Toward precision metabolic medicine: Multi-omics deconstruction and translational potential of herbal formulations in glycolipid metabolic disorders

Abstract

Glycolipid metabolic disorders represent a growing global health burden, characterized by interconnected dysregulations in glucose and lipid metabolism. Traditional Chinese medicine (TCM), broadly accepted as a holistic and multi-target approach, provides promising therapeutic directions for such complex conditions. Recently, Tian et al published a study in World Journal of Diabetes integrated transcriptomic and metabolomic analyses to investigate the mechanisms underlying the ameliorative effects of Jiangtang Tiaozhi formula (JTTZF) on high-fat diet-induced glycolipid dysregulation in mice. The findings revealed that JTTZF modulated key genes involved in lipid synthesis, insulin signaling, and inflammation, and it also restored metabolic pathways for energy production and steroid hormone biosynthesis. This editorial highlights the crucial role of multi-omics methodologies in elucidating the systemic effects of herbal formulations and discusses how such integrative approaches can link TCM with modern precision medicine in the future.

Key Words: Glycolipid metabolism; Traditional Chinese medicine; Herbal formulations; Multi-omics; Precision medicine

Core Tip: Multi-omics technologies are transforming the research paradigm of traditional Chinese medicine (TCM), transitioning it from an experience-based practice to an evidence-based science. The integrated transcriptomic and metabolomic study of the Jiangtang Tiaozhi Formula exemplifies how such approaches can systematically elucidate the “multi-component, multi-target” mechanisms of herbal formulations by revealing the regulation of gene networks and metabolic pathways in complex diseases, such as glycolipid metabolic disorder. Thus, the synergistic integration of traditional knowledge with modern systems biology provides a clear direction for the development of precise, mechanism-driven TCM therapies, promoting their incorporation into contemporary precision medicine.

This editorial refers to “Integrated hepatic transcriptome and metabolome reveal the mechanisms of Jiangtang Tiaozhi formula on improving glycolipid metabolic disorder” by Tian et al, 2026; https://doi.org/10.4239/wjd.v17.i2.111453.

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INTRODUCTION

The rising global incidence of glycolipid metabolic disorders, including type 2 diabetes, obesity, and non-alcoholic fatty liver disease, has highlighted the limitations of conventional single-target pharmacotherapies[1]. These conditions stem from dysregulated interactions across genetic, metabolic, and environmental axes, calling for therapeutic strategies capable of system-wide modulation[2]. Traditional Chinese medicine (TCM) has long embodied such a holistic philosophy, employing multi-herb formulations to simultaneously engage multiple biological links, pathways, and targets[3]. This approach constitutes a therapeutic philosophy that is highly consistent with the complex pathogenesis of metabolic diseases, such as glycolipid metabolic disorders[4,5]. However, the scientific validation and mechanistic elucidation of TCM have historically lagged, as hindered by the complexity of its components and the lack of tools to map its polypharmacological effects[6]. Therefore, developing innovative methodologies that can systematically capture and interpret the multi-level effects of TCM has become a critical imperative.

MULTI-OMICS ACTS AS A BRIDGE BETWEEN TRADITION AND MODERNITY

The advent of high-throughput omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and spatial omics, has provided revolutionary tools to address the inherent complexity of TCM[6,7]. These approaches enable comprehensive profiling of molecular changes at different biological levels (genes, transcripts, proteins, metabolites) in complex diseases, including glycolipid metabolic disorders, thereby aligning perfectly with the holistic feature of TCM interventions[6,8]. Recent reviews have systematically outlined the workflows and applications of mass-spectrometry-based proteomics, metabolomics, and mass-spectrometry imaging (MSI) in TCM research, covering composition analysis, quality evaluation, target identification, and mechanism exploration[6,9,10]. These methodologies enable researchers to move beyond single-pathway studies and capture the network-level perturbations induced by herbal formulations (Figure 1).

Figure 1  Application of multi-omics technology and data integration analysis in traditional Chinese medicine.

In this context, Tian et al[11] recently published a study in World Journal of Diabetes, serves as an exemplary application of integrated omics. By combining hepatic transcriptome and metabolome profiling, they systematically revealed how Jiangtang Tiaozhi formula (JTTZF) reversed high-fat diet-induced glycolipid dysregulation[11]. The mentioned study identified specific regulation of key genes related to lipid metabolism (e.g., Fabp3/4 and Cidea), insulin signaling, and inflammation (e.g., Gpnmb), and concurrently restored metabolic pathways involved in energy production and steroid hormone biosynthesis[11]. This dual-layer “transcript-metabolite” integration provides a more causal understanding of how a multi-component formula coordinately modulates biological networks, providing a solid scientific foundation for the therapeutic effects of TCM.

FROM OMICS DATA TO REGULATORY NETWORKS: THE INTEGRATING ROLE OF NETWORK PHARMACOLOGY

The generation of large-scale omics data necessitates advanced bioinformatic tools to extract biologically meaningful insights. Network pharmacology (Figure 1) has emerged as a key framework for integrating multi-omics results and constructing holistic “herb-compound-target-pathway-disease” networks[12-14]. Tian et al[11] identified several key genes and metabolites through differential expression and enrichment analyses; further network-based integration could position these molecules in larger regulatory cascades using TCM systems pharmacology, Herbal Medicine Prescription Database, and TCM-suite databases[11,15]. For instance, JTTZF-mediated restoration of lipid-related genes (Fabp3/4 and Cidea) and inflammation-related markers (Gpnmb) could be mapped onto PPAR signaling, insulin resistance, and adipocytokine pathways, representing the core pathways dysregulated in glycolipid metabolic disorders[16]. This system not only confirms the multi-target nature of TCM, but also helps identify candidate biomarkers for clinical monitoring and provides synergistic targets for combination therapy[17]. As emphasized in current reviews, network pharmacology is transforming TCM from an experience-based tradition into an evidence-informed system, providing a reproducible platform for mechanistic hypothesis generation and testing[6].

TOWARD PRECISION AND REPRODUCIBILITY: AN OMICS-ENABLED PIPELINE FOR TCM TRANSLATION

For TCM research to yield robust and translatable evidence, it is imperative to address two critical challenges: The stringent quality control of herbal materials and the standardization of experimental protocols[18]. Omics technologies offer powerful solutions for both[19,20]. DNA barcoding combined with metabolomic fingerprinting can authenticate botanical ingredients and ensure chemical consistency, thereby promoting the efficacy and safety of herbal products[21-23]. Moreover, standardized procedures for sample preparation, experimental design, and data analysis, including those detailed in proteomic and metabolomic workflows, are essential to ensure reproducibility and comparability across studies[6,24]. For complex herbal formulations, such as JTTZF, future studies will implement similar quality-by-design approaches using multi-omics profiling to assess batch-to-batch variability and to elucidate the contribution of specific herbs or compounds to the overall effect[6,9]. This robust approach is vital to enhance the reliability of TCM research and to promote its acceptance in international regulatory standards.

However, several significant challenges remain. The high cost and technical complexity of multi-omics platforms limit their widespread adoption. Integrating heterogeneous data from different omics layers to develop a coherent mechanistic narrative is non-trivial. Furthermore, factors intrinsic to TCM, such as herbal compatibility, processing method, and batch-to-batch variability, add layers of complexity that must be explicitly controlled and studied in omics experimental designs. Addressing these limitations requires concerted efforts in developing cost-effective workflows, robust data integration algorithms, and TCM-specific reporting standards.

FUTURE DIRECTIONS

The study conducted by Tian et al[11], while being robust, serves as a rigorous exemplar of contemporary multi-omics applications, while also highlighting the inherent dynamism of a field undergoing rapid transformation. As such, several important directions are essential to define the next stage of TCM research and clinical translation.

Deepening technological integration

Emerging technologies provide deeper mechanistic insights at unprecedented resolution. Spatial omics technologies, such as spatial transcriptomics and metabolomics, may map the precise hepatic zonation of JTTZF’s effects, distinguishing its action on periportal vs pericentral hepatocytes[25,26]. Single-cell sequencing may further dissect formula-induced changes in specific liver cell types (e.g., Kupffer cells in inflammation, hepatic stellate cells in fibrosis), moving decisively beyond bulk-tissue averages to resolve cell-type-specific contributions to glycolipid metabolic disorders[27-29]. Advanced MSI can directly visualize the spatial distribution of both herbal metabolites and endogenous lipids in tissues, providing crucial correlative insights at cellular or subcellular resolution[30]. Furthermore, integrating gut microbiome, metagenomics, and metaproteomics with hepatic omics data is essential, as several TCM compounds are metabolized by intestinal bacteria into active forms[31,32]. This multi-omics integration may be particularly important to deeply study compounds, such as JTTZF, and to provide a comprehensive understanding of TCM mechanisms through the “gut-liver axis”.

Advancing data integration and artificial intelligence

The future of TCM research will be defined by sophisticated data integration and synthesis[33,34]. The primary challenge is shifting from data generation to intelligent integration and interpretation[10,17]. Future analytical tools must progress beyond parallel pathway analysis toward causal network modeling, utilizing artificial intelligence-and machine learning-based methods to infer directional relationships among altered genes, metabolites, and phenotypic outcomes in metabolic diseases[10,35,36]. Platforms, such as the newly developed TCM-Suite (http://tcm-suite.aimicrobiome.cn/) that holistically links formula composition to network pharmacology, represent a positive step in this direction[37,38]. Next-generation databases need to be dynamic, incorporating real-world clinical and omics data to continuously refine TCM-disease interaction networks, including TCMSSD (http://tcmssd.ratcm.cn)[39,40]. Consequently, establishing standardized, open-access repositories for TCM multi-omics data, similar to those maintained by major biomedical consortia, is imperative for ensuring reproducibility, enabling meta-analysis, and advancing collective knowledge discovery[41]. International collaboration and data-sharing initiatives will be essential to overcome the current fragmentation in the field and to develop robust, generalizable models of TCM action.

Strengthening the clinical translation pathway

A deliberate and evidence-driven translational path is essential to convert research insights into clinical practice[32]. The next step logically involves dose-response multi-omics studies on preclinical models to identify the optimal therapeutic window for TCM, including JTTZF[6]. Subsequently, well-designed clinical trials in target populations (e.g., patients with prediabetes or early-stage type 2 diabetes) must incorporate pre- and post-treatment multi-omics profiling, involving serum metabolomics and peripheral blood mononuclear cell transcriptomics, to robustly validate preclinical findings in humans[12,16]. Recent studies have implemented this “omics-guided clinical trial” paradigm, applying multi-omics biomarkers to stratify patients and to monitor response to TCM interventions[42,43]. This “omics-guided clinical trial” paradigm was designed to identify responder biomarkers, elucidate mechanisms of action in patient populations, and ultimately solidify the scientific rationale for personalized, precision TCM interventions, thereby promoting integration into mainstream healthcare frameworks[8,9]. However, practical barriers, such as the need for multicenter standardization of omics protocols, regulatory pathways for complex TCM products, and the integration of omics-guided personalization into routine clinical workflows must be proactively addressed[36,44].

Addressing ethical, regulatory, and standardization gaps

The integration of TCM into precision medicine also raises important ethical and regulatory questions that must be considered. The collection and use of multi-omics data from TCM patients require robust ethical frameworks to ensure privacy, informed consent, and equitable data governance[45]. Furthermore, there is a pressing need for internationally harmonized regulatory standards that can evaluate the safety, efficacy, and quality of precision TCM therapies, mainly involving complex mixtures and personalized regimens[46]. Developing such standards will be essential for gaining broader acceptance and ensuring patient safety in the era of omics-driven TCM.

CONCLUSION

In conclusion, the integration of multi-omics technologies marks a transformative step in the TCM research. By capturing system-wide molecular and metabolic changes, these approaches systematically reveal how herbal formulations rebalance dysregulated networks through multi-component, multi-target coordination. This not only provides a modern scientific interpretation of TCM efficacy, but also promotes its integration with contemporary biomedicine. Looking ahead, the sustained convergence of state-of-the-art omics platforms, comprehensive bioinformatic integration, and stringent clinical validation, alongside concerted efforts to resolve technical, translational, and regulatory challenges, will advance TCM into a new era of precision medicine. By adhering to a research strategy that concentrates on multi-omics as the technological core, network pharmacology as the analytical framework, and standardization and clinical verification as the translation pathway, traditional herbal medicine can be transformed into a precise, evidence-based therapeutic option for complex metabolic and other diseases.