Australian scientists have made a significant breakthrough in understanding the genetic drivers of long COVID, a condition that has left millions suffering from persistent symptoms long after their initial infection. This discovery, achieved through the analysis of extensive biological datasets, could lead to the development of targeted treatments and personalized diagnostic tools.
The research team, led by experts from the University of South Australia, utilized genetic and molecular data from over 100 international studies to identify 32 causal genes associated with long COVID. Notably, 13 of these genes had not been previously linked to the condition. Their findings have been published in the journals PLOS Computational Biology and Critical Reviews in Clinical Laboratory Sciences.
Understanding Long COVID’s Genetic Underpinnings
Since 2020, an estimated 400 million people worldwide have experienced long COVID, which imposes an annual economic burden of $1 trillion globally. Characterized by symptoms such as prolonged fatigue, breathlessness, cardiovascular issues, and cognitive impairment, long COVID has proven difficult to diagnose and treat effectively. Symptoms can persist for weeks, months, or even years after the initial infection.
Lead author Sindy Pinero, a PhD candidate in Bioinformatics at UniSA, highlights the role of large-scale datasets and advanced computational methods in identifying the causes and risk factors of long COVID. These methods, which employ bioinformatics and artificial intelligence, analyze vast biological datasets known as “omics” data, including genomics, proteomics, metabolomics, transcriptomics, and epigenomics.
“These findings mark a major step towards a more precise way of diagnosing and treating the condition,” Pinero explains. “Long COVID is incredibly complex. It affects multiple organs, shows highly variable symptoms, and has no single final diagnostic marker.”
Key Genetic Discoveries and Implications
The study identifies numerous genetic, epigenetic, and protein-level biomarkers linked to immune dysfunction, persistent inflammation, and mitochondrial and metabolic abnormalities. Among the significant discoveries is a genetic variant in the FOX P4 gene, which is associated with immune regulation and lung function, potentially increasing susceptibility to long COVID.
Researchers also identified 71 molecular switches that can activate or deactivate genes, persisting a year after infection, and over 1500 altered gene expression profiles related to immune and neurological disruption. By integrating these findings with machine learning, the study demonstrates how different layers of biological data can predict patients’ risk of long-term complications and symptom evolution.
“This computational framework not only improves our understanding of long COVID but could also accelerate the search for treatments for other post-viral symptoms such as chronic fatigue and fibromyalgia,” according to Assoc Prof Thuc Le.
The Role of Computational Science
Associate Professor Thuc Le emphasizes the importance of computational science in solving the long COVID puzzle. Traditional biomedical research struggles to keep pace with the complexity of this condition. By applying artificial intelligence to global datasets, researchers can identify causal relationships that small clinical trials might miss, such as gene interactions with immune pathways driving persistent inflammation.
The review underscores the urgent need for larger, more diverse international datasets and longitudinal studies that track patients over several years post-infection. Many existing studies are small and inconsistent, complicating the identification of reliable biomarkers. Global collaboration and data sharing are crucial for producing results that can be translated into clinical tools.
“This research is not only about long COVID. It represents a blueprint for how global science can use big data, AI, and molecular biology to respond to future pandemics and complex chronic diseases,” Le states.
As the world continues to grapple with the long-term impacts of COVID-19, these findings offer hope for more effective diagnostic and treatment strategies, not only for long COVID but also for other chronic conditions that may arise from viral infections.
