Background: B-cell-deleted therapy has been successfully used for children with idiopathic nephrotic syndrome (INS), suggesting that B cells may be involved in the pathogenesis of INS. B cells are a heterogenous population comprised of subpopulations distinguished by their phenotypes. However, few studies have focused on the alteration of B-cell homeostasis in INS. Methods: We measured the levels of B-cell subsets in the blood of 87 INS children via flow cytometry, prior to treatment with steroids. INS patients were divided into steroid-sensitive nephrotic syndrome (SSNS) and steroid-resistant nephrotic syndrome (SRNS) groups based on their sensitivities to steroids after a one-month follow-up. Subsequently, we compared these INS patients with age- and sex-matched patients with relapse (n = 35) and remissions (n = 32), as well as healthy controls (n = 75). Results: We found that 65 SSNS patients exhibited an altered peripheral-blood B-cell-subset distribution, with increased levels of total, transitional, memory, IgM (immunoglobulin M) memory and switched-memory B cells compared to 22 SRNS patients. The proportion of total B cells was significantly higher in the SSNS group (22.1 ± 6.7% L, p < 0.001) than in the SRNS, remission, and control groups. In contrast, the levels of B-cell subsets in SRNS patients were generally the same as those in remission patients and healthy controls. Patients in relapse presented elevated memory B cells compared to those in other groups. The area under the ROC (receiver operating characteristic) curve of transition B cells at initial onset for the prediction of SSNS was 0.907 (95% confidence interval, 0.835–0.979). The analysis rendered an optimal cut-off value of 2.05 (% Lymphocyte) corresponding to 79.1% sensitivity and 90.9% specificity. Conclusions: We observed and verified that B-cell subsets are significantly altered in children with SSNS. We propose that elevated transitional B cells may be a promising marker for predicting successful immunosuppressive therapy during the initial onset of INS. Further research is needed to determine the function of memory B cells in INS.

Glycomics is a new subspecialty in omics systems sciences that offers significant promise for next-generation biomarkers on disease susceptibility, drug target discovery, and precision medicine. In this context, alternative immunoglobulin G (IgG) N -glycosylation has been reportedly implicated in several common chronic diseases, although systematic assessment is currently lacking in the literature. We conducted a systematic review of observational studies on IgG N -glycan variability and susceptibility to common chronic diseases. Observational studies reporting an association between diseases (such as colorectal cancer, dyslipidemia, ischemic stroke, rheumatoid arthritis, and systemic lupus erythematosus) and IgG N -glycans quantified by ultraperformance liquid chromatography were included. The glycans were categorized into 24 initial IgG glycan peaks (GPs). Notably, aging positively correlated with GP1, GP2, GP4–7, GP10, GP11, GP19, and GP24, while negatively correlated with GP8, GP12–15, GP17, GP18, GP20, GP21, and GP23 ( p < 0.05). The absolute value of significant correlation coefficients of age and IgG glycans ranged from 0.043 to 0.645. We found that the high levels of GP1–4, GP6, GP7, and GP24 and low levels of GP9, GP13–15, GP18, and GP23 could potentially increase the risk of disease. In conclusion, the present systematic review suggests that the field of glycomics, and GP1–4, GP6, GP7, GP9, GP13–15, GP18, GP23, and GP24 in particular, holds promise for further candidate biomarker research on susceptibility to common chronic diseases.

Previous genome-wide association studies (GWAS) have identified potential genetic variants involved in the risk of Alzheimer’s dementia, but their underlying biological interpretation remains largely unclear. In addition, the effects of DNA methylation and gene expression on Alzheimer’s dementia are not well understood. A network summary data-based Mendelian randomization (SMR) analysis was performed integrating cis- DNA methylation quantitative trait loci (mQTL) /cis- gene expression QTL (eQTL) data in the brain and blood, as well as GWAS summarized data for Alzheimer’s dementia to evaluate the pleiotropic associations of DNA methylation and gene expression with Alzheimer’s dementia and to explore the complex mechanisms underpinning Alzheimer’s dementia. After correction for multiple testing (false discovery rate [FDR] P < 0.05) and filtering using the heterogeneity in dependent instruments (HEIDI) test (P_HEIDI>0.01), we identified dozens of DNA methylation sites and genes showing pleiotropic associations with Alzheimer’s dementia. We found 22 and 16 potentially causal pathways of Alzheimer’s dementia (i.e., SNP→DNA methylation→Gene expression→Alzheimer’s dementia) in the brain and blood, respectively. Approximately two-thirds of the identified DNA methylation sites had an influence on gene expression and the expression of almost all the identified genes was regulated by DNA methylation. Our network SMR analysis provided evidence supporting the pleiotropic association of some novel DNA methylation sites and genes with Alzheimer’s dementia and revealed possible causal pathways underlying the pathogenesis of Alzheimer’s dementia. Our findings shed light on the role of DNA methylation in gene expression and in the development of Alzheimer’s dementia.

Background: Measuring the health of the population is of great significance to the development of a region. We aimed to estimate the population, probability of death, and quality of life in western China. Methods: We calculated the age-specific mortality rate and prevalence rate of diseases and injuries using the Full Population Database and the Home Page of Inpatient Medical Record. We used multiple interpolation methods to insert missing information from the death data and the model of Kannisto to adjust the mortality rate for elderly individuals. The age-specific prevalence rate of diseases and injuries was adjusted according to the standard ratio of age and methods of equal proportional allocation. Life expectancy was calculated by a life table, and the quality of life was estimated using the Sullivan method. Results: The total population continued to increase in 2015 to 2019 in the Shaanxi Province, China. The mortality rate of children under five has improved, and the mortality rate of people over 65 is decreasing year by year. Life expectancy increased from 74.66 years in 2015 to 77.19 years in 2019. Even with the total risk of disease and injury, the health-adjusted life expectancy increased by 1.90 years within 5 years, and the number of unhealthy years significantly improved. Health-adjusted life expectancy increased by 1.75 years when only considered the ten major disease systems (tumors; endocrinology, nutrition and metabolism; mental and behavioral disorders; nervous system; sensory diseases; circulatory system; respiratory system; digestive system; genitourinary system; musculoskeletal system and connective tissue), and the number of unhealthy years increased slightly. Conclusions: In the past five years, Shaanxi Province has made progress in improving life expectancy and controlling the development of chronic diseases. It is necessary to take specific preventive measures and improve the quality of basic public health services.

Background Socio-Demographic Index (SDI) is an index to evaluate social development. Healthy life expectancy (HLE/HALE) can comprehensively measure the population health. This paper analyzes the relationship and trend of Socio-Demographic Index, life expectancy (LE) and healthy life expectancy, which provides a reference for improving population health. Methods We used R Studio (version 1.2.5033) for correlation matrix analysis of SDI, HALE and LE. Meanwhile, we divided provinces into 3 regions according to the 2019 Chinese Health Statistics Yearbook and analyzed the distribution by ArcGIS 10.5 of healthy life expectancy and SDI of 31 provinces and cities in China.Results From 1990 to 2016, socio-demographic, life expectancy and healthy life expectancy showed a gradual increasing trend, and the level in eastern provinces were higher than western provinces in China. There is a correlation between socio-demographic (included its composition that education for aged 15 and older, Gross Domestic Product and total fertility rates under the age of 25), healthy life expectancy and life expectancy. Total fertility rates under the age of 25 has a negative correlation with other variables.Conclusions There is a strong positive correlation between healthy life expectancy, life expectancy and socio-demographic index. The government should consider take the implementation of personalized policies to steadily improve the development of SDI, at the same time to improve healthy life expectancy from improving maternal health and reducing infant mortality, paying attention to adult health, reducing the early death rate of chronic diseases.

Background: Multimorbidity has an effect on life expectancy, while its effect on healthy life years is unclear. This study aims to investigate the associations between healthy life years lost due to multimorbidity and living risk.Methods: The participants of The China Health and Retirement Longitudinal Study (CHARLS) were assessed at four visits between 2011 (baseline) and 2018. At baseline, 13,949 individuals were administered surveys. A combined score based on seven health-related factors was calculated, and the participants were classified into 3 groups based on living risk. We used the adjusted Cox regression methods to examine the associations between living risk groups and multimorbidity. We estimated the healthy life years lost due to multimorbidity using the Sullivan method.Results: A total of 9,091 adults aged 45 years or older (mean age of 59.55 ± 9.50 years with one disease, 52.60% women) were analyzed in the CHARLS. The probability of no multimorbidity over 7 years decreased from 0.9947 to 0.9697 in the low-risk group, whereas the probability of multimorbidity in low living risk was lower than that of high living risk, ranging from HR 1.253 (95% CI.992–1.581; P = 0.058) to 1.431 (1.05–1.949; P = 0.023) in sex, and ranging from HR 1.340 (95% CI 1.106–1.623; P = 0.003) to 2.002 (1.058–3.787; P = 0.033) in area. At 45 years, the healthy life years lost in men was <0.27 years compared to women in the low-risk group. Hypertension increased the risk of multimorbidity with an HR of 1.5 (95% CI 1.21–1.91; P < 0.001) in men. In urban areas, participants with diabetes had 3.2 times (95% CI 1.75–5.94, P < 0.001) higher risk of multimorbidity than participants without diabetes.Conclusions: These findings indicate that a low-risk lifestyle could decrease the loss of healthy life years under multimorbidity. The probability of multimorbidity in women and in urban areas was high. Hypertension was correlated with the hazard risk of multimorbidity.