Suboptimal health status (SHS) is a physical state between health and disease, characterized by the perception of health complaints, general weakness, chronic fatigue and low energy levels. SHS is proposed by the ancient concept of traditional Chinese medicine (TCM) from the perspective of preservative, predictive and personalized (precision) medicine. We previously created the suboptimal health status questionnaire 25 (SHSQ-25), a novel instrument to measure SHS, validated in various populations. SHSQ-25 thus affords a window of opportunity for early detection and intervention, contributing to the reduction of chronic disease burdens. To investigate the causative effect of SHS in non-communicable chronic diseases (NCD), we initiated the China suboptimal health cohort study (COACS), a longitudinal study starting from 2013. Phase I of the study involved a cross-sectional survey aimed at identifying the risk/protective factors associated with SHS; and Phase II: a longitudinal yearly follow-up study investigating how SHS contributes to the incidence and pattern of NCD. (1) Cross-sectional survey: in total, 4313 participants (53.8 % women) aged from 18 to 65 years were included in the cohort. The prevalence of SHS was 9.0 % using SHS score of 35 as threshold. Women showed a significantly higher prevalence of SHS (10.6 % in the female vs. 7.2 % in the male, P < 0.001). Risk factors for chronic diseases such as socioeconomic status, marital status, highest education completed, physical activity, salt intake, blood pressure and triglycerides differed significantly between subjects of SHS (SHS score ≥35) and those of ideal health (SHS score <35). (2) Follow up: the primary and secondary outcomes will be monitored from 2015 to 2024. The sex-specific difference in prevalence of SHS might partly explain the gender difference of incidence of certain chronic diseases. The COACS will enable a thorough characterization of SHS and establish a cohort that will be used for longitudinal analyses of the interaction between the genetic, lifestyle and environmental factors that contribute to the onset and etiology of targeted chronic diseases. The study together with the designed prospective cohort provides a chance to characterize and evaluate the effect of SHS systemically, and it thus generates an unprecedented opportunity for the early detection and prevention of chronic disease.

Rheumatoid arthritis (RA), a systemic, chronic, and progressive inflammatory autoimmune disease, affects up to 1.0% of the world population doubling mortality rate of patients and is a major global health burden. Worrisomely, we lack robust diagnostics of RA and its remission status. Research with the next-generation biomarker technology platforms such as glycomics offers new promises in this context. We report here a clinical case–control study comprising 128 patients suffering from chronic RA (80.22% in remission, 19.78% active clinically) and 195 gender- and age-matched controls, with a view to the putative glycan biomarkers of RA as well as its activity or remission status in Han Chinese RA patients. Hydrophilic interaction liquid chromatography–ultra-performance liquid chromatography (HILIC-UPLC) was used for the analysis of IgG glycans. The regression model identified the glycans that predict RA status, while a receiver operating characteristic (ROC) curve analysis validated the sensitivity and prediction power. Among the total 24 glycan peaks (GP1–GP24), ROC analysis showed only GP1 prediction to be highly sensitive with an area under the curve (AUC) = 0.881. Even though GP21 and GP22 could predict active status among the RA cases ( p < 0.05), they had lower sensitivity of prediction with an AUC = 0.658. Taken together, these observations suggest that GP1 might have potential as a putative biomarker for RA in the Han Chinese population, while the change in IgG glycosylation shows association with the RA active and remission states. To the best of our knowledge, this is the first glycomics study with respect to disease activity and remission states in RA.

Suboptimal health status (SHS) has been linked to cardiovascular risk factors, psychosocial stress, and unhealthy lifestyle. These factors also contribute to the shortening of telomere length (TL). A case–control study was conducted to examine the association between subjective health measures of SHS from the behavior perspective and also objective measures of TL at molecular level. SHS (cases = 294) was matched by age, sex, and body mass index with ideal health (controls = 294) using a propensity score matching method. Suboptimal health status questionnaire-25 (SHSQ-25) was used in the community-based health survey. A quantitative polymerase chain reaction was used to measure relative telomere length (RTL). Shorter RTL was found among the SHS group compared to the ideal health group ( p < 0.05). SHS was almost four times likely to be in the first quartile (odds ratio [OR] = 3.81; 95% confidence interval [CI] 2.21–6.56), almost thrice in second quartile (OR = 2.84; 95% CI 1.65–4.90), and almost twice likely to be in the third quartile (OR = 1.71; 95% CI 1.00–2.94) compared to the fourth quartile (the longest) of RTL after adjusting for socioeconomic, dietary intake, anthropometric, blood pressure, and biochemistry variables ( p < 0.05). Notably, SHS score was negatively correlated with RTL ( r = −0.218, p < 0.05). Our study confirms an association between SHS and short RTL. Combination of subjective (SHS) and objective (RTL) measures is a novel tool for health aging investigation. Therefore, SHSQ-25 could be used as a screening tool for measuring biological aging in low-income countries at community level where the expensive technique for RTL measurement is not applicable.

Background: More than 60 genetic susceptibility loci associated with type 2 diabetes mellitus (T2DM) have been established in populations of Asian and European ancestry. Given ethnic differences and environmental factors, validation of the effects of genetic risk variants with reported associations identified by Genome-Wide Association Studies (GWASs) is essential. The study aims at evaluating the associations of T2DM with 29 single nucleotide polymorphisms (SNPs) from 19 candidate genes derived from GWASs in a northern Han Chinese population. Method: In this case-control study, 461 T2DM-diagnosed patients and 434 controls were recruited at the Jidong oil field hospital (Hebei, China) from January 2009 to October 2013. A cumulative genetic risk score (cGRS) was calculated by summation of the number of risk alleles, and a weight GRS (wGRS) was calculated as the sum of risk alleles at each locus multiplied by their effect sizes for T2DM, using the independent variants selected. Result: The allelic frequency of the “A” allele at rs17106184 (Fas-associated factor 1, FAF1) was significantly higher in the T2DM patients than that of the healthy controls (11.7% vs. 6.4%, p < 0.001). Individuals in the highestquartile of wGRS had an over three-fold increased risk for developing T2DM compared with those in the lowest quartile (odds ratio = 3.06, 95% CI = 1.92–4.88, p < 0.001) adjusted for age, sex, BMI, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP) and diastolic blood pressure (DBP). The results were similar when analyzed with the cGRS. Conclusions: We confirmed the association between rs17106184 (FAF1) and T2DM in a northern Han Chinese population. The GRS calculated based on T2DM susceptibility variants may be a useful tool for predicting the T2DM susceptibility.