Back

Gene-Excessive Sleepiness Interactions Suggest Treatment Targets for Obstructive Sleep Apnea Subtype

Nagarajan, P.; Kurniansyah, N.; Lee, J.; Gharib, S. A.; Xu, Y.; Zhang, Y.; Spitzer, B.; Faquih, T.; Zhou, H.; Boerwinkle, E.; Chen, H.; Gottlieb, D. J.; Guo, X.; Heard-Costa, N. L.; Hidalgo, B. A.; Levy, D.; Liu, P. Y.; Mei, H.; Montalvan, R.; Mukherjee, S.; North, K. E.; O'Connor, G. T.; Palmer, L. J.; Patel, S. R.; Psaty, B. M.; Purcell, S. M.; Raffield, L. M.; Rich, S. S.; Rotter, J.; Saxena, R.; Smith, A. V.; Stone, K. L.; Zhu, X.; TOPMed Sleep Trait WG, ; Cade, B. E.; Sofer, T.; Redline, S.; Wang, H.

2024-10-28 genetic and genomic medicine
10.1101/2024.10.25.24316158 medRxiv
Show abstract

Obstructive sleep apnea (OSA) is a multifactorial sleep disorder characterized by a strong genetic basis. Excessive daytime sleepiness (EDS) is a symptom that is reported by a subset of OSA patients, persisting even after treatment with continuous positive airway pressure (CPAP). It is recognized as a clinical subtype underlying OSA carrying alarming heightened cardiovascular risk. Thus, conceptualizing EDS as an exposure variable, we sought to investigate EDSs influence on genetic variation linked to apnea-hypopnea index (AHI), a diagnostic measure of OSA severity. This study serves as the first large-scale genome-wide gene x environment interaction analysis for AHI, investigating the interplay between its genetic markers and EDS across and within specific sex. Our work pools together whole genome sequencing data from seven cohorts, enabling a diverse dataset (four population backgrounds) of over 11,500 samples. Among the total 16 discovered genetic targets with interaction evidence with EDS, eight are previously unreported for OSA, including CCDC3, MARCHF1, and MED31 identified in all sexes; TMEM26, CPSF4L, and PI4K2B identified in males; and RAP1GAP and YY1 identified in females. We discuss connections to insulin resistance, thiamine deficiency, and resveratrol use that may be worthy of therapeutic consideration for excessively sleepy OSA patients.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Sleep
26 papers in training set
Top 0.1%
34.4%
2
Scientific Reports
3102 papers in training set
Top 21%
5.1%
3
Communications Biology
886 papers in training set
Top 0.8%
4.5%
4
Nature Communications
4913 papers in training set
Top 36%
4.1%
5
Translational Psychiatry
219 papers in training set
Top 2%
2.9%
50% of probability mass above
6
iScience
1063 papers in training set
Top 7%
2.9%
7
Neuropsychopharmacology
134 papers in training set
Top 1%
1.8%
8
eLife
5422 papers in training set
Top 40%
1.8%
9
Psychiatry Research
35 papers in training set
Top 0.9%
1.8%
10
PLOS Genetics
756 papers in training set
Top 8%
1.8%
11
Genome Medicine
154 papers in training set
Top 4%
1.7%
12
PLOS Biology
408 papers in training set
Top 11%
1.5%
13
SLEEP
28 papers in training set
Top 0.3%
1.5%
14
Sleep Medicine
18 papers in training set
Top 0.3%
1.4%
15
Cell Genomics
162 papers in training set
Top 4%
1.4%
16
British Journal of Anaesthesia
14 papers in training set
Top 0.5%
1.3%
17
Neurobiology of Disease
134 papers in training set
Top 3%
1.3%
18
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 37%
1.3%
19
Frontiers in Neuroscience
223 papers in training set
Top 6%
1.0%
20
EBioMedicine
39 papers in training set
Top 0.6%
1.0%
21
Aging Cell
144 papers in training set
Top 3%
0.9%
22
The American Journal of Human Genetics
206 papers in training set
Top 3%
0.8%
23
Biological Psychiatry
119 papers in training set
Top 2%
0.8%
24
NeuroImage
813 papers in training set
Top 5%
0.8%
25
Nature Human Behaviour
85 papers in training set
Top 4%
0.8%
26
Molecular Psychiatry
242 papers in training set
Top 3%
0.8%
27
Journal of Sleep Research
31 papers in training set
Top 0.4%
0.8%
28
npj Digital Medicine
97 papers in training set
Top 3%
0.8%
29
Journal of Neuroscience Research
25 papers in training set
Top 0.7%
0.7%
30
Journal of Clinical Investigation
164 papers in training set
Top 7%
0.7%