Association between Anti-DENV IgM Serum Prevalence and CD11b Expression by Classical Monocytes in Obesity.
Karine Beatriz CostaBruna Caroline Chaves GarciaMarina Luiza Baêta CostaYara Gomes PenaEduardo Augusto Barbosa FigueiredoMarcelo Henrique Fernandes OttoniJuliane Duarte SantosVinícius de Oliveira OttoneDanilo Bretas de OliveiraEtel Rocha VieiraPublished in: Viruses (2023)
Dengue and obesity are currently highly prevalent conditions worldwide and the association between these two conditions may result in greater risk for DENV infection and disease severity. In this study the association between obesity and recent, inapparent dengue was investigated. Serum DENV IgM and NS1 were evaluated in 49 adult volunteers (15 lean and 34 individuals with obesity, according to body mass index), between September 2017 and June 2018. Adiposity, endocrine, metabolic, and immune data of the participants were also obtained. None of the study participants tested positive for the DENV NS1 antigen. DENV IgM was detected in 33.3% of the lean individuals, and in 44.1% of those with obesity; the presence of DENV IgM was not associated with body mass index (OR = 1.32, 95% CI = 0.59-2.98, p = 0.48). However, body fat index was higher in obese individuals who had recent inapparent dengue (14.7 ± 3.1 versus 12.7 ± 2.1 kg/m 2 , p = 0.04), as was the expression of CD11b by classical (CD14 ++ CD16 - ) monocytes (1103.0 ± 311.3 versus 720.3 ± 281.1 mean fluoresce intensity). Our findings suggest an association between adiposity and recent inapparent dengue and the involvement of classical monocytes in this association.
Keyphrases
- dengue virus
- weight gain
- insulin resistance
- zika virus
- weight loss
- body mass index
- metabolic syndrome
- aedes aegypti
- type diabetes
- high fat diet induced
- adipose tissue
- bariatric surgery
- poor prognosis
- skeletal muscle
- dendritic cells
- peripheral blood
- risk factors
- physical activity
- machine learning
- immune response
- bone mineral density
- young adults
- long non coding rna
- body composition
- big data
- deep learning