Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disorder primarily characterized by extreme fatigue that lasts for at least six months. Symptoms worsen with physical or mental activity, but do not fully improve with adequate rest. 

It is estimated that between 5 – 9 million Americans suffer from ME/CFS and estimates vary from 17 – 24 million casesworldwide. Research has shown that ME/CFS is about 2 – 4 times more likely to occur in women than men.

Long COVID is defined as a chronic condition that occurs after SARS-CoV-2 infection and is present for at least 3 months. It includes a wide range of symptoms or conditions that may improve, worsen, or be ongoing over different lengths of time. These symptoms and conditions can range from mild to severe, may require comprehensive care, and can even result in a disability.

While rates of new cases of Long COVID have decreased since the beginning of the COVID-19 pandemic, it remains a serious public health concern as millions of U.S. adults and children continue to be affected.

This is a low-risk study with no intervention or treatment. Sample collection, using a cheek swab, involves minimal to no physical risk and no research related injuries are expected. The most significant risk to a participant is for their personal or genetic information to be accidentally released and for them or their family to suffer the consequences of that release. We limit exposure by ensuring data is de-identified, coded with an ID that has no direct link to the participant, and all data is securely stored and accessed by trained staff only.

Our primary objective is to develop a research-grade test that identifies a participant’s relative lifetime risk of developing ME/CFS and/or Long COVID. Once validated, the information provided by this test will one day be used by clinicians to support ME/CFS and Long COVID diagnoses and identify personalized treatments that are matched to a patient’s disease genetics.

Overall, we conclude that 500-550 cases will be needed to obtain sufficient statistical power to detect significance for clinically meaningful data. With 1000 cases, we would have strong power to detect moderate increases in disease risk. Once these numbers are met, the study will be considered full and enrollment will end. Download the app by using the buttons above to get alerts to future studies and clinical trials.