Nipaporn Teerawattanapong

Gestational diabetes mellitus (GDM) is a frequently occurring condition characterized by glucose intolerance that is first detected during pregnancy and has significant implications for both matern...

Hyperglycemia has increasingly been recognized among individuals recovering from coronavirus disease 2019 (COVID‐19); the host factors contributing to heterogeneous metabolic outcomes remain poorly understood. This cohort study investigated the association between innate immune genetic polymorphisms and hyperglycemia in post‐COVID‐19 patients. A total of 471 adults with previous mild‐to‐moderate COVID‐19 were enrolled through the post‐COVID follow‐up program at Siriraj Hospital, Thailand, and classified as normoglycemic (HbA1c < 5.7%, n = 252) or hyperglycemic (HbA1c ≥ 5.7%, n = 219). Clinical characteristics, metabolic parameters, inflammatory biomarkers, and immunological measurements were collected during follow‐up. Genotyping was performed using the Axiom Human Genotyping SARS‐CoV‐2 Research Array, focusing on candidate polymorphisms in innate immune‐related genes. Associations between genetic variants and hyperglycemia were evaluated using multivariable logistic regression adjusted for age, body mass index, and underlying comorbidities. Participants with hyperglycemia were significantly older and had higher body mass index, greater prevalence of cardiometabolic comorbidities, elevated C‐reactive protein levels, and higher LDL cholesterol compared with normoglycemic individuals. Significant associations were identified in NOS2 and CCL2 . The NOS2 rs4795067 variant was associated with increased odds of hyperglycemia (adjusted OR = 1.770, 95% CI: 1.137–2.756, p = 0.011), whereas rs35051118 showed a protective effect (adjusted OR = 0.613, 95% CI: 0.386–0.975, p = 0.039). In CCL2 , rs28730833 was strongly associated with hyperglycemia (adjusted OR = 2.977, 95% CI: 1.349–6.572, p = 0.007). These findings suggest that innate immune genetic variation may contribute to hyperglycemia in post‐COVID‐19 patients, although independent validation is required.

Type 2 diabetes is a heterogeneous disease with strong genetic components. We showed earlier that newly diagnosed type 2 diabetes in Thai patients could be categorized into four clusters. This study aimed to determine the evidence of hereditary factors in these type 2 diabetes clusters. A total of 487 subjects who were diagnosed with type 2 diabetes in two years were enrolled in the Siriraj Diabetes Center, Siriraj Hospital Bangkok, Bangkok, Thailand. They were divided into four clusters as previously described. The associations between patients' characteristics, degree of family history of diabetes (FHD), and type 2 diabetes clusters were tested using multinomial logistic regression. Among four clusters of newly diagnosed type 2 diabetes, there were significant differences in characteristics at baseline, including age at diagnosis, BMI, waist circumference, blood sugar levels, vital signs, triglyceride, HDL, calculated LDL, creatinine and eGFR (all p < .05). A relatively young age at the time of diabetes diagnosis was associated with having second-degree relatives with diabetes (p < .05) in all clusters when using mild age-related diabetes (MARD) cluster with no FHD as a control. Patients in the severe insulin-deficient diabetes (SIDD) cluster had more first-degree relatives with diabetes (odds ratio = 1.85; p = .0354), while patients in the metabolic syndrome diabetes (MSD) cluster (odds ratio = 10.73; p < .001) and the mild obesity-related diabetes (MOD) group (odds ratio = 6.66; p = .002), had more second-degree relatives with diabetes. Genetic factors might have various roles in the pathogenesis of type 2 diabetes, at least in newly diagnosed Thai patients. Our findings supported that genetic heterogeneity contributed to clinical heterogeneity or four different clusters. Further studies are needed in a larger sample size of these patients is needed to identify genetic loci associated with each cluster.

BACKGROUND In a number of patients, post-acute COVID syndrome develops after acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Long COVID [LC]). Here, we examined the immune responses and clinical characteristics of individuals with LC compared to age- and gender-matched healthy recovered COVID individuals (HC) during the Omicron pandemic. Immune responses following BNT162b2 (Pfizer) booster are also determined. METHODS This retrospective cohort study included 292 patients (LC, 158; HC, 134) confirmed to have SARS-CoV-2 infection from January to August 2022. We determined anti-SARS-CoV-2 receptor-binding domain immunoglobulin G (anti-RBD IgG), surrogate virus neutralization test (sVNT), T-cell subsets, and neutralization of wild-type, BA.1 and BA.5. A subset of patients was voluntarily recruited for booster vaccination with BNT162b2 vaccine and immunogenicity was assessed 4weeks after vaccination. RESULTS Cycle thresholds were higher in the HC group than in the LC group (20.7 vs. 19.7; PCONCLUSIONS These findings imply that LC produced increased neutralizing antibody responses than those with HC. During the Omicron pandemic, immunity after LC has still waned; therefore, a booster vaccine may be needed after 2-3 months from last infection. (ClinicalTrials.gov number, NCT05484700)

Purpose: This study investigated the prevalence and characteristics of prediabetes (PreDM) and metabolic syndrome (MetS) in seemingly healthy persons attending a health check-up clinic at a tertiary care hospital. Patients and Methods: This was a cross-sectional study that enrolled 1213 subjects (339 male, 874 female) who underwent an annual health check-up at Siriraj Hospital, Bangkok, Thailand from 2009 to 2019. Factors that independently related to PreDM were analyzed using unconditional logistic regression analysis with adjustments for age, BMI, and gender. Results: The prevalence of PreDM and MetS was 54.3% and 19.7% respectively. Participants with impaired fasting glucose (IFG) and glycated hemoglobin (HbA_1c) 38.8– 46.4 mmol/mol had significantly higher waist circumference (WC) and blood pressure (BP) compared to those with IFG or HbA_1c 38.8– 46.4 mmol/mol alone (P < 0.05). Among three PreDM subgroups, the average age was lowest in the HbA_1c 38.8– 46.4 mmol/mol subgroup (P < 0.001). PreDM participants with MetS were older (p = 0.03), had higher WC, BP, fasting plasma glucose and serum triglyceride level (all P < 0.001) but had lower serum high-density lipoprotein (HDL) cholesterol level (P < 0.001). Multivariate analysis revealed high MetS score, obesity, and low serum HDL cholesterol level to be independently associated with PreDM with odds ratios of 9.02 (95% confidence interval [CI]: 4.03– 20.18), 1.8 (95% CI: 1.07– 3.04), and 1.42 (95% CI: 1.02– 1.96), respectively. Conclusion: The prevalence of PreDM and MetS was relatively high in seemingly healthy persons. Distinct PreDM subgroups with or without MetS exhibited diverse clinical and biochemical features suggesting dissimilar pathogenesis.