Using a genome-wide scan and meta-analysis to identify a novel IBD locus and confirm previously identified IBD loci

Seven loci that potentially confer susceptibility to inflammatory bowel disease (IBD) or one of its subtypes have been identified to date; however, most are unconfirmed, and the complete set of loci contributing to disease susceptibility has not yet been determined. The authors aim to identify loci contributing to disease susceptibility in an IBD population from Canada and to compare their results in a systematic manner with those of previously published IBD data sets. The authors performed genome-wide linkage analysis on 63 IBD families from Nova Scotia, Canada. They then undertook a meta-analysis to combine the results of their study with those of the four previously published IBD genome-wide scans with complete data reported. Their genome-wide scan identified three regions of suggestive linkage to IBD: 11p, and The locus on chromosome 11p has not been previously reported. Meta-analysis of multiple scans revealed linked regions corresponding to the, and loci. Meta-analysis of linkage data is a powerful approach for identifying and confirming common susceptibility loci and specifically shows that, and are the major, common IBD susceptibility loci in the populations studied thus far.     

A German genome-wide linkage scan for type 2 diabetes supports the existence of a metabolic syndrome locus on chromosome 1p36.13 and a type 2 diabetes locus on chromosome 16p12.2

Aims/hypothesis The aim was to identify type 2 diabetes susceptibility regions in 250 German families. Subjects and methods We conducted a genome-wide linkage scan using 439 short tandem repeat polymorphisms at an average resolution of 7.76 ± 3.80 cM (Marshfield). In an affected-only-design (affected sib pairs), we performed nonparametric multipoint linkage analyses. Conditional analyses were applied where linkage signals were found in the baseline analyses. Results We identified two loci with nominal evidence for linkage on chromosomes 1p36.13 and 16p12.2 (D1S3669, 37.05 cM, logarithmic odds ratio [LOD] = 1.49, p = 0.004; D16S403, 43.89 cM, LOD = 1.85, p = 0.002). D16S403 crossed the empirically obtained threshold of genome-wide suggestive significance of LOD = 1.51. Positive findings in those regions have been reported by the following other linkage studies on: (1) symptomatic/clinical gall bladder disease with type 2 diabetes in Mexican Americans from the San Antonio Family Diabetes/Gallbladder Study (LOD = 3.7, D1S1597–D1S407, 29.93–33.75 cM); (2) body size-adiposity in another Mexican American population (D1S1597, LOD = 2.53, 29.93 cM); (3) lipid abnormalities (LOD = 3.1, D1S2826–D1S513, 41.92–60.01 cM); and (4) hypertension in Australian sib pairs (LOD = 3.1, D1S2834–D1S2728, 31.02–33.75 cM); as well as (5) a meta-analysis of four European type 2 diabetes-related genome scans (LOD = 1.09, D16S412, 42.81 cM). In linkage analyses conditional on evidence for linkage at D16S403 we identified a LOD increase (ΔLOD) of 1.55 (p = 0.0075) at D17S2180. Similar conditioning on D17S2180 revealed evidence for interaction with D1S3669 (ΔLOD = 1.67, p = 0.0055), D16S403 (ΔLOD = 1.48, p = 0.0091) and another locus on chromosome 1 where several genome scans have reported evidence for linkage (∼200 cM, ΔLOD = 1.60, p = 0.0066). Conclusions/interpretation Our results and the findings of other studies are consistent with the presence of a locus for a complex metabolic syndrome on chromosome 1p36.13. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorised users.     

强直性脊柱炎全基因组扫描易感基因研究的Meta分析

目的通过强直性脊柱炎(AS)全基因组扫描研究,进一步确定AS遗传易感基因的染色体区域定位。方法2007年12月于山东省立医院图书馆检索分析已发表的有关AS和血清阴性脊柱关节病(SpA)的全基因扫描文献结果,采用全基因组扫描研究的Meta分析(GSMA)软件进行分析。结果4项AS全基因组扫描研究共纳入479个家系1151例AS患者,GSMA结果显示5个区域最可能含有AS的易感位点,分别是6p22.3-p21.1、6pter-p22.3、17pter-p12、2p12-q22.1和5q34-qter。5项AS和SpA全基因组扫描研究共纳入544个家系1331例AS和SpA患者,GSMA结果发现6p22.3-p21和16q23.1-qter2个区域最可能含有AS的易感位点。结论GSMA显示6p22.3-p21.1是AS显著连锁区域,6pter-p22.3、17pter-p12、2p12-q22.1、5q34-qter和16q23.1-qter是AS的连锁区域。     

Type 2 diabetes candidate gene <Emphasis Type="Italic">CAPN10:</Emphasis> First,but not last

CAPN10, which encodes the cysteine protease calpain 10, was the first type 2 diabetes mellitus (T2DM) susceptibility gene identified through a genome-wide scan followed by positional cloning. A haplotype combination comprising three intronic CAPN10 single-nucleotide polymorphisms (UCSNP-43, -19, and -63) was associated with increased risk of T2DM in the population in which linkage was first found. Follow-up studies have been published from a wide range of populations; some confirm the original finding, but some do not. The exact function of calpain 10 remains to be determined, but it has been implicated both in glucose transporter 4 translocation to the cell membrane, regulation of pancreatic insulin secretion, and pancreatic β-cell apoptosis. This article reviews the genetic evidence for the association between CAPN10 and T2DM. The latest understanding of the biologic function of calpain 10 is discussed, along with results from recent genome-wide association studies that have failed to put CAPN10 among the top signals.     

A genome-wide scan in type 2 diabetes mellitus provides independent replication of a susceptibility locus on 18p11 and suggests the existence of novel Loci on 2q12 and 19q13

A genome-wide scan was performed, using nonparametric linkage analyses, to find susceptibility loci for type 2 diabetes mellitus in the Dutch population. We studied 178 families from The Netherlands, who constituted 312 affected sibling pairs. The first stage of the genome scan consisted of 270 DNA markers, with an average intermarker spacing of 13 cM. Because obesity and type 2 diabetes mellitus are interrelated, the data set was stratified for the subphenotype body mass index, corrected for age and gender. This resulted in a suggestive maximum multipoint LOD score of 2.3 (single-point P value, 9.7 x 10(-4); genome-wide P value, 0.028) for the most obese 20% pedigrees of the data set, between marker loci D18S471 and D18S843. In the lowest 80% obese pedigrees, two interesting loci on chromosome 2 and 19 were found, with LOD scores of 1.5 and 1.3. We provide independent evidence that the chromosome 18p11 locus, reported earlier from a Finnish/Swedish population, is of definite interest for type 2 diabetes mellitus in connection with obesity. Subsequently, our results indicate that two novel loci may reside on chromosomes 2 and 19, with minor effects involved in the development of type 2 diabetes mellitus in the Dutch population.     

Genetics of type 2 diabetes

After several years of uncertain progress, the stage is now set for a transformation in understanding the genetic landscape of type 2 diabetes. Advances in genome informatics, genotyping technology, and statistical methodology, allied to availability of large-scale clinical material, are having a salutary effect on susceptibility gene discovery. The advent of genuinely genome-wide association scans and the prospects for combining genetics with high-throughput genomics are additional sources of optimism for the future.     

An updated meta-analysis of genome scans for hypertension and blood pressure in the NHLBI Family Blood Pressure Program (FBPP)

A meta-analysis of the results from a multicenter genome-wide linkage study for hypertension and blood pressure (BP) based on an initial sample of 6,245 individuals was published in 2003. We report here a combined linkage analysis of hypertension and BP using the complete Family Blood Pressure Program (FBPP) dataset, which includes a total of 12,028 genotyped individuals. Genome-wide linkage analyses for hypertension and BP were first performed in each of the studied ethnic group within each network and the results were combined with a meta-analysis using a modified Fisher's method of combining P values. Our meta-analysis of genome scans for the latest FBPP dataset reveals suggestive linkage for hypertension and BP at several regions on the human genome. Strong evidence for linkage at two of these regions, 2p14 and 3p14.1, have also been published in previous meta-analyses, making them good candidate locations for susceptibility variants.     

Genome-wide association scans identify multiple confirmed susceptibility loci for Crohn's disease: lessons for study design

The last 12 months have seen unprecedented progress in identifying the susceptibility genes that predispose to common disease in general and Crohn's disease in particular. Success has derived from the new technique of genome-wide association scanning in large panels of cases and controls. This has itself been made possible by the sequencing of the human genome,12 development of a map of common human haplotype structure (HapMap),3 and advances in genotyping technologies permitting ascertainment of hundreds of thousands of genetic variants in multiple individuals. Several previously unsuspected pathways particularly relating to innate immunity and the early host response to bacteria have been revealed as key determinants of Crohn's disease susceptibility. These will provide a solid foundation for directed functional and translational research. Further, the wealth of confirmed association data coming from unbiased surveys of the genome provided by genome-wide association scans provide several key pointers regarding design and analysis of inflammatory bowel disease genetics studies in the future.     

Calpain 10 and genetics of type 2 diabetes

Positional cloning studies conducted on a region of chromosome 2q providing evidence for linkage to type 2 diabetes implicated genetic variation at the calpain-10 gene (CAPN10) in susceptibility to type 2 diabetes. The variants identified in these studies are located in introns, rather than in coding sequence. It was proposed that the cumulative effects of a combination of variants, rather than variation at a single site, increase the risk of type 2 diabetes. Confirmation of the hypothesis that non-coding sequence variation in CAPN10 affects susceptibility to type 2 diabetes has implications for how we search for susceptibility variants and interpret results of positional cloning studies for complex disorders, and suggests a new pathway in glucose homeostasis. We review the results of follow-up studies on the CAPN10 finding, and consider the issues inherent in conclusively establishing that particular genetic variation affects a complex phenotype.     

The search for type 2 diabetes susceptibility loci: The chromosome 1q story

The unbiased approach of genome-wide linkage analysis has shown evidence for linkage of type 2 diabetes mellitus to the chromosome 1q21–25 region in at least eight independent studies. More than 26 candidate genes have already been evaluated, but to date none explain the evidence for linkage in this gene-dense region. Considerable data suggest that multiple genes account for this linkage result. The search for these genes is now the focus of an international consortium of groups reporting linkage of type 2 diabetes to this region of chromosome 1q21–q25.     

Genetic determinants of the metabolic syndrome

Complex interactions between inherited factors and the environment determine an individual’s susceptibility to type 2 diabetes mellitus and related syndromes. Insulin resistance, obesity, hypertension, and hyperlipidemia frequently precede the development of frank diabetes and aggregate in families. Several genome-wide scans have recently been performed in families with this constellation of findings, called the “metabolic syndrome.” These analyses strongly support an inherited component to the syndrome. In this review, we provide an overview of the evidence in support of an inherited contribution to the metabolic syndrome and the search for causative genomic regions. When multiple genome scans involving different patient cohorts implicate a common genomic region as susceptible to the metabolic syndrome, it is highly likely that causative genes reside in that area. Identification of these genes will dramatically improve our understanding of the mechanisms that underlie the metabolic syndrome, and could lead to novel treatment strategies. It is hoped that these therapies will also prevent the future development of type 2 diabetes mellitus and atherosclerotic complications, both common among individuals affected by the metabolic syndrome.     

Genetics of diabetic nephropathy in the Pima Indians

Diabetic nephropathy is the leading cause of renal failure in industrialized countries. There is strong evidence that diabetic nephropathy is influenced by genetic factors. Studies in the Pima Indians as well as in other populations demonstrate that diabetic nephropathy aggregates in families. The hypothesis that the familial aggregation reflects the effect of a major gene was formally tested by segregation analysis of diabetic nephropathy in Pima Indians with type 2 diabetes. The segregation analysis provided strong evidence for a major genetic effect on the prevalence of diabetic nephropathy; this suggests that some of the genetic determinants of diabetic nephropathy may have effects of sufficient magnitude to be detected by linkage analysis. Therefore, we analyzed data from a genome-wide scan to identify susceptibility loci for nephropathy in diabetic Pima Indians. Analyses conducted by both parametric (model-based) and nonparametric methods revealed tentative evidence for nephropathy susceptibility loci on chromosomes 3q, 7q, 18q, and 20p.     

部分基因组扫描研究2型糖尿病易感基因座位的初步报告

目的　通过部分基因组扫描筛查与 2型糖尿病连锁的位点 ,为进一步定位和克隆 2型糖尿病的易感基因奠定基础。方法　采用以微卫星DNA标记为基础的荧光标记 半自动基因组扫描技术 ,应用Perkin Elmer的试剂盒 (ABIPrismLinkageMappingSetVersion 2 ) ,共 6 3对引物 ,研究 2型糖尿病家系 5 8个 ,共 2 6 4份样品 ,其中糖尿病患者 15 2人 ,非糖尿病患者 112人 ,有同胞关系的患者74人 ,组成 45对患病同胞对 ,对 1号、12号、18号、2 0号染色体进行部分基因组扫描。连锁分析采用GENEHUNTERversion 2连锁分析软件包。结果　非参数连锁分析结果提示 ,1号染色体 1p31区域的D1S2 86 8位点同 2型糖尿病连锁 ,其NPL值为 1.192 ,P值为 0 .0 45 ,2 0号染色体短臂末端 2 0 p13区域的位点D2 0S117和D2 0S889以及 2 0号染色体长臂 2 0q13 .3区域的D2 0S196位点同 2型糖尿病连锁 ,其NPL值分别为 1.36 2、1.36 0、1.199,P值分别为 0 .0 30、0 .0 30和 0 .0 49。结论　 1号染色体短臂 1p31区域及 2 0号染色体短臂 2 0 p13区域及长臂 2 0 q13.3区域可能存在有 2型糖尿病的易感基因。     

Genetic analysis of type 1 diabetes using whole genome approaches.

Whole genome linkage analysis of type 1 diabetes using affected sib pair families and semi-automated genotyping and data capture procedures has shown how type 1 diabetes is inherited. A major proportion of clustering of the disease in families can be accounted for by sharing of alleles at susceptibility loci in the major histocompatibility complex on chromosome 6 (IDDM1) and at a minimum of 11 other loci on nine chromosomes. Primary etiological components of IDDM1, the HLA-DQB1 and -DRB1 class II immune response genes, and of IDDM2, the minisatellite repeat sequence in the 5' regulatory region of the insulin gene on chromosome 11p15, have been identified. Identification of the other loci will involve linkage disequilibrium mapping and sequencing of candidate genes in regions of linkage.     

Meta-analysis of five genome-wide linkage studies for body mass index reveals significant evidence for linkage to chromosome 8p

OBJECTIVE: To perform a meta-analysis of genome-wide linkage scans using body mass index (BMI) to identify genetic loci predisposing to obesity. DATA: A total of 13 published genome scans on obesity have used BMI as their primary end point. Five of these 13 groups agreed to provide detailed results from their scans that were required for a meta-analysis. Collectively, these five studies included a total of 2814 individuals from 505 families. METHODS: The results of the five studies were analysed using the GSMA (genome scans meta-analysis) method. RESULTS: The analysis revealed significant evidence for linkage of the quantitative phenotype BMI to 8p (P<0.0005).     

Linkage analysis of rheumatoid arthritis in US and UK families reveals interactions between HLA–DRB1 and loci on chromosomes 6q and 16p

Objective

HLA is the most strongly associated locus in rheumatoid arthritis (RA), accounting for up to one‐third of the genetic contribution. Conditioning on the effect of true disease loci such as HLA can lead to increased power to detect effects at other loci and, in addition, allows investigation of the underlying disease models, including interactions. The aim of this study was to detect susceptibility loci for RA by conditioning on HLA in a large sample of affected sibling pairs (ASPs) and to test for evidence of interaction between novel loci and HLA.

Methods

Genotype data from 3 whole‐genome linkage scans for RA in a US population and a UK population were pooled, resulting in a combined data set of 886 ASPs. This pooling of data increased the power to detect loci showing low levels of heterogeneity. Nonparametric linkage analysis was performed to identify regions of interest. Joint 2‐locus analysis was then performed for HLA and each of the loci that demonstrated evidence of linkage in the 886 ASPs.

Results

Evidence for linkage was most significant at HLA (P = 4 × 10⁻¹⁶), with 7 non‐HLA loci showing some evidence for linkage (P = 0.05–0.003). Joint modeling of these loci with HLA provided evidence for linkage at a genome‐wide significance level for loci on 6q (P = 2.7 × 10⁻⁶) and 16p (P = 2 × 10⁻⁴).

Conclusion

These data provide the most convincing evidence to date that 6q and 16p harbor susceptibility genes. In addition, these loci may interact with HLA, facilitating the search for candidate genes within this region.

     

Genome-wide linkage analysis of the acute coronary syndrome suggests a locus on chromosome 2

A positive family history is a recognized cardiovascular risk factor, and genome-wide scans may reveal susceptibility loci for coronary artery disease. The acute coronary syndrome, consisting of myocardial infarction and unstable angina, is the most important manifestation of coronary disease and is characterized by atherosclerotic plaque disruption and coronary thrombosis. From approximately 6000 hospital admissions to cardiology units, we identified affected sibling pairs (n=61) who had documented acute coronary syndrome before the age of 70 years. A 10-cM resolution genetic map and MAPMAKER/SIBS were used for genome-wide linkage analysis. One locus on chromosome 2q36-q37.3 showed linkage with a lod score of 2.63 (P<0.0001). Separate multipoint fine-mapping of this locus with independent markers replicated the linkage results (lod 2.64). Two other regions on chromosomes 3q26-q27 and 20q11-q13 showed lod scores in excess of 1.5 (P<0.005). This genome scan in acute coronary syndrome suggests 1 locus that encompasses the gene encoding the insulin receptor substrate-1 gene. Two other potential loci were identified. These data imply that a limited number of potent susceptibility genes exist for the acute coronary syndrome. Such genes are likely to be relevant to the combined processes of atherosclerosis, plaque instability, and coronary thrombosis.     

Agreement among type 2 diabetes linkage studies but a poor correlation with results from genome-wide association studies

Aims/hypothesis  Little of the genetic basis for type 2 diabetes has been explained, despite numerous genetic linkage studies and the discovery of multiple genes in genome-wide association (GWA) studies. To begin to resolve the genetic component of this disease, we searched for sites at which genetic results had been corroborated in different studies, in the expectation that replication among studies should direct us to the genomic locations of causative genes with more confidence than the results of individual studies. Methods  We have mapped the physical location of results from 83 linkage reports (for type 2 diabetes and diabetes precursor quantitative traits [QTs, e.g. plasma insulin levels]) and recent large GWA reports (for type 2 diabetes) onto the same human genome sequence to identify replicated results in diabetes genetic ‘hot spots’. Results  Genetic linkage has been found at least ten times at 18 different locations, and at least five times in 56 locations. All replication clusters contained study populations from more than one ethnic background and most contained results for both diabetes and QTs. There is no close relationship between the GWA results and linkage clusters, and the nine best replication clusters have no nearby GWA result. Conclusions/interpretation  Many of the genes for type 2 diabetes remain unidentified. This analysis identifies the broad location of yet to be identified genes on 6q, 1q, 18p, 2q, 20q, 17pq, 8p, 19q and 9q. The discrepancy between the linkage and GWA studies may be explained by the presence of multiple, uncommon, mildly deleterious polymorphisms scattered throughout the regulatory and coding regions of genes for type 2 diabetes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorised users.     

Mechanisms of disease: genetic insights into the etiology of type 2 diabetes and obesity

Until recently, progress in identification of the genetic variants influencing predisposition to common forms of diabetes and obesity has been slow, a sharp contrast to the large number of genes implicated in rare monogenic forms of both conditions. Recent advances have transformed the situation, however, enabling researchers to undertake well-powered scans able to detect association signals across the entire genome. For type 2 diabetes, the six high-density genome-wide association studies so far performed have extended the number of loci harboring common variants implicated in diabetes susceptibility into double figures. One of these loci, mapping to the fat mass and obesity associated gene (FTO), influences diabetes risk through a primary effect on fat mass, making this the first common variant known to influence weight and individual risk of obesity. These findings offer two main avenues for clinical translation. First, the identification of new pathways involved in disease predisposition-for example, those influencing zinc transport and pancreatic islet regeneration in the case of type 2 diabetes-offers opportunities for development of novel therapeutic and preventative approaches. Second, with continuing efforts to identify additional genetic variants, it may become possible to use patterns of predisposition to tailor individual management of these conditions.