scholarly journals 0024 PTSD with Concurrent Excessive Daytime Sleepiness Alters Gene Expression in Military Personnel and Veterans; An RNA-Sequencing Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A9-A10
Author(s):  
C L Pattinson ◽  
K Edwards ◽  
V A Guedes ◽  
S Mithani ◽  
S Yun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Military Personnel ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Gene Networks ◽  
Sleep Disturbances ◽  
Rna Seq ◽  
Gene Dysregulation ◽  
Examine Gene Expression ◽  
Significant Gene

Abstract Introduction Up to 91% of military personnel and veterans with posttraumatic stress disorder (PTSD) report co-occurring sleep disturbances, including. insomnia and excessive daytime sleepiness (EDS). Sleep disturbances have been shown not only to increase the risk of developing PTSD, but to exacerbate and maintain PTSD symptomology. The aim of this study was to examine gene expression in active duty military personnel and veterans with PTSD, with and without EDS. Participants were categorized into three groups; 1) PTSD with EDS (PTSDwEDS; n=21), 2) PTSD without EDS (PTSDnoEDS; n=25), or 3) Controls (no PTSD and no EDS; n=57). Methods Participants were 79% male, mean age of 37.6years (SD=11.2years). PTSD symptoms were measured using the PTSD checklist for civilians (PCL-C); participants were classified as PTSD-present using DSM-IV-TR criteria of “moderate-to-severe”. Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS), high sleepiness was indicated by an ESS score >13. We performed RNA-seq with Illumina’s HiSeq 2500 in paired-end. We conducted quality control using FastQC and aligned to GRCh38 reference genome using STAR (v2.5.3a). Differentially expressed genes identified using DESeq2 (v1.20.0) with False Discovery Rate of 0.10. Finally, Ingenuity Pathway Analysis (IPA) was conducted to identify dysregulated gene networks. Results Between the Controls and PTSDnoEDS groups, two genes were significantly dysregulated. In controls and PTSDwEDS groups, 251 genes were dysregulated. The IPA networks showed that genes associated with inflammation were significantly dysregulated. Finally, between PTSDwEDS and PTSDnoEDS there were 1,873 significantly dysregulated genes. The IPA networks identified dysregulation of genes related to sleep, fatigue, circadian, and mitochondrial function. Conclusion Taken together this data indicates that EDS that is co-morbidly experienced with PTSD is associated with significant gene dysregulation, above and beyond that observed in participants with PTSD without significant EDS and controls. Treating EDS in military personnel and veterans with PTSD is important. Support This work was supported by the Center for Neuroscience and Regenerative Medicine (CNRM)

scholarly journals Excessive daytime sleepiness is associated with altered gene expression in military personnel and veterans with posttraumatic stress disorder: an RNA sequencing study

SLEEP ◽  
2020 ◽  
Vol 43 (9) ◽  
Author(s):  
Cassandra L Pattinson ◽  
Vivian A Guedes ◽  
Katie Edwards ◽  
Sara Mithani ◽  
Sijung Yun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Rna Sequencing ◽  
Military Personnel ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Stress Disorder ◽  
Gene Dysregulation ◽  
And Function

Abstract Study Objectives Posttraumatic stress disorder (PTSD) is a common condition for military personnel and veterans. PTSD has been shown to impact gene expression, however, to date no study has examined comorbid conditions which may also impact gene expression, for example, excessive daytime sleepiness (EDS). As such, this study sought to examine gene expression using RNA sequencing across three group comparisons of military personnel and veterans: (1) PTSD with EDS (PTSDwEDS) versus PTSD without EDS (PTSDw/outEDS), (2) Controls (no PTSD or EDS) versus PTSDwEDS, and (3) Controls versus PTSDw/outEDS. Methods We performed experimental RNA-seq using Illumina’s HiSeq 2500 Sequencing System. We also used Ingenuity Pathway Analysis (IPA), a bioinformatics application, to identify gene pathways and networks which may be disrupted. Results There were only two genes that were significantly dysregulated between the Controls and PTSDw/outEDS, therefore IPA analysis was not conducted. However, comparisons revealed that there was significant gene dysregulation between Controls and the PTSDwEDS (251 genes), and the PTSDwEDS versus the PTSDw/outEDS (1,873 genes) groups. Four candidate networks were identified via the IPA software for analysis. Significantly dysregulated genes across the four candidate networks were associated with sleep and circadian function, metabolism, mitochondrial production and function, ubiquitination, and the glutamate system. Conclusions These results suggest that PTSD with concurrent EDS is associated with gene dysregulation. This dysregulation may present additional biological and health consequences for these military personnel and veterans. Further research, to track these gene changes over time and to determine the cause of the EDS reported, is vital.

scholarly journals Cigarette smoke alters the transcriptome of non-involved lung tissue in lung adenocarcinoma patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Giulia Pintarelli ◽  
Sara Noci ◽  
Davide Maspero ◽  
Angela Pettinicchio ◽  
Matteo Dugo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Cigarette Smoke ◽  
Lung Tissue ◽  
Gene Networks ◽  
Lung Parenchyma ◽  
Fold Change ◽  
Differentially Expressed ◽  
Significant Gene ◽  
Never Smokers

Abstract Alterations in the gene expression of organs in contact with the environment may signal exposure to toxins. To identify genes in lung tissue whose expression levels are altered by cigarette smoking, we compared the transcriptomes of lung tissue between 118 ever smokers and 58 never smokers. In all cases, the tissue studied was non-involved lung tissue obtained at lobectomy from patients with lung adenocarcinoma. Of the 17,097 genes analyzed, 357 were differentially expressed between ever smokers and never smokers (FDR < 0.05), including 290 genes that were up-regulated and 67 down-regulated in ever smokers. For 85 genes, the absolute value of the fold change was ≥2. The gene with the smallest FDR was MYO1A (FDR = 6.9 × 10−4) while the gene with the largest difference between groups was FGG (fold change = 31.60). Overall, 100 of the genes identified in this study (38.6%) had previously been found to associate with smoking in at least one of four previously reported datasets of non-involved lung tissue. Seven genes (KMO, CD1A, SPINK5, TREM2, CYBB, DNASE2B, FGG) were differentially expressed between ever and never smokers in all five datasets, with concordant higher expression in ever smokers. Smoking-induced up-regulation of six of these genes was also observed in a transcription dataset from lung tissue of non-cancer patients. Among the three most significant gene networks, two are involved in immunity and inflammation and one in cell death. Overall, this study shows that the lung parenchyma transcriptome of smokers has altered gene expression and that these alterations are reproducible in different series of smokers across countries. Moreover, this study identified a seven-gene panel that reflects lung tissue exposure to cigarette smoke.

scholarly journals The Epworth Sleepiness Scale in Service Members with Sleep Disorders

2019 ◽  
Vol 184 (11-12) ◽  
pp. e701-e707 ◽  
Author(s):  
April Hurlston ◽  
Shannon N Foster ◽  
Jennifer Creamer ◽  
Matthew S Brock ◽  
Panagiotis Matsangas ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Disorders ◽  
Military Personnel ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Epworth Sleepiness Scale ◽  
Clinical Utility ◽  
Obstructive Sleep ◽  
The Military

ABSTRACTIntroductionExcessive daytime sleepiness affects an estimated 20% of the general population. While the prevalence of sleepiness in the military is largely unknown, it is well established that short sleep duration is endemic. The reasons for this include: the demanding nature of their duties, shift work and 24-hour duty periods, deployments and exigencies of military service as well as sleep disorders. The Epworth Sleepiness Scale (ESS) is the most widely used sleep questionnaire and provides a self-assessment of daytime sleepiness. To date the clinical utility of this questionnaire in differentiating sleep disorders in military patients with sleep disorders has never been evaluated.Materials and MethodsThe primary aim of this manuscript was to assess if Epworth Sleepiness Scale (ESS) scores differed between military personnel with insomnia, obstructive sleep apnea (OSA), comorbid insomnia/obstructive sleep apnea (COMISA), and a group with neither insomnia nor obstructive sleep apnea (NISA). This study assessed the clinical utility of the ESS in differentiating sleep disorders amongst a sample (N = 488) of U.S. military personnel with insomnia (n = 92), OSA (n = 142), COMISA (n = 221), and a NISA group (n = 33) which served as the control population.ResultsIn the present sample, 68.4% of service members reported excessive daytime sleepiness (EDS) with an ESS &gt; 10. ESS scores differed between military personnel with COMISA (13.5 ± 4.83) and those with OSA only (11.5 ± 4.08; p &lt; 0.001) and the NISA group (9.46 ± 4.84; p &lt; 0.001). Also, ESS scores differed between patients with insomnia only (13.0 ± 4.84) and the NISA group (p &lt; 0.01).ConclusionsOverall, the ESS had poor ability to differentiate sleep disorders. In military personnel, the ESS appears elevated in the most common sleep disorders, likely due to their insufficient sleep, and does not help to differentiate OSA from insomnia. Further studies are required to validate this questionnaire and determine an appropriate threshold value for abnormal sleepiness in the military population.

scholarly journals RNA-seq: primary cells, cell lines and heat stress

2015 ◽  
Author(s):  
Carl J Schmdt ◽  
Elizabeth M Pritchett ◽  
Liang Sun ◽  
Richard V.N. Davis ◽  
Allen Hubbard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heat Stress ◽  
Sequence Data ◽  
Expression Patterns ◽  
Effective Means ◽  
Cost Effective ◽  
Rna Seq ◽  
Individual Gene ◽  
Examine Gene Expression ◽  
A Cell

Transcriptome analysis by RNA-seq has emerged as a high-throughput, cost-effective means to evaluate the expression pattern of genes in organisms. Unlike other methods, such as microarrays or quantitative PCR, RNA-seq is a target free method that permits analysis of essentially any RNA that can be amplified from a cell or tissue. At its most basic, RNA-seq can determine individual gene expression levels by counting the number of times a particular transcript was found in the sequence data. Transcript levels can be compared across multiple samples to identify differentially expressed genes and infer differences in biological states between the samples. We have used this approach to examine gene expression patterns in chicken and human cells, with particular interest in determining response to heat stress.

scholarly journals Sleep Duration and Excessive Daytime Sleepiness Are Associated with Obesity Independent of Diet and Physical Activity

Nutrients ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1219 ◽  
Author(s):  
Andrea Maugeri ◽  
Jose Medina-Inojosa ◽  
Sarka Kunzova ◽  
Antonella Agodi ◽  
Martina Barchitta ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sleep Duration ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Central Obesity ◽  
Sleep Disturbances ◽  
Short Sleep Duration ◽  
Cross Sectional ◽  
Short Sleep ◽  
Diet And Physical Activity

In the European Union, Czech Republic ranks 3rd and 6th for the incidence of obesity and cardiovascular diseases, respectively. Worldwide, short sleep duration and excessive daytime sleepiness (EDS) characterize obese subjects, which in turn exhibit scarce physical activity and unhealthy diet. We aimed to understand the relationship between irregular sleep patterns, obesity and lifestyle factors, such as diet and physical activity, in a vulnerable Czech population. 1482 members of the Kardiovize cohort, a random sample of the Czech urban population, were included in a cross-sectional study. Exposure variables included self-reported sleep duration and EDS, assessed by the Epworth Sleepiness Scale. Primary outcomes were BMI and waist-to-hip ratio or prevalence of obesity and central obesity. Covariates included physical activity and diet. Associations and interactions between variables were evaluated using logistic regression analyses. After adjustment for covariates, short sleep duration (<7 h) was associated with greater odds of overweight (BMI > 25; OR = 1.42; 95%CI = 1.06–1.90; p = 0.020) and obesity (BMI > 30; OR = 1.40; 95%CI = 1.02–1.94; p = 0.047), while EDS was associated with greater odds of central obesity (OR = 1.72; 95%CI = 1.06–2.79; p = 0.030), independent of diet and physical activity. However, due to the cross-sectional nature of our study, further prospective, large-scale studies are needed to evaluate the etiological link and causality between sleep disturbances and obesity.

scholarly journals Sleep, Sleep Disturbances among Medical Students and their Academic Performance and Health: A Global Issue

2019 ◽  
Vol 3 (4) ◽  
pp. 181
Author(s):  
Mainul Haque ◽  
Zubair Kamal
Keyword(s):  
Academic Performance ◽  
Medical Students ◽  
Sleep Disorders ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Sleep Disturbances ◽  
Health Sciences ◽  
Sleep Phase ◽  
Global Issue ◽  
Sleep Debt

Sleep disorders, medical students, ICSD-3 classification, advanced sleep phase syndrome, excessive daytime sleepiness, burnout, sleep debt, nonrefreshing sleep, and academic performance.International Journal of Human and Health Sciences Vol. 03 No. 04 October’19 Page : 181-185

scholarly journals 1097 Sleep Disturbances, Sleep Burden, And Depressive Symptoms In US Hispanics/Latinos: Results From The HCHS/SOL Sueño Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A417-A418
Author(s):  
C Alcantara ◽  
M Wallace ◽  
D Sotres-Alvarez ◽  
C Vetter ◽  
A J Phillips ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Sleep Duration ◽  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Sleep Disturbances ◽  
The United States ◽  
Sleep Efficiency ◽  
Sensitivity Analyses ◽  
Poor Sleep ◽  
Sleep Timing

Abstract Introduction While sleep disturbances and depression often co-occur, these associations are understudied among Hispanics/Latinos. We examined the associations of sleep disturbances and sleep burden with depressive symptoms among Hispanic/Latino adults in the United States. Methods We used cross-sectional data from the Hispanic Community Health Study/Study of Latinos Sueño Ancillary study (2010-2013). The study enrolled 2072 adults (ages 18-64; 51.5% females) who completed one-week wrist-actigraphy and sleep questionnaires. Sleep burden was operationalized as the total count of sleep disturbances across six domains (duration, efficiency, midpoint, variability, insomnia, sleepiness). Depressive symptoms were assessed using the Center for Epidemiological Studies Depression scale (CESD-10). We used weighted survey linear regressions to evaluate the association of sleep disturbances and sleep burden with elevated depressive symptoms (CESD≥10) in individual models adjusted for age, gender, site, heritage, nativity, education, income, and employment. Sensitivity analyses further adjusted for behavioral health risk factors and apnea-hypopnea index. Results An estimated 28.3% had elevated depressive symptoms, 8.0% had short sleep duration (&lt;6 hours of sleep), 10.9% had long sleep duration (&gt;9 hours), 45.2% exhibited a later sleep midpoint (≥4:00AM), 38.4% had high sleep timing variability (upper third tertile for between day sleep midpoint), 15.3% had insomnia (ISI≥10), 17.3% had excessive daytime sleepiness (ESS ≥10), 21.5% had poor sleep efficiency (&lt;85%), and 77.4% had a total sleep burden count of ≥0. Insomnia (ß=0.49,95%CI:.43,.56), later sleep timing (ß=0.10,95%CI:.04,.16), excessive daytime sleepiness (ß=0.19,95%CI:.11,.27), poor sleep efficiency (ß=0.09,95%CI:.02,.17), high variability (ß=0.07, 95%CI:.01,.12), and sleep burden (ß=0.11,95%CI:.09,.13), were each positively associated with elevated depressive symptoms in individual adjusted models and sensitivity analyses. Extreme sleep durations were not associated with elevated depressive symptoms. Conclusion Multiple inter-related sleep disturbances, particularly those pertaining to sleep quality and timing, are associated with depression and may be targets for future interventions aimed at improving mood among Hispanics/Latinos. Support HL127307, HL098927, HL125748

scholarly journals Leveraging RNA-Seq to Characterize Resistance to Brown Stem Rot and the Rbs3 Locus in Soybean

2018 ◽  
Vol 31 (10) ◽  
pp. 1083-1094 ◽  
Author(s):  
Chantal E. McCabe ◽  
Silvia R. Cianzio ◽  
Jamie A. O’Rourke ◽  
Michelle A. Graham
Keyword(s):  
Gene Expression ◽  
Gene Networks ◽  
Iron Homeostasis ◽  
Complex Disease ◽  
Stem Rot ◽  
Infected Leaf ◽  
Nucleotide Polymorphisms ◽  
Rna Seq ◽  
Brown Stem Rot ◽  
Phialophora Gregata

Brown stem rot, caused by the fungus Phialophora gregata, reduces soybean yield by up to 38%. Although three dominant resistance loci have been identified (Rbs1 to Rbs3), the gene networks responsible for pathogen recognition and defense remain unknown. Further, identification and characterization of resistant and susceptible germplasm remains difficult. We conducted RNA-Seq of infected and mock-infected leaf, stem, and root tissues of a resistant (PI 437970, Rbs3) and susceptible (Corsoy 79) genotype. Combining historical mapping data with genotype expression differences allowed us to identify a cluster of receptor-like proteins that are candidates for the Rbs3 resistance gene. Reads mapping to the Rbs3 locus were used to identify potential novel single-nucleotide polymorphisms within candidate genes that could improve phenotyping and breeding efficiency. Comparing responses to infection revealed little overlap in differential gene expression between genotypes or tissues. Gene networks associated with defense, DNA replication, and iron homeostasis are hallmarks of resistance to P. gregata. This novel research demonstrates the utility of combining contrasting genotypes, gene expression, and classical genetic studies to characterize complex disease resistance loci.

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