Abstract Background and Aims As a major public health problem, chronic kidney disease (CKD) has substantial comorbidities and disease burden. It is necessary to discover new therapeutic targets considering its irreversibly. Traditional Chinese medicine (TCM) has become indispensable for the integrated treatment of CKD. The current study aims to explore potential new TCM targets in high-throughput experiment- and reference-guided database (HERB) that are related to renal phenotypes utilizing multi-omics. Method We conducted comprehensive Mendelian Randomization and Bayesian colocalization on more than 2,000 HERB target integrating genomes and transcriptomes, using summary statistics of genome-wide association study and cis gene expression quantitative trait loci. The results were validated through differential gene expression in public database, previous literature reports and clinical kidney biopsy specimens. Results In all, we discovered 34 targets associated with renal phenotypes among the 2,421 HERB TCM targets in the data mining part. Among them, most of the targets can be validated by differential gene expression analysis in GEO and Nephroseq, and have been reported by basic research, thus confirming the reliability of this method. In addition, PRKCI, KNG1, PKN3, GGT7, GBA, APEH and GSTA2 are expected to be potential new therapeutic targets for CKD. Immunohistochemical staining using clinical kidney biopsy specimens of PKN3 and KNG1, two targets with the highest evidence level, further confirm the results. Conclusion Integration of multi-omics can extensively and efficiently screen potential drug targets related to CKD. The new targets discovered in the current study, especially PKN3 and KNG1, need to be further validated in basic research.