Glycated hemoglobin (HbA1c) is widely used to assess long-term glycemic control in individuals with diabetes. However, various conditions that affect hemoglobin levels or the lifespan of red blood cells can compromise the accuracy of HbA1c measurements. Despite extensive research, the relationship between HbA1c and hemoglobin remains unclear. This study aims to clarify this relationship by examining its correlation across diverse age and gender cohorts.
Data from 217,991 participants aged 20 to 69 years were collected from health examination centers in Southwest China. Standardized methodologies were used to measure HbA1c and hemoglobin levels. Generalized additive models (GAM) were utilized to analyze non-linear relationships and adjust for potential confounding variables. Gender-specific reference intervals (RIs) for hemoglobin were also established.
A gender-specific association was observed between HbA1c and hemoglobin levels. In men, HbA1c levels decreased with increasing hemoglobin. Among women, a negative correlation was observed in premenopausal women (aged ≤ 45 years), whereas postmenopausal women (aged > 45 years) showed a positive correlation, with HbA1c levels increasing as hemoglobin levels rose. Additionally, HbA1c levels increased with age in both genders, with a more pronounced rise in women after the age of 45.
This study highlights significant gender- and age-related differences in the relationship between HbA1c and hemoglobin. The findings suggest that estrogen-related metabolic changes may influence HbA1c levels, with potential implications for diabetes management and hormone therapy in postmenopausal women.
This study aimed to examine microvascular lesions and neurodegenerative changes in diabetic retinopathy (DR) compared to type 2 diabetes mellitus (T2DM) without DR (NDR) using structural MRI and to explore their associations with DR.
243 patients with NDR and 122 patients with DR were included. Participants underwent conventional brain MRI scans, clinical measurements, and fundus examinations. Cerebral small vessel disease (CSVD) imaging parameters were obtained using AI-based software, manually verified, and corrected for accuracy. Volumes of major cortical and subcortical regions representing neurodegeneration were assessed using automated brain segmentation and quantitative techniques. Statistical analysis included T-test, chi-square test, Mann–Whitney U test, multivariate analysis of variance (MANCOVA), multivariate logistic regression, area under the receiver operating characteristic curve (AUC), and Delong test.
DR group exhibited significant differences in 11 CSVD features. Meanwhile, DR showed an atrophy trend in the frontal cortex, occipital cortex, and subcortical gray matter (GM) compared to NDR. After adjustment, DR patients exhibited greater perivascular spaces (PVS) numbers in the parietal lobe (OR = 1.394) and deep brain regions (OR = 1.066), greater dilated perivascular spaces (DPVS) numbers in the left basal ganglia (OR = 2.006), greater small subcortical infarcts (SSI) numbers in the right hemisphere (OR = 3.104), and decreased left frontal PVS (OR = 0.824), total left DPVS (OR = 0.714), and frontal cortex volume (OR = 0.959) compared to NDR. Further, the CSVD model showed a larger AUC (0.823, 95% CI: 0.781–0.866) than the brain atrophy model (AUC = 0.757, 95% CI: 0.706–0.808).
Microvascular and neurodegeneration are significantly associated with DR. CSVD is a better imaging biomarker for DR than brain atrophy.
This study aims to explore the link between iron deficiency anemia (IDA) and diabetic kidney disease (DKD) and assess the safety of iron supplementation. It also investigates key mechanisms and molecules involved in iron deficiency's role in disease development.
A retrospective analysis was conducted on 1,398 T2DM patients using propensity score matching to identify risk factors for DKD. Mendelian randomization (MR) was used to explore causal relationships between IDA, iron supplementation, liver iron content, and DKD. The GSE27999 dataset was analyzed to examine how an iron-deficient diet affects kidney-related gene expression. Key pathways and molecules were identified through GSEA, GO/KEGG, and PPI analysis.
Retrospective data showed a correlation between hemoglobin levels and DKD risk. Logistic regression confirmed that IDA increased DKD risk independently of other factors. MR revealed a causal link between IDA and DKD, with no significant effect from iron supplementation. GSE27999 analysis identified 580 differentially expressed genes, enriched in pathways like cytokine signaling, oxidative biology, and small molecule transport. PPI analysis highlighted 10 key hub genes, including Cyp2d26 and Fgf4.
IDA increases susceptibility to DKD, possibly through oxidative stress and altered small molecule transport. However, iron supplementation does not appear to increase the risk of DKD.
Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and is highly associated with adverse perinatal outcomes and long-term health problems for the mother and offspring. However, there are respective limitations in the pharmacological strategies for the current treatment of GDM. Glucokinase regulatory protein (GCKR) has been associated with GDM in observational studies and animal experiments and thus represents a potential drug target of interest for investigation.
We applied two-sample Mendelian randomization (MR) and colocalization analysis using summary-level data from genome-wide association studies of GCKR and GDM. Two-step MR was used to explore the mediating effects of several metabolic factors on the association. We also applied MR to explore the associations of GCKR levels with GDM-related outcomes. Finally, we performed a phenome-wide association study (PheWAS) to query the potential effects of altered GCKR levels across multiple health categories.
We found a significant association between elevated GCKR levels and GDM (OR = 3.466, 95% CI = 2.401–5.002, p = 3.16 × 10−11), also supported by the colocalization analysis ([Pcoloc] = 0.997). The estimates were replicated in an independent study (OR = 2.640, 95% CI = 1.983–3.513, p = 2.84 × 10−11, Pcoloc = 0.983). Elevated GCKR levels were also associated with higher risk of type 2 diabetes (OR = 2.183, 95% CI = 1.846–2.581, p = 6.53 × 10−20). Two-step MR suggested that fasting glucose, fasting insulin, and triglycerides partly mediated the causal relationship. PheWAS found that targeting GCKR may improve renal function and glucose homeostasis but cause dyslipidemia and uric acid abnormalities.
This study provided novel evidence that circulating GCKR levels are causally implicated in GDM and related complications, suggesting that it may be a promising target for treatment.
To examine the relationship between serum carotenoid levels and cardiovascular-kidney-metabolic (CKM) syndrome in a representative sample of US adults.
Data from the fasting subsample of the NHANES 2017–2018 were analyzed using a survey-weighted approach to ensure the findings are representative of the broader US adult population. Serum levels of α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin, and lycopene were measured using high-performance liquid chromatography. CKM syndrome stages were defined according to the 2023 American Heart Association guidelines, with advanced CKM syndrome categorized as stages 3 or 4. Associations between serum carotenoids and advanced CKM syndrome were assessed using logistic regression and weighted quantile sum (WQS) regression.
The study included 1671 adults aged 20 years and older, with a mean age of 48.7 years and a gender distribution of 50.9% female and 49.1% male. Higher serum levels of α-carotene, β-carotene, α-cryptoxanthin, lutein/zeaxanthin, and lycopene were inversely associated with advanced CKM syndrome. Specifically, compared to the lowest quartile, the highest quartile of α-carotene had an odds ratio (OR) of 0.29 (95% CI: 0.16–0.55), β-carotene 0.35 (95% CI: 0.16–0.78), α-cryptoxanthin 0.23 (95% CI: 0.11–0.49), lutein/zeaxanthin 0.26 (95% CI: 0.14–0.48), and lycopene 0.58 (95% CI: 0.35–0.98). However, β-cryptoxanthin did not show a significant association. Moreover, the combined effect of all carotenoids was significantly negatively correlated with advanced CKM syndrome (OR = 0.67, 95% CI: 0.53–0.86), with lutein/zeaxanthin contributing the most (44.56%).
Elevated serum carotenoid levels are inversely associated with the prevalence of advanced CKM syndrome in a dose-dependent manner, with this association remaining consistent across diverse demographic and health subgroups.
Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are established treatment options for type 2 diabetes (T2D). In addition to their glycemic benefit, GLP-1 RAs also induce weight loss by suppressing appetite via hypothalamic pathways. However, it remains unclear whether weight reduction is the primary driver of glycemic improvement.
We retrospectively evaluated 256 patients with T2D who were treated with exenatide (n = 84), dulaglutide (n = 99), or semaglutide (n = 73) for 2.5 years without interruption in real-world clinical practice. Body weight and A1C were measured every 6 months. Baseline characteristics included an average age of 61.8 ± 11.9 years, 51.5% female, diabetes duration of 12.9 ± 8.3 years, weight of 103.1 ± 20.7 kg, BMI of 35.7 ± 7.5 kg/m2, and A1C of 8.2% ± 1.5%. Patients were stratified into tertiles based on percentage weight change at 2.5 years within the overall cohort and for each GLP-1 RA group.
The first tertile experienced an average weight loss of −12.2% ± 5.7% (p < 0.0001), the second tertile lost −3.5% ± 1.4% (p < 0.0001), and the third tertile gained +2.8% ± 3.4% (p < 0.0001). The average changes in A1C were − 0.98 ± 1.8% (p < 0.0001), −0.56% ± 1.4% (p < 0.001), and −0.19% ± 1.9% (p = 0.4), respectively. A1C strongly correlated with weight change (p < 0.001). The same observations were reproducible in each medication group.
These findings suggest that the long-term improvement in glycemic control associated with GLP-1 RA therapy is primarily driven by weight loss rather than any other intrinsic effect of GLP-1 RA. This highlights the importance of weight reduction as a key therapeutic target for optimizing glycemic outcomes in patients with T2D receiving GLP-1 RAs.
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