SUMMARY The epidemiology of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) indicates a significant relationship in the population for both close (first or second cousins) and distant (third cousins) relatives. Our objective is to identify DNA differences that distinguish people with ME/CFS from healthy controls. We will use a well-established, well-powered, genome-wide association study (GWAS) design that has a demonstrated ability to identify genes, as well as novel molecular and cellular pathways, contributing to susceptibility for other complex diseases. GWAS have shown that about 10-times more cases will be needed to be well-powered. We will obtain saliva DNA from a minimum of 5,000 individuals meeting Institute of Medicine/National Academy of Medicine (IOM/NAM) and/or Canadian Consensus Criteria (CCC) for ME/CFS. ME/CFS subjects will be recruited via a questionnaire created by the Solve ME/CFS Initiative (Solve ME) and will utilize a smartphone application designed by Care Evolution. Genotyping data from these US-based ME/CFS cases will be compared to data from 400,000 healthy controls genotyped by the Kaiser Permanente Research Bank (KPRB) using the Axiom Precision Medicine Diversity v2 Plus Array. Once data from US-based cases is obtained (Solve ME and KPRB), it will be used in a US case-control GWAS, before being trans-ancestry meta-analyzed with UK cohort data from the DecodeME Study and the UK Biobank (UKB). The two cohorts are complementary by providing opportunities for replicating associated loci and for using diverse genetic ancestries to enhance predictive power. We anticipate that genetic associations will provide the evidence base necessary to improve the perception of ME/CFS among health care professionals and the general public and yield insights into risk and pathogenesis that have the potential to result in interventions.