title: Responsiveness of the innate immune system and glucose concentrations in the oldest old.
abstract: Patients with diabetes mellitus show increased risk of infectious disease as well as disturbances in innate immunity. In critical care settings, hyperglycemia is associated with increased risk of sepsis. It is unclear whether elevated glucose concentrations and innate immunity are associated in a non-clinical setting. We aimed to assess the association between glucose concentrations and innate immune response in the oldest old, who are at increased risk of both disturbed glucose metabolism as well as infectious disease. This study was part of the Leiden 85-plus Study. In 562 subjects aged 85 years old of the general population, venous blood samples were taken for measurement of morning glucose, C-reactive protein (CRP) and glycated hemoglobin (HbA1c). The innate immune response was assessed by performing ex vivo whole blood lipopolysaccharide (LPS) stimulation for production capacity of tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), interleukin 1-beta (IL1-β), interleukin 10 (IL-10) and interleukin 1 receptor antagonist (IL-1Ra). Using linear regression analysis, cross-sectional analysis between glucose and cytokine production capacity was performed. We found a significant negative association between glucose concentrations, but not HbA1c, and cytokine response capacity in four out of five measured cytokines (all p < 0.05). Both glucose and HbA1c were positively associated with circulating levels of CRP. Higher glucose concentrations in non-diabetic elderly are associated with lower innate immune response. As elderly show increased vulnerability for disturbances in glucose metabolism as well as infectious disease, this relation could be of clinical significance.
authors.affiliation: Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands. c.a.wijsman@lumc.nl
authors.forename: Carolien A
authors.initials: CA
authors.lastname: Wijsman
authors.forename: Simon P
authors.initials: SP
authors.lastname: Mooijaart
authors.forename: Rudi G J
authors.initials: RG
authors.lastname: Westendorp
authors.forename: Andrea B
authors.initials: AB
authors.lastname: Maier
mesh_terms: D000369:Aged, 80 and over; D000375:Aging / Q000276:immunology* / Q000502:physiology; D002097:C-Reactive Protein / Q000276:immunology* / Q000378:metabolism; D003430:Cross-Sectional Studies; D016207:Cytokines / Q000276:immunology* / Q000378:metabolism; D005260:Female; D015577:Geriatric Assessment / Q000379:methods; D005947:Glucose / Q000378:metabolism*; D006442:Glycated Hemoglobin / Q000276:immunology / Q000378:metabolism; D006801:Humans; D007113:Immunity, Innate / Q000276:immunology / Q000502:physiology*; D007375:Interleukin-1 / Q000276:immunology / Q000378:metabolism; D015850:Interleukin-6 / Q000276:immunology / Q000378:metabolism; D016014:Linear Models; D008297:Male; D011446:Prospective Studies
chemical_list: D002097:C-Reactive Protein; D016207:Cytokines; D005947:Glucose; D006442:Glycated Hemoglobin; D007375:Interleukin-1; D015850:Interleukin-6