In humans, genetic variation in endocannabinergic signaling has been associated with anthropometric measures of obesity. In randomized trials, pharmacological blockade at the level of the cannabinoid receptor 1 (CNR1) receptor not only facilitates weight reduction, but also improves insulin sensitivity and clinical measures of lipid homeostasis. We therefore tested the hypothesis that genetic variation in CNR1 is associated with common obesity-related metabolic disorders.
Materials & methods
A total of six haplotype tagging SNPs were selected for CNR1, using data available within the Human HapMap (Centre d’Etude du Polymorphisme Humain population) these included: two promoter SNPs, three exonic SNPs, and a single SNP within the 3′-untranslated region. These tags were then genotyped in a rigorously phenotyped family-based collection of obese study subjects of Northern European origin.
Results & conclusions
A common CNR1 haplotype (H4; prevalence 0.132) is associated with abnormal lipid homeostasis. Additional statistical tests using single tagging SNPs revealed that these associations are partly independent of body mass index.
CNR1; genetic association; haplotype; HDL; high-density lipoprotein; LDL; low-density lipoprotein; obesity; triglyceride
Chemokine signals and their cell-surface receptors are important modulators of HIV-1 disease and cancer. To aid future case/control association studies, aim to further characterise the haplotype structure of variation in chemokine and chemokine receptor genes. To perform haplotype analysis in a population-based association study, haplotypes must be determined by estimation, in the absence of family information or laboratory methods to establish phase. Here, test the accuracy of estimates of haplotype frequency and linkage disequilibrium by comparing estimated haplotypes generated with the expectation maximisation (EM) algorithm to haplotypes determined from Centre d'Etude Polymorphisme Humain (CEPH) pedigree data. To do this, they have characterised haplotypes comprising alleles at 11 biallelic loci in four chemokine receptor genes (CCR3, CCR2, CCR5 and CCRL2), which span 150 kb on chromosome 3p21, and haplotyes of nine biallelic loci in six chemokine genes [MCP-1(CCL2), Eotaxin(CCL11), RANTES(CCL5), MPIF-1(CCL23), PARC(CCL18) and MIP-1α(CCL3) ] on chromosome 17q11-12. Forty multi-generation CEPH families, totalling 489 individuals, were genotyped by the TaqMan 5'-nuclease assay. Phased haplotypes and haplotypes estimated from unphased genotypes were compared in 103 grandparents who were assumed to have mated at random.
For the 3p21 single nucleotide polymorphism (SNP) data, haplotypes determined by pedigree analysis and haplotypes generated by the EM algorithm were nearly identical. Linkage disequilibrium, measured by the D' statistic, was nearly maximal across the 150 kb region, with complete disequilibrium maintained at the extremes between CCR3-Y17Y and CCRL2-1243V. D'-values calculated from estimated haplotypes on 3p21 had high concordance with pairwise comparisons between pedigree-phased chromosomes. Conversely, there was less agreement between analyses of haplotype frequencies and linkage disequilibrium using estimated haplotypes when compared with pedigree-phased haplotypes of SNPs on chromosome 17q11-12. These results suggest that, while estimations of haplotype frequency and linkage disequilibrium may be relatively simple in the 3p21 chemokine receptor cluster in population samples, the more complex environment on chromosome 17q11-12 will require a higher resolution haplotype analysis.
chemokine; SNP; haplotype estimation; pedigree analysis; linkage disequilibrium
We report the identification of two novel minor histocompatibility antigens (mHAgs), encoded by two separate single nucleotide polymorphisms on a single gene, BCL2A1, and restricted by human histocompatibility leukocyte antigen (HLA)-A*2402 (the most common HLA-A allele in Japanese) and B*4403, respectively. Two cytotoxic T lymphocyte (CTL) clones specific for these mHAgs were first isolated from two distinct recipients after hematopoietic cell transplantation. Both clones lyse only normal and malignant cells within the hematopoietic lineage. To localize the gene encoding the mHAgs, two-point linkage analysis was performed on the CTL lytic patterns of restricting HLA-transfected B lymphoblastoid cell lines obtained from Centre d'Etude du Polymorphisme Humain. Both CTL clones showed a completely identical lytic pattern for 4 pedigrees and the gene was localized within a 3.6-cM interval of 15q24.3–25.1 region that encodes at least 46 genes. Of those, only BCL2A1 has been reported to be expressed in hematopoietic cells and possess three nonsynonymous nucleotide changes. Minigene transfection and epitope reconstitution assays with synthetic peptides identified both HLA-A*2402– and B*4403-restricted mHAg epitopes to be encoded by distinct polymorphisms within BCL2A1.
minor histocompatibility antigen; hematopoietic cell transplantation; cytotoxic T lymphocyte; graft-versus-leukemia effect; linkage analysis
The International HapMap Consortium has determined the linkage disequilibrium (LD) patterns of four major human populations. The aim of our investigation was to compare the LD patterns of the HapMap CEPH (Centre d’Etude du Polymorphisme Humain) samples with a family-based cohort of similar ancestry to determine its usefulness as a reference population for disease association studies. We examined four genomic regions on chromosomes 7q, 12p, and 14q totaling 14.3 Mb, initially identified in our linkage study of obesity and the metabolic syndrome. Near identical patterns of LD were detected in both populations. Furthermore, tagSNPs selected based on the HapMap CEPH cohort data capture over 98% of the variants at an r2 > 0.8 in the disease cohort. This confirms the usefulness of the CEPH cohort of the HapMap as a reference sample for further investigations into the genomic variation of populations of Northern European descent.
CEPH; HapMap; haplotype; tagSNP
The definition of human MHC class I haplotypes through association of HLA-A, HLA-Cw and HLA-B has been used to analyze ethnicity, population migrations and disease association.
Here, we present HLA-E allele haplotype association and population linkage disequilibrium (LD) analysis within the ~1.3 Mb bounded by HLA-B/Cw and HLA-A to increase the resolution of identified class I haplotypes. Through local breakdown of LD, we inferred ancestral recombination points both upstream and downstream of HLA-E contributing to alternative block structures within previously identified haplotypes. Through single nucleotide polymorphism (SNP) analysis of the MHC region, we also confirmed the essential genetic fixity, previously inferred by MHC allele analysis, of three conserved extended haplotypes (CEHs), and we demonstrated that commercially-available SNP analysis can be used in the MHC to help define CEHs and CEH fragments.
We conclude that to generate high-resolution maps for relating MHC haplotypes to disease susceptibility, both SNP and MHC allele analysis must be conducted as complementary techniques.
Linkage maps have been invaluable for the positional cloning of many genes involved in severe human diseases. Standard genetic linkage maps have been constructed for this purpose from the Centre d'Etude du Polymorphisme Humain and other panels, and have been widely used. Now that attention has shifted towards identifying genes predisposing to common disorders using linkage disequilibrium (LD) and maps of single nucleotide polymorphisms (SNPs), it is of interest to consider a standard LD map which is somewhat analogous to the corresponding map for linkage. We have constructed and evaluated a cosmopolitan LD map by combining samples from a small number of populations using published data from a 10-megabase region on chromosome 20. In support of a pilot study, which examined a number of small genomic regions with a lower density of markers, we have found that a cosmopolitan map, which serves all populations when appropriately scaled, recovers 91 to 95 per cent of the information within population-specific maps. Recombination hot spots appear to have a dominant role in shaping patterns of LD. The success of the cosmopolitan map might be attributed to the co-localisation of hot spots in all populations. Although there must be finer scale differences between populations due to other processes (mutation, drift, selection), the results suggest that a whole-genome standard LD map would indeed be a useful resource for disease gene mapping.
linkage disequilibrium; single nucleotide polymorphism; genetic map; map integration
Using single-nucleotide polymorphism (SNP) genotypes and selected gene expression phenotypes from 14 CEPH (Centre d'Etude du Polymorphisme Humain) pedigrees provided for Genetic Analysis Workshop 15 (GAW15), we analyzed quantitative traits with artificial neural networks (ANNs). Our goals were to identify individual linkage signals and examine gene × gene interactions. First, we used classical multipoint methods to identify phenotypes having nominal linkage evidence at two or more loci. ANNs were then applied to sib-pair identity-by-descent (IBD) allele sharing across the genome as input variables and squared trait sums and differences for the sib pairs as output variables. The weights of the trained networks were analyzed to assess the linkage evidence at each locus as well as potential interactions between them.
Loci identified by classical linkage analysis could also be identified by our ANN analysis. However some ANN results were noisy, and our attempts to use cross-validated training to avoid overtraining and thereby improve results were only partially successful. Potential interactions between loci with high-ranked weight measures were also evaluated, with the resulting patterns suggesting existence of both synergistic and antagonistic effects between loci.
Our results suggest that ANNs can serve as a useful method to analyze quantitative traits and are a potential tool for detecting gene × gene interactions. However, for the approach implemented here, optimizing the ANNs and obtaining stable results remains challenging.
Several recent studies have shown a genetic influence on gene expression variation, including variation between the two chromosomes within an individual and variation between individuals at the population level. We hypothesized that genetic inheritance may also affect variation in chromatin states. To test this hypothesis, we analyzed chromatin states in 12 lymphoblastoid cells derived from two Centre d'Etude du Polymorphisme Humain families using an allele-specific chromatin immunoprecipitation (ChIP-on-chip) assay with Affymetrix 10K SNP chip. We performed the allele-specific ChIP-on-chip assays for the 12 lymphoblastoid cells using antibodies targeting at RNA polymerase II and five post-translation modified forms of the histone H3 protein. The use of multiple cell lines from the Centre d'Etude du Polymorphisme Humain families allowed us to evaluate variation of chromatin states across pedigrees. These studies demonstrated that chromatin state clustered by family. Our results support the idea that genetic inheritance can determine the epigenetic state of the chromatin as shown previously in model organisms. To our knowledge, this is the first demonstration in humans that genetics may be an important factor that influences global chromatin state mediated by histone modification, the hallmark of the epigenetic phenomena.
Human health and disease are determined by an interaction between genetic background and environmental exposures. Both normal development and disease are mediated by epigenetic regulation of gene expression. The epigenetic regulation causes heritable changes in gene expression, which is not associated with DNA sequence changes. Instead, it is mediated by chemical modification of DNA such as DNA methylation or by protein modifications such as histone acetylation and methylation. Although much has been known about epigenetic inheritance during development, little is known about the influence of the genetic background on epigenetic processes such as histone modifications. In this report the authors studied five histone modifications on a genome-wide level in cells from different families. Global epigenetic states, as measured by these histone modifications, showed a similar pattern for cells derived from the same family. This study demonstrates that genetic inheritance may be an important factor influencing global chromatin states mediated by histone modifications in humans. These observations illustrate the importance of integrating genetic and epigenetic information into studies of human health and complex diseases.
A recent high-density linkage screen confirmed that the HLA complex contains the strongest genetic factor for the risk of multiple sclerosis (MS). In parallel, a linkage disequilibrium analysis using 650 single nucleotide polymorphisms (SNP) markers of the HLA complex mapped the entire genetic effect to the HLA-DR-DQ subregion, reflected by the well-established risk haplotype HLA-DRB1*15,DQB1*06. Contrary to this, in a cohort of 1,084 MS patients and 1,347 controls, we show that the HLA-A gene confers an HLA-DRB1 independent influence on the risk of MS (P = 8.4×10−10). This supports the opposing view, that genes in the HLA class I region indeed exert an additional influence on the risk of MS, and confirms that the class I allele HLA-A*02 is negatively associated with the risk of MS (OR = 0.63, P = 7×10−12) not explained by linkage disequilibrium with class II. The combination of HLA-A and HLA-DRB1 alleles, as represented by HLA-A*02 and HLA-DRB1*15, was found to influence the risk of MS 23-fold. These findings imply complex autoimmune mechanisms involving both the regulatory and the effector arms of the immune system in the triggering of MS.
The 11q23.1 genomic region has been associated with nicotine dependence in Black and White Americans.
By conducting linkage disequilibrium analyses of 7 informative single nucleotide polymorphisms (SNPs) within the tetratricopeptide repeat domain 12 (TTC12)/ankyrin repeat and kinase containing 1 (ANKK1)/dopamine (D2) receptor gene cluster, we identified haplotype block structures in 270 Black and 368 White (n = 638) participants, from the Baltimore Epidemiologic Catchment Area cohort study, spanning the TTC12 and ANKK1 genes consisting of three SNPs (rs2303380–rs4938015–rs11604671). Informative haplotypes were examined for sex-specific associations with daily tobacco smoking initiation and cessation using longitudinal data from 1993–1994 and 2004–2005 interviews.
There was a Haplotype × Sex interaction such that Black men possessing the GTG haplotype who were smokers in 1993–2004 were more likely to have stopped smoking by 2004–2005 (55.6% GTG vs. 22.0% other haplotypes), while Black women were less likely to have quit smoking if they possessed the GTG (20.8%) versus other haplotypes (24.0%; p = .028). In Whites, the GTG haplotype (vs. other haplotypes) was associated with lifetime history of daily smoking (smoking initiation; odds ratio = 1.6; 95% CI = 1.1–2.4; p = .013). Moreover, there was a Haplotype × Sex interaction such that there was higher prevalence of smoking initiation with GTG (77.6%) versus other haplotypes (57.0%; p = .043).
In 2 different ethnic American populations, we observed man–woman variation in the influence of the rs2303380–rs4938015–rs11604671 GTG haplotype on smoking initiation and cessation. These results should be replicated in larger cohorts to establish the relationship among the rs2303380–rs4938015–rs11604671 haplotype block, sex, and smoking behavior.
Finding a genetic marker associated with a trait is a classic problem in human genetics. Recently, two-stage approaches have gained popularity in marker-trait association studies, in part because researchers hope to reduce the multiple testing problem by testing fewer markers in the final stage. We compared one two-stage family-based approach to an analogous single-stage method, calculating the empirical type I error rates and power for both methods using fully simulated data sets modeled on nuclear families with rheumatoid arthritis, and data sets of real single-nucleotide polymorphism genotypes from Centre d'Etude du Polymorphisme Humain pedigrees with simulated traits. In these analyses performed in the absence of population stratification, the single-stage method was consistently more powerful than the two-stage method for a given type I error rate. To explore the sources of this difference, we performed a case study comparing the individual steps of two-stage designs, the two-stage design itself, and the analogous one-stage design.
In the present study, we investigate patterns of variation in the KIR cluster in a large and well-characterized sample of worldwide human populations in the Human Genome Diversity Project—Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) panel in order to better understand the patterns of diversity in the region. Comparison of KIR data with that from other genomic regions allows control for strictly demographic factors; over 500,000 additional genomic markers have been typed in this panel by other investigators and the data made publicly available. Presence/absence frequencies and haplotypic associations for the KIR region are analyzed in the 52 populations comprising the panel and in accordance with major world regions (Africa, Middle East, Central Asia, East Asia, Europe, Americas, and Oceania). These data represent the first overview of KIR population genetics in the well-documented HGDP-CEPH panel and suggest different evolutionary histories and recent selection in the KIR gene cluster.
Electronic supplementary material
The online version of this article (doi:10.1007/s00251-012-0629-x) contains supplementary material, which is available to authorized users.
Killer cell immunoglobulin-like receptor; KIR; HGDP-CEPH; Population; Diversity
Two single nucleotide polymorphisms (SNPs) in adjacent genes, lymphotoxin alpha (LTA +252G, rs909253 A>G) and tumor necrosis factor (TNF −308A, rs1800629 G>A), form the G-A haplotype repeatedly associated with increased risk of non-Hodgkin’s lymphoma (NHL) in individuals uninfected with HIV-1. This association has been observed alone or in combination with HLA-B* 08 or HLA-DRB1*03 in the major histocompatibility complex (MHC). Which gene variant on this highly conserved extended haplotype (CEH 8.1) in Caucasians most likely represents a true etiologic factor remains uncertain. We aimed to determine whether the reported association of the G-A haplotype of LTA-TNF with non-AIDS NHL also occurs with AIDS-related NHL. SNPs in LTA and TNF and in six other genes nearby were typed in 140 non-Hispanic European American pairs of AIDS-NHL cases and matched controls selected from HIV-infected men in the Multicenter AIDS Cohort Study. The G-A haplotype and a 4-SNP haplotype in the neighboring gene cluster (rs537160 (A) rs1270942 (G), rs2072633 (A) and rs6467 (C)) were associated with AIDS-NHL (OR=2.7, 95% CI: 1.5–4.8, p=0.0009 and OR=3.2, 95% CI: 1.6–6.6 p=0.0008; respectively). These two haplotypes occur in strong linkage disequilibrium with each other on CEH 8.1. The CEH 8.1-specific haplotype association of MHC class III variants with AIDS-NHL closely resembles that observed for non-AIDS NHL. Corroboration of an MHC determinant of AIDS and non-AIDS NHL alike would imply an important pathogenetic mechanism common to both.
Human Leukocyte Antigen; HIV; CD4; Multicenter AIDS Cohort NHL Study
Protein tyrosine phosphatase non-receptor type 22 (PTPN22) is the third major locus affecting risk of type I diabetes (T1D), after HLA-DR/DQ and INS. The most associated single-nucleotide polymorphism (SNP), rs2476601, has a C->T variant and results in an arginine (R) to tryptophan (W) amino acid change at position 620. To assess whether this, or other specific variants, are responsible for T1D risk, the Type I Diabetes Genetics Consortium analyzed 28 PTPN22 SNPs in 2295 affected sib-pair (ASP) families. Transmission Disequilibrium Test analyses of haplotypes revealed that all three haplotypes with a T allele at rs2476601 were overtransmitted to affected children, and two of these three haplotypes showed statistically significant overtransmission (P=0.003 to P=5.9E-12). Another haplotype had decreased transmission to affected children (P=3.5E-05). All haplotypes containing the rs2476601 T allele were identical for all SNPs across PTPN22 and only varied at centromeric SNPs. When considering rs2476601 ‘C’ founder chromosomes, a second haplotype (AGGGGC) centromeric of PTPN22 in the C1orf178 region was associated with protection from T1D (odds ratio=0.81, P=0.0005). This novel finding requires replication in independent populations. We conclude the major association of PTPN22 with T1D is likely due to the recognized non-synonymous SNP rs2476601 (R620W).
PTPN22; haplotypes; type I diabetes; T1DGC
Our genotype inference method combines sparse marker data from a linkage scan and high-resolution SNP genotypes for several individuals to infer genotypes for related individuals. We illustrate the method’s utility by inferring over 53 million SNP genotypes for 78 children in the Centre d’Etude du Polymorphisme Humain families. The method can be used to obtain high-density genotypes in different family structures, including nuclear families commonly used in complex disease gene mapping studies.
Systemic lupus erythematosus (SLE) is a chronic multisystem genetically complex autoimmune disease characterised by the production of autoantibodies to nuclear and cellular antigens, tissue inflammation and organ damage. Genome-wide association studies have shown that variants within the major histocompatibility complex (MHC) region on chromosome 6 confer the greatest genetic risk for SLE in European and Chinese populations. However, the causal variants remain elusive due to tight linkage disequilibrium across disease-associated MHC haplotypes, the highly polymorphic nature of many MHC genes and the heterogeneity of the SLE phenotype.
A high-density case-control single nucleotide polymorphism (SNP) study of the MHC region was undertaken in SLE cohorts of Spanish and Filipino ancestry using a custom Illumina chip in order to fine-map association signals in these haplotypically diverse populations. In addition, comparative analyses were performed between these two datasets and a northern European UK SLE cohort. A total of 1433 cases and 1458 matched controls were examined.
Using this transancestral SNP mapping approach, novel independent loci were identified within the MHC region in UK, Spanish and Filipino patients with SLE with some evidence of interaction. These loci include HLA-DPB1, HLA-G and MSH5 which are independent of each other and HLA-DRB1 alleles. Furthermore, the established SLE-associated HLA-DRB1*15 signal was refined to an interval encompassing HLA-DRB1 and HLA-DQA1. Increased frequencies of MHC region risk alleles and haplotypes were found in the Filipino population compared with Europeans, suggesting that the greater disease burden in non-European SLE may be due in part to this phenomenon.
These data highlight the usefulness of mapping disease susceptibility loci using a transancestral approach, particularly in a region as complex as the MHC, and offer a springboard for further fine-mapping, resequencing and transcriptomic analysis.
Genotyping technologies enable us to genotype multiple Single Nucleotide Polymorphisms (SNPs) within selected genes/regions, providing data for haplotype association analysis. While haplotype-based association analysis is powerful for detecting untyped causal alleles in linkage-disequilibrium (LD) with neighboring SNPs/haplotypes, the inclusion of extraneous SNPs could reduce its power by increasing the number of haplotypes with each additional SNP.
Here, we propose a haplotype-based stepwise procedure (HBSP) to eliminate extraneous SNPs. To evaluate its properties, we applied HBSP to both simulated and real data, generated from a study of genetic associations of the bactericidal/permeability-increasing (BPI) gene with pulmonary function in a cohort of patients following bone marrow transplantation.
Under the null hypothesis, use of the HBSP gave results that retained the desired false positive error rates when multiple comparisons were considered. Under various alternative hypotheses, HBSP had adequate power to detect modest genetic associations in case-control studies with 500, 1,000 or 2,000 subjects. In the current application, HBSP led to the identification of two specific SNPs with a positive validation.
These results demonstrate that HBSP retains the essence of haplotype-based association analysis while improving analytic power by excluding extraneous SNPs. Minimizing the number of SNPs also enables simpler interpretation and more cost-effective applications.
Here we describe the data provided for Problem 1 of Genetic Analysis Workshop 15. The data provided for Problem 1 were unusual in two ways. First, the phenotype was the level of gene expression for each gene, not a conventional phenotype like height or disease, and second, there were more than 3500 such phenotypes. Natural variation in gene expression was a new idea in 2004 when these data were collected and published. Because the phenotypes were measured in members of 14 Centre d'Etude du Polymorphisme Humain (CEPH) families, there was an opportunity for linkage mapping on a very large scale. For this purpose, 2882 single-nucleotide polymorphism genotypes were also provided for each family member.
The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to HLA-DRB1 alleles. Yet controversy persists about the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 seropositive cases and 14,974 controls, we imputed and tested classical alleles and amino acid polymorphisms for HLA-A, B, C, DPA1, DPB1, DQA1, DQB1, and DRB1 along with 3,117 SNPs across the MHC. Conditional and haplotype analyses reveal that three amino acid positions (11, 71 and 74) in HLA-DRβ1, and single amino acid polymorphisms in HLA-B (position 9) and HLA-DPβ1 (position 9), all located in the peptide-binding grooves, almost completely explain the MHC association to disease risk. This study illustrates how imputation of functional variation from large reference panels can help fine-map association signals in the MHC.
The goal of this study was to develop and implement methodology that would aid in the analysis of extended high-density single nucleotide polymorphism (SNP) major histocompatibility complex (MHC) haplotypes combined with human leucocyte antigen (HLA) alleles in relation to type 1 diabetes risk.
High-density SNP genotype data (2918 SNPs) across the MHC from the Type 1 Diabetes Genetics Consortium (1240 families), in addition to HLA data, were processed into haplotypes using PEDCHECK and MERLIN, and extended DR3 haplotypes were analysed.
With this large dense set of SNPs, the conservation of DR3-B8-A1 (8.1) haplotypes spanned the MHC (≥99% SNP identity). Forty-seven individuals homozygous for the 8.1 haplotype also shared the same homozygous genotype at four ‘sentinel’ SNPs (rs2157678 ‘T’, rs3130380 ‘A’, rs3094628 ‘C’ and rs3130352 ‘T’). Conservation extended from HLA-DQB1 to the telomeric end of the SNP panels (3.4 Mb total). In addition, we found that the 8.1 haplotype is associated with lower risk than other DR3 haplotypes by both haplotypic and genotypic analyses [haplotype: p = 0.009, odds ratio (OR) = 0.65; genotype: p = 6.3 × 10−5, OR = 0.27]. The 8.1 haplotype (from genotypic analyses) is associated with lower risk than the high-risk DR3-B18-A30 haplotype (p = 0.01, OR = 0.23), but the DR3-B18-A30 haplotype did not differ from other non-8.1 DR3 haplotypes relative to diabetes association.
The 8.1 haplotype demonstrates extreme conservation (>3.4 Mb) and is associated with significantly lower risk for type 1 diabetes than other DR3 haplotypes.
8.1 haplotype; extended haplotypes; major histocompatibility complex; T1DGC; type 1 diabetes
HLA haplotype sharing was studied in 35 sibships in which there were two or more members with rheumatoid arthritis (RA). Haplotype sharing RA siblings was random in 15 sibships which included members with clinical or immunological features of autoimmune thyroid disease. In the remaining 20 'non-thyroid' sibships the frequencies of RA siblings sharing 0, 1, or 2 haplotypes were 0.04, 0.48, and 0.48 respectively (p = 0.006). 67% of RA probands in the 'thyroid' families and 90% in the other families were HLA-DR4 positive. It is suggested that there is genetic heterogeneity in the pathogenesis of RA with at least two independent genes within the major histocompatibility complex (MHC) predisposing to RA. One gene is in linkage disequilibrium with HLA-DR4, while results of comparison of DR antigen frequencies in DR4 negative RA and control groups suggest that the other is in linkage disequilibrium with HLA-DR1 and 3. In the thyroid disease families both genes are frequently present and as either may predispose to arthritis, HLA haplotype sharing is random. The frequencies of HLA haplotype sharing in the 'non-thyroid' families suggest that there is a dominant susceptibility gene in linkage disequilibrium with HLA-DR4, whose frequency is 5% and penetrance about 20%.
The Genetic Analysis Workshop 15 (GAW15) Problem 1 contained baseline expression levels of 8793 genes in immortalized B cells from 194 individuals in 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees. Previous analysis of the data showed linkage and association and evidence of substantial individual variations. In particular, correlation was examined on expression levels of 31 genes and 25 target genes corresponding to two master regulatory regions. In this analysis, we apply Bayesian network analysis to gain further insight into these findings. We identify strong dependences and therefore provide additional insight into the underlying relationships between the genes involved. More generally, the approach is expected to be applicable for integrated analysis of genes on biological pathways.
Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system of unknown etiology with both genetic and environmental factors playing a role in susceptibility. To date, the HLA DR15/DQ6 haplotype within the major histocompatibility complex on chromosome 6p, is the strongest genetic risk factor associated with MS susceptibility. Additional alleles of IL7 and IL2 have been identified as risk factors for MS with small effect. Here we present two independent studies supporting an allelic association of MS with polymorphisms in the ST8SIA1 gene, located on chromosome 12p12 and encoding ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 1. The initial association was made in a single three-generation family where a single-nucleotide polymorphism (SNP) rs4762896, was segregating together with HLA DR15/DQ6 in MS patients. A study of 274 family trios ( affected child and both unaffected parents) from Australia validated the association of ST8SIA1 in individuals with MS, showing transmission disequilibrium of the paternal alleles for three additional SNPs, namely rs704219, rs2041906, and rs1558793, with p = 0.001, p = 0.01 and p = 0.01 respectively. These findings implicate ST8SIA1 as a possible novel susceptibility gene for MS.
Background: It is well established that estrogen increases endometrial cancer risk, whereas progesterone opposes the estrogen effects. The PROGINS allele of the progesterone receptor (PGR) gene reduces the function of PGR and has been associated with increased risk of the endometrioid type ovarian cancer. We investigated whether genetic variation in PGR is also associated with endometrial cancer risk using a haplotype-based approach. Methods: We pooled data from two endometrial cancer case–control studies that were nested within two prospective cohorts, the Multiethnic Cohort Study and the California Teachers Study. Seventeen haplotype-tagging single nucleotide polymorphisms (SNPs) across four linkage disequilibrium (LD) blocks spanning the PGR locus were genotyped in 583 incident cases and 1936 control women. Odds ratios (ORs) and 95% confidence intervals (CIs) associated with each haplotype were estimated using conditional logistic regression, stratified by age and ethnicity. Results: Genetic variation in LD block 3 of the PGR locus was associated with endometrial cancer risk (Pglobal test = 0.002), with haplotypes 3C, 3D and 3F associated with 31–34% increased risk. Among whites (383 cases/840 controls), genetic variation in all four blocks was associated with increased endometrial cancer risk (Pglobal test = 0.010, 0.013, 0.005 and 0.020). Haplotypes containing the PROGINS allele and several haplotypes in blocks 1, 3 and 4 were associated with 34–77% increased risk among whites. SNP analyses for whites suggested that rs608995, partially linked to the PROGINS allele (r2 = 0.6), was associated with increased risk (OR = 1.30, 95% CI = 1.06–1.59). Conclusions: Our results suggest that genetic variation in the PGR region is associated with endometrial cancer risk.
The tumor necrosis factor (TNF) alpha gene lies within the class III region of the major histocompatibility complex (MHC), telomeric to the class II and centromeric to the class I region. We have recently described the first polymorphism within the human TNF-alpha locus. This is biallelic and lies within the promoter region. Frequency analysis of the TNF-alpha polymorphism, using the polymerase chain reaction and single-stranded conformational polymorphism, in HLA-typed individuals, reveals a very strong association between the uncommon TNF allele and HLA A1, B8, and DR3 alleles. This is the first association between TNF- alpha and other MHC alleles and raises the possibility that the uncommon TNF-alpha allele may contribute to the many autoimmune associations of the A1,B8,DR3 haplotype.