获得性部分性脂肪萎缩患者长期随访研究

目的探讨获得性部分性脂肪萎缩疾病（APL）患者的临床特点、病程及对治疗的反应。方法回顾分析1991年至2012年北京协和医院诊断的3例APL患者的临床治疗及实验室检查资料,并进行长期随访。结果3例患者均为女性,起病年龄均为10岁左右,诊断年龄20～62岁,随访2～12年。3例患者均有上半身脂肪明显减少下半身脂肪不变或增加,均患有糖尿病,有明显高胰岛素血症、高甘油三酯血症及脂肪肝,最严重患者甘油三酯达48．32mmol/L。2例患者补体C3降低。2例患者有正常月经,其中1例患者正常妊娠。例3患者（65岁）有轻度颈动脉内中膜增厚。3例患者均无肾小球肾炎,均未合并其他自身免疫疾病,均无糖尿病微血管并发症。采用以吡格列酮为基础的药物治疗,血糖控制基本满意,甘油三酯可基本控制于正常范围,但患者上半身脂肪萎缩情况无明显改善。结论APL患者通过以吡格列酮为基础的治疗,可以获得基本良好的代谢控制,但是脂肪萎缩情况无明显改善。     

糖尿病血糖控制与C肽水平相关性研究

对36例2型糖尿病患者,用胰岛素强化治疗.对血糖和C肽结果进行相关分析.结果治疗后C肽水平于60′、120′差异有显著性.从而提示2型糖尿病病人在高血糖时存在一种可逆性的C肽分泌受抑制现象.结论2型糖尿病"高糖抑制"解除后胰岛B细胞分泌功能部分好转.     

糖尿病血糖控制与C肽水平相关性研究

对36例2型糖尿病患者，用胰岛素强化治疗。对血糖和C肽结果进行相关分析。结果治疗后C肽水平于60’、120’差异有显著性。从而提示2型糖尿病病人在高血糖时存在一种可逆性的C肽分泌受抑制现象。结论2型糖尿病“高糖抑制”解除后胰岛B细胞分泌功能部分好转。     

2型糖尿病合并肢体部分性脂肪萎缩:一种新的脂肪萎缩表型

脂肪萎缩在糖尿病患者中并不罕见,2013年8期Diabetes Care刊登了Stricklan等的《2型糖尿病合并肢体部分性脂肪萎缩》一文,该文介绍了一种新的脂肪萎缩表型。来自NIH的Rother与Brown对该文进行了文献复习和评论。鉴于目前我国和全球T2DM患病者迅猛增加,而脂肪萎缩也是糖尿病合并症之一,为了引起临床医师对本合并症的重视,避免误漏诊,编辑部特将此二文介绍给本刊读者以供参考。     

先天性全身脂肪萎缩性糖尿病的分子发病机制

先天性全身脂肪萎缩性糖尿病(CGL),也称Berardinell-Seip综合征,属常染色体隐性遗传,主要表现为全身脂肪萎缩、胰岛素抵抗、高甘油三酯血症和肝脂肪变性.近年,通过定位克隆的方法,在CGL家系中筛选出2个致病基因,即AGPAT2(BSCL1)和BSCL2,分别编码1-酰基甘油-3-磷酸-O-酰基转移酶2和seipin蛋白.AGPAT2突变导致脂肪细胞甘油三酯合成和储存障碍,而seipin蛋白的功能目前仍不清楚.致病基因的鉴定和克隆有助于CGL的分子诊断.     

瘦素与2型糖尿病心肌病变

2型糖尿病患者多存在高瘦素血症和瘦素抵抗，高瘦素血症和瘦素抵抗导致在心肌细胞内脂质沉积和脂肪氧化增加；高瘦素血症通过作用于下丘脑增强交感神经活性，加重心脏负荷和增加心肌脂肪氧化。脂肪氧化增加、脂质沉积和心脏负荷加重可损伤心肌细胞，促进糖尿病心肌病变的发生。因此，瘦素与2型糖尿病心肌病变的关系密切。     

2型糖尿病患者单核细胞内皮黏附功能的改变

2型糖尿病是动脉粥样硬化性疾病的高危因素,2型糖尿病中的高血糖常与其并存的胰岛素抵抗、高胰岛素血症和高甘油三酯血症等均与此有关,但这些代谢异常与动脉粥样硬化之间的联系机制目前还不清楚.单核细胞黏附到血管内皮是动脉粥样硬化在细胞水平的第一步.已有人初步在糖尿病动物模型和糖尿病患者中发现单核细胞对血管内皮的黏附性增强.本研究旨在观察糖尿病患者外周血单个核细胞对培养的血管内皮细胞的黏附性,以及血糖、胆固醇、甘油三酯、胰岛素浓度和体重指数等与该黏附性的关系.     

LMNA基因突变所致家族性部分脂肪萎缩综合征2型二例报道

家族性部分脂肪萎缩综合征2型（FPLD2）是LMNA基因突变引起的常染色体显性遗传病，其特征是四肢脂肪丢失，颈面部脂肪堆积，可能导致类似库欣的外观以及其他IR表现。本文报道2例FPLD2患者，临床表现差异大，需结合基因检测明确诊断。     

老年2型糖尿病标准脂餐后胰岛素及C肽的分析

对30例老年2型糖尿病患者及10例健康老年人空腹及标准脂肪餐后2h,4h,6h,8h胰岛素及C肽水平进行同步测定并加以分析.结果 各时点胰岛素,老年糖尿病组高于对照组,空腹,餐后6h及8h统计学上有显著差异(P＜0.05);老年糖尿病组各时点C肽水平低于对照组,有显著差异(P＜0.05).结论老年2型糖尿病患者标准脂肪餐后胰岛素及C肽分泌试验出现分离现象,即出现高胰岛素低C肽现象,为今后2型糖尿病患者使用C肽治疗奠定理论基础.     

老年2型糖尿病标准脂餐后胰岛素及C肽的分析

对30例老年2型糖尿病患者及10例健康老年人空腹及标准脂肪餐后2h，4h，6h，8h胰岛素及C肽水平进行同步测定并加以分析。结果各时点胰岛素，老年糖尿病组高于对照组，空腹，餐后6h及8h统计学上有显著差异（P〈0．05）：老年糖尿病组各时点C肽水平低于对照组，有显著差异（P〈0．05）。结论老年2型糖尿病患者标准脂肪餐后胰岛素及C肽分泌试验出现分离现象，即出现高胰岛素低C肽现象，为今后2型糖尿病患者使用C肽治疗奠定理论基础。     

Preventing type 2 diabetes after gestational diabetes

PURPOSE: The purposes of this article are to examine the epidemiology of gestational diabetes mellitus (GDM) and subsequent type 2 diabetes, identify risk factors for the development of GDM and subsequent type 2 diabetes, discuss protocols for postpartum screening, and recommend evidence-based interventions to delay or prevent type 2 diabetes after GDM. METHODS: A review of the research literature from 1995 to 2005 concerning gestational diabetes was done using MEDLINE, CINAHL, National Institutes of Health, and American Diabetes Association internet resources. The criteria set for selection included the following: the research explored risk factors for and epidemiology of gestational diabetes, the relationship of gestational diabetes and the subsequent development of type 2 diabetes, and/or the prevention of type 2 diabetes after GDM. RESULTS: Women with pregnancies complicated by GDM are at increased risk for subsequent development of type 2 diabetes. Research suggests that modification of lifestyle-based risk factors including obesity, poor nutrition, and lack of exercise can delay or prevent the onset of type 2 diabetes in these women. However, there is evidence that recommended postpartum screening protocols for women with GDM are not being followed; hence, those women at high risk for type 2 diabetes are not identified, and no intervention is undertaken to reduce their risks. CONCLUSIONS: Diabetes educators must play an integral role in increasing awareness of the need for postpartum screening and intervention for women with gestational diabetes. Only with early identification and intensive intervention can the devastating toll of diabetes be averted for many of these women.     

Beyond type 2 diabetes: sodium glucose co-transporter-inhibition in type 1 diabetes

Use of sodium glucose cotransporter (SGLT) inhibitors are a well-established therapeutic option in type 2 diabetes (T2D) with a variety of proven therapeutic benefits. They have become a pillar of current treatment guidelines. In type 1 diabetes (T1D), initial exploratory studies have shown benefits in glycemic control, weight control, and cardiovascular risk parameters, leading to trials aiming for regulatory submission with several agents. Results from four 1-year trials, which included a total of 3052 patients, are now available, demonstrating promising findings that target the unmet needs of patients with T1D with a novel insulin-independent adjunct therapy. However, these positive effects must be balanced against the risks associated with this class of drugs. Specifically, current T1D studies have shown an increased risk of diabetic ketoacidosis (DKA), which, in some cases, presented with only slightly elevated glucose levels. While this complication may be clinically manageable once detected, the metabolic shift towards ketogenesis associated with this class of agents mandates appropriate patient selection. Currently, there are no validated tools for DKA risk assessment. Although the experience gained in studies and off-label use provides some indication for appropriate patient selection, this would have to be evaluated closely in the event that these drugs would receive regulatory approval. Risk mitigation includes training in ketone measurement (preferably as blood β-hydroxybutyrate testing), teaching the concept of euglycemic DKA, and providing a clear treatment algorithm to avoid progression of ketosis to full-blown DKA. Because similar unmet needs also exist in pediatric population studies, risk mitigation in youth should be initiated as well to allow an evidence-based, risk-benefit assessment in this vulnerable population.     

No association of multiple type 2 diabetes loci with type 1 diabetes

Aims/hypothesis  

We used recently confirmed type 2 diabetes gene regions to investigate the genetic relationship between type 1 and type 2 diabetes, in an average of 7,606 type 1 diabetic individuals and 8,218 controls, providing >80% power to detect effects as small as an OR of 1.11 at a false-positive rate of 0.003.     

暴发性1型糖尿病研究现状

暴发性1型糖尿病起病急骤,病情进展迅速,短期内胰岛β细胞几乎全部破坏,临床上常以严重的酮症酸中毒为首发症状,但糖化血红蛋白却接近正常,并叮伴有胰酶水平的升高.该病在亚洲人群中多见,其确切的发病机制尚不清楚,目前认为是遗传和环境凶素共同作用的结果.现时暴发性1型糖尿病的流行病学特点、临床及免疫学特征、发病机制、诊断标准、治疗及预后进行综述.     

Predicting type 1 diabetes

Predicting type 1 diabetes mellitus (T1DM) is a prerequisite for disease prevention. Prediction is currently performed on three levels, which include the genetic susceptibility for disease, the identification of preclinical T1DM by way of circulating islet autoantibodies, and the use of metabolic tests to stage preclinical disease into late or early prediabetes. Combinations of genetic markers such as HLA genotype, INS genotype, and if and how much family history of T1DM is present can stratify disease risk more than 1000-fold, and can be used for selection of first-degree relatives of patients with T1DM for primary intervention trials. Measurement of autoantibodies in genetically at-risk subjects identifies future cases of T1DM. Further stratification of diabetes risk in autoantibody-positive subjects can be made on the basis of autoantibody characteristics that correspond to the magnitude of the autoantibody response.     

Autoimmune markers in slow type 1 diabetes: confrontation to type 1 diabetes

Slow onset type 1 diabetes is an heterogeneous entity. Its clinical features may mimick type 2 diabetes but its pathophysiological mechanisms are close to type 1 diabetes. AIM OF THE STUDY: To find out the frequencies, levels and associations of ICA, GADab and IA-2ab in type 2 diabetic patients with atypical phenotype. To compare it to type 1 diabetes. PATIENTS AND METHODS: ICA, GADab and IA-2ab were determined in: - 61 patients (age at diagnosis 48.2 +/- 10, range 36-73 years) with an initial diagnosis of type 2 diabetes but having at least one symptom suggesting a slow type 1 diabetes (loss of weight, absence of obesity at diagnosis or secondary failure of oral hypoglycaemic agents). - 70 patients with type 1 diabetes (age 18 +/- 8.9, range 2-35 years). Clinical data evaluated in slow type 1 were maximal BMI, BMI and loss of weight at diagnosis and autoimmune disease. Fasting C-peptide and insulinemia were also assessed. RESULTS: (Slow type 1 diabetes versus type 1 diabetes). ICA (43% vs 70%; p <0.01) and IA-2ab (16% vs 75%; p <0.01) were more frequent in type 1. GADab were as frequent (62% vs 74%). Association of the three antibodies (15.7% vs 58.5%; p <0.05) were more frequent in type 1. Prevalence of GADab alone (27.5% vs 7.5%; p <0.05) was higher in slow type 1 diabetes and with higher levels (median 55.5 UI/ml vs 17 UI/ml; p <0.01). There was no difference for levels of ICA (25.5 UJDF/ml vs 28 UJDF/ml) or IA-2ab (11.5 UI/ml vs 38.5 UI/ml). BMI of GADab positive patients was lower. Delay of insulinotherapy was shorter in GADab or ICA positive patients. We did not find any relationship between antibodies presence and fasting C-peptide or insulinemia. CONCLUSION: Slow type 1 diabetes should be evoked in atypical type 2 diabetes. Slow onset type 1 diabetic patients have different autoimmune patterns suggesting a different pathophysiological process. GADab and ICA are useful markers to predict future insulinopenia.     

Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes

Aims/hypothesis

More than 40 regions of the human genome confer susceptibility for type 1 diabetes and could be used to establish population screening strategies. The aim of our study was to identify weighted sets of SNP combinations for type 1 diabetes prediction.

Methods

We applied multivariable logistic regression and Bayesian feature selection to the Type 1 Diabetes Genetics Consortium (T1DGC) dataset with genotyping of HLA plus 40 SNPs within other type 1 diabetes-associated gene regions in 4,574 cases and 1,207 controls. We tested the weighted models in an independent validation set (765 cases, 423 controls), and assessed their performance in 1,772 prospectively followed children.

Results

The inclusion of 40 non-HLA gene SNPs significantly improved the prediction of type 1 diabetes over that provided by HLA alone (p?=?3.1?×?10^?25), with a receiver operating characteristic AUC of 0.87 in the T1DGC set, and 0.84 in the validation set. Feature selection identified HLA plus nine SNPs from the PTPN22, INS, IL2RA, ERBB3, ORMDL3, BACH2, IL27, GLIS3 and RNLS genes that could achieve similar prediction accuracy as the total SNP set. Application of this ten SNP model to prospectively followed children was able to improve risk stratification over that achieved by HLA genotype alone.

Conclusions

We provided a weighted risk model with selected SNPs that could be considered for recruitment of infants into studies of early type 1 diabetes natural history or appropriately safe prevention.     

Neutrophils in type 1 diabetes

Type 1 diabetes is an autoimmune disease that afflicts millions of people worldwide. It occurs as the consequence of destruction of insulin‐producing pancreatic β‐cells triggered by genetic and environmental factors. The initiation and progression of the disease involves a complicated interaction between β‐cells and immune cells of both innate and adaptive systems. Immune cells, such as T cells, macrophages and dendritic cells, have been well documented to play crucial roles in type 1 diabetes pathogenesis. However, the particular actions of neutrophils, which are the most plentiful immune cell type and the first immune cells responding to inflammation, in the etiology of this disease might indeed be unfairly ignored. Progress over the past decades shows that neutrophils might have essential effects on the onset and perpetuation of type 1 diabetes. Neutrophil‐derived cytotoxic substances, including degranulation products, cytokines, reactive oxygen species and extracellular traps that are released during the process of neutrophil maturation or activation, could cause destruction to islet cells. In addition, these cells can initiate diabetogenic T cell response and promote type 1 diabetes development through cell–cell interactions with other immune and non‐immune cells. Furthermore, relevant antineutrophil therapies have been shown to delay and dampen the progression of insulitis and autoimmune diabetes. Here, we discuss the relationship between neutrophils and autoimmune type 1 diabetes from the aforementioned aspects to better understand the roles of these cells in the initiation and development of type 1 diabetes.