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SCN9A: Proposal of Voltage-Gated Ion Channels as a Novel Diagnostic Marker for Alzheimer's Disease

Shah, D.; Shah, R.; Waldron, A.; Leonardi, D.

2023-05-20 neurology
10.1101/2023.05.18.23289925 medRxiv
Show abstract

Alzheimers disease (AD) is an age-related neurodegenerative disease that affects over 6 million adults each year. As individuals age, their cells do not repair themselves which leads to proliferation arrest known as senescence. In the nervous system, astrocyte senescence has been associated with neuroinflammation and other AD processes. Thus, studying senescence may be a unique approach to understanding AD pathology. This study looks at the correlation between SCN9A, a novel gene target, and AD. Results suggest SCN9A may be a potential diagnostic marker for AD. A model was created with an 80%+ accuracy rate in predicting AD. Overall, this study suggests SCN9A plays a large role in neurodegeneration and treating AD.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Journal of Alzheimer's Disease
○ 48 papers in training set
Top 0.1%
12.7%
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2
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Top 0.1%
11.9%
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3
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Top 0.1%
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4
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5
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Top 0.4%
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7
Frontiers in Neurology
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Top 0.9%
3.2%
8
The Journal of Prevention of Alzheimer's Disease
○ 13 papers in training set
Top 0.2%
3.2%
50% of probability mass above
9
Alzheimer's & Dementia
177 papers in training set
Top 1%
3.2%
10
npj Aging
○ 22 papers in training set
Top 0.1%
2.6%
11
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Top 0.8%
2.1%
12
GeroScience
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Top 1.0%
2.0%
13
Neurobiology of Aging
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Top 0.8%
2.0%
14
Heliyon
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Top 3%
1.7%
15
Frontiers in Neuroscience
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Top 3%
1.7%
16
Alzheimer's & Dementia: Translational Research & Clinical Interventions
○ 17 papers in training set
Top 0.2%
1.7%
17
European Journal of Neurology
○ 22 papers in training set
Top 0.4%
1.5%
18
International Journal of Molecular Sciences
○ 494 papers in training set
Top 11%
1.1%
19
Scientific Reports
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Top 63%
1.1%
20
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Top 1%
1.1%
21
Journal of Biomedical Science
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Top 0.2%
1.1%
22
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○ 50 papers in training set
Top 1%
1.1%
23
The Journals of Gerontology: Series A
◐ 29 papers in training set
Top 0.4%
1.0%
24
eLife
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Top 63%
1.0%
25
Molecular Neurobiology
○ 53 papers in training set
Top 1%
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26
Diabetes Research and Clinical Practice
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Top 0.3%
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27
European Journal of Neuroscience
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28
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29
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0.8%
30
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Top 0.9%
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.