Application of systems biology to the study of chronic kidney disease

Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal histopathological results and clinical parameters. However, this information is not sufficient to predict CKD progression risk reliably or to guide preventive interventions. Nowadays, the appearance of systems biology has brought forward the concepts of ＂-omics＂ technologies, including genomics, transcriptomics, proteomics, and metabolomics. Systems biology, together with molecular analysis approaches such as microarray analysis, genome-wide association studies （GWAS）, and serial analysis of gene expression （SAGE）, has provided the framework for a comprehensive analysis of renal disease and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. In particular, analysis of urinary mRNA and protein levels is rapidly evolving as a non-invasive approach for CKD monitoring. All these systems biological molecular approaches are required for application of the concept of ＂personalized medicine＂ to progressive CKD, which will result in tailoring therapy for each patient, in contrast to the ＂one-size-fits-all＂ therapies currently in use.

Reduction in COVID-19 related resource loss and decline in prevalence of probable depression in Chinese adults:an application of the Conservation of Resource Theory

Background The levels of resource losses due to coronavirus disease 2019(COVID-19)and mental distress may change during the pandemic period.Based on the Conservation of Resource(COR)Theory,this study investigated such changes and the mediation between survey time(Round 2 versus Round 1)and depression via resource losses.Methods Two serial random population-based telephone surveys interviewed 209 and 458 Hong Kong Chinese adults in April 2020 and May 2021,respectively.Probable depression was defined as 9-item Patient Health Questionnaire(PHQ-9)score≥10.The validated Conservation of Resources Scale for COVID-19(CORS-COVID-19)scale was used to assess resource losses due to COVID-19.Multivariable logistic regression analysis,hierarchical logistic regression analysis,and structural equation modeling(SEM)was conducted to test the association,interaction,and mediation hypotheses,respectively.Results The prevalence of probable depression declined from 8.6%to 1.0%over time,together with reductions in losses of financial resource(Cohen’s d=0.88),future control(Cohen’s d=0.39),social resource(Cohen’s d=0.60),and family resource(Cohen’s d=0.36)due to COVID-19.All the overall scale/subscales of the CORS-COVID-19 were positively and associated with probable depression[adjusted odds ratio(aOR)ranged from 2.72 to 42.30].In SEM,the survey time was negatively associated with the latent variable of resource loss(β=−0.46),which in turn was positively associated with probable depression(β=0.73).In addition,the direct effect of survey time on probable depression was statistically non-significant(β=−0.08),indicating a full mediation effect of resource losses.Conclusions The lessening of the resource losses might have fully accounted for the significant decline in probable depression from Month 3 to 15 since the first COVID-19 outbreak in Hong Kong,China.The level of depression might have increased during the first phase of the pandemic,but might decline in the later phases if resources losses could be lessened.All stakeholders should hence work together to minimize individuals’COVID-19-related resource losses to prevent depression in the general population,as COVID-19 might be lasting.