Report: GWAS to therapy
GWAS to therapy: Using GWAS data for therapeutics
Joowon Yoon
School of Lifesciences, Ulsan National Institute of Science and Technology
Abstract
Gene risk factor for disease can be detected by Genome-Wide Association Study (GWAS). Our goal is not just finding risk factors but use them in therapy. I studied 4 methods for use GWAS data to therapy- (1) Prevention, (2) Overlap between GWAS and known drug, (3) Finding new mechanisms of metabolic disease, (4) Gene therapy. I will suggest the future tasks for GWAS to therapeutics.
Introduction
GWAS is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. The primary goal of these studies is to better understand the biology of disease, under the assumption that a better understanding will lead to prevention or better treatment. Science is study of the world, and Engineering applies scientific knowledge to useful things. GWAS is kinds of science, so we need engineering process that use GWAS data to make novel therapy.
Result
1. Prevention
GWAS can give information of risk factor of specific trait. That means, if someone has high risk factor of specific disease, he or she has high probability of that disease. Scientist can give advices to prevent the disease.
One example is Angelina Jolie, the famous actress. She inherited breast cancer risk gene, BRCA1. She decided to have surgery to reduce her breast cancer risk. It is not the ideal prevention, there might be high risk for breast or ovarian cancer if she did not get the surgery.
In the case of cancer, early detecting is very important for patient’s survival rate. But it is difficult to detect if the cancer has no physiological trait in early stage. Understanding association of gene and trait could help early intervention or prevention of disease. For example, if someone has high risk factor of pancreatic cancer, he can have regular checkup to prevention and early diagnosis.
2. Overlap between GWAS and known drug
GWAS data can be overlapped with known drug. In general, drug targets that are genetically informed have a higher probability of making it to phase 3 trial or to market. This imply potential huge cost savings to the healthcare industry.
Overlapping GWAS data can help understanding the response mechanisms of drug in the organs, tissues, and cells. This understanding lead to reducing side-effects of known drug or even increasing efficiency.
3. Finding new mechanisms of metabolic disease.
Actually, most of variants discovered by GWAS are Non-Coding Genes. There are 2 possible reason. First, if a non-coding gene and real high-risk factor is highly linked (the distance is very close), that gene can be discovered by GWAS with risk factor even if they are not risk factor. Second, those non-coding genes affect gene expression in epigenetic way. In this case, it would be possible to find novel mechanisms of metabolic disease. Furthermore, this novel mechanism can give information of new drug target.
4. Gene therapy
Gene therapy is the therapeutic delivery of nucleic acid into a patient’s cell as a drug to treat disease. There are 3 main methods for gene therapy.
- Gene therapy using an adenovirus vector.
Using adenovirus vector, new gene can be inserted in patient’s cell. It can transduce both non-diving and dividing cells. Carry up to 8Kbp heterologous DNA, and ensure high levels of transgene expression.
For example, assume that according to GWAS data, loss of copy number variants (CNVs) of gene A is related with disease D. D is related with loss of function. Inserting extra copy number of A can be helpful for treatment of D.
But this adenovirus vector has disadvantages. 1) It is highly immunogenic. 2) Vector genome does not integrate into the host genome, so it is not permanent therapy. 3) Hard to control expression levels 4) Hard to “Knock-out” host gene.
- Gene therapy Using RNA interference.
RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression or translation by neutralizing targeted mRNA molecules. It can effectively silence specific target gene. In August 2018, FDA approved the first RNAi drug (Onpattro). RNAi can be used even if the mRNA is not translated to protein. If GWAS data gives a information about specific mRNA is associated with a disease, RNAi can inhibit it.
But RNAi is also not permanent, and hard to treat loss-of-function problem.
- Gene editing using CRISPR/Cas9
CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) / Cas9 (CRISPR- associated protein 9) is a unique technology that enables geneticists and medical researchers to edit parts of the genome by removing, adding or altering sections of the DNA sequence. It edits host genome, so therapy with CRISPR/Cas9 is permanent. Both “Knock-out” and “Knock-in) are possible. It can edit specific loci. So, I think this gene editing is very powerful tool to adjust treatment from GWAS data.
But recent researches show CRISPR/Cas9 can make unexpected mutations, and also cause unwanted off-target effects.
We need to make safer the CRISPR/Cas9 system, or find next generation genome editing system for human gene therapy.
Discussion
Future GWAS will discover more variants and more genes associated with one or more traits. The genetic predictors will be more accurate, a greater ability to evaluate disease heterogeneity and to derive genetically informed diagnoses that might be more aligned to specific treatments.
The future GWAS will have some challenges. The next phase of GWAS research will require more systematic, integrated and comprehensive methods. To translate GWAS findings into therapeutics, efficient genetic testing and prediction models have to be improved. Besides, GWAS requires large amount of sample, both financially and intellectually, which are extremely costly and hardly available for many researchers. The application of GWAS should be carried out sensibly, with care for social, ethical and economic considerations. The most important thing in conducting scientific research is always having the specific research questions in mind (cause of disease or response to treatment, etc.) and using the appropriate methods (good study design, well-conducted statistical analysis, etc.) to answer these questions. GWAS, like other research tools, are used for solving the problems; they cannot lead the study directions.
Finally, I hope genomic personalized or precision medicine (or treatment) is likely to be widespread in prevention, intervention and also treatment steps with GWAS data.
Reference
- Visscher, P.M., Brown, M.A., McCarthy, M.I., and Yang, J. (2017). 10 Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet. 2017 Jul 6;101(1):5-22.
- Du, Yan., Xie, Jiaxin., Chang, Wenjun., Han, Yifang., Cao, Guangwen. Genome-wide association studies: Inherent limitations and future challenges. Frontiers of medicine. 2012 Nov
- https://en.wikipedia.org/wiki/Genome-wide_association_study
- https://en.wikipedia.org/wiki/Gene_therapy
- https://en.wikipedia.org/wiki/RNA_interference
- https://en.wikipedia.org/wiki/CRISPR
- https://www.yourgenome.org/facts/what-is-crispr-cas9
