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Examining the causal genetic effects of substance use on aging

Balbona, J. V.; Jeffries, P.; Gorelik, A. J.; Nelson, E. C.; Bogdan, R.; Agrawal, A.; Johnson, E. C.

2024-10-15 genetic and genomic medicine
10.1101/2024.10.14.24315472 medRxiv
Show abstract

Substance use shortens lifespan, impedes health, and accelerates the biological aging process. We found widespread genetic correlations between alcohol, tobacco, cannabis, and opioid use and use disorders with indices of aging across the lifespan. There was evidence of tobacco and alcohol use and use disorders causally impacting physical, cognitive, and biological aging, with the effects of alcohol being more dependent on quantity of consumption; evidence of reverse causality was scant.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Nature Aging
○ 60 papers in training set
Top 0.1%
19.2%
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2
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13.6%
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6.5%
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Top 19%
6.5%
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Nature Communications
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Top 28%
5.4%
7
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Top 0.8%
2.9%
8
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 19%
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9
Nature Medicine
○ 125 papers in training set
Top 1%
2.5%
10
Molecular Psychiatry
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Top 3%
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11
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Top 0.7%
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12
The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences
◐ 26 papers in training set
Top 0.2%
2.0%
13
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○ 107 papers in training set
Top 0.8%
1.8%
14
Molecular Neurodegeneration
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Top 1%
1.2%
15
Cell Metabolism
○ 57 papers in training set
Top 0.9%
1.2%
16
Scientific Reports
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Top 61%
1.2%
17
Translational Psychiatry
○ 260 papers in training set
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1.2%
18
Genome Medicine
○ 183 papers in training set
Top 5%
0.9%
19
Clinical Epigenetics
○ 60 papers in training set
Top 0.6%
0.6%
20
Nature
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Top 11%
0.6%
21
Frontiers in Genetics
○ 230 papers in training set
Top 6%
0.6%
22
eBioMedicine
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Top 8%
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23
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
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Top 1%
0.5%
24
iScience
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Top 44%
0.5%
25
Nature Metabolism
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Top 2%
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26
Annals of Neurology
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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.