Tests for genetic interactions in type 1 diabetes: linkage and stratification analyses of 4,422 affected sib-pairs

OBJECTIVE

Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions.

RESEARCH DESIGN AND METHODS

To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci.

RESULTS

Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci.

CONCLUSIONS

This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods.Type 1 diabetes is an autoimmune disease in which the insulin-producing β-cells are destroyed. The defective immune mechanisms in type 1 diabetes have not been identified, although clearly both genes and environmental factors contribute to risk (1,2). Many studies have been performed on the genetics of type 1 diabetes, and identification of the risk genes is ongoing. The Type 1 Diabetes Genetics Consortium (T1DGC) was established in response to the need to identify type 1 diabetes risk genes (3).The T1DGC has assembled DNA, sera, cell lines, and data from 17,129 individuals in 3,892 affected–sib-pair (ASP) families, representing the largest family collection in any immune-mediated disease. Using these resources, the T1DGC performed smaller genome-wide linkage studies (4,5) and association studies, finding 21 new loci (6). In addition, the T1DGC conducted the most detailed investigation of the HLA complex in disease, characterizing over 3,000 single nucleotide polymorphisms (SNPs), and independently tested all previously reported type 1 diabetes susceptibility genes (7,8; and associated special reports).From these and other studies, over 50 loci have been identified that affect the risk of developing type 1 diabetes (6) (www.t1dbase.org). Foremost among these is the HLA complex, which is long recognized as the most important risk factor in type 1 diabetes and other immune diseases. The second locus identified was INS, but this and other non-HLA loci have relatively minor risk effects comparable to loci mapped in other common diseases, with risk estimates typically between 1.05 and 2.0 (6).Despite the T1DGC’s success, not all the estimated familial heritability for type 1 diabetes has been found. Twin studies suggest ~80% of clustering is a result of sharing of susceptibility alleles at multiple loci. This issue of “missing heritability” also arises in other complex genetic diseases (9). A number of other issues pertaining to type 1 diabetes remain unresolved. For example, can it be subdivided into disease subtypes with different genetic etiology? Can we identify major genetic interactions in susceptibility? Are there loci with multiple rare risk alleles that may have gone undetected in association studies? Does genomic instability in the form of structural variants play a role?Motivated by these issues, we report here the genotyping of the final 1,583 T1DGC ASPs and perform linkage analyses on a total of 3,892 families and 17,129 individuals. The T1DGC family collection provides 80% power to search for loci undetectable by genome-wide association SNP scanning with effects of the same magnitude as the insulin gene with allelic odds ratio of ~2 and an allele frequency of 0.3. If there is residual “missing heritability” (i.e., loci that were not found by the SNP studies), this large dataset is a valuable resource to search for it. In this report, we describe a linkage search for genetic interactions in type 1 diabetes.     

Stepwise or linear decrease in penetrance of type 1 diabetes with lower-risk HLA genotypes over the past 40 years

OBJECTIVE

The objective of this study was to test if the proportion of new-onset diabetic subjects with the HLA-DR3/4-DQB1*0302 genotype is decreasing over time.

RESEARCH DESIGN AND METHODS

We analyzed HLA class II genotype frequencies over time in two large populations with type 1 diabetes diagnosed at ≤18 years of age. There were 4,075 subjects from the Type 1 Diabetes Genetics Consortium (T1DGC) and 1,675 subjects from the Barbara Davis Center (BDC).

RESULTS

Both T1DGC and BDC cohorts showed a decrease of the highest-risk HLA-DR3/4-DQB1*0302 genotype over time. This decrease was greatest over time in T1DGC subjects with age of onset ≤5 years (P = 0.004) and onset between ages 6 and 10 years (P = 0.002). The overall percent of HLA-DR3/4-DQB1*0302 was greater in the T1DGC population compared with the BDC population. There was an increased percent over time of other HLA genotypes without HLA-DR3 or -DR4 in T1DGC new onsets (P = 0.003), and the trend was similar in BDC subjects (P = 0.08). Analyzing time trend, there appears to be a large stepwise decrease in percent DR3/4 in the 1980s in T1DGC subjects with onset age <5 years (P = 0.0001).

CONCLUSIONS

The change in frequency of multiple different genotypes and a possible stepwise decrease in percent DR3/4 suggest a change in genetic risk factors and environmental determinants of type 1 diabetes. Larger studies are needed to confirm the changing pattern of genetic risk because a stepwise change may have direct bearing on defining critical environmental determinants of type 1 diabetes.The incidence of type 1 diabetes has been increasing worldwide by approximately 3% per year (1,2), with the highest increase occurring in young children (3,4). The major type 1 diabetes susceptibility locus maps to the HLA class II genes and accounts for 30–50% of genetic type 1 diabetes risk (5,6). Age at onset is inversely related to the frequency of high-risk HLA genotypes, with young children having the greatest proportion of HLA-DR3/4-DQB1*0302 genotype (7,8). Although 40% of Caucasians in the U.S. have an HLA-DR3 (with DQB1*0201) or -DR4 (with DQB1*0302) allele, at least one of these alleles is present in 95% of patients with type 1 diabetes. The estimated risk of developing type 1 diabetes for children in the general population who have the HLA DR3-DQB1*0201/DR4-DQB1*0302 genotype is ∼1:15–1:25 (9). Only 2.4% of the general population carries this genotype compared with 30–40% of type 1 diabetic patients. In siblings, HLA-DR3/4 heterozygosity identifies higher risk of type 1 diabetes than HLA identity (10). A combination of HLA-DR3/4 heterozygosity and HLA identity in siblings is associated with extreme diabetes risk of 55% by age 12 years in the Diabetes Autoimmunity Study in the Young (DAISY) population (11).However, as type 1 diabetes incidence increases, the percentage of those cases with high-risk HLA genotype is decreasing (12). A study from the U.K. (13) compared two cohorts and found a decrease in the high-risk HLA-DR3/4-DQB1*0302 genotype from 47% (Golden Years cohort diagnosed more than 50 years ago) to 35% in the more recently diagnosed cohort (between 1985–2002). Hermann et al. (8) reported a similar decrease in high-risk HLA genotypes over time (from 25 to 18%), although both of these studies (8,13) compared contemporary subjects with selective cohorts of surviving adults with childhood-onset type 1 diabetes. A study from Australia by Fourlanos et al. (14) with continuous information available reports a decrease in the high-risk HLA genotype from 79% in 1950–1969 to 28% in 2000–2005 in 462 subjects diagnosed before age 18 years; the authors conclude that the rising incidence of type 1 diabetes in childhood is accounted for by cases with lower-risk HLA genotypes.In this study, we analyze HLA class II allele frequencies over a time period ranging from 1965 to 2008 in two large populations of type 1 diabetic subjects diagnosed at age ≤18 years and describe a possible stepwise decrease in percent DR3/4.     

感恩问卷GQ-6的修订及信效度检验

目的了解感恩问卷GQ-6中文修订版在我国青少年群体中的测试情况,并考察其信效度。方法对广州市511名中学生进行初测,对1 396名中学生进行正式施测,并随机抽取其中205名进行4周后的重测,采用SPSS 11.5和AMOS 7.0软件进行数据处理。结果探索性和验证性因素分析表明,修订后的感恩问卷与原问卷具有相同的单因素结构,且模型拟合良好;效标效度良好(β1=-0.40,β2=-0.41,β3=0.30,P值均<0.01),效标分别为外化问题行为、焦虑抑郁和学业成就;内部一致性信度、分半信度和重测信度分别为0.81,0.82和0.70。结论修订后的感恩问卷具有较好的心理测量学属性,可作为评定我国青少年感恩的有效工具。     

Thirteen-year prospective study between fish consumption,long-chain N-3 fatty acids intakes and cognitive function

Objectives  

Because of their structural, anti-inflammatory and antithrombic properties, longchain n-3 fatty acids may be key factors in the aging process. We sought to elucidate the association between intake of long-chain n-3 fatty acids and/or fish and cognitive function evaluated 13 years after dietary assessment.     

我国老年人认知水平变化轨迹及其分化

目的 探究影响我国老年人认知水平的变化趋势，分离出年龄、队列效应。方法 基于CLHLS（2002—2018）多重队列追踪数据，以Stata16.0软件为工具，运用分层生长曲线模型进行统计分析。结果 本研究发现，个体行为生活方式、社会经济地位、性别、慢性病数量对认知水平均具有统计学意义；年龄、队列对认知水平的变化具有独立效应；随着年龄的增长，我国老年人认知水平下降，认知水平的城乡、性别差异明显；较年轻出生队列的老年人认知水平较好，认知水平的城乡差异随着队列的年轻化而变大，性别差异在较年轻队列有略微缩小的趋势。结论 影响认知水平因素复杂，认知障碍会增加医疗成本及照护负担，因此需准确把握老年认知水平的变化规律与作用路径，从而为卫生服务、养老保障、长期医疗照护的资源配置提供科学依据。     

PSMA-CAR-CIK转基因细胞体外杀伤三种前列腺癌细胞株效率的研究北大核心

目的:本研究通过检测前列腺特异性膜抗原(prostate specific membrane antigen,PSMA)-肿瘤特异性嵌合抗原受体(chimeric antigen receptor,CAR)-细胞因子诱导的杀伤细胞(cytokine induced killer cell,CIK)转基因细胞杀伤三种前列腺癌细胞株的效率,鉴定其用于后期治疗前列腺癌的可行性。方法:通过已经构建的二代PSMA-CAR慢病毒表达载体转染CIK细胞,构建PSMA-CAR-CIK转基因细胞;通过CCK8法检测CIK细胞及PSMA-CAR-CIK转基因细胞杀伤三种前列腺癌细胞株PC3、LNCaP、DU145的效率及效靶比。结果:转基因PSMA-CAR-CIK细胞构建成功;3 h~3.5 h为检测效应细胞对靶细胞细胞毒活性时与CCK8试剂孵育的最佳时间;两种效应细胞均在效靶比为10∶1、15∶1、20∶1时,杀伤率逐步增高,无统计学意义(P>0.05),但与其它组相比差异显著(P<0.05)。结论:两种效应细胞对于前列腺癌细胞的杀伤,只要效靶比达到10∶1的比例,就能起到一个较好的杀瘤效果,并且随着效应细胞的增加,其抗肿瘤能力逐步加强;转基因PSMA-CAR-CIK细胞的构建为CAR技术治疗前列腺癌的临床应用奠定了基础。     

外泌体在肿瘤细胞与TAMs之间相互作用中“桥梁”和调控作用的研究进展北大核心

外泌体是一类直径为30~100 nm的圆盘囊泡,其内包含许多组分,诸如复杂RNA和蛋白质等,主要参与细胞间的信号转导。肿瘤相关巨噬细胞(tumor-associated macrophages,TAMs)是肿瘤微环境中普遍存在的巨噬细胞,通过对肿瘤生长、免疫逃逸、侵袭和转移、耐药性等多方面的作用影响肿瘤进程。外泌体在肿瘤相关巨噬细胞的招募、极化及抗肿瘤免疫调控等方面发挥着重要的调节功能。同时,TAMs以外泌体为媒介作用于肿瘤细胞,从而构成了外泌体、TAMs与肿瘤细胞之间相互作用的调控通路。综上所述,本文旨在阐明肿瘤细胞与TAMs之间,以外泌体为“桥梁”相互影响的潜在机制,以及靶向肿瘤细胞和TAMs来源的外泌体在恶性肿瘤治疗中的展望。     

成都市女性社区居民对宫颈癌及人乳头瘤病毒的认知度调查研究

目的 了解成都市女性社区居民对宫颈癌及HPV的基线认知水平；评价以医务人员为主导的健康教育能否有效提高社区居民宫颈癌相关认知水平。方法 2015 - 2018年每年妇女节期间通过对社区女性进行问卷调查，比较4年间（2015 - 2018）培训前后社区女性认知水平的变化情况以及疫苗上市前（2015 - 2016）和疫苗上市后（2017 - 2018）社区女性基线认知的变化。结果 健康教育前、后有效问卷分别为591、449份。健康教育前，32.1%的调查对象认为HPV病毒感染是引起宫颈癌最重要的原因，47.2%认为HPV的传播途径为性传播，25.2%认为HPV疫苗接种的最佳年龄为初次性生活前；健康教育后，以上比例分别增长至45.4%、73.7%、62.8%（P均＜0.05）。疫苗上市后，基线愿意接受筛查的调查对象比例由疫苗上市前的95.4%下降到86.1%（P＜0.05）。“医院展板”对基线认知的影响最大，接触过该途径人群的平均认知得分比未接触人群高3.4分（P＜0.05）。结论 成都市社区女性对宫颈癌及HPV相关的基线认知水平较低，疫苗上市后筛查意愿有明显下降趋势。以医院医生为主导的宫颈癌及HPV健康教育应当纳入社区人群健康教育的常规模式，同时应加强宣传疫苗接种后仍应进行宫颈癌筛查的重要性。     

吸毒人员回归社会后的应对方式与生活质量——自我概念的中介作用

目的 本研究旨在探讨吸毒人员回归社会后的自我概念及应对方式是否会影响其生活质量。方法 在四川省成都市、德阳市、西昌市、宜宾市等地招募201名已回归社会的男性吸毒人员（平均年龄22.65±8.31岁，年龄16~59岁）进行调查。参与者完成田纳西自我概念量表（TSCS）、特质应对方式问卷（TCSQ）和药物成瘾者生命质量测定量表（QOL-DA）。结果 高自我概念组吸毒人员的积极应对得分和生活质量均高于低自我概念组，差异具有统计学意义（P<0.05）；吸毒人员的自我概念在积极应对与生活质量之间的中介效应值为0.224（95%CI:0.063~0.434），中介效应显著，占总效应的26.4%。结论 自我概念介导了回归社会的吸毒人员应对方式与生活质量之间的关系，应在学校和特定社区开展提高自我概念和应对技巧的培训。     

IL-1β基因多态性与汉族人群抑郁障碍相关性研究

目的:探讨白细胞介素（IL）-1β基因多态性与汉族人群生活事件及抑郁障碍的关系。方法:共纳入重性抑郁障碍患者433例作为病例组，并纳入基本情况相匹配的正常对照者421名作为对照组 。以HAMD-17方法分别评定两组受试者抑郁障碍的严重程度，同时以生活事件量表（LES）对病例组近1年的生活事件进行评定。从被试者静脉血中提取基因组DNA，选取IL-1β基因上3个位点:rs13032029 、rs1143623和rs3917368。采用以基质辅助激光解吸电离飞行时间质谱（MALDI-TOF-MS）进行候选基因多态性位点基因分型。运用SPSS22.0统计软件包进行数据分析。结果:在病例组和对照组中，IL-1 β基因rs13032029位点的基因型频率分别为:CC型28.6%和28.5%，CT型47.3%和52.7%，TT型23.8%和18.5%，差异无统计学意义（?字2=4.028，P=0.258）。在病例组和对照组中，rs1143623位点基因型频 率分别为:CC型36.5%和31.1%，GC型45.3%和51.8%，GG型18.0%和16.6%，差异无统计学意义（?字2=4.29，P=0.232）。在病例组和对照组中，rs3917368位点基因型频率分别为:CC型24.5%和25.4%，CT型 47.6%和46.6%，TT型27.3%和27.6%，差异无统计学意义（?字2=0.302，P=0.960）。3个位点不同基因型患者的HAMD总分、各条目之间的差异没有统计学意义。LES总分及生活事件的多元回归分析差异无统 计学意义。结论:未发现IL-1β基因rs13032029、rs1143623和rs3917368基因多态性与汉族人群生活事件和抑郁障碍的发病存在相关性。