Obesity and cardiometabolic disease often, but not always, coincide. Distinguishing subpopulations within which cardiometabolic risk diverges from the risk expected for a given body mass index (BMI) may facilitate precision prevention of cardiometabolic diseases. Accordingly, we performed unsupervised clustering in four European population-based cohorts (N ≈ 173,000). We detected five discordant profiles consisting of individuals with cardiometabolic biomarkers higher or lower than expected given their BMI, which generally increases disease risk, in total representing ~20% of the total population. Persons with discordant profiles differed from concordant individuals in prevalence and future risk of major adverse cardiovascular events (MACE) and type 2 diabetes. Subtle BMI-discordances in biomarkers affected disease risk. For instance, a 10% higher probability of having a discordant lipid profile was associated with a 5% higher risk of MACE (hazard ratio in women 1.05, 95% confidence interval 1.03, 1.06, P = 4.19 × 10⁻¹⁰; hazard ratio in men 1.05, 95% confidence interval 1.04, 1.06, P = 9.33 × 10⁻¹⁴). Multivariate prediction models for MACE and type 2 diabetes performed better when incorporating discordant profile information (likelihood ratio test P < 0.001). This enhancement represents an additional net benefit of 4−15 additional correct interventions and 37−135 additional unnecessary interventions correctly avoided for every 10,000 individuals tested.

Relative fat mass (RFM) is a novel sex-specific anthropometric equation (based on height and waist measurements) to estimate whole-body fat percentage. To examine associations of RFM with incident type-2 diabetes (T2D), and to benchmark its performance against body-mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR). This prospective longitudinal study included data from three Dutch community-based cohorts free of baseline diabetes. First, we examined data from the PREVEND cohort (median age and follow-up duration: 48.0 and 12.5 years, respectively) using Cox regression models. Validation was performed in the Lifelines (median age and follow-up duration: 45.5 and 3.8 years, respectively) and Rotterdam (median age and follow-up duration: 68.0 and 13.9 years, respectively) cohorts. Among 7961 PREVEND participants, 522 (6.6%) developed T2D. In a multivariable model, all adiposity indices were significantly associated with incident T2D (P_all<0.001). While 1 SD increase in BMI, WC and WHR were associated with 68%, 77% and 61% increased risk of developing T2D [Hazard ratio (HR)_BMI: 1.68 (95%CI: 1.57-1.80), HR_WC: 1.77 (95% CI: 1.63-1.92) and HR_WHR: 1.61 (95%CI: 1.48-1.75)], an equivalent increase in RFM was associated with 119% increased risk [HR: 2.19 (95%CI: 1.96-2.44)]. RFM was associated with incident T2D across all age groups, with the largest effect size in the youngest (<40 years) age category [HR: 2.90 (95%CI: 2.15-3.92)]. Results were broadly similar in Lifelines (n = 93,870) and Rotterdam (n = 5279) cohorts. RFM is strongly associated with new-onset T2D and displays the potential to be used in the general practice setting to estimate the risk of future diabetes.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally and ozone exposure is a main cause of its disease burden. However, studies on COPD hospitalizations from short-term ambient level ozone exposure have not generated consensus results. To address the knowledge gap, comprehensive and systematic searches in several databases were conducted using specific keywords for publications up to February 14, 2020. Random-effect models were used to derive overall excess risk estimates between short-term ambient-level ozone exposure and COPD hospitalizations. The influence analyses were used to test the robustness of the results. Both meta-regression and subgroup analyses were used to explore the sources of heterogeneity and potential modifying factors. Based on the results from 26 eligible studies, the random-effect model analyses show that a 10 µg/m³ increase in maximum 8-h ozone concentration was associated with 0.84% (95% CI: 0.09%, 1.59%) higher COPD hospitalizations. The estimates were higher for warm season and multiple-day lag but lower for old populations. Results from subgroup analyses also indicate a multiple-day lag trend and bigger significant health effects during longer day intervals. Although characteristics of individual studies added modest heterogeneity to the overall estimates, the results remained robust during further analyses and exhibited no evidence of publication bias. Our systematic review and meta-analysis indicate that short-term ambient level ozone exposure was associated with increased risk of COPD hospitalizations. The significant association with multiple-day lag trend indicates that a multiple-day exposure metric should be considered for establishing ambient ozone quality and exposure standards for improvement of population health. Future investigations and meta-analysis studies should include clinical studies as well as more careful lag selection protocol.

Context The evidence of long-term polyethylene glycol recombinant human GH (PEG-rhGH) in pediatric GH deficiency (GHD) is limited. Objective This study aimed to examine the effectiveness and safety of long-term PEG-rhGH in children with GHD in the real world, as well as to examine the effects of dose on patient outcomes. Design A prospective, observational, posttrial study (NCT03290235). Setting, participants and intervention Children with GHD were enrolled from 81 centers in China in 4 individual clinical trials and received weekly 0.2 mg/kg/wk (high-dose) or 0.1 to <0.2 mg/kg/wk (low-dose) PEG-rhGH for 30 months. Main outcomes measures Height SD score (Ht SDS) at 12, 24, and 36 months. Results A total of 1170 children were enrolled in this posttrial study, with 642 patients in the high-dose subgroup and 528 in the low-dose subgroup. The Ht SDS improved significantly after treatment in the total population (P < 0.0001), with a mean change of 0.53 ± 0.30, 0.89 ± 0.48, 1.35 ± 0.63, 1.63 ± 0.75 at 6 months, 12 months, 24 months, and 36 months, respectively. In addition, the changes in Ht SDS from baseline were significantly improved in the high-dose subgroup compared with the low-dose subgroup at 6, 12, 24, and 36 months after treatment (all P < 0.05). A total of 12 (1.03%) patients developed serious adverse events. There was no serious adverse event related to the treatment, and no AEs leading to treatment discontinuation or death occurred. Conclusions PEG-rhGH showed long-term effectiveness and safety in treating children with GHD. Both dose subgroups showed promising outcomes, whereas PEG-rhGH 0.2 mg/kg/wk might show additional benefit.

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.

Lead (Pb) is known to induce detrimental health effects in exposed populations, including hematotoxicity and genotoxicity. Complete blood count (CBC) is a cost-effective and easy way to determine toxicity, and variations in proportion of different types of leukocytes: neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) are further evidence of hematotoxicity. However, few studies have been conducted to systematically evaluate effects of occupational Pb exposure on NLR and LMR, and their associations with genotoxicity. Our study was aimed to systematically assess the effects of current occupational Pb exposure on NLR and LMR, and their associations with genotoxicity. Our investigation was performed on 1176 workers from a newly built battery factory in North China. The workers had just entered their current job position in recent years and most of them had no previous history of occupational exposure to Pb. Blood lead levels (BLLs) and leukocytes indices were detected for all participants. Cytokinesis-blocked micronucleus assay (MN; n = 675) and alkaline comet assay (% tail DNA; n = 869) were used to assess genotoxicity. Multivariate linear and Poisson regression analyses were conducted to examine associations between leukocytes indices, genotoxic biomarkers and BLLs with adjustment for covariates. Spearman correlation and mediation analyses were used to investigate relationships between NLR and genotoxicity. Among all the exposed workers, NLR increased with increasing BLLs. However, WBC and LMR did not change significantly. Significant and dose-dependent increases in both MN frequencies and % tail DNA were observed among groups with different exposure doses. Compared with the normal NLR group (1.48 ≤ NLR < 4.58), the high NLR group (NLR ≥ 4.58) had higher % tail DNA. In addition, there was a significant and positive association between NLR and % tail DNA among all the workers, and % tail DNA mediated 15% of the effect of Pb on increasing NLR. Our large-scale population study shows that Pb exposure increased NLR and induced genotoxicity. There was an association between elevated NLR and DNA damage. In addition, the mediation effect of % tail DNA on the relationship between BLLs and NLR provided mechanistic evidence that certain mechanisms, e.g. inflammation, may be involved in elevation of NLR from Pb exposure. Therefore, NLR may be a convenient and sensitive biomarker for indication of Pb toxicity. Further studies are needed to validate the proposed mechanism and NLR as a biomarker.