Shan Gao

Amino acid (AA) dysregulation has been associated with metabolic diseases. However, its potential as a childhood determinant of adult diabetes risk remains understudied, particularly among children with normoglycemia. Leveraging a 10-year follow-up cohort, we investigated whether AA profiles distinguished childhood glycemic phenotypes and predicted future diabetes risk. Among 947 children from the Beijing Children and Adolescents Metabolic Syndrome (BCAMS) study, participants were categorized as having normoglycemia with insulin sensitivity (NG-IS), normoglycemia with insulin resistance (NG-IR), or impaired fasting glucose (IFG), and plasma AA profiles were assessed by targeted metabolomics. At follow-up, 297 participants with baseline normoglycemia underwent a 2-h oral glucose tolerance test to assess incident dysglycemia, and five adipokines were measured. After adjusting for age, sex, and relevant covariates, distinct AA signatures were identified cross-sectionally across glycemic groups, with a core cluster (Ile, Val, Tyr, Phe, Ala, Pro, and branched-chain AA score) independently associated with IR and IFG. Prospectively, children in the NG-IR group had a 4.3-fold higher risk of incident dysglycemia than those in the NG-IS group. Six AAs (Ile, Leu, Tyr, Phe, Lys, and Hyl) significantly predicted 10-year dysglycemia risk, with 22.6–42.1% of their associations estimated through follow-up IR, with the largest proportion observed for Ile. In separate Ile–IR models, estimated proportions through follow-up leptin and high-molecular-weight adiponectin were 72% and 38%, respectively. Furthermore, dietary Ile restriction in obese mice reduced body weight by 25% and leptin by 50% and improved IS by 22%. These findings identify childhood plasma AA dysregulation as an early biomarker for diabetes risk, and Ile emerges as a potentially modifiable target. Article Highlights: Prospective evidence linking childhood amino acid (AA) dysregulation with future diabetes risk remains limited. We examined whether AA profiles distinguished childhood glycemic phenotypes and predicted dysglycemia risk in the Beijing Children and Adolescents Metabolic Syndrome (BCAMS) cohort. AA alterations were already detectable in children with normoglycemia and insulin resistance; six AAs were associated with 10-year dysglycemia risk, and their addition to clinical variables improved prediction. Ile showed the largest estimated indirect association with incident dysglycemia through follow-up insulin resistance; dietary Ile restriction in obese mice produced concordant metabolic changes, supporting AA profiling for early risk identification and Ile as a candidate modifiable target.

Background: Polycystic ovary syndrome (PCOS) is associated with increased cardiovascular disease (CVD) risk, but differences across phenotypes in Chinese women remain unclear. This study aimed to characterize clinical profiles of PCOS phenotypes, predict CVD risks, and evaluate associations between phenotypes and CVD risk. Methods: A total of 206 women with PCOS were included from an initial cohort of 211 and classified into four phenotypes according to Rotterdam criteria. Clinical data, laboratory results, and imaging measurements were collected. CVD risks were estimated using the China-PAR model. One-way ANOVA and the Kruskal-Wallis test were used for continuous variables, and Pearson’s chi-square or Fisher’s exact test for categorical variables. Firth logistic regression was employed to assess the association between PCOS phenotypes and CVD risk, and mediation analysis detected the indirect effects. Results: Among 206 patients with PCOS, 104 (50.5%), 36 (17.5%), 19 (9.2%) and 47 (22.8%) were classified as phenotype A, B, C and D. BMI, WC, SBP, and DBP were significantly higher in phenotypes A, B, and C than in D (P<0.05). UA, LDL-C, TG, and HOMA-IR were significantly higher in phenotypes A and B than in D, while HDL-C and ISI-Matsuda were significantly lower (P<0.05). Lifetime CVD risk scores were significantly higher in phenotypes A, B, and C compared with D (P< 0.05), with values of 15.55%, 17.65%, 17.30%, and 9.90%. After adjusting for diet, physical activity, and medication use, phenotypes A (OR 3.18, 95% CI: 1.30-8.84, P = 0.010), B (OR 4.90, 95% CI: 1.58-16.44, P = 0.006), and C (OR 4.67, 95% CI: 1.39-16.64, P = 0.013) were significantly associated with higher odds of high lifetime CVD risk compared with D. The mediating effects of BMI, HOMA-IR, and UA were significant (P< 0.05), with BMI exhibiting the largest mediating effect, accounting for 94.7%, 70.9%, and 42.9% of the total effect in phenotypes A, B, and C compared with D. Conclusions: Our results demonstrated that more adverse clinical abnormalities and significantly higher CVD risk in women with phenotypes A, B, and C compared with D. BMI, HOMA-IR, and UA play a significantly mediating role between phenotypes and CVD risk. This study suggests that it may be necessary to conduct regular CVD risk assessments for patients with different phenotypes of PCOS, in order to guide early individualized treatment strategies, with a focus on weight and metabolic management.

Sleep disturbance is increasingly common and has been linked to adverse metabolic outcomes. This study investigated whether sleep recovery (SR) mitigates the effects of chronic sleep fragmentation (SF) on glucose metabolism, with a focus on gut microbiota and inguinal white adipose tissue (iWAT) transcriptomics. Mice were subjected to 8 weeks of SF followed by SR. After 2 weeks of SR (SF 8w–SR 2w), glucose intolerance persisted, accompanied by significant alterations in gut microbiota composition and iWAT gene expression. Key hub genes (Ncapg, Cenpe, Ttk) and glucose metabolism–related genes (Lnpep, Pten, Apoe, Cebpb, Ido1, Ahsg) were identified. Bacterial genera were significantly altered and associated with glucose metabolism. After 8 weeks of SR (SF 8w–SR 8w), glucose tolerance was restored, although alterations in gut microbiota composition persisted. Notably, Rikenellaceae_RC9_gut_group and Defluviitaleaceae_UCG-011 remained persistently altered. These findings indicate that short-term SR is insufficient to reverse SF-induced glucose intolerance, which is associated with changes in the gut microbiota and iWAT transcriptome. Although prolonged SR improves glucose metabolism, persistent microbial alterations suggest a lasting impact of SF, underscoring the potential role of gut dysbiosis in metabolic dysfunction following sleep disturbances.

Objective The underlying connections between obesity and non-alcoholic fatty liver disease (NAFLD) are not fully understood. One potential link might be the imbalanced adipokines and hepatokines. We aimed to explore the associations between specific adipokines/hepatokines and NAFLD in Chinese youth and to determine how these biomarkers mediate the obesity–NAFLD relationship. Methods We analyzed data from the 10-year follow-up visit of the Beijing Children and Adolescents Metabolic Syndrome (BCAMS) study (n = 509; mean age = 20.2 years) for a comprehensive metabolic risk assessment, including liver ultrasound and plasma measurements of adiponectin, leptin, fibroblast growth factor 21 (FGF21), retinol-binding protein 4 (RBP4), and angiopoietin-like protein 8 (ANGPTL8). Longitudinal analysis was performed on a subgroup (n = 307), with complete baseline (mean age = 12.2 years) and follow-up data. Mediation models assessed how obesity at baseline and follow-up influence NAFLD through these biomarkers. Results Participants with NAFLD exhibited a high prevalence of central obesity (90.9%). Both cross-sectional and prospective analyses identified increased RBP4, FGF21, leptin, and decreased adiponectin levels as significant predictors of NAFLD. More adipokine/hepatokine abnormalities were linked to higher NAFLD risk. Furthermore, ratios reflecting adipokine/hepatokine imbalances, including leptin/adiponectin, FGF21/adiponectin, and RBP4/adiponectin, demonstrated stepwise changes correlating with NAFLD severity (all p < 0.05). Mediation analysis indicated that these four adipokines/hepatokines accounted for approximately 72.4% of the central obesity–NAFLD relationship and 80.1% in the subgroup analysis using baseline childhood data. Conclusions Dysregulated adipokines/hepatokines may explain the onset or progression of obesity-related NAFLD in youths. Higher RBP4, FGF21 and leptin, alongside lower adiponectin, could serve as early biomarkers for NAFLD. Graphical abstract

The mechanisms link obesity and hypertension are not well understood. One possibility is the alterations in adipose-derived adipokines that modulate insulin resistance (IR) and cardiovascular homeostasis. We aimed to assess the associations between hypertension and four adipokine levels in Chinese youth, and to examine to what extent the associations are mediated by IR. We utilized cross-sectional data from the Beijing Children and Adolescents Metabolic Syndrome (BCAMS) Study Cohort (n = 559, mean age = 20.2 years). Plasma leptin, adiponectin, retinol binding protein 4 (RBP4) and fibroblast growth factor 21 (FGF21) levels were assayed. The relationships between adipokines and hypertension and the possible mediation effect of IR were evaluated. Youth with hypertension have lower adiponectin and higher leptin, FGF21 (all P < 0.001) and RBP4 levels (p = 0.06) compared to their counterparts. Moreover, the co-existence of these two or more adipokine abnormalities in youth leads to a 9-fold increased risk for hypertension (OR: 9.19; 95% CI, 4.01–21.08) compared with these without abnormalities. However, in the fully adjusted and BMI-adjusted analyses, only FGF21 was a significant predictor of hypertension (OR: 2.12; 95% CI, 1.34–3.36). Mediation analysis revealed that the associations between leptin, adiponectin, RBP4 and hypertension are totally mediated by IR (proportion: 63.9%, 65.4%, and 31.6%, respectively), while BMI and IR partly mediated the association between FGF21 and hypertension (proportion: 30.6%, 21.2%). Our findings suggest that dysregulation of adipokines might result in hypertension in youth. Leptin, adiponectin and RBP4 may exert their functions in hypertension through adiposity-related IR, whereas FGF21 might be used as an independent marker of hypertension in youth.