Unraveling the Role of Genomics in Diagnosing Degenerative Diseases - Research PAper

Introduction

Genomics play a crucial role in the diagnosis of degenerative diseases. Conditions such as Alzheimer and diabetes are often associated with improper alignment of proteins that impair the functioning of different organs in the body. The brain is one of the most affected organs in an occurrence of degenerative disorders. Some of the causes include gene mutations noted in the past diagnosis, infections and unstable proteins.

Is your time best spent reading someone else’s essay? Get a 100% original essay FROM A CERTIFIED WRITER!

Order now

Alzheimer is a neurodegenerative condition that causes dementia among adults. The disease is caused by mutation of genes such as the amyloid-beta, a precursor presenilin1 (PSEN1) and PSEN2 (Giri et al., 2017). GWAS demonstrates that many genes code for AD. The condition results in complicated instances of AD pathogenesis that is featured by irreversible pathway.

The condition is featured through diverse biological and biochemical pathways. Apart from the genome component, the plaques and neuro-fibrillar also provide the critical hallmarks noted in the brains of patients with AD. Aggregates of the beta amyloids are cleaved along with its precursor's APP to initiate the condition (Giri et al., 2017). The case of mutation on the APP or presenilin and proteins in alpha-secretase can also cleave APP into Av.

AD's inheritance pattern occurs in the form of autosomal dominant pattern. The process is featured when one copy of genes is encoded differently, and the inheritance pattern is uncertain (Jung et al., 2018). However, most of the victims inherit the condition through ApoE e4 allele, which has increased the chances of developing the diseases. The ApoE gene is one of the genes that codes for apolipoprotein E production. The protein interacts with lipids that then cause high cholesterol levels to affect the e3 allele, which contributes to high cases of Alzheimer responsible for packaging cholesterol. Apart from ApoE, the CLU, CR1, BIN1, and ABCA7 are significantly associated with the condition (Jung et al., 2018). The genetic risks associated with AD is revealed through cellular signalling pathways responsible for cholesterol metabolism. However, the e4 allele of the ApoE contains SNP linked to AD (Kwok et al., 2018). Besides, the synthesis of the ApoE involves a process that increases injury to brain cells and increases neuro-degeneration.

ApoE is located in chromosome 19 and identified through its three isoforms that exist in the form of e1, e2, and e3 (Jung et al., 2018). ApoE effects vary based on the isoforms contained in the genes. For instance, the ApoE3 is one of the most common isoforms that contain cysteine and e4 contain arginine at the receptor-binding region of the N-terminal domain of the gene. The ability of these genes to encode for different proteins is crucial in determining the amino acids substitutions in the genes (Kwok et al., 2018). The deviations noted with their binding ability to the lipids and Av determines the chances of the occurrence of AD. The more the copies of the AOP allele, the higher the chances of developing AD. Similar to the ApoE4 allele has an underlying mechanism that highly contributes to complications associated with AD pathogenesis.

Additionally, a rare case of the TREM2 gene has been noted as one of the risks factors that causes AD. The gene is located on chromosome 6p21.1 and encodes for different proteins (Hu et al., 2017). However, one of its significant encoding roles is that of the transmembrane receptor, which is primarily expressed in the brain. The cells affected by this process include those associated with microglia, which plays a crucial role in maintaining homeostasis in the brain. The expression of TREM 2 signals an occurrence of the binding ligands related to anionic bacterial. It also induces the phosphorylation of the DAP12 (Jung et al., 2018). The process increases phagocytosis and decreased pro-inflammation. As a result, the process causes the alteration of microglia, and this process then plays a crucial role in AD progression.

The rapid use of microarray and next-generation sequencing technologies has enhanced the development of massive data regarding the AD. Through the application of these processes, the complex process of the pathology of AD has been established. However, more research based on genome studies is still required to develop simple pathogenesis based on gene sequencing to explain the occurrence of the condition (Jung et al., 2018). Most of the transcription and genomic-based studies have shown a simple model in the development of the state through neurodegenerative effects of gene alteration and mutations.

The existing treatment of Alzheimer alleviates symptoms since the condition has no effective drug treatment. The genetic validation of drugs is becoming popular. For instance, some few drugs identified with SNP-based are used for AD treatment. However, Genome-Wide Association Studies (GWAS) has not established the effect of low frequency. Determining the targets of these treatments further requires consideration of functional genetic units. The genetic loci the SNP is identified; this provides an opportunity to identify the pathways of drugs that targets specific genes responsible for AD condition. Through the Kyoto Encyclopedia of Genes and Genomes (KEGG), drug bank and drug repurposing Hub (Kwok et al., 2018). Most of the drugs targeted these genes. However, the effects were to regulate gene proteins and limit symptoms associated with AD. The use of computational drug target is also important in determining drug interactions and identifying pharmacological and biochemical properties of the drugs.

References

Giri, M., Shah, A., Upreti, B., & Rai, J. C. (2017). Unraveling the genes implicated in Alzheimer's disease. Biomedical reports, 7(2), 105-114. doi:10.3892/br.2017.927 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5526178/

Hu, Y. S., Xin, J., Hu, Y., Zhang, L., & Wang, J. (2017). Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach. Alzheimer's research & therapy, 9(1), 29. doi:10.1186/s13195-017-0252-z https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406904/

Jung, Y. J., Kim, Y. H., Bhalla, M., Lee, S. B., & Seo, J. (2018). Genomics: New Light on Alzheimer's Disease Research. International journal of molecular sciences, 19(12), 3771. doi:10.3390/ijms19123771 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6321384/

Kwok, M. K., Lin, S. L., & Schooling, C. M. (2018). Re-thinking Alzheimer's disease therapeutic targets using gene-based tests. EBioMedicine, 37, 461-470. doi:10.1016/j.ebiom.2018.10.001 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6446018/