Homozygosity mapping on homozygosity haplotype analysis to detect recessive disease-causing genes from a small number of unrelated, outbred patients

Genes involved in disease that are not common are often difficult to identify; a method that pinpoints them from a small number of unrelated patients will be of great help. In order to establish such a method that detects recessive genes identical-by-descent, we modified homozygosity mapping (HM) so that it is constructed on the basis of homozygosity haplotype (HM on HH) analysis. An analysis using 6 unrelated patients with Siiyama-type α1-antitrypsin deficiency, a disease caused by a founder gene, the correct gene locus was pinpointed from data of any 2 patients (length: 1.2-21.8 centimorgans, median: 1.6 centimorgans). For a test population in which these 6 patients and 54 healthy subjects were scrambled, the approach accurately identified these 6 patients and pinpointed the locus to a 1.4-centimorgan fragment. Analyses using synthetic data revealed that the analysis works well for IBD fragment derived from a most recent common ancestor (MRCA) who existed less than 60 generations ago. The analysis is unsuitable for the genes with a frequency in general population more than 0.1. Thus, HM on HH analysis is a powerful technique, applicable to a small number of patients not known to be related, and will accelerate the identification of disease-causing genes for recessive conditions.     

Haplotype-based linkage disequilibrium mapping via direct data mining

MOTIVATION: With the availability of large-scale, high-density single-nucleotide polymorphism markers and information on haplotype structures and frequencies, a great challenge is how to take advantage of haplotype information in the association mapping of complex diseases in case-control studies. RESULTS: We present a novel approach for association mapping based on directly mining haplotypes (i.e. phased genotype pairs) produced from case-control data or case-parent data via a density-based clustering algorithm, which can be applied to whole-genome screens as well as candidate-gene studies in small genomic regions. The method directly explores the sharing of haplotype segments in affected individuals that are rarely present in normal individuals. The measure of sharing between two haplotypes is defined by a new similarity metric that combines the length of the shared segments and the number of common alleles around any marker position of the haplotypes, which is robust against recent mutations/genotype errors and recombination events. The effectiveness of the approach is demonstrated by using both simulated datasets and real datasets. The results show that the algorithm is accurate for different population models and for different disease models, even for genes with small effects, and it outperforms some recently developed methods.     

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.     

Comparing gene expression profiles of Kashin-Beck and Keshan diseases occurring within the same endemic areas of China

In this study, differentially expressed genes in peripheral blood from patients with Kashin-Beck disease and Keshan disease were compared to further investigate the etiology and pathogenesis of both diseases, which occur in a common endemic area of China. Twenty Kashin-Beck disease patients and 12 healthy controls, and 16 Keshan disease patients and 16 healthy controls, were grouped into four pairs. Patients and controls were selected from common endemic areas for the two diseases. Total RNA was isolated from peripheral blood mononuclear cells from all patients and controls, and gene expression profiles analyzed by oligonucleotide microarrays. Sixteen genes differentially expressed in both Kashin-Beck disease and Keshan disease (versus controls) were identified, and comprised nine genes showing synchronous and seven asynchronous expression. The Comparative Toxicogenomics Database shows that expression and biological function of these genes can be affected by multiple environmental factors, including mycotoxin and selenium content, potential environmental risk factors for the two diseases. Thus, these shared differentially expressed genes may contribute to the distinct organ lesions, caused by common environmental risk factors of Kashin-Beck disease and Keshan disease.     

Recent progress in the genetics of generalized vitiligo

Vitiligo is an acquired disease characterized principally by patchy depigmentation of skin and overlying hair. Generalized vitiligo (GV), the predominant form of the disorder, results from autoimmune loss of melanocytes from affected regions. GV is a “complex trait”, inherited in a non-Mendelian polygenic, multifactorial manner. GV is epidemiologically associated with other autoimmune diseases, both in GV patients and in their close relatives, suggesting that shared genes underlie susceptibility to this group of diseases. Early candidate gene association studies yielded a few successes, such as PTPN22, but most such reports now appear to be false-positives. Subsequent genomewide linkage studies identified NLRPI and XBPI, apparent true GV susceptibility genes involved in immune regulation, and recent genome-wide association studies (GWAS) of GV in Caucasian and Chinese populations have yielded a large number of additional validated GV susceptibility genes.Together, these genes highlight biological systems and pathways that reach from the immune cells to the melanocyte, and provide insights into both disease pathogenesis and potential new targets for both treatment and even prevention of GV and other autoimmune diseases in genetically susceptible individuals.     

The contribution of three strong candidate schizophrenia susceptibility genes in demographically distinct populations

Here we characterize and compare the contribution of three recently identified strong candidate schizophrenia susceptibility genes; G72, neuregulin 1 (NRG1) and dystrobrevin-binding protein 1 (DTNBP1) in two independent datasets of patients with distinct genetic backgrounds. On the basis of corrected P-values from single- and multilocus transmission distortion tests our analysis provides no support for a contribution of G72, NRG1 or DTNBP1 in the tested samples. When transmission of individual haplotypes was considered, a picture more consistent with the original studies emerged, where transmission distortions in the same direction as the original samples and involving the same core haplotypes were observed for G72 and NRG1. Interestingly, whereas the NRG1 gene analysis was dominated by the presence of over-transmitted haplotypes, the G72 gene analysis was consistently dominated in both datasets by under-transmissions. Negative transmissions involved a core haplotype complementary to the originally detected over-transmitted haplotype, suggesting the presence of a protective variant within the G72 locus.     

Gene SNPs and mutations in clinical genetic testing: haplotype-based testing and analysis

Haplotype-based analysis using high-density single nucleotide polymorphism (SNP) markers have gained increasing attention in evaluating candidate genes in various clinical situations. For example, haplotype information is useful for predicting the severity and prognosis of certain genetic disorders. The intragenic cis-interactions between the common polymorphisms and the pathogenic mutations of prion protein (PRNP) and cystic fibrosis transmembrane conductance regulator (CFTR) genes greatly influence the phenotypes and the disease penetrance of hereditary Creutzfeldt-Jakob disease and cystic fibrosis. Merits of haplotype study are more evident in the fine mapping of complex diseases and in identifying genetic variations that influence individual's response to drugs. Knowledge-based approaches and/or linkage analyses using SNP tagged haplotypes are effective tools in detecting genetic associations. For example, haplotype studies in the inflammatory bowel disease susceptibility loci revealed diverse cis and trans gene-gene interactions, which can affect the clinical outcomes. Although currently, we have very limited knowledge on haplotype-phenotypic characterizations of most genes, these examples demonstrate that increased understanding of the clinically relevant haplotypes will provide better results in the diagnosis and possibly in the treatment of both monogenic and polygenic diseases.     

Positional cloning of disease genes: advantages of genetic isolates.

Genetic isolates with a history of a small founder population, long-lasting isolation and population bottlenecks represent exceptional resources in the identification of disease genes. Specific rare, monogenic diseases become enriched, and families with multiple affected individuals occur frequently enough to be used in linkage analyses for locus identification. Further, the vast majority of cases are caused by the same mutation, and disease alleles reveal linkage disequilibrium (LD) with markers over significant genetic intervals; this facilitates disease locus identification by similarity search for a shared genotype or haplotype in small study samples consisting of few affected individuals. LD observed in disease alleles adds power to linkage analyses and helps to define the exact location of disease loci on the genetic map. Typically, based on the linkage disequilibrium and the ancient haplotype, the critical DNA region can be defined from the original 1- to 2-cM resolution obtained in linkage analysis to 50-200 kb, greatly facilitating the targeting of physical cloning and sequencing efforts. These advantages have been well demonstrated in the positional cloning of several rare monogenic diseases enriched in population isolates like the example of Finland used here. How useful genetic isolates will prove to be in the identification of complex disease genes is dependent on the genealogical history of the isolate, including the size of the founding population and the expansion rate during the history of the population.     

Fine mapping of IGAD1 in IgA deficiency and common variable immunodeficiency: identification and characterization of haplotypes shared by affected members of 101 multiple-case families

To limit the region containing a mutation predisposing to selective IgA deficiency (IgAD) and common variable immunodeficiency (CVID), 554 informative members of 101 multiple-case families were haplotyped at the IGAD1 candidate locus in the MHC. Microsatellite markers were placed onto the physical map of IGAD1 to establish their order and permit rapid haplotype analyses. Linkage analysis of this extended family set provided additional support for a strong susceptibility locus at IGAD1 with a maximum multipoint nonparametric linkage score in excess of 3. Although the transmission of maternal IGAD1 haplotypes from unaffected heterozygous parents to the affected offspring was in excess, this was not apparent in multiple-case families with a predominance of affected mothers, suggesting that this parental bias is influenced by the affection status of transmitting parents and supporting a maternal effect in disease susceptibility. Of 110 haplotypes shared by 258 affected family members, a single haplotype (H1) was found in 44 pairs of affected relatives, accounting for the majority of the IGAD1 contribution to the development of IgAD/CVID in our families. The H1 allelic variability was higher in the telomeric part of the class III region than in the distal part of the class II region in both single- and multiple-case families. Incomplete H1 haplotypes had most variant alleles in the telomeric part of the analyzed region in homozygous IgAD/CVID patients, whereas this was not observed in unaffected homozygotes. These data suggest that a telomeric part of the class II region or centromeric part of the class III region is the most likely location of IGAD1.     

An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases

Groups of distinct but related diseases often share common symptoms, which suggest likely overlaps in underlying pathogenic mechanisms. Identifying the shared pathways and common factors among those disorders can be expected to deepen our understanding for them and help designing new treatment strategies effected on those diseases. Neurodegeneration diseases, including Alzheimer''s disease (AD), Parkinson''s disease (PD) and Huntington''s disease (HD), were taken as a case study in this research. Reported susceptibility genes for AD, PD and HD were collected and human protein-protein interaction network (hPPIN) was used to identify biological pathways related to neurodegeneration. 81 KEGG pathways were found to be correlated with neurodegenerative disorders. 36 out of the 81 are human disease pathways, and the remaining ones are involved in miscellaneous human functional pathways. Cancers and infectious diseases are two major subclasses within the disease group. Apoptosis is one of the most significant functional pathways. Most of those pathways found here are actually consistent with prior knowledge of neurodegenerative diseases except two cell communication pathways: adherens and tight junctions. Gene expression analysis showed a high probability that the two pathways were related to neurodegenerative diseases. A combination of common susceptibility genes and hPPIN is an effective method to study shared pathways involved in a group of closely related disorders. Common modules, which might play a bridging role in linking neurodegenerative disorders and the enriched pathways, were identified by clustering analysis. The identified shared pathways and common modules can be expected to yield clues for effective target discovery efforts on neurodegeneration.     

Genetic analysis of completely sequenced disease-associated MHC haplotypes identifies shuffling of segments in recent human history

The major histocompatibility complex (MHC) is recognised as one of the most important genetic regions in relation to common human disease. Advancement in identification of MHC genes that confer susceptibility to disease requires greater knowledge of sequence variation across the complex. Highly duplicated and polymorphic regions of the human genome such as the MHC are, however, somewhat refractory to some whole-genome analysis methods. To address this issue, we are employing a bacterial artificial chromosome (BAC) cloning strategy to sequence entire MHC haplotypes from consanguineous cell lines as part of the MHC Haplotype Project. Here we present 4.25 Mb of the human haplotype QBL (HLA-A26-B18-Cw5-DR3-DQ2) and compare it with the MHC reference haplotype and with a second haplotype, COX (HLA-A1-B8-Cw7-DR3-DQ2), that shares the same HLA-DRB1, -DQA1, and -DQB1 alleles. We have defined the complete gene, splice variant, and sequence variation contents of all three haplotypes, comprising over 259 annotated loci and over 20,000 single nucleotide polymorphisms (SNPs). Certain coding sequences vary significantly between different haplotypes, making them candidates for functional and disease-association studies. Analysis of the two DR3 haplotypes allowed delineation of the shared sequence between two HLA class II-related haplotypes differing in disease associations and the identification of at least one of the sites that mediated the original recombination event. The levels of variation across the MHC were similar to those seen for other HLA-disparate haplotypes, except for a 158-kb segment that contained the HLA-DRB1, -DQA1, and -DQB1 genes and showed very limited polymorphism compatible with identity-by-descent and relatively recent common ancestry (<3,400 generations). These results indicate that the differential disease associations of these two DR3 haplotypes are due to sequence variation outside this central 158-kb segment, and that shuffling of ancestral blocks via recombination is a potential mechanism whereby certain DR-DQ allelic combinations, which presumably have favoured immunological functions, can spread across haplotypes and populations.     

Evidence for common autoimmune disease genes controlling onset, severity, and chronicity based on experimental models for multiple sclerosis and rheumatoid arthritis

The pathogenicity of multiple sclerosis is still poorly understood, but identification of susceptibility genes using the animal model experimental allergic encephalomyelitis (EAE) could provide leads. Certain genes may be shared between different autoimmune diseases, and identification of such genes is of obvious importance. To locate gene regions involved in the control of EAE and to compare the findings with the susceptibility loci recently identified in a model for rheumatoid arthritis (pristane-induced arthritis), we made crosses between the encephalomyelitis- and arthritis-susceptible rat strain DA and the resistant E3 strain. Genetic analysis of animals produced in a F2 intercross identified 11 loci associated with specific EAE-associated traits. Interestingly, five of these loci were situated at the same position as major loci controlling pristane-induced arthritis and showed similarities in inheritance pattern and subphenotype associations. Our results show that different phases of EAE are controlled by different sets of genes and that common genes are likely to be involved in different autoimmune diseases.     

Genomewide scan for affective disorder susceptibility Loci in families of a northern Swedish isolated population

We analyzed nine multigenerational families with ascertained affective spectrum disorders in northern Sweden's geographically isolated population of Vasterbotten. This northern Swedish population, which originated from a limited number of early settlers approximately 8,000 years ago, is genetically more homogeneous than outbred populations. In a genomewide linkage analysis, we identified three chromosomal loci with multipoint LOD scores (MPLOD) >/=2 at 9q31.1-q34.1 (MPLOD 3.24), 6q22.2-q24.2 (MPLOD 2.48), and 2q33-q36 (MPLOD 2.26) under a recessive affected-only model. Follow-up genotyping with application of a 2-cM density simple-tandem-repeat (STR) map confirmed linkage at 9q31.1-q34.1 (MPLOD 3.22), 6q23-q24 (MPLOD 3.25), and 2q33-q36 (MPLOD 2.2). In an initial analysis aimed at identification of the underlying susceptibility genes, we focused our attention on the 9q locus. We fine mapped this region at a 200-kb STR density, with the result of an MPLOD of 3.70. Genealogical studies showed that three families linked to chromosome 9q descended from common founder couples approximately 10 generations ago. In this approximately 10-generation pedigree, a common ancestral haplotype was inherited by the patients, which reduced the 9q candidate region to 1.6 Mb. Further, the shared haplotype was observed in 4.2% of patients with bipolar disorder with alternating episodes of depression and mania, but it was not observed in control individuals in a patient-control sample from the Vasterbotten isolate. These results suggest a susceptibility locus on 9q31-q33 for affective disorder in this common ancestral region.     

ADAM33, a new candidate for psoriasis susceptibility

Psoriasis is a chronic skin disorder with multifactorial etiology. In a recent study, we reported results of a genome-wide scan on 46 French extended families presenting with plaque psoriasis. In addition to unambiguous linkage to the major susceptibility locus PSORS1 on Chromosome 6p21, we provided evidence for a susceptibility locus on Chromosome 20p13. To follow up this novel psoriasis susceptibility locus we used a family-based association test (FBAT) for an association scan over the 17 Mb candidate region. A total of 85 uncorrelated SNP markers located in 65 genes of the region were initially investigated in the same set of large families used for the genome wide search, which consisted of 295 nuclear families. When positive association was obtained for a SNP, candidate genes nearby were explored more in detail using a denser set of SNPs. Thus, the gene ADAM33 was found to be significantly associated with psoriasis in this family set (The best association was on a 3-SNP haplotype P = 0.00004, based on 1,000,000 permutations). This association was independent of PSORS1. ADAM33 has been previously associated with asthma, which demonstrates that immune system diseases may be controlled by common susceptibility genes with general effects on dermal inflammation and immunity. The identification of ADAM33 as a psoriasis susceptibility gene identified by positional cloning in an outbred population should provide insights into the pathogenesis and natural history of this common disease.     

Ig H chain variable and C region genes in common variable immunodeficiency. Characterization of two new deletion haplotypes.

Common variable immunodeficiency, a disorder characterized by diminished antibody production, manifests clinically as an increased susceptibility to bacterial infections. We have investigated the Ig H chain V and C region gene segments in 33 patients with common variable immunodeficiency, to identify the possible role these genes may have in the molecular basis of the defect. No major deletions were recognized for the VH gene segments of the VH2, VH5, and VH6 families, nor were there any differences in the RFLP patterns of mu- or alpha- switch regions or of C gamma genes. Two new deletion haplotypes were identified for the C region genes, the first encompassing C gamma 1 on a different haplotype from the C gamma 1 deletion described previously, and the second a novel deletion encompassing both C gamma 2 and C gamma 4. Based on these and previously described deletions in the IGHC region, we postulate that homologous regions are involved in the deletion process and that other new deletions likely exist in the population.     

Haplotype identity between individuals who share a CFTR mutation allele “identical by descent”: demonstration of the usefulness of the haplotype-sharing concept for gene mapping in real populations

Cystic fibrosis (CF) patients with the A455E mutation, in both the French Canadian and the Dutch population, share a common haplotype over distances of up to 25 cM. French Canadian patients with the 621+1G→T mutation share a common haplotype of more than 14 cM. In contrast, haplotypes containing the ΔF508 mutation show haplotype identity over a much shorter genomic distance within and between populations, probably because of the multiple introduction of this most common mutation. Haplotype analysis for specific mutations in CF or in other recessive diseases can be used as a model for studying the occurrence of genetic drift conditional on gene frequencies. Moreover, from our results, it can be inferred that analysis of shared haplotypes is a suitable method for genetic mapping in general. Received: 30 November 1995 / Revised: 11 April 1996     

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Reverse engineering gene networks to identify key drivers of complex disease phenotypes

Diseases such as obesity, diabetes, and atherosclerosis result from multiple genetic and environmental factors, and importantly, interactions between genetic and environmental factors. Identifying susceptibility genes for these diseases using genetic and genomic technologies is accelerating, and the expectation over the next several years is that a number of genes will be identified for common diseases. However, the identification of single genes for disease has limited utility, given that diseases do not originate in complex systems from single gene changes. Further, the identification of single genes for disease may not lead directly to genes that can be targeted for therapeutic intervention. Therefore, uncovering single genes for disease in isolation of the broader network of molecular interactions in which they operate will generally limit the overall utility of such discoveries. Several integrative approaches have been developed and applied to reconstructing networks. Here we review several of these approaches that involve integrating genetic, expression, and clinical data to elucidate networks underlying disease. Networks reconstructed from these data provide a richer context in which to interpret associations between genes and disease. Therefore, these networks can lead to defining pathways underlying disease more objectively and to identifying biomarkers and more-robust points for therapeutic intervention.     

Genome-wide association filtering using a highly locus-specific transmission/disequilibrium test

Multimarker transmission/disequilibrium tests (TDTs) are powerful association and linkage tests used to perform genome-wide filtering in the search for disease susceptibility loci. In contrast to case/control studies, they have a low rate of false positives for population stratification and admixture. However, the length of a region found in association with a disease is usually very large because of linkage disequilibrium (LD). Here, we define a multimarker proportional TDT (mTDT _P ) designed to improve locus specificity in complex diseases that has good power compared to the most powerful multimarker TDTs. The test is a simple generalization of a multimarker TDT in which haplotype frequencies are used to weight the effect that each haplotype has on the whole measure. Two concepts underlie the features of the metric: the ‘common disease, common variant’ hypothesis and the decrease in LD with chromosomal distance. Because of this decrease, the frequency of haplotypes in strong LD with common disease variants decreases with increasing distance from the disease susceptibility locus. Thus, our haplotype proportional test has higher locus specificity than common multimarker TDTs that assume a uniform distribution of haplotype probabilities. Because of the common variant hypothesis, risk haplotypes at a given locus are relatively frequent and a metric that weights partial results for each haplotype by its frequency will be as powerful as the most powerful multimarker TDTs. Simulations and real data sets demonstrate that the test has good power compared with the best tests but has remarkably higher locus specificity, so that the association rate decreases at a higher rate with distance from a disease susceptibility or disease protective locus.     

Populationsgenetik des humanen X-Chromosoms

Mitochondrial DNA and the Y chromosome (ChrY) are both highly informative regarding human evolution, demographic history, and the genetic relationships between extant populations. The major reason for this is that both genomic compartments do not recombine, except for the pseudo-autosomal regions of ChrY, and that typing of haploid markers automatically allows the identification of haplotypes. In terms of its recombination behaviour, the X chromosome (ChrX) falls between autosomes and ChrY. The significance of ChrX in terms of population genetics is partially based on the fact that its haplotypes are easier to determine than those of autosomes. While ChrY and mtDNA each represent a single locus only, with a common evolutionary history of all their constituents, ChrX comprises several regions that may each reflect its own history. Therefore, ChrX studies seem most suitable for distinguishing between subpopulations or for research on regional ethnic structures. The analysis of linkage disequilibrium (LD) is one of the key aspects of population genetics studies of ChrX markers because LD may be an indicator of genetic isolation or of the emergence from a small founder population. Populations with high LD play an important role in the identification of genes involved in the aetiology of multifactorial diseases.     

DASH: a method for identical-by-descent haplotype mapping uncovers association with recent variation

Rare variants affecting phenotype pose a unique challenge for human genetics. Although genome-wide association studies have successfully detected many common causal variants, they are underpowered in identifying disease variants that are too rare or population-specific to be imputed from a general reference panel and thus are poorly represented on commercial SNP arrays. We set out to overcome these challenges and detect association between disease and rare alleles using SNP arrays by relying on long stretches of genomic sharing that are identical by descent. We have developed an algorithm, DASH, which builds upon pairwise identical-by-descent shared segments to infer clusters of individuals likely to be sharing a single haplotype. DASH constructs a graph with nodes representing individuals and links on the basis of such segments spanning a locus and uses an iterative minimum cut algorithm to identify densely connected components. We have applied DASH to simulated data and diverse GWAS data sets by constructing haplotype clusters and testing them for association. In simulations we show this approach to be significantly more powerful than single-marker testing in an isolated population that is from Kosrae, Federated States of Micronesia and has abundant IBD, and we provide orthogonal information for rare, recent variants in the outbred Wellcome Trust Case-Control Consortium (WTCCC) data. In both cohorts, we identified a number of haplotype associations, five such loci in the WTCCC data and ten in the isolated, that were conditionally significant beyond any individual nearby markers. We have replicated one of these loci in an independent European cohort and identified putative structural changes in low-pass whole-genome sequence of the cluster carriers.