Prospects for whole-genome linkage disequilibrium mapping of common disease genes.

Recently, attention has focused on the use of whole-genome linkage disequilibrium (LD) studies to map common disease genes. Such studies would employ a dense map of single nucleotide polymorphisms (SNPs) to detect association between a marker and disease. Construction of SNP maps is currently underway. An essential issue yet to be settled is the required marker density of such maps. Here, I use population simulations to estimate the extent of LD surrounding common gene variants in the general human population as well as in isolated populations. Two main conclusions emerge from these investigations. First, a useful level of LD is unlikely to extend beyond an average distance of roughly 3 kb in the general population, which implies that approximately 500,000 SNPs will be required for whole-genome studies. Second, the extent of LD is similar in isolated populations unless the founding bottleneck is very narrow or the frequency of the variant is low (<5%).     

Haplotype tagging for the identification of common disease genes

Genome-wide linkage disequilibrium (LD) mapping of common disease genes could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping effort and cost of producing such an LD map could be reduced. Although different metrics that measure the extent of LD have been evaluated, even the most recent studies have not placed significant emphasis on the most informative and cost-effective method of LD mapping-that based on haplotypes. We have scanned 135 kb of DNA from nine genes, genotyped 122 single-nucleotide polymorphisms (SNPs; approximately 184,000 genotypes) and determined the common haplotypes in a minimum of 384 European individuals for each gene. Here we show how knowledge of the common haplotypes and the SNPs that tag them can be used to (i) explain the often complex patterns of LD between adjacent markers, (ii) reduce genotyping significantly (in this case from 122 to 34 SNPs), (iii) scan the common variation of a gene sensitively and comprehensively and (iv) provide key fine-mapping data within regions of strong LD. Our results also indicate that, at least for the genes studied here, the current version of dbSNP would have been of limited utility for LD mapping because many common haplotypes could not be defined. A directed re-sequencing effort of the approximately 10% of the genome in or near genes in the major ethnic groups would aid the systematic evaluation of the common variant model of common disease.     

The genetically isolated populations of Finland and sardinia may not be a panacea for linkage disequilibrium mapping of common disease genes

The choice of which population to study in the mapping of common disease genes may be critical. Isolated founder populations, such as that found in Finland, have already proved extremely useful for mapping the genes for specific rare monogenic disorders and are being used in attempts to map the genes underlying common, complex diseases. But simulation results suggest that, under the common disease-common variant hypothesis, most isolated populations will prove no more useful for linkage disequilibrium (LD) mapping of common disease genes than large outbred populations. There is very little empirical data to either support or refute this conclusion at present. Therefore, we evaluated LD between 21 common microsatellite polymorphisms on chromosome 18q21 in 2 genetic isolates (Finland and Sardinia) and compared the results with those observed in two mixed populations (United Kingdom and United States of America). Mean levels of LD were similar across all four populations. Our results provide empirical support for the expectation that genetic isolates like Finland and Sardinia will not prove significantly more valuable than general populations for LD mapping of common variants underlying complex disease.     

Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.     

A comprehensive linkage analysis for myocardial infarction and its related risk factors

Coronary artery disease and myocardial infarction (MI) are leading causes of death in the western world. Numerous studies have shown that risk factors such as diabetes mellitus, arterial hypertension and hypercholesterolemia contribute to the development of the disease. Although each risk factor by itself is partly under genetic control, a positive family history is an independent predictor, which suggests that there are additional susceptibility genes. We have scanned the whole genome in 513 families to identify chromosomal regions linked to myocardial infarction and related risk factors that are known to be under genetic control. Here we show, by using variance component analysis and incorporating risk factors, that risk of myocardial infarction maps to a single region on chromosome 14 with a significant lod score of 3.9 (pointwise P=0.00015, genome-wide P<0.05), providing evidence of a principal MI locus. To characterize this locus we analyzed each risk factor by itself. Serum concentrations of lipoprotein (a) show linkage to both the apolipoprotein (a) locus (lod score 26.99) and a new locus on chromosome 1 (lod score 3.8). There is suggestive linkage for diabetes mellitus on chromosome 6 (lod score 2.96), for hypertension on chromosomes 1 and 6, for high-density and low-density lipoprotein cholesterol on chromosomes 1 and 17, and for triglyceride concentrations on chromosome 9. Although some of these risk factors overlap with previously identified loci, none overlaps with the newly identified susceptibility locus for myocardial infarction and coronary artery disease.     

Systematic screen for human disease genes in yeast

High similarity between yeast and human mitochondria allows functional genomic study of Saccharomyces cerevisiae to be used to identify human genes involved in disease. So far, 102 heritable disorders have been attributed to defects in a quarter of the known nuclear-encoded mitochondrial proteins in humans. Many mitochondrial diseases remain unexplained, however, in part because only 40-60% of the presumed 700-1,000 proteins involved in mitochondrial function and biogenesis have been identified. Here we apply a systematic functional screen using the pre-existing whole-genome pool of yeast deletion mutants to identify mitochondrial proteins. Three million measurements of strain fitness identified 466 genes whose deletions impaired mitochondrial respiration, of which 265 were new. Our approach gave higher selection than other systematic approaches, including fivefold greater selection than gene expression analysis. To apply these advantages to human disorders involving mitochondria, human orthologs were identified and linked to heritable diseases using genomic map positions.     

Expression profiling of medulloblastoma: PDGFRA and the RAS/MAPK pathway as therapeutic targets for metastatic disease.

Little is known about the genetic regulation of medulloblastoma dissemination, but metastatic medulloblastoma is highly associated with poor outcome. We obtained expression profiles of 23 primary medulloblastomas clinically designated as either metastatic (M+) or non-metastatic (M0) and identified 85 genes whose expression differed significantly between classes. Using a class prediction algorithm based on these genes and a leave-one-out approach, we assigned sample class to these tumors (M+ or M0) with 72% accuracy and to four additional independent tumors with 100% accuracy. We also assigned the metastatic medulloblastoma cell line Daoy to the metastatic class. Notably, platelet-derived growth factor receptor alpha (PDGFRA) and members of the downstream RAS/mitogen-activated protein kinase (MAPK) signal transduction pathway are upregulated in M+ tumors. Immunohistochemical validation on an independent set of tumors shows significant overexpression of PDGFRA in M+ tumors compared to M0 tumors. Using in vitro assays, we show that platelet-derived growth factor alpha (PDGFA) enhances medulloblastoma migration and increases downstream MAP2K1 (MEK1), MAP2K2 (MEK2), MAPK1 (p42 MAPK) and MAPK3 (p44 MAPK) phosphorylation in a dose-dependent manner. Neutralizing antibodies to PDGFRA blocks MAP2K1, MAP2K2 and MAPK1/3 phosphorylation, whereas U0126, a highly specific inhibitor of MAP2K1 and MAP2K2, also blocks MAPK1/3. Both inhibit migration and prevent PDGFA-stimulated migration. These results provide the first insight into the genetic regulation of medulloblastoma metastasis and are the first to suggest a role for PDGFRA and the RAS/MAPK signaling pathway in medulloblastoma metastasis. Inhibitors of PDGFRA and RAS proteins should therefore be considered for investigation as possible novel therapeutic strategies against medulloblastoma.     

Leukaemia disease genes: large-scale cloning and pathway predictions

Retroviral insertional mutagenesis in BXH2 and AKXD recombinant inbred mice induces a high incidence of myeloid or B- and T-cell leukaemia and the proviral integration sites in the leukaemias provide powerful genetic tags for disease gene identification. Some of the disease genes identified by proviral tagging are also associated with human disease, validating this approach for human disease gene identification. Although many leukaemia disease genes have been identified over the years, many more remain to be cloned. Here we describe an inverse PCR (IPCR) method for proviral tagging that makes use of automated DNA sequencing and the genetic tools provided by the Mouse Genome Project, which increases the throughput for disease gene identification. We also use this IPCR method to clone and analyse more than 400 proviral integration sites from AKXD and BXH2 leukaemias and, in the process, identify more than 90 candidate disease genes. Some of these genes function in pathways already implicated in leukaemia, whereas others are likely to define new disease pathways. Our studies underscore the power of the mouse as a tool for gene discovery and functional genomics.     

A literature network of human genes for high-throughput analysis of gene expression

We have carried out automated extraction of explicit and implicit biomedical knowledge from publicly available gene and text databases to create a gene-to-gene co-citation network for 13,712 named human genes by automated analysis of titles and abstracts in over 10 million MEDLINE records. The associations between genes have been annotated by linking genes to terms from the medical subject heading (MeSH) index and terms from the gene ontology (GO) database. The extracted database and accompanying web tools for gene-expression analysis have collectively been named 'PubGene'. We validated the extracted networks by three large-scale experiments showing that co-occurrence reflects biologically meaningful relationships, thus providing an approach to extract and structure known biology. We validated the applicability of the tools by analyzing two publicly available microarray data sets.     

Integrated detection and population-genetic analysis of SNPs and copy number variation

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.     

Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions

Systematic genetic interaction studies have illuminated many cellular processes. Here we quantitatively examine genetic interactions among 26 Saccharomyces cerevisiae genes conferring resistance to the DNA-damaging agent methyl methanesulfonate (MMS), as determined by chemogenomic fitness profiling of pooled deletion strains. We constructed 650 double-deletion strains, corresponding to all pairings of these 26 deletions. The fitness of single- and double-deletion strains were measured in the presence and absence of MMS. Genetic interactions were defined by combining principles from both statistical and classical genetics. The resulting network predicts that the Mph1 helicase has a role in resolving homologous recombination-derived DNA intermediates that is similar to (but distinct from) that of the Sgs1 helicase. Our results emphasize the utility of small molecules and multifactorial deletion mutants in uncovering functional relationships and pathway order.     

Genetic linkage of vitelliform macular degeneration (Best's disease) to chromosome 11q13.

Macular degeneration is the most common cause of legal blindness in older patients in developed countries. Best's vitelliform dystrophy is an early-onset, autosomal dominant form of macular degeneration characterized by an egg-yolk-like collection of lipofuscin beneath the pigment epithelium of the retinal macula. Fifty-seven members of a five-generation family affected with this disease were studied. A combination of ophthalmoscopy and electro-oculography was used for diagnosis; 29 patients were found to be affected and 16 unaffected. Linkage analysis mapped the disease-causing gene to chromosome 11q13. Three markers in this region were found to be significantly linked (Zmax > 3.0) to the disease. Multipoint analysis yielded a maximum Lod score of 9.3 in the interval between markers INT2 and D11S871.     

Magnitude and distribution of linkage disequilibrium in population isolates and implications for genome-wide association studies

The genome-wide distribution of linkage disequilibrium (LD) determines the strategy for selecting markers for association studies, but it varies between populations. We assayed LD in large samples (200 individuals) from each of 11 well-described population isolates and an outbred European-derived sample, using SNP markers spaced across chromosome 22. Most isolates show substantially higher levels of LD than the outbred sample and many fewer regions of very low LD (termed 'holes'). Young isolates known to have had relatively few founders show particularly extensive LD with very few holes; these populations offer substantial advantages for genome-wide association mapping.