Making Precision Medicine a Reality: Genomics Researchers Discover Road Map to Disease Origin

TUCSON, Ariz. – Researchers are one step closer to understanding the genetic and biological basis of diseases like cancer, diabetes, Alzheimer’s and rheumatoid arthritis – and identifying new drug targets and therapies – thanks to work by three computational biology research teams from the University of Arizona Health Sciences, University of Pennsylvania and Vanderbilt University.

The researchers’ findings – a method demonstrating that independent DNA variants linked to a disease share similar biological properties – were published online in the April 27 edition of npj Genomic Medicine.

“The discovery of these shared properties offer the opportunity to broaden our understanding of the biological basis of disease and identify new therapeutic targets,” said Yves A. Lussier, MD, FACMI, lead and senior corresponding author of the study and UAHS associate vice president for health sciences and director of the UAHS Center for Biomedical Informatics and Biostatistics (CB2).

The researchers are striving to better understand the common genetic and biological backgrounds that make certain people susceptible to the same disease. They have developed a method to demonstrate how individual, disease-associated DNA variants share similar biological properties that provide a road map for disease origin.

Over the last ten years, genetics researchers have conducted large studies, called Genome Wide Association Studies (GWAS), which analyze DNA variants across thousands of human genomes to identify those that are more frequent in people with a disease. However, the impact of many of these disease-associated variants on the function and regulation of genes remains elusive, making clinical interpretation difficult.

A method to explore the biological impact of these variants and how they are linked to disease was developed through the collaboration of bioinformatics and systems biology researchers Dr. Lussier; Haiquan Li, PhD, research associate professor and director for translational bioinformatics, Department of Medicine, UA College of Medicine – Tucson; Ikbel Achour, PhD, director for precision health, CB2; Jason H. Moore, PhD, director, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania; and Joshua C. Denny, MD, MS, FACMI, associate professor of biomedical informatics and medicine, Vanderbilt University, along with their teams.

In their new paper, the researchers demonstrate that DNA risk variants can affect biological activities such as gene expression and cellular machinery, which together provide a more comprehensive picture of disease biology. When DNA risk variants for a given disease were analyzed in combination, similar biological activities were discovered, suggesting that distinct risk variants can affect the same or shared biological functions and thus cause the same disease. More detailed analyses of variants linked to bladder cancer, Alzheimer’s disease and rheumatoid arthritis showed that two variants can contribute to disease independently, but also interact genetically. Therefore, the precise combination of DNA variants of a patient may work to increase or decrease the relative risk of disease.

The team of researchers also is pursuing the development of methods to unveil the biological incidence of “long-time overlooked” DNA variants with the aim to more precisely inform clinical decisions with treatments tailored to a patient’s genetic and biological background. Since two of these research teams (Lussier’s and Denny’s) recently committed to the White House Precision Medicine Initiative (PMI), this innovative study demonstrates how strategic collaboration is key to making precision medicine a reality, noted Dr. Lussier.

The paper, “Integrative genomics analyses unveil downstream biological effectors of disease-specific polymorphisms buried in intergenic regions,” has been identified as one of the best 30 of the year in computational biology and bioinformatics, and will be presented as a “highlight of the year” at the 2016 Intelligent Systems for Molecular Biology (ISMB) conference, the largest international conference of computational biology/bioinformatics, in July in Orlando, Fla.

In addition to Drs. Lussier, Li, Achour, Denny and Moore, study contributors included Joanne Berghout, Vincent Gardeux, Jianrong Li and Kenneth S. Ramos (UAHS); Lisa Bastarache (Vanderbilt); Younghee Lee (University of Utah); and Lorenzo Pesce, Xinan Yang and Ian Foster (University of Chicago). Drs. Haiquan Li, Achour, Berghout, Gardeux, Jianrong Li and Lussier also are members of the UA BIO5 Institute, and Dr. Lussier is a member of the University of Arizona Cancer Center. The work also was conducted in part at the University of Illinois.

The study was supported in part by grants from the Computation Institute BEAGLE Cray Supercomputer of the University of Chicago and Argonne National Laboratory (NIH 1S10RR029030-01), the NIH National Library of Medicine (R01-LM010685, K22-LM008308, LM009012, LM010098, LM010685), the University of Arizona Cancer Center (NCI P30CA023074), the University of Arizona Health Sciences (UL1RR024975), the University of Illinois CTSA (UL1TR000050) and the Vanderbilt University CTSA (UL1TR000445).

EXTRA INFO

Abstract

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 (OR>12). 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 (entropyP=0.039), and rheumatoid arthritis (PheWAS case–control P<10−4). 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 "road map" of disease mechanisms emerging from GWAS and further identify candidate therapeutic targets among downstream effectors of intergenic SNPs.

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About the University of Arizona Health Sciences
The University of Arizona Health Sciences is the statewide leader in biomedical research and health professions training. The UA Health Sciences includes the UA Colleges of Medicine (Phoenix and Tucson), Nursing, Pharmacy and Mel and Enid Zuckerman College of Public Health, with main campus locations in Tucson and the growing Phoenix Biomedical Campus in downtown Phoenix. From these vantage points, the UA Health Sciences reaches across the state of Arizona and the greater Southwest to provide cutting-edge health education, research, patient care and community outreach services. A major economic engine, the UA Health Sciences employs almost 5,000 people, has nearly 1,000 faculty members and garners more than $126 million in research grants and contracts annually. For more information: https://healthsciences.arizona.edu/

Media Contact: UAHS Office of Public Affairs

ALSO SEE:
“Making precision medicine a reality: Genomics researchers unveil road map to disease origin” (Science Daily) | Posted April 29, 2016
“White House Announcement: UA Health Sciences Commits Biomedical Informatics and Genome Medicine Teams to National Precision Medicine Initiative” | Posted Feb. 25, 2016