<aside> 🧫 Developing a rapid gene target discovery pipeline to test the causal relationship between the anatomic features of Alzheimer’s and the genetic profile of innate immune inflammation.
</aside>
Neurodegenerative disorders, like Alzheimer's and Parkinson's, afflict nearly a billion individuals worldwide, causing decreased brain function and movement. Current clinical studies focus on remediating symptoms of these diseases rather than removing underlying causes; along with having a lack of understanding and complexity from a neural transcriptome perspective, many scientists struggle to find a permanent solution to these issues.
By leveraging transcriptome and MRI imaging, this study aims to expand possible gene targets for future drug discovery methods in Alzheimer's and other neurodegenerative diseases. After discovering inflamed areas from brain scans using convolutional neural networks and mapping them to neural regions, differential expression can find statistically significant genes, with feature selection methods optimizing the efficacy of the expression dataset.
This venture will provide new targets for researchers and increase savings through an automated workflow and accessibility through open-source code; additional testing can be run to validate these hypotheses, allowing for much stronger targeted treatments than before.
Nearly 1 billion individuals are afflicted with neurological diseases, from Alzheimer's disease to migraines to multiple sclerosis, with 6.8 million deaths each year. Currently, there are no cures for neurological diseases due to the complexity of neural systems and lack of understanding from a genome and transcriptome perspective.
Because disease research is heavily symptoms-oriented and focused on proteins that cause neurodegenerative diseases, genomic and transcriptomic resources are underutilized, passing up on hundreds of potential gene and RNA targets that could be used in the drug discovery pipeline. By analyzing gene datasets, neurodegenerative research can expand, providing new pathways for reducing the impact of these harmful ailments.
Approximately 44 million (around .6% of the global population) individuals are afflicted with Alzheimer's disease globally, being the most prevalent and deadly neurodegenerative disorder as it causes uncontrolled cell death and loss of brain function.
Prevailing hypotheses have sourced a buildup of amyloid, an uncontrolled protein deposited in animal tissues, to be the leading cause of this disease; this has spurred a number of treatments (28% of research space) and billions of dollars of R&D to reduce amyloid, with little avail. Little research has been performed outside of the amyloid space, and with rates of Alzheimer's increasing, there's an increasing necessity for more permanent solutions.
Other research focuses in the Alzheimer's space, like in metabolism (4.1%), neuroendocrine mechanisms (3.5%), and immunity (9.4%) often require additional genetic testing to continue their research further; however, due to the lack of knowledge in the space and inaccessibility of certain datasets, this research is often discontinued before it makes an impact.
Billions of dollars are being poured into Alzheimer's and other neurodegenerative diseases. Specifically, **OECD notes 60% of research in scientific fields is carried out by industry, while 20% and 10% respectively are carried out by universities and government.**
In 2013, the United States spent nearly $456.1 billion on research, of which $34 billion is going to neurodegenerative diseases. Industry is the biggest contributor due to the potential for profit that comes from a breakthrough; however, due to little to no progress in the field and major clinical trial failures (from focusing on specific protein targets), financial investments are waning, indicating a need to shift to a new approach to research. Additionally, universities fund heavily for Alzheimer's research and are ramping up investment, as seen by Brown's recent Center for Alzheimer's Disease Research and a $55.6 million grant from the University of Washington. Similar to industry, little progress will decrease financial investments over time, indicating a need for a new method.
Lastly, the government, particularly the NIH, has a large stake in Alzheimer's research, with over 5% of its total budget going towards funding neurodegenerative disease research; government spending has ramped up, due to increases in grant applications and the government wanting to "bring in fresh ideas". This is evidenced by their change in spending, with a decrease in ~10% in β-amyloid from 27.2% and a ~3% increase in genetics research from 9.3%, among other novel ideas. Lastly, out of 452 that won Alzheimer's grants, 27% received their first NIH grant, while only 36% were established, indicating, in NIH Director Richard Hodes' words, that "[they're] not just repeating the things that failed and hoping [they] get a different result."
Code for building the pipeline can be accessed here.
To relate inflammation data to genomic markers, the Allen Brain Atlas data portal was used, containing extensive gene expression levels for various gene classifications and parts of the body. This study looked specifically at gene classifications of transcription factors, Alzheimer's, and inflammation mediated by chemokine and cytokine signaling pathways.
To provide differential gene expression, FASTQ files were needed in conjunction with gene/transcript expression matrices. The Aging, Dementia, and Traumatic Brain Injury Study in conjunction with Guan et. al 2021. provided the requisite files needed.