Suavaluk Songlilitchuwong
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Suavaluk Songlilitchuwong has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Nipaporn Teerawattanapong
Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University
2 shared publications - Saranya Innang
Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University
2 shared publications - Sarocha Suthon
Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
2 shared publications - Tassanee Narkdontri
Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University
2 shared publications - Watip Tangjittipokin
Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
2 shared publications Alessia Micieli
1 shared publication
Latest Publications
- Open Access
- 17 July 2026
- Published by Taylor & Francis in Annals of Medicine
- Vol. 58 (1) , 2703311
Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1 , and CMIP variants
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...
- 17 July 2026
- Published by Taylor & Francis in Annals of Medicine
- Vol. 58 (1) , 2703311
Open AccessGenetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1 , and CMIP variants
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...
- Open Access
- 1 January 2026
- Published by Wiley in BioMed Research International
- Vol. 2026 (1)
Genetic Variants in NOS2 and CCL2 Modulate Risk of Post‐COVID‐19 Hyperglycemia via Immune‐Metabolic Interactions
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.
- 1 January 2026
- Published by Wiley in BioMed Research International
- Vol. 2026 (1)
Open AccessGenetic Variants in NOS2 and CCL2 Modulate Risk of Post‐COVID‐19 Hyperglycemia via Immune‐Metabolic Interactions
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.