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Impact of Metabolic States on SARS-CoV-2 Vaccine Responses in Mouse Models of Obesity and Diabetes
The emergence of SARS-CoV-2 has resulted in a significant impact on public health, particularly for individuals with underlying health conditions such as obesity and diabetes. While vaccination efforts have played a crucial role in reducing hospitalizations, it remains unclear whether the effectiveness of these vaccines varies among different population groups. In this study, we investigated the immune responses generated by various SARS-CoV-2 vaccine platforms in mouse models with obesity and diabetes, focusing on both cell-mediated and humoral immune responses. Our findings revealed diminished immune responses in diabetic and obese mice compared to healthy counterparts. After vaccination with adjuvanted subunit or mRNA lipid nanoparticle (LNP) vaccines, both humoral and cell-mediated responses were significantly reduced in diabetic mice. Obese mice also exhibited decreased immunogenicity, albeit to a lesser extent. However, it should be noted that mRNA vaccines demonstrated strong neutralizing responses across all metabolic states, while adjuvanted subunit vaccines elicited higher antibody avidity in mice with type 2 diabetes (T2D) and obesity compared to healthy mice. These results suggest that the impaired humoral and cell-mediated responses observed in altered metabolic states may be linked to chronic inflammation associated with obesity and suboptimal glycemic control in diabetes. Understanding the impact of these metabolic disturbances on vaccine immunogenicity is crucial for developing optimized vaccines that can effectively enhance immune responses and provide long-lasting protection against SARS-CoV-2, even in individuals with obesity and diabetes. By contributing these findings, we support efforts to improve vaccine efficacy in populations affected by metabolic disorders, advancing effective immunization against SARS-CoV-2. © 2024 by the authors.
Authors : Smith O.A.; Fujimoto B.; Wong T.A.S.; To A.; Odo T.; Ball A.; Haun B.K.; Muramatsu H.; Tam Y.K.; Pardi N.; Lehrer A.T.
Source : Multidisciplinary Digital Publishing Institute (MDPI)
Article Information
| Year | 2025 |
| Type | Article |
| DOI | 10.3390/covid5010002 |
| ISSN | 26738112 |
| Volume | 5 |
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