob

Post-doctoral fellow
Institute for Next Generation Healthcare
Icahn School of Medicine at Mount Sinai
New York, New York

Acne is a common skin condition that can have physical as well as psychological/emotional consequences. Some factors, such as age, sex, and diet, help predict risk of developing acne, yet pathogenesis is far from fully understood. Many treatment options exist to treat a range of acne severity, though response to treatment is variable. Additionally, the most aggressive treatment options don't always eliminate acne and can lead to severe side effects, so better treatment options are needed. Recently, I have used multi-omics data (genome, transcriptome, proteome, microbiome) to explore differences between acne and non-acne patients as well as differences between healthy and acne skin of acne patients. Both comparisons shed light on different aspects of acne pathogenesis. Comparing lesion and non-lesion skin of acne patients has generally highlighted the inflammatory component of acne. Comparing non-lesion (healthy) skin of acne and non-acne patients has yielded differentially expressed genes, with gene set enrichment pointing to factors such as epithelial-to-mesenchymal transition, coagulation, and UV response. Unsurprisingly, the gene expression signatures had similarities between other skin diseases, such as psoriasis, eczema, lupus, and contact dermatitis. We are currently performing PacBio sequencing of the microbiome, which will yield high-resolution, long genomic reads, to better characterize influencing factors of acne.

Hall, Molly

Principal Investigator
Veterinary and Biomedical Sciences
The Pennsylvania State University
University Park, Pennsylvania

My research is focused on building tools to elucidate the complex genetic and environmental underpinnings of human disease. I work to integrate genetic (genotype, sequence, structural variation) and exposure (derived from surveys and metabolomics methods) big data to predict disease status. The ultimate goals of this work are to 1) enrich our understanding of the complex mechanisms that lead to common disease and 2) provide methods to identify those most at risk of disease (based on their genetic and exposure backgrounds) in a clinical setting. I am, therefore, very interested in this symposium; I am excited to hear talks and interact with others focused on exposure research across diverse populations.

hernandez_wenndyHernandez, Wenndy

Post-doctoral fellow
Department of Medicine
University of Chicago
Chicago, Illinois

My graduate training provided me with a solid foundation in multiple aspects of cancer biology including molecular mechanisms, genomics, drug resistance, and translational research approaches. I have acquired analytical skills in methods that measure and apply population genetic ancestry to genetic association studies, an essential step towards personalized medicine. I have successfully integrated molecular and analytical skills to identify population-specific genetic associations to complex diseases, particularly in the context of prostate cancer, warfarin pharmacogenomics, and venous thromboembolism.

Currently, my training entails quantitative and computational methods and tools that utilize large-scale data in aggregate which coupled with my molecular background will allow me to formulate new questions through the vast amount of data generated. My ultimate goals are to utilize novel and more complex methods to analyze and integrate a wide variety of genetic data types to understand the basis of cardiovascular diseases; design novel prediction models in order to provide patients with optimal treatment; and to establish a resource database collected exclusively on African American ischemic stroke patients from which to study the relationship between genetic variation and gene expression in order to improve our understanding of the molecular signatures underlying ischemic stroke and its subtypes.

I began graduate school knowing that I would pursue a career conducting research that may one day help reduce the health disparity gap. My graduate training provided me with a solid foundation in multiple aspects of cancer biology including molecular mechanisms, genomics, drug resistance, and translational research approaches. While I had several options for a post-doctoral position, I was committed to conducting genetic research among under-represented populations.  I joined Dr. Minoli Perera’s lab in September 2012 and began research in pharmacogenomics that led to an algorithm for predicting therapeutic warfarin dose for African Americans.  My novel warfarin dosing algorithm outperformed the most widely used algorithm and standard clinical practice for dosing African Americans, and it’s currently being implemented in a pilot clinical study through the 1200 Patients project (Dr. Odonnell) at the University of Chicago. I observed that nearly 60% of the African American warfarin patients were placed on warfarin due to venous thromboembolism (VTE) which provided an opportunity to conduct a case-control study on VTE risk susceptibility -- in fact, this resulted in the genome-wide association study on VTE susceptibility among African Americans.  Translational research that integrates population-specific genomic variation and complexity has tremendous potential to reduce health disparities and improve clinical practice.  My future research plans will do exactly that by integrating polygenic risk models and gene expression regulation into analyses aimed to improve our understanding on the etiology of stroke and discover targets for intervention.

El Rouby, Nihal

Post-doctoral fellow
Department of Pharmacotherapy and Translational Research
University of Florida
Gainesville, Florida

I’m a Post doctoral fellow with a concentration on Pharmacogenomics in the Department of Pharmacotherapy and Translational Research at UF. My previous research as a PhD student focused on studying the genetic determinants of Resistant Hypertension. The ultimate goal of this research is to identify genetic predictors, which can be used along with other clinical predictors to identify high-risk patients and individualize their drug treatment. I realize and appreciate the value of Computational Genomics and Bioinformatics during my PhD training, and have been seizing any and every opportunity to learn different methodologies to analyze big data, with the goal of using this knowledge to learn about important genetic, racial, environmental determinants that will help in facilitating precision medicine approaches. My long term career goal is to be a successful academic researcher with a focus on Pharmacogenomics.

Martucci, Victoria

MD/PhD student
Medical Scientist Training Program (Human Genetics)
Vanderbilt University
Nashville, Tennessee

I am an MD/PhD student at Vanderbilt entering my second year of my PhD in human genetics. As a PhD student, my thesis will focus on unravelling the complexities of chronic obstructive pulmonary disease (COPD) genetics using information in Vanderbilt’s electronic health record (EHR) system. COPD is the third leading cause of mortality worldwide, so understanding genetic risk factors for COPD development could allow early intervention to reduce the devastating effects of this disease. COPD is highly heterogeneous in its clinical presentation, which makes studies of its genetics and development challenging. COPD research is also complicated by difficulties identifying COPD cases. The gold standard for COPD diagnosis is pulmonary function testing via spirometry, but this test is not routinely performed as a screening tool. Therefore, individuals who are asymptomatic or have mild disease may be undiagnosed, causing misclassification biases in performing case-control studies. One of the major goals of my project will be the development of an algorithm to identify individuals with COPD without using spirometry data based on information in the EHR. Once I have identified cases of COPD, I plan to leverage the wide array of clinical information available in the EHR to identify subphenotypes of COPD, with the goal of identifying unique genetic variants associated with each subphenotype. My research using EHR and existing genetic data will help discover some of the underlying mechanisms of COPD development, which can be used to better understand, treat, and ultimately prevent this highly prevalent disease.

McDonough (Rowe), Caitrin

Research Assistant Professor
Department of Pharmacotherapy and Translational Research
Center for Pharmacogenomics
University of Florida
Gainesville, Florida

I have a strong foundational background in human genetics and pharmacogenomics. As I have always been interested in genetics, and research that impacts human disease, my studies took me from working with fruit flies as an undergraduate to studying the genetics of diabetic nephropathy in African Americans as a doctoral student at Wake Forest University to investigating cardiovascular pharmacogenomics as a postdoctoral fellow at the University of Florida (UF). Upon completing my training, I moved into a faculty position as a Research Assistant Professor in the College of Pharmacy at UF in 2013. Over the past four years, I have continued to expand my knowledge in the areas of cardiovascular pharmacogenomics, clinical trials, and precision medicine. In April 2016, I was appointed as a KL2 scholar through the UF CTSA. My KL2 project focuses on developing a resistant hypertension (RHTN) computable phenotype, utilizing electronic health record (EHR)-based data from the OneFlorida DataTrust - a database that contains longitudinal EHR-based data from providers throughout the state of Florida. Additionally, as part of the training component of the KL2 award, I am completing a Master’s degree in Biomedical Informatics. I also remain active in genomic and pharmacogenomics research through collaborations in the Stroke Genetics Network, and the International Consortium for Antihypertensive Pharmacogenomics Studies, and I am involved with the Precision Medicine Program at UF. All of these activities allow me to maintain my expertise in human genetics and pharmacogenomics, while gaining additional knowledge and skills in biomedical informatics and “Big Data”.

Restrepo, Nicole

Staff scientist, bioinformatics
Department of Biomedical and Translational Informatics
Geisinger Health Systems
Rockville, Maryland

 I am a bioinformatics staff scientist in the Department of Biomedical and Translational Informatics at Geisinger Health Systems. Although formally trained as a genetic epidemiologist, my work in genetics and Electronic Health Records phenotyping intersect bioinformatics and precision medicine. My previous research and training involved the identification of common and rare genetic variation contributing to ocular disease (i.e., age-related macular degeneration, diabetic retinopathy, and glaucoma) in diverse populations of African American and Hispanic descent. My studies also look to dissect the interactions of genetic and environmental modifiers of ocular disease risk in unique Founder populations with a focus on precision medicine outcomes.

Singh, Abanish

Assistant Professor
Psychiatry and Behavioral Sciences
Duke University School of Medicine
Durham, North Carolina

My research training was focused on computational biology, high-throughput genomics, and big data analytics, which resulted in some of prominent findings on human genome. These findings included that the overrepresentation of short DNA elements in the human genome was a result of ancient duplication followed by degeneration activities in human DNA (Singh et al, 2007; Singh et al. 2010) and that the RNA-Seq can identify well human coding variants just using transcriptome as compared to the whole genome (PMID:20598109).  With a unique skillsets as resulted from an outstanding training, my sole aim was to help improve the human health through the cutting edge translational research that may lead to the precision medicine. I became interested in understanding the measurement of biobehavioral risk factors and environmental stressors and their interactions with genes that may influence CVD risk factors and endophenotypes.  My relatively recent work (Singh et al., EJHG, 2015) identified a novel CVD risk gene EBF1, where a common variant contributed to inter-individual differences in central obesity (hip, waist, and BMI) in the presence of chronic psychosocial stress. I also developed an algorithm to create a synthetic measure of stress using the proxy indicators of its components (PMID:26202568). More work that is recent (Singh et al. ASHG 2017) has elucidated the race, sex, and age related differences in the EBF1 x stress interaction and demonstrates the need for careful evaluation of environmental measures in different ethnicities in cross-ethnic gene-by-stress interaction studies.

Thomas, Kia

Undergraduate student
College of Arts & Sciences
Emory University
Atlanta, Georgia

My past and current research experience is in Dr. Gregory Melikian's lab at Emory School of Medicine department of pediatric infectious disease where I do work-study. Here we are researching the method of fusion employed by HIV and Lassa virus, and my role is to do data analysis using ImageJ/Fiji. My past research also includes working in Dr. Sam Speck's lab as a part of IMSD, where I worked with a post-doc to investigate the role of antigen M2 in the murine gammaherpes virus MHV68. Here I learned microbiology lab techniques such as PCR, western blotting, gel electrophoresis, DNA purification, cell culture, and flow cytometry. My current research is at the University of Chicago department of anesthesia and critical care in Dr. Daniel McGehee's lab. Here I am working with a post-doc on how to manipulate the dopamine reward pathway to find a new treatment for Parkinson's disease, using behavioral analysis (in-vivo), imaging, microscopy, immunohistochemistry, and electrophysiology. My role in this project is to see how Parkinson's influences the synaptic plasticity of affected neurons in the mouse model. In the fall I will be doing research in Dr. Bernardo Mainou's lab in Emory School of Medicine's department of pediatric infectious disease. My research will focus on using reovirus as a mechanism to treat triple-negative breast cancer.

My current research is related to precision medicine in that HIV and its many variances affect everyone differently. It is important to specify the types of treatments to the individual and the exposure they are privy to following their diagnosis. I am aware that HIV is sometimes treated with a "cocktail" of medications, different depending on the individual's conditions. I hope to improve this method of treatment and to make it more accurate and efficient, using precision medicine. With more of my research experience having been in infectious disease, I hope to go into a doctoral program and have a following career focused on the challenge that is the treatment of HIV and other communicable diseases.