Scania Diabetes Registry

The Scania Diabetes Registry contains over 7000 diabetes patients recruited at hospitals in Scania, Sweden as from 1996. The majority of the patients come from the city of Malmö, and they account for about 25% of all diabetic patients in the region. At the clinic, all patients with Diabetes Mellitus were asked if they would like to participate in Scania Diabetes Registry. The diagnosis of the diabetes was made in the clinic, and the majority of patients were on antidiabetic treatment. Additional information has been added from the routinely clinical follow-ups. Information about onset of diabetes, and mode of treatment, BMI, HbA1C, creatinine, lipids, albumin excretion rate (AER) as well as smoking habits was obtained from patient records. In addition, blood samples were obtained for measurement of C-peptide, GAD antibodies and for DNA. Follow-up information on metabolic control, progression of disease, development of diabetic complications is obtained from patient records. Information includes retinopathy, nephropathy, neuropathy and macrovascular diseases. Purpose: To 1) Create a databank and bio-bank of all available diabetic patients in Scania to allow more precise classification of diabetic subgroups, 2) identify genetic variants predisposing to micro and macrovascular complications 3) study how the identified biomarkers and genetic markers can predict development and progression of complications and 4) identify means to prevent the development of these complications.斯科讷糖尿病登记处（Scania Diabetes Registry）自1996年起，收录了瑞典斯科讷地区多家医院招募的7000余名糖尿病患者。其中绝大多数受试者来自马尔默市，该群体约占该地区全部糖尿病患者的25%。该登记处的招募流程为：诊所内所有确诊为糖尿病（Diabetes Mellitus）的患者均会被征询是否愿意加入斯科讷糖尿病登记处。患者的糖尿病诊断均在就诊诊所内完成，且多数受试者已接受抗糖尿病治疗。额外补充的研究数据来源于常规临床随访记录。 研究人员可从患者病历中获取多项临床信息，包括糖尿病起病时间、治疗方案、体重指数（Body Mass Index, BMI）、糖化血红蛋白（HbA1C）、肌酐、血脂、白蛋白排泄率（Albumin Excretion Rate, AER）以及吸烟习惯等。此外，还采集了血液样本，用于检测C肽、谷氨酸脱羧酶（GAD）抗体及脱氧核糖核酸（DNA）。代谢控制情况、疾病进展及糖尿病并发症发生发展的随访信息同样取自患者病历，涵盖视网膜病变、肾病、神经病变及大血管病变等多种并发症类型。 研究目标如下： 1） 构建斯科讷地区所有符合条件的糖尿病患者的数据库与生物样本库，以实现对糖尿病亚组的精准分类； 2） 筛选出与微血管及大血管并发症易感相关的遗传变异； 3） 探究已识别的生物标志物与遗传标记如何预测并发症的发生与进展； 4） 明确预防此类并发症发生的有效干预手段。