Martinez Maria Månsson, Spiliopoulos Lampros, Salami Falastin, Agardh Daniel, Toppari Jorma, Lernmark Åke, Kero Jukka, Veijola Riitta, Tossavainen Päivi, Palmu Sauli, Lundgren Markus, Borg Henrik, Katsarou Anastasia, Larsson Helena Elding, Knip Mikael, Maziarz Marlena, Törn Carina
Department of Clinical Sciences, Lund University CRC, Skåne University Hospital, Jan Waldenströms gata 35, Box 503 32, SE-214 28, Malmö, Sweden.
Department of Pediatrics, Turku University Hospital, Turku, Finland.
Clin Diabetes Endocrinol. 2022 Jan 5;7(1):23. doi: 10.1186/s40842-021-00135-6.
Individuals with multiple islet autoantibodies are at increased risk for clinical type 1 diabetes and may proceed gradually from stage to stage complicating the recruitment to secondary prevention studies. We evaluated multiple islet autoantibody positive subjects before randomisation for a clinical trial 1 month apart for beta-cell function, glucose metabolism and continuous glucose monitoring (CGM). We hypothesized that the number and type of islet autoantibodies in combination with different measures of glucose metabolism including fasting glucose, HbA1c, oral glucose tolerance test (OGTT), intra venous glucose tolerance test (IvGTT) and CGM allows for more precise staging of autoimmune type 1 diabetes than the number of islet autoantibodies alone.
Subjects (n = 57) at 2-50 years of age, positive for two or more islet autoantibodies were assessed by fasting plasma insulin, glucose, HbA1c as well as First Phase Insulin Response (FPIR) in IvGTT, followed 1 month later by OGTT, and 1 week of CGM (n = 24).
Autoantibodies against GAD65 (GADA; n = 52), ZnT8 (ZnT8A; n = 40), IA-2 (IA-2A; n = 38) and insulin (IAA; n = 28) were present in 9 different combinations of 2-4 autoantibodies. Fasting glucose and HbA1c did not differ between the two visits. The estimate of the linear relationship between log2-transformed FPIR as the outcome and log2-transformed area under the OGTT glucose curve (AUC) as the predictor, adjusting for age and sex was - 1.88 (- 2.71, - 1.05) p = 3.49 × 10-5. The direction of the estimates for all glucose metabolism measures was positive except for FPIR, which was negative. FPIR was associated with higher blood glucose. Both the median and the spread of the CGM glucose data were significantly associated with higher glucose values based on OGTT, higher HbA1c, and lower FPIR. There was no association between glucose metabolism, autoantibody number and type except that there was an indication that the presence of at least one of ZnT8(Q/R/W) A was associated with a lower log2-transformed FPIR (- 0.80 (- 1.58, - 0.02), p = 0.046).
The sole use of two or more islet autoantibodies as inclusion criterion for Stage 1 diabetes in prevention trials is unsatisfactory. Staging type 1 diabetes needs to take the heterogeneity in beta-cell function and glucose metabolism into account.
ClinicalTrials.gov identifier: NCT02605148 , November 16, 2015.
具有多种胰岛自身抗体的个体患临床1型糖尿病的风险增加,且可能会逐步发展,这使得二级预防研究的招募工作变得复杂。我们在一项临床试验随机分组前1个月,对多种胰岛自身抗体呈阳性的受试者进行了评估,以了解其β细胞功能、葡萄糖代谢及持续葡萄糖监测(CGM)情况。我们假设,与单独的胰岛自身抗体数量相比,胰岛自身抗体的数量和类型与包括空腹血糖、糖化血红蛋白(HbA1c)、口服葡萄糖耐量试验(OGTT)、静脉葡萄糖耐量试验(IvGTT)和CGM在内的不同葡萄糖代谢指标相结合,能够更精确地对自身免疫性1型糖尿病进行分期。
对年龄在2至50岁、两种或更多种胰岛自身抗体呈阳性的57名受试者进行了空腹血浆胰岛素、葡萄糖、HbA1c检测,以及IvGTT中的第一相胰岛素反应(FPIR)检测,1个月后进行OGTT检测,随后进行1周的CGM检测(n = 24)。
针对谷氨酸脱羧酶65(GADA;n = 52)、锌转运体8(ZnT8A;n = 40)、胰岛抗原2(IA - 2A;n = 38)和胰岛素(IAA;n = 28)的自身抗体以2至4种自身抗体的9种不同组合形式存在。两次检测时的空腹血糖和HbA1c无差异。以log2转换后的FPIR为结果变量、log2转换后的OGTT葡萄糖曲线下面积(AUC)为预测变量,并对年龄和性别进行校正后,二者线性关系的估计值为 - 1.88(- 2.71,- 1.05),p = 3.49×10 - 5。除FPIR为负外,所有葡萄糖代谢指标估计值的方向均为正。FPIR与更高的血糖相关。CGM葡萄糖数据的中位数和离散度均与基于OGTT的更高血糖值、更高的HbA1c以及更低的FPIR显著相关。除了有迹象表明至少存在一种ZnT8(Q/R/W)A与更低的log2转换后的FPIR相关(- 0.80(- 1.58,- 0.02),p = 0.046)外,葡萄糖代谢、自身抗体数量和类型之间无关联。
在预防试验中,仅将两种或更多种胰岛自身抗体作为1型糖尿病1期的纳入标准并不理想。对1型糖尿病进行分期需要考虑β细胞功能和葡萄糖代谢的异质性。
ClinicalTrials.gov标识符:NCT02605148,2015年11月16日。