Genetics and genomics have allowed us to map the entire human genome, investigating the function of a single gene as well as the interactions of all genes. But, what does this mean for those with genetic disorders?
Image Credit: hafakot/Shutterstock.com
Genetic disorders are the result of changes in the DNA sequence of a gene or genes, chromosomal abnormalities, or a combination of genetic mutations and environmental influences. According to the Online Mendelian Inheritance in Man (OMIM), there are a near 7,000 known phenotypes of genetic disorders. These “defects” in the genome can be passed from parent to child, or acquired during a person’s life. Hereditary diseases are a result of the former; caused by an inherited variation(s) in the genetic sequence, also known as a disease allele.
The incidence and prevalence of hereditary diseases vary greatly across certain populations. Cystic fibrosis is estimated to affect 1/3,000 people in Europe, but in Ireland there is an estimated prevalence of 1/1,400. What’s more, sickle cell disease has an estimated birth prevalence of 1/2,300 in Europe, but 1/90 in Africa. While people suffering with these diseases can have the same phenotype, they often have distinct genotypes.
Genetic heterogeneities influencing disease pathogenesis and clinical presentation can complicate diagnosis and treatment. Cystic fibrosis has 5 known distinct classes of disease alleles, grouped by their effect on the cystic fibrosis transmembrane conductance regulator (CFTR).
For monogenic disorders, like cystic fibrosis and sickle cell disease, determining the region of DNA responsible for the disease phenotype is relatively easy. Forward genetics can utilize pedigree analyses to pinpoint where the causative gene is located.
Polygenic inherited diseases
When the disease doesn’t follow Mendelian inheritance patterns, connecting phenotype and genotype can be more complicated than pedigree data can link with any degree of certainty. Comparing an individual’s genome to the mapped sequence, enables identification of regions where the code varies from the ‘normal’.
For polygenic traits, genome-wide association study (GWAS) can help identify candidate genes for susceptibility to disease, or causing disease. These genes are identified through markers associated with the phenotype, most useful of which is single-nucleotide polymorphisms (SNPs). Many of the disease-associated SNPs have already mapped, with details of the DNA contributor’s medical and lifestyle history logged in Biobanks.
These population-based Biobanks provide the groundwork for understanding disease alleles and their frequency in different populations. The ‘All of Us’ Research Program is one of the largest Biobank’s globally; they collect, analyze, store and distribute biological samples for research purposes.
Working towards improving health care, this program hopes to improve our understanding of risk factors for diseases, as well as aid in determining most efficacious treatment options. The program has also recently awarded seven community partners funding to help expand participation and research, particularly in historically underrepresented groups.
Gene maps and CRISPR systems
Biobanks also aid research into gene therapies, with the potential to cure genetic disorders. Understanding the genetic code of the normal and diseased alleles is required for gene therapy to work.
Variation in regions of the genome which control variable traits, are also known as quantitative trait loci (QTL) and often contain several genes. Genome maps use SNPs and other genetic markers to identify a gene or QTL responsible for a characteristic; locating these can inform gene therapy, as well as lifestyle decisions based on predispositions to disease.
With the region and sequence of DNA identified, CRISPR/Cas systems can remove the disease-causing variant and insert the normal sequence. CRISPR based biotech startup Mammoth Biosciences (who’s co-founder is Jennifer Doudna, renowned for her work with Emmanuelle Charpentier, demonstrating the capacity of CRISPR in 2012) aims to create a “toolbox” of these genetic “scissors”. By utilizing novel Cas endonucleases, Mammoth Biosciences is able to expand the scope of application and address current barriers to access. Their systems are also reportedly more accurate, with unique protospacer adjacent motif (PAM) requirements.
The PAM sequence assists in targeting the CRISPR system to the disease allele; it is a short sequence of DNA that interacts with RNA in the Cas endonuclease, as part of a process called interrogation. This interaction is required for DNA strand separation, the subsequent formation of the RNA:DNA heteroduplex, and activation of nuclease activity.
Thorough gene maps of disease and knowledge of the individual’s genome, we can build increasingly specific treatments to target genetic disorders. Before the human genome was mapped in its entirety, Collins and McKusick speculated the importance of genetics in identification and characterization of genetic variants. They stated: “By the year 2010, it is expected that predictive genetic tests will be available for as many as a dozen common conditions”.
As of 2016, there were reported to be over 2,000 genetic tests in use. These tests can help people to better understand treatments that will work for their unique disease genotype as well as healthy lifestyle choices, based on their genome and predispositions to disease.
Sources:
- Brown, T.A., (2017) Genomes 4 (4th. ed.). Garland Science.
- National Human Genome Research Institute. (2018). Genetic Disorders. [Online] National Institute of Health. Available at: https://www.genome.gov/For-Patients-and-Families/Genetic-Disorders (Accessed on 10 September 2021).
- OMIM. (2021). OMIM Gene Map Statistics. [Online] OMIM, John Hopkins University. Available at: https://www.omim.org/statistics/geneMap (Accessed on 10 September 2021).
- Liou, T. (2020). Cystic Fibrosis. [Online]. Orphanet encyclopedia. Available at: www.orpha.net/.../group%20of%20diseases=Cystic-fibrosis&title=Cystic%20fibrosis&search=Disease_Search_Simple (Accessed on 10 September 2021).
- Wastnedge, E., et al. (2018). The global burden of sickle cell disease in children under five years of age: a systematic review and meta-analysis. Journal of global health. https://doi.org/10.7189/jogh.08.021103
- Drumm, M. L., Ziady, A. G., & Davis, P. B. (2012). Genetic variation and clinical heterogeneity in cystic fibrosis. Annual review of pathology. https://doi.org/10.1146/annurev-pathol-011811-120900
- Swede, H., Stone, C. & Norwood, A. (2007). National population-based biobanks for genetic research. Genet Med. https://doi.org/10.1097/GIM.0b013e3180330039
- All of Us Research Program. (2018). All of Us Research Program Overview. [Online] National Institute of Health. Available at: https://allofus.nih.gov/about/program-overview (Accessed on 10 September 2021).
- All of Us Research Program. (2021). All of Us Research Program Awards Funding to Seven Community Partners. [Online]. National Institute of Health. Available at: allofus.nih.gov/.../all-us-research-program-awards-funding-seven-community-partners (Accessed on 10 September 2021).
- Betuel, E. (2021). Breakout ‘CRISPR platform’ company Mammoth Biosciences is officially a unicorn. [Online]. Tech Crunch. Available at: techcrunch.com/.../?guccounter=1 (Accessed on 10 September 2021).
- Sternberg, S.H., et al. (2014). DNA interrogation by the CRISPR RNA-guided endonuclease Cas9. [Online]. Nature. https://doi.org/10.1038/nature13011
- Collins F.S., and McKusick V.A. (2001). Implications of the Human Genome Project for Medical Science. [Online]. JAMA. doi:10.1001/jama.285.5.540
- Tidy, C., and Jackson, C. (2016). Genetic Testing. [Online]. Patient. Available at: https://patient.info/treatment-medication/genetic-testing (Accessed on 10 September 2021).
Further Reading