One of the most prevalent and costly obstacles facing dairy producers is the occurrence of mastitis. Mastitis is a worldwide endemic disease causing both short and long-term cow health and economic repercussions with production losses in terms of reduced milk yield, clinical treatment, culling of animals, and discarded milk. The objective of this study was to conduct a genome-wide association study (GWAS) for mastitis and explore the use of milk microbiome profiles to identify novel mastitis QTL using the Illumina Bovine High-Density (777K SNPs) Beadchip on a cohort of US Holstein dairy cows. To this end, 2 GWAS were run comparing Holstein cows; the first compared cows phenotypically characterized as having clinical mastitis (CM) or healthy based on their somatic cell score (SCS) and the second GWAS used a linear score based on their mammary microbiome profile. The mammary microbiome profile was generated sequencing 16S rRNA of the milk microbiota, directly correlated with mastitis incidence, to generate a cow specific profile. Four genomic regions demonstrating significant association to CM incidence were identified on BTA 5, 16, 26, and 29 using SCS and 5 regions on BTA 5, 9, 16, 26, and 29 were significantly associated with microbiome profile GWAS (corrected P-value < 0.05). Of particular interest to this study was to identify regions of similar association and those different between the 2 trait GWAS, CM as opposed to microbiome profile. Regions on BTA 5, 9, and 26 validated previous mastitis QTL findings. Both GWAS approaches in this study identified novel QTL on BTA 16 and 29 potentially being the product of a more generalized immune response to infection. In contrast, marker associations on BTA 1, 2, and 11 show more variation between the 2 GWAS and may reflect a genetic predisposition to specific microbiota. In all, the study validated previously discovered QTL and identified novel QTL with both similarities and variation in the comparison of the 2 trait GWA studies. Further studies are required to validate specific candidate genes and their influence on mastitis and the potential identification of diagnostic markers for the selection of mastitis resistant dairy cows.