Inflammation is a feature of coronary heart disease (CHD), but the role of proinflammatory microbial infection in CHD remains understudied. CHD was defined in the MESA (Multi-Ethnic Study of Atherosclerosis) as myocardial infarction (251 participants), resuscitated arrest (2 participants), and CHD death (80 participants). We analyzed sequencing reads from 4421 MESA participants in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program using the PathSeq workflow of the Genome Analysis Tool Kit and a 65-gigabase microbial reference. Paired reads aligning to 840 microbes were detected in >1% of participants. The association of the presence of microbe reads with incident CHD (follow-up, ~18 years) was examined. First, important variables were ascertained using a single regularized Cox proportional hazard model, examining change of risk as a function of presence of microbe with age, sex, education level, Life's Simple 7, and inflammation. For variables of importance, the hazard ratio (HR) was estimated in separate (unregularized) Cox proportional hazard models including the same covariates (significance threshold Bonferroni corrected P<6×10-5, 0.05/840). Reads from 2 microbes were significantly associated with CHD: Gemella morbillorum (HR, 3.14 [95% CI, 1.92-5.12]; P=4.86×10-6) and Pseudomonas species NFACC19-2 (HR, 3.22 [95% CI, 2.03-5.41]; P=1.58×10-6). Metagenomics of whole-genome sequence reads opens a possible frontier for detection of pathogens for chronic diseases. The association of G morbillorum and Pseudomonas species reads with CHD raises the possibilities that microbes may drive atherosclerotic inflammation and that treatments for specific pathogens may provide clinical utility for CHD reduction.