Health traits impact the profitability of dairy production and affect animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) to identify genomic regions, and preferably candidate genes associated with Clinical Mastitis (CM), Metritis (MET) and Ketosis (KET) in US Holstein cattle. Data consisted of 28,000 producer-recorded health event records from 14,000 cows in one large commercial dairy farm. Whole-genome single nucleotide polymorphism (SNP) data were available for 7,500 animals. The association analyses were performed using the single-step genomic BLUP approach combining all the available phenotypic, pedigree and genotypic data into threshold models. These models included year-season and parity as fixed effects, and animal and permanent environmental as random effects. Candidate regions were identified based on the amount of genetic variance explained by 2-Mb SNP windows. Several genomic regions were associated with these 3 relevant postpartum diseases. For instance, 4 regions located on BTA5, BTA6, BTA8 and BTA 29 explained together more than 3.0% of the genetic variance for CM. These regions harbor many candidate genes, such as CXCL13, SPTLC1, and FADD that are involved in mammary gland inflammation. Similarly, different regions on BTA9, BTA13, BTA14 and BTA29 explained between 0.75% and 1.0% of the genetic variance for MET. These regions harbor several interesting genes, including GSDMC and CCR6 that are directly involved in inflammation of uterine tissues. Two other potential candidate genes in these regions, RASSF2 and WDR37, induce cell arrest and apoptosis of the uterine tissue. For KET, strong genetic signals were found on BTA8, BTA14 and BTA16. Interestingly, the genomic region on BTA14 explained more than 2.5% of the genetic variance and contains 2 candidate genes, DENND3 and PTK2, that are directly implicated in the metabolism of ketone bodies. Overall, our findings could contribute to a better understanding of the genetic control of these 3 important postpartum diseases. In addition, our findings may provide opportunities for improving these health traits in dairy cattle through marker-assisted selection.