Science：“证”- 疾病诊疗的系统生物学方法

TraditionalChinese medicine (TCM) is an ancient medical practice system which emphasizesregulating the integrity of the human body and its interrelationship withnatural environments. As a key concept in TCM, Zheng (meaning syndrome orpattern)is the overall physiological and/or pathological pattern of the humanbody in response to a given internal and external condition, which usually isan abstraction of internal disharmony defined by a comprehensive analysis ofthe clinical symptoms and signs gathered by a practitioner using inspection,auscultation, olfaction, interrogation, and palpation of the pulses (1).Correctly identifying the Zheng is fundamental for the diagnosis and treatmentof diseases.to systems level is important for advancing the identificationandtreatment of these syndromes, and for providing more objective and quantitativediagnostic criteria.

In Western medicine, a disease is a particular abnormal and pathological conditionthat affects part or all of the human body and is often construed as a medicalcondition associated with specific symptoms. By contrast, Zheng puts forth avery different definition of a disease and encompasses all of the symptoms apatient presents.

Becauseof the highly interconnected nature of the human interactome, it is difficultto study different diseases at the molecular level completely independent ofone another (3), and this issue also applies to Zhengs. Moreover, Zhengs aredynamic with changing boundaries, overlapping symptoms,Moreover, Zheng has beenhistorically applied as the key pathological principle guiding the prescriptionof herbal formulas (Figure 1).

A lackof research on Zheng has left us with little understanding of its underlyingbiology or the relationships between different Zhengs, diseases, and drugs.Moreover, there have been attempts to integrate Zheng differentiation withmodern biomedical diagnostic methods, though these efforts have not achievedthe desired results (2). Many well-known herbal recipes, such as Liu Wei DiHuang Wan and Jin Kui Shen Qi Wan, have long been used for the clinicaltreatment of Zheng disorders; however, Zheng-guided treatments are still scarcedue to the lack of evidence-based interpretations of syndromes and treatmentefficacies. Thus, investigating the biological basis of Zhengs from a molecularand a multiscale nature, which makes them difficult to understand at abiological and mechanistic level. Thus, we propose that a comprehensive Zhengmap be constructed that links together all the Zhengs based on their molecularand cellular relationships. Further, we suggest creating the “Zhengome” as a new 'omics field, in which a networkis the basic research unit used to investigate the hierarchy present in thehuman body,from the molecular to the systems level. Acomprehensiveunderstanding of the Zhengome requires us to bring togethermultiple sources of evidence, from shared genes to proteinprotein interactions,shared environmental factors, common treatments, and phenotypic and clinicalmanifestations, in order to capture the relationships between the differentZhengs.

Zheng uses the Yin-Yang, exterior-interior, cold-heat, and deficiency-excessdefinitions to describe patients’ conditions, which are then managed byZheng-specific recipes (Figure 1). Modern 'omics techniques combined withbioinformatics and bionetwork models through a systems biology approach havebeen applied to investigate the differences between Zhengs and to identifynovel biomarkers. For instance, rheumatoid arthritis (RA) patients differentiatedon the basis of “hot” and “cold” Zhengs have been shown to be associatedwith different underlying genomic and metabolomic profiles, with the RA hotgroup showing more apoptotic activity than the cold group (4). Additionally, Liet al. used a network-based computational model to understand Zheng in thecontext of the neuro-endocrine-immune network and found that cold and hotZhengs were closely related to a metabolism-immune imbalance (5). Wang andcolleagues investigated the urine metabolome of patients with jaundice syndromeand its two subtypes of Yang Huang (acute) and Yin Huang (chronic), andidentified several biomarker metabolites (6). However, most of the currentstudies have relied on only one or two approaches for molecular profiling and havelacked an efficient method to integrate data obtained at different 'omiclevels. These studies also did not look at combining the analysis of moleculardata with clinical variables, possibly missing an opportunity to generate moreconvincing conclusions. Considering the limitations of past studies, futureefforts should integrate an analysis for all levels of 'omics (e.g., genomics,transcriptomics, epigenomics, and proteomics) data from a large number ofpatient samples for different Zhengs and include an investigation of theprognostic and therapeutic utilities of the data as a whole. Moreover,combining these molecular data with patients’ clinical information could provideevidence-based theoretical interpretations for Zhengs and enable an assessmentof Zheng-based therapeutic approaches.

Zhengs may change dynamically during disease progression. Differentiating the specificZheng involved in each stage of a disease could provide valuable guidance forprescribing a dynamic therapeutic recipe. Using dynamic network modeling, adisease process can be conceptualized as spatio-temporal changes in networkstructures. The changes associated with a Zheng under dynamic therapy can beused to identify the key factors in the dynamic biological networks. Appropriatenetwork perturbation models and subsequent robustness and topology analysiscould help unveil potential disease-related genes or therapeutic targetsinvolved in a disease’s progression or evolution (7). Therelationships between the different aspects of a disease (e.g., main symptomsversus complications) in a specific Zheng as well as the psychological, social,and even environmental factors should be taken into account during the modelingand simulation process in order to uncover the dynamic nature of complexdiseases.Combining a Zhengome approach with dynamic modeling has the potentialfor establishing an accurate and quantitative Zheng research model, as well asfor creating a new system for performing disease research.

Despite considerable progress in genome, transcriptome,proteome, and metabolome-basedhigh throughput screening methods and in rational drug design, drug discoveryoften encounters considerable costly failures that challenge the fidelity ofthe modern drug discovery system. Zheng-driven drug discovery has showntremendous success for traditional drug discovery throughout Chinese medicine’s history. However, since this concept iscompletely new to Western medicine, it is no easy task to incorporateZheng-driven drug discovery into modern drug discovery workflows. Here, wepropose the “Zheng to TCM” and “TCM to Zheng” strategies within the framework of systemspharmacology to investigate biological systems and develop new therapeutics(Figure 2). The first strategy, Zheng to TCM, proposes developing a pipelinefrom Zheng diagnoses to TCM drugs,including differentiating Zhengs, identifyingZheng-related diseases and the associated genes and proteins, reverse targetingof drug effects, constructing and analyzing network/systems, and finally identifyingeffective herbal medicines (8). In effect, this strategy can be considered areverse targeting and screening approach that is designed to uncover drugs fromnatural products that can target multiple Zhengs or related diseases. The goalof this method is to help researchers identify the active components withinmedicinal plants and multi-ingredient synergistic herbal formulas or drugcombinations (9). In fact, this novel strategy has already been successfullyapplied in a qi-blood study, where we identified the active compounds in theqi-enriching and blood-tonifying herbs, their targets, and the correspondingpathways involved in the treatment of qi and blood deficiency syndromes (8).The second strategy, TCM to Zheng, consists of a wholesystem evaluation processstarting with herbs or herbal formulas and culminating in identifying theZhengs. This process includes the initial collection and classification ofherbal medicines; screening the ingredients for absorption, distribution,metabolism, excretion, and toxicity (ADME/T); performing targeted drugscreenings and tissue localization; constructing and analyzing networks; andfinally identifying Zhengs/diseases (10). Using this strategy, it is possibleto identify novel multitarget drugs in natural products (11). One particularlystriking example is the systematic analysis of blood stasis and qi deficiencysyndrome in coronary heart disease and the herbal drugs used to treat thesyndromes.The results indicate that the herbs for eliminating blood stasis havepharmacological activity that acts to dilate blood vessel, improve themicrocirculation, reduce blood viscosity, and regulate blood lipid, whileqi-enhancing herbs have the potential for enhancing energy metabolism andantiinflammatory activity (12). The TCM to Zheng strategy can also help toelucidate the pharmacological effectiveness of herbs and formulas.

In ourongoing work investigating Pi-deficiency syndrome(PDS) in the context of Zheng,we are analyzing patient samples using the sequencing alternativepolyadenylation sites (SAPAS) method, RNA sequencing (13), lipid metabolomics,proteomics, and transcriptomics in order to decipher the pathogenesis andcomplex responses of the human body to PDS. From a drug developmentperspective, we plan to systematically investigate the Si Jun Zi decoction, awidely used herbal recipe for PDS, within the framework of the “TCM to Zheng” strategy, so as to understand why thisrecipe can regulate the immune response, stimulate blood circulation, andadjust gastrointestinal digestive functions. Despite the progress inZheng-guided drug discovery, its future success requires the integration ofmultidisciplinary technologies, together with further innovations in thesetechnologies, to facilitate the understanding of multifactorial diseases andthe development of new therapies.

References

1. F.Cheung, Nature 480, S82 (2011).

2. A.Lu, M. Jiang, C. Zhang, K. Chan, J. Ethnopharmacol. 141, 549

(2012).

3. A.L. Barabasi, N. Gulbahce, J. Loscalzo, Nat. Rev. Genet. 12, 56

(2011).

4. H.van Wietmarschen et al., J. Clin. Rheumatol. 15, 330 (2009).

5. S.Li et al., IET Syst. Biol. 1, 51 (2007).

6. X.Wang et al., Mol. Cell. Proteomics 11, 370 (2012).

7. P.Csermely, T. Korcsmaros, H. J. M. Kiss, G. London, R. Nussinov,

Pharmacol.Therapeut. 138, 333 (2013).

8. J.Liu et al., Evid. Based Compl. Alt. Med. 2013, 938764 (2013).

9. P.Li et al., J. Ethnopharmacol. 151, 93 (2014).

10. C.Huang et al., Brief. Bioinform. 15, 710 (2014).

11. C.Zheng et al., Mol. Diversity 18, 621 (2014).

12. W.Zhou, Y. Wang, J. Ethnopharmacol. 151, 66 (2014).

13. Y.G. Fu et al., Genome Res. 21, 741 (2011).