Task force makes recommendations for studying biological systems as part of Long COVID research

Although researchers have learned much about Long COVID since it was first recognized as a chronic condition, many gaps in knowledge remain about why Long COVID develops, why some people develop Long COVID and others don’t, and why the condition affects people differently. The RECOVER Initiative was started to help address these gaps using knowledge gained from a wide range of research fields. It is a comprehensive, patient-centered research program whose mission is to support better understanding, diagnosis, treatment, and prevention of Long COVID.

While research continues to advance scientific knowledge about Long COVID, the impacts of the condition on many biological systems, the ways those systems interact, and the biological markers of Long COVID’s impacts remain less understood. 

To address this gap in scientific knowledge, RECOVER clinicians, pathologists, and other scientists formed a task force focused on “omics.” The term omics refers to scientific fields that study specific aspects of biological systems. Studying these biological systems can help researchers understand how Long COVID impacts the complex mechanisms that influence how our bodies work.

In a paper published in the journal Frontiers in Systems Biology, RECOVER’s Omics Task Force described their work to develop recommendations for a multi-omics approach. A multi-omics approach combines knowledge from multiple omics fields through cutting-edge systems biology technologies. This approach can bring together data from across three different RECOVER studies to help better understand, treat, and predict a condition that can affect every body system. The task force also made recommendations for applying a multi-omics approach to future RECOVER research.

What are omics?

The term omics refers to scientific fields that study a wide range of biological systems to understand the complex mechanisms that influence how our bodies work.

RECOVER scientists can use multi-omics, which integrates layers of information from multiple omics fields, to better understand the biological processes associated with Long COVID.

Genomics studies the structure and function of DNA (deoxyribonucleic acid). Researchers can use genomics to understand how genetic differences may affect who develops Long COVID and why.

Epigenomics studies chemical changes to DNA, often in response to the environment or life experiences. Researchers are interested in studying how these chemical changes may be linked to the severity of Long COVID symptoms, as seen with some viral illnesses.

Transcriptomics studies an enzyme called ribonucleic acid, or RNA, that helps turn DNA instructions into proteins that help the body function. Changes in RNA may help researchers discover unique Long COVID biomarkers to support diagnosis and treatment.

Proteomics studies proteins, which are responsible for many important functions like creating antibodies to fight infections, digesting food, and building tissues. Proteins may be useful for diagnosing, preventing, and treating Long COVID.

Metabolomics studies metabolism, which is the body’s chemical process of converting food and drink into energy. Studying metabolites, chemicals that are part of the metabolism process, can help researchers understand how body processes might change with Long COVID.

Microbiomics studies the microbiome, or the collection of microorganisms in our gut (or gastrointestinal tract). Changes in the microbiome may play an important part in our overall health.

As described in the paper, RECOVER researchers created a group called the Omics Task Force to help guide RECOVER research as it relates to systems biology and the various omics specialties. This multidisciplinary group, which included doctors, lab scientists, and data experts, met twice per month to evaluate evidence, make recommendations, and inform study design. The Omics Task Force developed recommendations for how to study RECOVER biosamples (e.g., blood, saliva, and urine) and provided input about how multi-omics could be used to improve understanding of Long COVID.

RECOVER’s Omics Task Force made the following recommendations:

Researchers should look at information from more than one omics technique to better understand how Long COVID affects people differently. Long COVID can cause a wide range of symptoms that vary from person to person and may affect multiple organs or body systems. Because Long COVID has a wide range of severity and symptom profiles across populations, and there is no single diagnostic test for Long COVID, health care providers may find it difficult to diagnose Long COVID and help patients manage the symptoms associated with the condition. A multi-omics approach can allow researchers to look at how the different layers of omics information work together, providing a clearer understanding of cause-and-effect in complex biological systems. This could provide insights into the causes of symptoms, why symptoms vary, and which factors may influence those differences. Combining multi-omics data with the deep clinical and demographic data from RECOVER could lead to more personalized care and better outcomes.

Biosamples should be collected and analyzed from all adults, pregnant people, and children who have joined the RECOVER study—more than 34,000 people total. Instead of small groups being analyzed separately, biosamples from the full participant group should be analyzed all together. Including more data in a large-scale approach might help RECOVER researchers find patterns linked to different presentations of Long COVID.

All biosamples should be tested using the same methods in central laboratories. Standardizing processes and using centralized laboratories to run the same tests on all biosamples would help reduce variability in findings and strengthen results. This approach could also reduce technical differences across laboratories that can affect results. Standardized testing would make it easier to spot real biological changes linked to Long COVID—rather than differences caused by how or where the sample was tested. In other words, it would improve consistency in data, strengthen findings, and make them more reliable.

Biosamples should be collected and analyzed from participants at multiple points in time. Studying samples from the same people collected at least two different time points could give researchers a clearer view of how Long COVID develops and changes in the body. Using a multi-omics approach, researchers could analyze and compare many types of biomarkers (or traits that can be observed and measured in lab tests) to identify those that are unique to Long COVID. Over time, these findings may contribute to the development of more accurate tests that can help diagnose and treat Long COVID.

Leveraging multi-omics in RECOVER

The RECOVER Initiative includes people from all walks of life who are affected by the condition. RECOVER studies to date have collected more than 48 million datapoints and 873,000 biosamples, representing more than 34,000 participants. The initiative’s large scope and available datasets provide an important opportunity for researchers to understand how Long COVID works. 

The Omics Task Force made recommendations for how RECOVER researchers can leverage this opportunity while harnessing the power of multi-omics. Combining multi-omics data with the deep clinical and demographic data from RECOVER allows researchers to create the most complete picture of how Long COVID affects people. This approach could lead to new, meaningful findings on the biological processes and different sub-types of the condition that supports RECOVER in its mission to better understand, diagnose, treat, and prevent Long COVID. 

Read the full publication in Frontiers in Systems Biology