TCM Symptom-based Network Classification Of Liver Diseases Subgroups With Study Characteristics Of Phenotype And Molecular

ObjectiveLiver disease is a multifactorial complex disease with high global prevalence and poor long-term clinical efficacy and it has become one of the diseases that cause most deaths and economic burdens.liver diseases are often accompanied by various comorbidities and the patients with different comorbidities often incorporate multiple phenotypes in the clinic.It’s not only increases the mortality rate of patients,but also makes the treatment plan more complicated.Thus,there is a pressing need to improve understanding of the complexity of clinical liver population to help gain more accurate disease subtypes for personalized treatment and improve their diagnosis,treatment,and prognosis.MethodsIndividualized treatment of the traditional Chinese medicine provides a theoretical basis to the study of personalized classification of complex diseases.Utilizing the TCM clinical electronic medical records of 6475 liver inpatient cases,we builta liver disease comorbidity network to show the complicated associations between liver diseases and their comorbidities,and then constructed a patient similarity network with shared symptom.Finally,we identified liver patient subgroups using community detection methods and performed enrichment analyses to find both distinct clinical and molecular characteristics(with the phenotype-genotype associations and interact networks)of these patient subgroups.ResultFrom the comorbidity network,we found that clinical liver patients have a wide range of disease comorbidities,in which the basic liver diseases(e.g.hepatitis b,decompensated liver cirrhosis),and the common chronic diseases(e.g.hypertension,type 2 diabetes),which have high degree of disease comorbidities.In addition,we identified 303 patient modules(representing the liver patient subgroups)from the patient similarity network,in which the top 6 modules with large number of cases include 51.68% of the whole cases and 251 modules contain only 10 or fewer cases,which indicates the manifestation diversity of liver diseases.Furthermore,we identified the distinct pathwaysof patient subgroups-associated comorbidities and the basic liver diseases(hepatitis b and cirrhosis),respectively.The highdegree of overlapping pathways between them(e.g.module7(M7)with 64.71% shared enriched pathways with hepatitis b,M10 with64.52% shared enriched pathways with cirrhosis)indicates the underlying molecular network mechanism between liver diseases and comorbidities.Finally,we found that the patient subgroups have distinct characteristics of phenotypes,diseases and their underlying molecular pathways,For example,M6(n=638)and M2(n=623)were mostly related to the syndrome of liver stagnation and spleen deficiency and the symptoms of fatigue,anorexia,irritability.Bothof them associated to common chronic liver disease conditions(hepatitis b and hepatitis c)and the overlapping pathways of M6 associated to infection disease,which reflected the general characteristics of liver subgroups.M30(n = 36)was related to the syndrome of dampness-heat flowing downward and the symptomsof diarrhea,abdominal pain.It was related to acute gastroenteritis,which reflected the individual characteristics of liver subgroups.ConclusionOur results demonstrate the utility and comprehensiveness of disease classification study based on community detection of patient network using shared Traditional Chinese Medicine symptom phenotypes and it can be used to other more complex diseases.