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The diagnosis and treatment of Alzheimer's disease (AD) have been problematic, mainly because of the varying degrees of degeneration and cognitive impairment seen in different patients. Researchers at the University of California, San Diego's School of Medicine used the transcriptome for the first time to evaluate the proteins from the genes of AD patients likely to facilitate diagnosis.
A transcriptome is the sum of all the messenger RNA (mRNA) molecules expressed by the genetic code of an individual. The study is published in the latest issue of the journal Cell reports, entitled "The Integration of Gene and Protein Expression Reveals Disrupted Functional Networks in Alzheimer's Disease."
In brains affected by Alzheimer's disease, abnormal levels of beta-amyloid protein clump together to form plaques (visible in brown) that accumulate between neurons and disrupt cell function. . Abnormal collections of tau protein accumulate and form entanglements (visible in blue) in neurons, impeding synaptic communication between nerve cells. Image credit: National Institute on Aging, NIH
For their study, the team of researchers compared the transcriptome of 414 participants in the study. These people had been diagnosed clinically earlier with Alzheimer's disease. Their genetic makeup was compared to a control participant of the same age but lacking the characteristics of dementia. The results revealed that there was a complex interplay between genetic alterations and various proteins in AD, which could help in the diagnosis of this disease, even in the absence of cognitive decline and neurodegeneration characteristics.
The results revealed that people with a family history of AD usually had a strong genetic link with the disease, which was not surprising. On the other hand, those who suffer from sporadic AD have multiple factors that determine their condition. Many of these factors are unknown. Sporadic AD remains the most common form of AD, according to the researchers. Some risk factors include gender, age and other social, biological and psychosocial factors.
The team explains that there is an accumulation of two types of proteins in the brain and that it is the key pathology of AD. These proteins are the formation of amyloid protein plaques and the development of abnormal entanglements of neurofibrillary tau proteins. These plaques and entanglements tend to kill neurons and lead to the characteristics of AD and its progression. Other factors such as inflammation, cerebral atrophy and blood circulation problems have all been attributed to AD and its progression, the study authors added. The team wrote that these factors "correlate with the clinical symptoms of cognitive decline and have led to a change in diagnostic criteria over the last decade".
The team wrote that some of the previously known AD-related genetic mutations include "Genetic mutations in the precursor protein of amyloid (APP), preseniline 1 (PSEN1) and preseniline 2 (PSEN2) badociated with autosomal dominant AD. "The team added in its study that the loss of regulation ofEGR3The gene could be responsible for synaptic deficits or deficiencies of nerve synapses in AD. They explain that this may be due to the targeting of the synaptic vesicle cycle that is altered in AD. They proposed "the loss of regulation of EGR3, crucial for short-term memory, regulates synaptic deficits by targeting the synaptic vesicular cycle "and its badociation with AD in their study.
Lead author Robert Rissman, PhD, professor of neuroscience at the Faculty of Medicine at the University of San Diego, explained that their study focused specifically on genetic alterations and badociated protein interactions in AD. Rissman is also Director of the Biomarker Core for the Alzheimer's Disease Collaborative Study (ADCS) and the Neuropathology / Brain Bank and Biomarker Research Center of the Alzheimer's Disease Research Center in San Diego Shiley-Marcos.
He explained that these genes are identifiable composite clusters and that their level of expression is related to AD. He added that these genes could affect the cell cycle, metabolic processes within the cell, immune responses and, ultimately, cell survival. These factors are all related to the pathology of AD, he explained. The team wrote that these gene clusters were identified with the help of "Leuven algorithm for community detection".
The authors of the study explained: "The Leuven algorithm does not require precise selection or parameter setting, unlike other clbadification algorithms such as the K-means clbadification and the hierarchical clbadification (like those used in the WGCNA R package). Clusters are rather determined by looking for gene pools that have many connections within a group and little between them. This algorithm has proved useful for detecting modules, or clusters, in protein-protein interaction networks. "
In a statement, Rissman said, "One of the big problems in AD research is identifying patients at risk at the right time. Understanding gene networks that may change within specific patient groups can help streamline clinical trial recruitment efforts and reduce the costs and time required to enroll. As the field evolves more and more towards pre-symptomatic disease, we must deepen our understanding of the molecular mechanisms underlying the entire spectrum of the disease.
Journal reference:
Integration of Gene and Protein Expression Reveals Disrupted Functional Networks in Alzheimer's Disease
Canchi, Saranya et al. Cell Reports, Volume 28, Number 4, 1103 – 1116.e4, https://doi.org/10.1016/j.celrep.2019.06.073
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