title: Glutamic acid decarboxylase antibodies are indicators of the course, but not of the onset, of diabetes in middle-aged adults: the Atherosclerosis Risk in Communities Study.
abstract: To efficiently examine the association of glutamic acid decarboxylase antibody (GADA) positivity with the onset and progression of diabetes in middle-aged adults, we performed a case-cohort study representing the ~9-year experience of 10,275 Atherosclerosis Risk in Communities Study participants, initially aged 45-64 years. Antibodies to glutamic acid decarboxylase (GAD65) were measured by radioimmunoassay in 580 incident diabetes cases and 544 non-cases. The overall weighted prevalence of GADA positivity (>or=1 U/mL) was 7.3%. Baseline risk factors, with the exception of smoking and interleukin-6 (P <or= 0.02), were generally similar between GADA-positive and -negative individuals. GADA positivity did not predict incident diabetes in multiply adjusted (HR = 1.04; 95%CI = 0.55, 1.96) proportional hazard analyses. However, a small non-significant adjusted risk (HR = 1.29; 95%CI = 0.58, 2.88) was seen for those in the highest tertile (>or=2.38 U/mL) of positivity. GADA-positive and GADA-negative non-diabetic individuals had similar risk profiles for diabetes, with central obesity and elevated inflammation markers, aside from glucose, being the main predictors. Among diabetes cases at study's end, progression to insulin treatment increased monotonically as a function of baseline GADA level. Overall, being GADA positive increased risk of progression to insulin use almost 10 times (HR = 9.9; 95%CI = 3.4, 28.5). In conclusion, in initially non-diabetic middle-aged adults, GADA positivity did not increase diabetes risk, and the overall baseline profile of risk factors was similar for positive and negative individuals. Among middle-aged adults, with the possible exception of those with the highest GADA levels, autoimmune pathophysiology reflected by GADA may become clinically relevant only after diabetes onset.
authors.affiliation: Programa de Pós-Graduação em Epidemiologia, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brasil. alvaro.vigo@ufrgs.br
authors.forename: A
authors.initials: A
authors.lastname: Vigo
authors.forename: B B
authors.initials: BB
authors.lastname: Duncan
authors.forename: M I
authors.initials: MI
authors.lastname: Schmidt
authors.forename: D
authors.initials: D
authors.lastname: Couper
authors.forename: G
authors.initials: G
authors.lastname: Heiss
authors.forename: J S
authors.initials: JS
authors.lastname: Pankow
authors.forename: C M
authors.initials: CM
authors.lastname: Ballantyne
mesh_terms: D017668:Age of Onset; D001323:Autoantibodies / Q000097:blood* / Q000276:immunology; D015415:Biomarkers / Q000097:blood; D015331:Cohort Studies; D003920:Diabetes Mellitus / Q000201:enzymology / Q000276:immunology*; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005968:Glutamate Decarboxylase / Q000276:immunology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011863:Radioimmunoassay; D012307:Risk Factors
chemical_list: D001323:Autoantibodies; D015415:Biomarkers; D005968:Glutamate Decarboxylase