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Long COVID presents a complex and multi-systemic disease that poses a significant global public health challenge. Symptoms can vary widely, ranging from asymptomatic to severe, making the condition challenging to diagnose and manage effectively. Furthermore, identifying appropriate phenotypes in genome-wide association studies of COVID-19 remains unresolved. This study aimed to address these challenges by analyzing 220 deep-phenotype genome-wide association data sets (159 diseases, 38 biomarkers and 23 medication usage) from BioBank Japan (BBJ) (n=179,000), UK Biobank and FinnGen (n=628,000) to investigate pleiotropic effects of known COVID-19 risk associated single nucleotide variants. Our findings reveal 32 different phenotypes that share the common genetic risk factors with COVID-19 ( p < 7.6×10 −11 ), including two diseases (myocardial infarction and type 2 diabetes), 26 biomarkers with seven categories (blood cell, metabolic, liver-related, kidney-related, protein, inflammatory and anthropometric), and four medications (antithrombotic agents, HMG CoA reductase inhibitors, thyroid preparations and anilides). As long COVID continues to coexist with humans, our results highlight the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.