Poster Presentation 46th Lorne Genome Conference 2025

Decoding transcriptome stress signals from sleep deprivation to predict performance in high-pressure work environments using saliva (#223)

Muthukuttige Madusha Nuwanthi Perera 1 2 , Angus Bagley 2 , Danielle Young 1 2 , Luke Schmidt 1 2 , Tony Parker 1 2 , Daniel Broszczak 2 , Jonathan Flintoff 1 2 , Louis de Waal 2 , Benjamin McMaster 3 , Virginie PERLO 1 2 , Sarah Ahamed 4 , Shannon Edmed 5 , Shahnewaz Ali 6 , Tharindu Fernando 6 7 , Clinton Fookes 6 7 , Andrew Hunt 2 , Graham Kerr 1 3 , Ottmar Lipp 4 , Kerrie Mengersen 4 7 , Ajay Pandey 6 , Parth Pandit 1 6 , Cassandra Pattinson 5 , Jonathan Peake 2 , Simon Smith 5 , Ian Stewart 3 , Karen Sullivan 4 , Chamindie Punyadeera 8
  1. Centre for Biomedical Technologies, Brisbane, QUEENSLAND
  2. School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia
  3. School of Exercise & Nutrition Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia
  4. School of Psychology and Counselling, Queensland University of Technology, Kelvin Grove, QLD, Australia
  5. Institute for Social Science Research, University of Queensland, Indooroopilly, QLD, Australia
  6. School of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD, Australia
  7. Centre for Data Science, Queensland University of Technology, Brisbane, QLD, Australia
  8. Institute for Biomedicine and Glycomics, Griffith University, Nathan, QLD, Australia

Background: High-pressure occupations, such as those in the military, healthcare, and emergency response, require swift, accurate decision-making under conditions of sleep deprivation. Sleep deprivation triggers complex molecular responses that influence human behaviour and cognitive functions. Understanding these responses at a molecular level is essential for effectively predicting individual performance outcomes.
Purpose: This study explores the potential of two types of regulatory non-coding RNAs (ncRNAs) in saliva, which are crucial for understanding stress responses in real-time. MicroRNAs (miRNAs), stable and measuring 22-23 nucleotides in length, and long-non-coding RNAs (lncRNAs), which exceed 200 nucleotides, represent a largely underexplored domain that regulates gene expression post-transcriptionally. These ncRNAs are evaluated as non-invasive biomarkers for predicting performance under sleep stress.
Approach: A controlled human trial with 24 participants aged 18-45 was conducted. Participants underwent 36 hours of continuous sleep deprivation in a laboratory setting. Saliva samples were collected at pre-stress, during-stress, and post-stress phases for RNA isolation, followed by RNA sequencing and real-time PCR (qRT-PCR).
Results: Out of 1,997 miRNAs identified, 24 showed significant expression changes following sleep deprivation, with 14 upregulated and 10 downregulated. Of the 3,323 lincRNAs identified from RNA sequencing, a selected few were subjected to qRT-PCR analysis. These data are being analysed alongside information on perceived stress levels and cognitive performance metrics. Specific stress responses in both miRNAs and lncRNAs highlight their potential as biomarkers for evaluating the impact of sleep deprivation stress in high-pressure work environments.
Conclusion: The differential expression of miRNAs underscores their potential as biomarkers for evaluating stress in high-pressure environments. Future work will correlate stress levels and performance with miRNA and lncRNA profiles to clarify their regulatory roles in sleep deprivation. Key RNA targets will be validated, and their gene targets and pathways further explored.