King’s College London scientists examined biological samples from hundreds of participants in a European study. The researchers studied the biological data at different stages, including genes, proteins, metabolites, cognitive function, clinical diagnosis, and the development of Alzheimer’s disease (AD). The researchers present new perspectives on the variations of specific proteins and metabolites associated with Alzheimer’s disease endophenotypes, the AT(N) framework, and AD polygenic risk scores (PRS). These identified proteins and metabolites may be suitable for further analysis in understanding the mechanisms of AD pathology. Additionally, they may serve as potential therapeutic targets in the initial phases of AD.
Alzheimer’s disease is a neurodegenerative condition that deteriorates over time and causes memory loss and cognitive decline. In elderly people, it is the most typical cause of dementia. The underlying mechanisms of AD remain unknown despite years of research. According to new research, during AD progression, tau protein and amyloid beta (A) accumulate in the brain, resulting in neurofibrillary tangles (NFTs) and senile plaques.
ATN-Derived Networks
Researchers studied the ATN framework, a new classification scheme for Alzheimer’s disease that takes into account neurodegeneration, amyloid pathology, and tau pathology biomarkers. However, these three indicators only offer a limited understanding of the intricate pathophysiology of the disease. The study delves into the impact of the relationship between alterations in ATN, genetic factors, and other molecular transformations on the advancement of the disease.
By employing data science techniques, the researchers conducted an analysis on clusters comprising several hundred proteins and small molecules, including metabolites, which are impacted by the ailment. Instead of examining these individual components separately, they examined them as a cohesive unit, which yielded a more precise understanding of their interrelationships. The team also charted the clustering in relation to the ATN network and clinical information to establish variances in the biological indicators at different phases of the disease.
Causal Links in AD
In addition to identifying molecules, the authors employed a statistical approach to differentiate between the causal and consequential paths of Alzheimer’s disease. They discovered that a specific protein named PCSK7 has a causal association with the illness. This discovery is promising as targeting PCSK7 as therapy may help improve memory impairment, as it is located in an area of the brain that may be responsible for such impairments.
In addition, the researchers discovered alterations in a protein known as RCN2 and molecules referred to as sphingomyelins in individuals with Alzheimer’s disease. The APOE gene, which is the most common genetic risk factor for Alzheimer’s disease, seems to have an impact on these connections. These modifications imply the involvement of a potential vascular factor in Alzheimer’s, indicating a significant shared mechanism between vascular disease and dementia that warrants further exploration.
Implications for Diagnosis and Treatment
The study suggests several ways to diagnose and treat Alzheimer’s disease. First, the study’s discovery of molecular networks linked to AD may help create new biomarkers for the condition. The early detection and diagnosis of AD and the tracking of the disease’s progression depend heavily on biomarkers.
Second, uncovering the causal relationship between molecular changes and the onset of Alzheimer’s disease may help develop new therapeutic targets. By focusing on the molecular pathways that contribute to the progression of AD, researchers can create new treatments that slow or stop the progression of the disease.
Limitations of the Study
The sample consisted of individuals of European descent who were largely afflicted with amyloid pathology and carriers of APOE ε4. Hence, they may not be fully reflective of the wider population. To ensure the validity of the findings, it was crucial to replicate them in separate groups, particularly in different ethnicities and community-based samples.
Conclusion
The research stands out as the most extensive study to date investigating multi-omics concerning Alzheimer’s disease (AD) endophenotypes, with a specific focus on the AT(N) framework. The results provide fresh perspectives on the alterations of distinct proteins and metabolites associated with AD endophenotypes, the AT(N) framework, and AD PRS. These identified proteins and metabolites could be feasible candidates for further mechanistic studies on the pathology of AD. Additionally, they could potentially serve as effective targets for drug development during the early stages of AD.
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Dr. Tamanna Anwar is a Scientist and Co-founder of the Centre of Bioinformatics Research and Technology (CBIRT). She is a passionate bioinformatics scientist and a visionary entrepreneur. Dr. Tamanna has worked as a Young Scientist at Jawaharlal Nehru University, New Delhi. She has also worked as a Postdoctoral Fellow at the University of Saskatchewan, Canada. She has several scientific research publications in high-impact research journals. Her latest endeavor is the development of a platform that acts as a one-stop solution for all bioinformatics related information as well as developing a bioinformatics news portal to report cutting-edge bioinformatics breakthroughs.
