Genetic epidemiology of single-nucleotide polymorphisms

Functional nsSNPs from carcinogenesis-related genes expressed in breast tissue: potential breast cancer risk alleles and their distribution across human populations

Although highly penetrant alleles of BRCA1 and BRCA2 have been shown to predispose to breast cancer, the majority of breast cancer cases are assumed to result from the presence of low-moderate penetrant alleles and environmental carcinogens. Non-synonymous single nucleotide polymorphisms (nsSNPs) are hypothesised to contribute to disease susceptibility and approximately 30 per cent of them are predicted to have a biological significance. In this study, we have applied a bioinformatics-based strategy to identify breast cancer-related nsSNPs from 981 carcinogenesis-related genes expressed in breast tissue. Our results revealed a total of 367 validated nsSNPs, 109 (29.7 per cent) of which are predicted to affect the protein function (functional nsSNPs), suggesting that these nsSNPs are likely to influence the development and homeostasis of breast tissue and hence contribute to breast cancer susceptibility. Sixty-seven of the functional nsSNPs presented as commonly occurring nsSNPs (minor allele frequencies ≥ 5 per cent), representing excellent candidates for breast cancer susceptibility. Additionally, a non-uniform distribution of the common functional nsSNPs among different human populations was observed: 15 nsSNPs were reported to be present in all populations analysed, whereas another set of 15 nsSNPs was specific to particular population(s). We propose that the nsSNPs analysed in this study constitute a unique resource of potential genetic factors for breast cancer susceptibility. Furthermore, the variations in functional nsSNP allele frequencies across major population backgrounds may point to the potential variability of the molecular basis of breast cancer predisposition and treatment response among different human populations.

Cosmopolitan linkage disequilibrium maps

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.

Pharmacogenomics

So far no pharmacogenetic/genomic study has been conducted specifically for anxiety disorders. Some of the presented results, however, do pertain to such disorders. For example, pharmacokinetic aspects of antidepressant drug therapy likely also apply to patients with anxiety disorders, and several genetic polymorphisms in the cytochrome P450 (CYP) gene family and drug transporter molecules, such as the multidrug resistance (MDR) gene type 1, have been reported to influence the pharmacokinetics of antidepressant drugs. At this stage of pharmacogenomics research, it is difficult to interpret the relevance of pharmacodynamic-genetic association studies conducted in depressed patients for anxiety disorders. A number of studies have reported an influence of polymorphisms of genes mostly in the serotonergic pathway on the response to antidepressant drugs in patients suffering from depression. In order to know whether they can be extrapolated to patients with anxiety disorders, clinical studies are warranted. Despite all the shortcomings of the currently available pharmacogenetic studies, this field holds great promise for the treatment of anxiety disorders. In the future, psychiatrists may be able to base treatment decisions (i.e., the type and dose of prescribed drug) on more objective parameters than only the diagnostic algorithms used now. This will limit unwanted side effects and adverse drug reactions, and could reduce time to response, resulting in a more individualized pharmacotherapy.

A two-stage design for multiple testing in large-scale association studies

Modern association studies often involve a large number of markers and hence may encounter the problem of testing multiple hypotheses. Traditional procedures are usually over-conservative and with low power to detect mild genetic effects. From the design perspective, we propose a two-stage selection procedure to address this concern. Our main principle is to reduce the total number of tests by removing clearly unassociated markers in the first-stage test. Next, conditional on the findings of the first stage, which uses a less stringent nominal level, a more conservative test is conducted in the second stage using the augmented data and the data from the first stage. Previous studies have suggested using independent samples to avoid inflated errors. However, we found that, after accounting for the dependence between these two samples, the true discovery rate increases substantially. In addition, the cost of genotyping can be greatly reduced via this approach. Results from a study of hypertriglyceridemia and simulations suggest the two-stage method has a higher overall true positive rate (TPR) with a controlled overall false positive rate (FPR) when compared with single-stage approaches. We also report the analytical form of its overall FPR, which may be useful in guiding study design to achieve a high TPR while retaining the desired FPR.

Clinical genotyping: The need for interrogation of single nucleotide polymorphisms and mutations in the clinical laboratory

BACKGROUND

Detection of single nucleotide polymorphisms (SNPs) and gene mutations is becoming more routine to the clinical laboratory.

METHODS

Completion of the Human Genome Project has led to new scientific knowledge of human disease processes that has revealed the most fundamental of abnormalities in nucleic acids while at the same time bringing some of the most sophisticated diagnostic tools to the clinical laboratory. In addition, public awareness (both lay persons and healthcare providers) and sensitivity to human genetics has increased tremendously. Together, this rapidly evolving science and increased public education has led to an increasing demand for genotypic testing.

CONCLUSIONS

There are several clinical applications of human genotyping that are available using these newer technologies.

Mapping genes for common diseases: the case for genetic (LD) maps

We examine the current effort to develop a haplotype map of the human genome and suggest an alternative approach which represents linkage disequilibrium patterns in the form of a metric LD map. LD maps have some of the useful properties of genetic linkage maps but have a much higher resolution which is optimal for SNP-based association mapping of common diseases. The studies that have been undertaken to date suggest that LD and recombination maps show some close similarities because of abundant, narrow, recombination hot spots. These hot spots are co-localised in all populations but, unlike linkage maps, LD maps differ in scale for different populations because of differences in population history. The prospects for developing optimized panels of SNPs and the use of linkage disequilibrium maps in disease gene localisation are assessed in the light of recent evidence.

Detection of single nucleotide polymorphisms in coagulation factor XI deficient patients by multitemperature single-strand conformation polymorphism analysis

Factor XI (FXI) deficiency is a rare inherited disorder which can cause bleeding complications especially in case of hemostatic challenge and/or in tissues with high fibrinolytic activity. A number of causative mutations have been described in FXI deficient individuals which have been detected by various screening methods. In this study, we present the application of the multitemperature single-strand conformation polymorphism analysis (MSSCP) on the FXI gene, a recently developed methodology for the detection of single nucleotide exchanges. We analyzed a total of 217 polymerase chain reaction (PCR) fragments from the promoter region as well as from exons 1-7 and 11-15 and compared the results to automatic fluorescent sequencing. A total of 29 PCR fragments showed single nucleotide exchanges in conventional fluorescent sequencing, representing 10 different mutations (nine missense mutations, one small deletion) and four frequent polymorphisms. With MSSCP electrophoresis at a standard temperature profile (gel temperature 35-20-10 degrees C) we were able to detect 13 of 14 (93%) different nucleotide exchanges in 25 of 29 PCR fragments (86%). Hence, the detection rate for genetic variations in the FXI gene was 86%. To evaluate the reproducibility, MSSCP was performed twice for 174 PCR fragments and the consistency between two electrophoretic runs was 99%. We conclude that the MSSCP is a sensitive, fast, and cost effective screening method for the detection of FXI gene mutations.

Durability of marker-quantitative trait loci haplotypes in structured populations

Given the relative ease of identifying genetic markers linked to QTL (compared to finding the loci themselves), it is natural to ask whether linked markers can be used to address questions concerning the contemporary dynamics and recent history of the QTL. In particular, can a marker allele found associated with a QTL allele in a QTL mapping study be used to track population dynamics or the history of the QTL allele? For this strategy to succeed, the marker-QTL haplotype must persist in the face of recombination over the relevant time frame. Here we investigate the dynamics of marker-QTL haplotype frequencies under recombination, population structure, and divergent selection to assess the potential utility of linked markers for a population genetic study of QTL. For two scenarios, described as "secondary contact" and "novel allele," we use both deterministic and stochastic methods to describe the influence of gene flow between habitats, the strength of divergent selection, and the genetic distance between a marker and the QTL on the persistence of marker-QTL haplotypes. We find that for most reasonable values of selection on a locus (s < or = 0.5) and migration (m > 1%) between differentially selected populations, haplotypes of typically spaced markers (5 cM) and QTL do not persist long enough (>100 generations) to provide accurate inference of the allelic state at the QTL.

Shaking the tree: mapping complex disease genes with linkage disequilibrium

Much effort and expense are being spent internationally to detect genetic polymorphisms contributing to susceptibility to complex human disease. Concomitantly, the technology for detecting and genotyping single nucleotide polymorphisms (SNPs) has undergone rapid development, yielding extensive catalogues of these polymorphisms across the genome. Population-based maps of the correlations amongst SNPs (linkage disequilibrium) are now being developed to accelerate the discovery of genes for complex human diseases. These genomic advances coincide with an increasing recognition of the importance of very large sample sizes for studying genetic effects. Together, these new genetic and epidemiological data hold renewed promise for the identification of susceptibility genes for complex traits. We review the state of knowledge about the structure of the human genome as related to SNPs and linkage disequilibrium, discuss the potential applications of this knowledge to mapping complex disease genes, and consider the issues facing whole genome association scanning using SNPs.

Ancestral origins of the prion protein gene D178N mutation in the Basque Country

Fatal familial insomnia (FFI) and familial Creutzfeldt-Jakob disease (fCJD) are familial prion diseases with autosomal dominant inheritance of the D178N mutation. FFI has been reported in at least 27 pedigrees around the world. Twelve apparently unrelated FFI and fCJD pedigrees with the characteristic D178N mutation have been reported in the Prion Diseases Registry of the Basque Country since 1993. The high incidence of familial prion diseases in this region may reflect a unique ancestral origin of the chromosome carrying this mutation. In order to investigate this putative founder effect, we developed "happy typing", a new approach to the happy mapping method, which consists of the physical isolation of large haploid genomic DNA fragments and their analysis by the Polymerase Chain Reaction in order to perform haplotypic analysis instead of pedigree analysis. Six novel microsatellite markers, located in a 150-kb genomic segment flanking the PRNP gene were characterized for typing haploid DNA fragments of 285 kb in size. A common haplotype was found in patients from the Basque region, strongly suggesting a founder effect. We propose that "happy typing" constitutes an efficient method for determining disease-associated haplotypes, since the analysis of a single affected individual per pedigree should provide sufficient evidence.

Estimation of relative allele frequencies of single-nucleotide polymorphisms in different populations by microarray hybridization of pooled DNA

Single-nucleotide polymorphisms (SNPs) are considered useful polymorphic markers for genetic studies of polygenic traits. A new practical approach to high-throughput genotyping of SNPs in a large number of individuals is needed in association study and other studies on relationships between genes and diseases. We have developed an accurate and high-throughput method for determining the allele frequencies by pooling the DNA samples and applying a DNA microarray hybridization analysis. In this method, the combination of the microarray, DNA pooling, probe pair hybridization, and fluorescent ratio analysis solves the dual problems of parallel multiple sample analysis, and parallel multiplex SNP genotyping for association study. Multiple DNA samples are immobilized on a slide and a single hybridization is performed with a pool of allele-specific oligonucleotide probes. The results of this study show that hybridization of microarray from pooled DNA samples can accurately obtain estimates of absolute allele frequencies in a sample pool. This method can also be used to identify differences in allele frequencies in distinct populations. It is amenable to automation and is suitable for immediate utilization for high-throughput genotyping of SNP.

Evaluation of microsatellite markers in association studies: a search for an immune-related susceptibility gene in sarcoidosis

Association studies using linkage disequilibrium (LD) between candidate loci and nearby markers have been proposed to identify susceptibility genes for complex diseases. We analyzed polymorphisms of microsatellites (MSs) and LD patterns of the regions in which candidate genes related to the Th1 immune response have been annotated and attempted to identify a susceptibility gene for sarcoidosis in a marker-based association study. Nineteen MSs were identified in six Th1-related genes (IFNGR1, IFNGR2, IL12RB1, IL12RB2, STAT1 and STAT4) and then eight were further characterized as useful polymorphic markers. Most of these MSs showed LD with single nucleotide polymorphisms (SNPs) on both 5' and 3' ends of these candidate genes, in which r(2) values between at least one of the MS marker alleles and the SNPs were higher than 0.1. A significant association with one MS allele near STAT4 was shown and a cluster of SNPs in LD with the MS marker was associated with sarcoidosis. These results suggest that association studies using not only SNPs but also multi-allelic MS within or near candidate loci would be useful markers to search for a disease susceptibility gene, especially in populations with unknown LD structure.

Complexities in psychiatric genetics

A substantial contribution of genetic factors to the risk of psychiatric disorders such as schizophrenia, bipolar disorder, autism, and drug and alcohol dependence has already been established. However, the familial transmission of these disorders cannot be explained by simple Mendelian models of inheritance, and non-genetic factors must also play a substantial role in their etiologies. Furthermore, the prevalence of any major psychiatric disorder is a great deal higher than that of Mendelian disorders. It has been suggested that evolutionary forces would rapidly eliminate large gene effects, which would suggest that mental disorders, which are highly prevalent, are associated with minor gene effects (Risch, 1994). The current paradigm is that genes with small interacting genetic effects, in conjunction with environmental factors, affect the risk for psychiatric disease. New laboratory and statistical methodology and database tools, and the availability of large clinical samples for the study of linkage and association sustain optimism that genes involved with these diseases will be characterized in the near future. This accomplishment should in turn lead not only to a better understanding of the primary molecular pathophysiology and to more specific and effective therapies, but also to a better understanding of non-genetic risk factors that could be targets for preventive strategies.

Large-scale single-nucleotide polymorphism (SNP) and haplotype analyses, using dense SNP Maps, of 199 drug-related genes in 752 subjects: the analysis of the association between uncommon SNPs within haplotype blocks and the haplotypes constructed with haplotype-tagging SNPs

To optimize the strategies for population-based pharmacogenetic studies, we extensively analyzed single-nucleotide polymorphisms (SNPs) and haplotypes in 199 drug-related genes, through use of 4,190 SNPs in 752 control subjects. Drug-related genes, like other genes, have a haplotype-block structure, and a few haplotype-tagging SNPs (htSNPs) could represent most of the major haplotypes constructed with common SNPs in a block. Because our data included 860 uncommon (frequency <0.1) SNPs with frequencies that were accurately estimated, we analyzed the relationship between haplotypes and uncommon SNPs within the blocks (549 SNPs). We inferred haplotype frequencies through use of the data from all htSNPs and one of the uncommon SNPs within a block and calculated four joint probabilities for the haplotypes. We show that, irrespective of the minor-allele frequency of an uncommon SNP, the majority (mean +/- SD frequency 0.943+/-0.117) of the minor alleles were assigned to a single haplotype tagged by htSNPs if the uncommon SNP was within the block. These results support the hypothesis that recombinations occur only infrequently within blocks. The proportion of a single haplotype tagged by htSNPs to which the minor alleles of an uncommon SNP were assigned was positively correlated with the minor-allele frequency when the frequency was <0.03 (P<.000001; n=233 [Spearman's rank correlation coefficient]). The results of simulation studies suggested that haplotype analysis using htSNPs may be useful in the detection of uncommon SNPs associated with phenotypes if the frequencies of the SNPs are higher in affected than in control populations, the SNPs are within the blocks, and the frequencies of the SNPs are >0.03.

Using germ-line genetic variation to investigate and treat cancer

For many years, there has been spirited debate as to the relative importance of environmental and genetic factors in the pathogenesis of cancer. Current efforts to annotate the human genome for germ-line genetic variants should establish the foundation for dissecting the contribution of genetics to the risk for cancer susceptibility. Population-based studies should be conducted to determine the influence of germline genetic variation on cancer outcomes, including the efficacy of anti-cancer drugs and the risk for life-threatening toxicities. Although we are early in the investigation of the influence of germline genetics on cancer outcomes, it is likely that, in the future, it will be possible to individualize therapeutic interventions. In turn, knowledge of genetic risk factors could afford opportunities for prevention, early intervention and minimization of deleterious toxicities associated with cancer therapy.

The future of genetic research on appetitive behavior

The risk for developing obesity has a significant genetic component. Several quantitative trait loci and candidate genes have been identified using current methodological approaches however the information gained thus far is insufficient to adequately explain the genetics underlying human obesity. The completion of a draft of the human genome sequence, the potential benefit of single nucleotide polymorphisms association studies for identifying risk conferring alleles, and developing functional genomics technologies promise to accelerate obesity gene discovery. These advances, used with current evaluative tools (murine molecular genetic techniques), may increase our understanding of human obesity, and ultimately provide better approaches to diagnosis and treatment.

Positional cloning by linkage disequilibrium

Recently, metric linkage disequilibrium (LD) maps that assign an LD unit (LDU) location for each marker have been developed (Maniatis et al. 2002). Here we present a multiple pairwise method for positional cloning by LD within a composite likelihood framework and investigate the operating characteristics of maps in physical units (kb) and LDU for two bodies of data (Daly et al. 2001; Jeffreys et al. 2001) on which current ideas of blocks are based. False-negative indications of a disease locus (type II error) were examined by selecting one single-nucleotide polymorphism (SNP) at a time as causal and taking its allelic count (0, 1, or 2, for the three genotypes) as a pseudophenotype, Y. By use of regression and correlation, association between every pseudophenotype and the allelic count of each SNP locus (X) was based on an adaptation of the Malecot model, which includes a parameter for location of the putative gene. By expressing locations in kb or LDU, greater power for localization was observed when the LDU map was fitted. The efficiency of the kb map, relative to the LDU map, to describe LD varied from a maximum of 0.87 to a minimum of 0.36, with a mean of 0.62. False-positive indications of a disease locus (type I error) were examined by simulating an unlinked causal SNP and the allele count was used as a pseudophenotype. The type I error was in good agreement with Wald's likelihood theorem for both metrics and all models that were tested. Unlike tests that select only the most significant marker, haplotype, or haploset, these methods are robust to large numbers of markers in a candidate region. Contrary to predictions from tagging SNPs that retain haplotype diversity, the sample with smaller size but greater SNP density gave less error. The locations of causal SNPs were estimated with the same precision in blocks and steps, suggesting that block definition may be less useful than anticipated for mapping a causal SNP. These results provide a guide to efficient positional cloning by SNPs and a benchmark against which the power of positional cloning by haplotype-based alternatives may be measured.

Linkage disequilibrium in young genetically isolated Dutch population

The design and feasibility of genetic studies of complex diseases are critically dependent on the extent and distribution of linkage disequilibrium (LD) across the genome and between different populations. We have examined genomewide and region-specific LD in a young genetically isolated population identified in the Netherlands by genotyping approximately 800 Short Tandem Repeat markers distributed genomewide across 58 individuals. Several regions were analyzed further using a denser marker map. The permutation-corrected measure of LD was used for analysis. A significant (P<0.0004) relation between LD and genetic distance on a genomewide scale was found. Distance explained 4% of the total LD variation. For fine-mapping data, distance accounted for a larger proportion of LD variation (up to 39%). A notable similarity in the genomewide distribution of LD was revealed between this population and other young genetically isolated populations from Micronesia and Costa Rica. Our study population and experiment was simulated in silico to confirm our knowledge of the history of the population. High agreement was observed between results of analysis of simulated and empirical data. We conclude that our population shows a high level of LD similar to that demonstrated previously in other young genetic isolates. In Europe, there may be a large number of young genetically isolated populations that are similar in history to ours. In these populations, a similar degree of LD is expected and thus they may be effectively used for linkage or LD mapping.

Pyrosequencing-based SNP allele frequency estimation in DNA pools

Association screening involving numerous genetic markers is facilitated by the analysis of pooled DNA samples rather than individual samples. Several genotyping methods have shown high accuracy and precision of allele frequency estimation in pools. Here, we expand the validation of SNP allele frequency estimation in DNA pools using Pyrosequencing by analyzing 186 pools for three SNPs representing complex sequencing cases. The correlation coefficient between estimated and true allele frequencies ranged between 0.979 and 0.996 and tended to increase with pool size, whereas the difference between estimated and true allele frequencies was 2.37+/-0.11%, in post-PCR pools. The precision was 1.73%. Pool size had no significant effect on accuracy and precision. A comparison between post-PCR and pre-PCR pools showed that for pre-PCR pooling efforts to accurately quantify the genomic DNA samples to be pooled and subsequently amplified are critical. To conclude, Pyrosequencing can be used for allele frequency estimation in DNA pools of SNPs with complex sequencing scenarios with accuracy and precision values in ranges comparable with those of other SNP typing techniques. Considering the ease of use, short run and analysis times, and little instrument maintenance requirements, Pyrosequencing may even be a preferred option.

Automated SNP detection in expressed sequence tags: statistical considerations and application to maritime pine sequences

We developed an automated pipeline for the detection of single nucleotide polymorphisms (SNPs) in expressed sequence tag (EST) data sets, by combining three DNA sequence analysis programs: Phred, Phrap and PolyBayes. This application requires access to the individual electrophoregram traces. First, a reference set of 65 SNPs was obtained from the sequencing of 30 gametes in 13 maritime pine (Pinus pinaster Ait.) gene fragments (6671 bp), resulting in a frequency of 1 SNP every 102.6 bp. Second, parameters of the three programs were optimized in order to retrieve as many true SNPs, while keeping the rate of false positive as low as possible. Overall, the efficiency of detection of true SNPs was 83.1%. However, this rate varied largely as a function of the rare SNP allele frequency: down to 41% for rare SNP alleles (frequency < 10%), up to 98% for allele frequencies above 10%. Third, the detection method was applied to the 18498 assembled maritime pine (Pinus pinaster Ait.) ESTs, allowing to identify a total of 1400 candidate SNPs, in contigs containing between 4 and 20 sequence reads. These genetic resources, described for the first time in a forest tree species, were made available at http://www.pierroton.inra/genetics/Pinesnps. We also derived an analytical expression for the SNP detection probability as a function of the SNP allele frequency, the number of haploid genomes used to generate the EST sequence database, and the sample size of the contigs considered for SNP detection. The frequency of the SNP allele was shown to be the main factor influencing the probability of SNP detection.

Genetic epidemiology, genetic maps and positional cloning

Genetic epidemiology developed in the middle of the last century, focused on inherited causes of disease but with methods and results applicable to other traits and even forensics. Early success with linkage led to the localization of genes contributing to disease, and ultimately to the Human Genome Project. The discovery of millions of DNA markers has encouraged more efficient positional cloning by linkage disequilibrium (LD), using LD maps and haplotypes in ways that are rapidly evolving. This has led to large international programmes, some promising and others alarming, with laws about DNA patenting and ethical guidelines for responsible research still struggling to be born.

First-generation SNP/InDel markers tagging loci for pathogen resistance in the potato genome

A panel of 17 tetraploid and 11 diploid potato genotypes was screened by comparative sequence analysis of polymerase chain reaction (PCR) products for single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels), in regions of the potato genome where genes for qualitative and/or quantitative resistance to different pathogens have been localized. Most SNP and InDel markers were derived from bacterial artificial chromosome (BAC) insertions that contain sequences similar to the family of plant genes for pathogen resistance having nucleotide-binding-site and leucine-rich-repeat domains (NBS-LRR-type genes). Forty-four such NBS-LRR-type genes containing BAC-insertions were mapped to 14 loci, which tag most known resistance quantitative trait loci (QTL) in potato. Resistance QTL not linked to known resistance-gene-like (RGL) sequences were tagged with other markers. In total, 78 genomic DNA fragments with an overall length of 31 kb were comparatively sequenced in the panel of 28 genotypes. 1498 SNPs and 127 InDels were identified, which corresponded, on average, to one SNP every 21 base pairs and one InDel every 243 base pairs. The nucleotide diversity of the tetraploid genotypes (pi = 0.72 x 10(-3)) was lower when compared with diploid genotypes (pi = 2.31 x 10(-3)). RGL sequences showed higher nucleotide diversity when compared with other sequences, suggesting evolution by divergent selection. Information on sequences, sequence similarities, SNPs and InDels is provided in a database that can be queried via the Internet.

A Metric Linkage Disequilibrium Map of a Human Chromosome

We used LDMAP (Maniatis et al. 2002) to analyse SNP data spanning chromosome 22 (Dawson et al. 2002), to obtain a whole-chromosome metric LD map. The LD map, with map distances analogous to the centiMorgan scale of linkage maps, identifies regions of high LD as plateaus ('blocks') and characterises steps which define the relationship between these regions. From this map we estimate that block regions comprise between 32% and 55% of the euchromatic portion of chromosome 22 and that increasing marker density within steps may increase block coverage. Steps are regions of low LD which correspond to areas of variable recombination intensity. The intensity of recombination is related to the height of the step and thus intense recombination hot-spots can be distinguished from more randomly distributed historical events. The LD maps are more closely related to the high-resolution linkage map (Kong et al. 2002) than average measures of rho with recombination accounting for between 34% and 52% of the variance in patterns of LD (r=0.58 - 0.71, p=0.0001). Step regions are closely correlated with a range of sequence motifs including GT/CA repeats. The LD map identifies holes in which greater marker density is required and defines the optimal SNP spacing for positional cloning, which suggests that some multiple of around 50,000 SNPs will be required to efficiently screen Caucasian genomes. Further analyses which investigate selection of informative SNPs and the effect of SNP allele frequency and marker density will refine this estimate.

Genetic variation and hematology: single-nucleotide polymorphisms, haplotypes, and complex disease

In the course of generating a draft sequence of the human genome, we now recognize the enormous scope of genetic variation among humans, which can be used to probe the genetics of complex diseases such as leukemia or thrombosis. There is already mounting evidence of new susceptibility genes and genes that interact with environmental factors. Genetic variants, especially single-nucleotide polymorphisms (SNPs), also can be utilized to investigate potential modifiers of disease. Genetic variation can be applied to study pharmacogenomics, which could eventually drive the choice of therapeutic and interventional strategies. The genomic revolution ultimately should give insights into key mechanisms in hematological disorders that can be translated into targeted therapies.

Protein kinase C/ζ (PRKCZ) Gene is associated with type 2 diabetes in Han population of North China and analysis of its haplotypes

AIM: To identify the susceptible gene (s) for type 2 diabetes in the prevousely mapped region, 1p36.33-p36.23, in Han population of North China using single nucleotide polymorphisms (SNPs) and to analyze the haplotypes of the gene (s) related to type 2 diabetes.

METHODS: Twenty three SNPs located in 10 candidate genes in the mapped region were chosen from public SNP domains with bioinformatic methods, and the single base extension (SBE) method was used to genotype the loci for 192 sporadic type 2 diabetes patients and 172 normal individuals, all with Han ethical origin, to perform this case-control study. The haplotypes with significant difference in the gene (s) were further analyzed.

RESULTS: Among the 23 SNPs, 8 were found to be common in Chinese Han population. Allele frequency of one SNP, rs436045 in the protein kinase C/ζgene (PRKCZ) was statistically different between the case and control groups (P < 0.05). Furthermore, haplotypes at five SNP sites of PRKCZ gene were identified.

CONCLUSION: PRKCZ gene may be associated with type 2 diabetes in Han population in North China. The haplotypes at five SNP sites in this gene may be responsible for this association.

New approaches to investigating heterogeneity in complex traits

Great advances in the field of genetics have been made in the last few years. However, resolving the complexity that underlies the susceptibility to many polygenic human diseases remains a major challenge to researchers. The fast increase in availability of genetic data and the better understanding of the clinical and pathological heterogeneity of many autoimmune diseases such as multiple sclerosis, but also Parkinson's disease, Alzheimer's disease, and many more, have changed our views on their pathogenesis and diagnosis, and begins to influence clinical management. At the same time, more powerful methods that allow the analysis of large numbers of genes and proteins simultaneously open opportunities to examine their complex interactions. Using multiple sclerosis as a prototype, we review here how new methodologies such as gene expression profiling can be exploited to gain insight into complex trait diseases.

Genetic risk factors for cerebrovascular disease in children with sickle cell disease: design of a case-control association study and genomewide screen

BACKGROUND

The phenotypic heterogeneity of sickle cell disease is likely the result of multiple genetic factors and their interaction with the sickle mutation. High transcranial doppler (TCD) velocities define a subgroup of children with sickle cell disease who are at increased risk for developing ischemic stroke. The genetic factors leading to the development of a high TCD velocity (i.e. cerebrovascular disease) and ultimately to stroke are not well characterized.

METHODS

We have designed a case-control association study to elucidate the role of genetic polymorphisms as risk factors for cerebrovascular disease as measured by a high TCD velocity in children with sickle cell disease. The study will consist of two parts: a candidate gene study and a genomewide screen and will be performed in 230 cases and 400 controls. Cases will include 130 patients (TCD > or = 200 cm/s) randomized in the Stroke Prevention Trial in Sickle Cell Anemia (STOP) study as well as 100 other patients found to have high TCD in STOP II screening. Four hundred sickle cell disease patients with a normal TCD velocity (TCD < 170 cm/s) will be controls. The candidate gene study will involve the analysis of 28 genetic polymorphisms in 20 candidate genes. The polymorphisms include mutations in coagulation factor genes (Factor V, Prothrombin, Fibrinogen, Factor VII, Factor XIII, PAI-1), platelet activation/function (GpIIb/IIIa, GpIb IX-V, GpIa/IIa), vascular reactivity (ACE), endothelial cell function (MTHFR, thrombomodulin, VCAM-1, E-Selectin, L-Selectin, P-Selectin, ICAM-1), inflammation (TNFalpha), lipid metabolism (Apo A1, Apo E), and cell adhesion (VCAM-1, E-Selectin, L-Selectin, P-Selectin, ICAM-1). We will perform a genomewide screen of validated single nucleotide polymorphisms (SNPs) in pooled DNA samples from 230 cases and 400 controls to study the possible association of additional polymorphisms with the high-risk phenotype. High-throughput SNP genotyping will be performed through MALDI-TOF technology using Sequenom's MassARRAY system.

DISCUSSION

It is expected that this study will yield important information on genetic risk factors for the cerebrovascular disease phenotype in sickle cell disease by clarifying the role of candidate genes in the development of high TCD. The genomewide screen for a large number of SNPs may uncover the association of novel polymorphisms with cerebrovascular disease and stroke in sickle cell disease.

Genetic variation and hematopoietic stem cell transplantation: expansion of the paradigm

Genetic variation has been the mainstay of hematopoietic stem cell transplantation since the first transplants were attempted. A significant expansion of genetic knowledge is under way, as the draft sequence of the human genome is annotated. Hematopoietic stem cell transplantation is a field that will greatly benefit from this new knowledge, but the manner in which it is applied is daunting. Variation within key molecules related to hematopoietic stem cell transplant in combination with the current knowledge of human leukocyte antigen variation will serve to improve donor-recipient matches and clinical outcome.

Common 5' beta-globin RFLP haplotypes harbour a surprising level of ancestral sequence mosaicism

Blocks of linkage disequilibrium (LD) in the human genome represent segments of ancestral chromosomes. To investigate the relationship between LD and genealogy, we analysed diversity associated with restriction fragment length polymorphism (RFLP) haplotypes of the 5' beta-globin gene complex. Genealogical analyses were based on sequence alleles that spanned a 12.2-kb interval, covering 3.1 kb around the psibeta gene and 6.2 kb of the delta-globin gene and its 5' flanking sequence known as the R/T region. Diversity was sampled from a Kenyan Luo population where recent malarial selection has contributed to substantial LD. A single common sequence allele spanning the 12.2-kb interval exclusively identified the ancestral chromosome bearing the "Bantu" beta(s) (sickle-cell) RFLP haplotype. Other common 5' RFLP haplotypes comprised interspersed segments from multiple ancestral chromosomes. Nucleotide diversity was similar between psibeta and R/T-delta-globin but was non-uniformly distributed within the R/T-delta-globin region. High diversity associated with the 5' R/T identified two ancestral lineages that probably date back more than 2 million years. Within this genealogy, variation has been introduced into the 3' R/T by gene conversion from other ancestral chromosomes. Diversity in delta-globin was found to lead through parts of the main genealogy but to coalesce in a more recent ancestor. The well-known recombination hotspot is clearly restricted to the region 3' of delta-globin. Our analyses show that, whereas one common haplotype in a block of high LD represents a long segment from a single ancestral chromosome, others are mosaics of short segments from multiple ancestors related in genealogies of unsuspected complexity.

Nonparametric disequilibrium mapping of functional sites using haplotypes of multiple tightly linked single-nucleotide polymorphism markers

As the speed and efficiency of genotyping single-nucleotide polymorphisms (SNPs) increase, using the SNP map, it becomes possible to evaluate the extent to which a common haplotype contributes to the risk of disease. In this study we propose a new procedure for mapping functional sites or regions of a candidate gene of interest using multiple linked SNPs. Based on a case-parent trio family design, we use expectation-maximization (EM) algorithm-derived haplotype frequency estimates of multiple tightly linked SNPs from both unambiguous and ambiguous families to construct a contingency statistic S for linkage disequilibrium (LD) analysis. In the procedure, a moving-window scan for functional SNP sites or regions can cover an unlimited number of loci except for the limitation of computer storage. Within a window, all possible widths of haplotypes are utilized to find the maximum statistic S* for each site (or locus). Furthermore, this method can be applied to regional or genome-wide scanning for determining linkage disequilibrium using SNPs. The sensitivity of the proposed procedure was examined on the simulated data set from the Genetic Analysis Workshop (GAW) 12. Compared with the conventional and generalized TDT methods, our procedure is more flexible and powerful.

Complex haplotypes of IRS2 gene are associated with severe obesity and reveal heterogeneity in the effect of Gly1057Asp mutation

In order to understand the role of the insulin receptor substrate-2 (IRS2) gene (chromosome region: 13q34) in obesity, a complex disorder associated with insulin resistance and glucose intolerance, we determined single nucleotide polymorphims (SNPs) and complex haplotypes in women with morbid obesity and a body mass index (BMI) of 41+/-0.8 kg/m2 ( n=99) compared with controls having a BMI of 23.8+/-0.1 kg/m2 ( n=92). Sequencing of unphased DNA or digestion of polymerase chain reaction fragments revealed seven SNPs, including a new C/T(-769) replacement at the 5' untranslated region. Considering four or seven SNPs, we reconstructed with the PHASE program nine or 24 haplotypes, respectively, that were well correlated into the cladogram. Logistic regression analysis with nine haplotypes in the whole sample revealed that obesity was associated with haplotype H3, with P<0.025, an odds ratio (OR) of 1.9 and a 95% confidence interval (CI) of 1.1-3.4, or pairs 3/3 ( P<0.005, OR=8.7, CI=1.9-40.1) and 3/4 ( P<0.023, OR=2.5, CI=1.1-5.6), all containing the the Gly1057Asp allelic variant of IRS2, whereas controls were associated with H5 and H6 ( P<0.02, OR=0.2, CI=0.01-0.81). Although obese H5 carriers (also containing Gly1057Asp mutation) were the most insulin resistant, haplotypes of IRS2 were poorly correlated (analysis of variance) with insulin resistance. By contrast, haplotypes H3, H4 and pairs 3/3 were consistently associated with increased 2-h glucose levels during an oral glucose tolerance test in obese individuals ( P<0.0005, 0.025 and 0.027, respectively). These data indicate that IRS2 is an influential gene in severe obesity and glucose intolerance in this population, whereas gene-based haplotypes of IRS2 have revealed heterogeneity in the behaviour of the Gly1057Asp mutation in relation to insulin resistance.

Novel association suggests multiple independent QTLs within chromosome 5q21-33 region control variation in total humans IgE levels

Asthma is a common, heterogeneous, complex disease accompanied by raised total and specific immunoglobulin-E (IgE) antibody levels. Despite numerous previous reports of linkage and association of asthma, atopy and serum IgE levels to genes within the 5q21-33 region, definitive, replicable results are still not available. We used the classical twin design to (i) estimate the relative contributions of genes and environment to variation in total IgE levels, (ii) assess genetic linkage, and (iii) examine allelic association of 11 microsatellite markers spanning the 5q21-33 region to total IgE. Variation in total IgE level was shown to be highly heritable (65%). Although evidence for linkage of the 11 microsatellites to IgE was not observed, the omnibus test of association, not confounded by population substructure, showed positive association of D5S393 and D5S673 to IgE. Genes in the vicinity of D5S673 include hepatitis A virus receptor (HAVCR-1) and IL-12B. Recently, the mouse orthologue of HAVCR-1, the T-cell membrane family of proteins, have been shown to be in strong association with expression of airway hyperactivity in a mouse model of human asthma and atopy. IL-12B subserves many proinflammatory functions and also induces B cells proliferation.

Analysis of multiple single nucleotide polymorphisms of candidate genes related to coronary heart disease susceptibility by using support vector machines

Coronary heart disease (CHD) is a complex genetic disease involving gene-environment interaction. Many association studies between single nucleotide polymorphisms (SNPs) of candidate genes and CHD have been reported. We have applied a new method to analyze such relationships using support vector machines (SVMs), which is one of the methods for artificial neuronal network. We assumed that common haplotype implicit in genotypes will differ between cases and controls, and that this will allow SVM-derived patterns to be classifiable according to subject genotypes. Fourteen SNPs of ten candidate genes in 86 CHD patients and 119 controls were investigated. Genotypes were transformed to a numerical vector by giving scores based on difference between the genotypes of each subject and the reference genotypes, which represent the healthy normal population. Overall classification accuracy by SVMs was 64.4% with a receiver operating characteristic (ROC) area of 0.639. By conventional analysis using the chi2 test, the association between CHD and the SNP of the scavenger receptor B1 gene was most significant in terms of allele frequencies in cases vs. controls (p = 0.0001). In conclusion, we suggest that the application of SVMs for association studies of SNPs in candidate genes shows considerable promise and that further work could be usefully performed upon the estimation of CHD susceptibility in individuals of high risk.

Extent and distribution of linkage disequilibrium around the SLC11A1 locus

The SLC11A1 (or NRAMP1) locus on human chromosome 2q35 encodes for the protein solute carrier family 11, member 1. It is expressed in macrophages and involved in the early stages of macrophage priming and activation. Different association studies have shown that the SLC11A1 gene affects susceptibility to infectious diseases and autoimmune inflammatory diseases. Although functional SLC11A1 polymorphisms may account for its role in affecting the susceptibility to these diseases, the positive association can also be because of flanking polymorphisms showing linkage disequilibrium (LD) with this locus. This is the first systematic study to investigate the LD pattern within and around the gene. LD was investigated by genotyping 17 genetic markers in a Chinese population (n=360). The results indicate that LD is maintained at least 110 kb both upstream and downstream of the locus. The complex LD pattern demands that association studies with SLC11A1 should be carried out with both 5' and 3' markers. The strong LD between IL8RB and the 5' SLC11A1 markers also dictates that IL8RB be tested for association with these diseases. Thus, positive association with SLC11A1 should be interpreted cautiously, and IL8RB should also be considered as a potential candidate susceptibility gene unless proven otherwise.

Association testing by DNA pooling: an effective initial screen

With an ever-increasing resource of validated single-nucleotide polymorphisms (SNPs), the limiting factors in genome-wide association analysis have become genotyping capacity and the availability of DNA. We provide a proof of concept of the use of pooled DNA as a means of efficiently screening SNPs and prioritizing them for further study. This approach reduces the final number of SNPs that undergo full, sample-by-sample genotyping as well as the quantity of DNA used overall. We have examined 15 SNPs in the cholesteryl ester transfer protein (CETP) gene, a gene previously demonstrated to be associated with serum high-density lipoprotein cholesterol levels. The SNPs were amplified in two pools of DNA derived from groups of individuals with extremely high and extremely low serum high-density lipoprotein cholesterol levels, respectively. P values <0.05 were obtained for 14 SNPs, supporting the described association. Genotyping of the individual samples showed that the average margin of error in frequency estimate was approximately 4% when pools were used. These findings clearly demonstrate the potential of pooling techniques and their associated technologies as an initial screen in the search for genetic associations.

Haplotype and linkage disequilibrium architecture for human cancer-associated genes

To facilitate association-based linkage studies we have studied the linkage disequilibrium (LD) and haplotype architecture around five genes of interest for cancer risk: ATM, BRCA1, BRCA2, RAD51, and TP53. Single nucleotide polymorphisms (SNPs) were identified and used to construct haplotypes that span 93-200 kb per locus with an average SNP density of 12 kb. These markers were genotyped in four ethnically defined populations that contained 48 each of African Americans, Asian Americans, Hispanic Americans, and European Americans. Haplotypes were inferred using an expectation maximization (EM) algorithm, and the data were analyzed using D', R(2), Fisher's exact P-values, and the four-gamete test for recombination. LD levels varied widely between loci from continuously high LD across 200 kb to a virtual absence of LD across a similar length of genome. LD structure also varied at each gene and between populations studied. This variation indicates that the success of linkage-based studies will require a precise description of LD at each locus and in each population to be studied. One striking consistency between genes was that at each locus a modest number of haplotypes present in each population accounted for a high fraction of the total number of chromosomes. We conclude that each locus has its own genomic profile with regard to LD, and despite this there is the widespread trend of relatively low haplotype diversity. As a result, a low marker density should be adequate to identify haplotypes that represent the common variation at a locus, thereby decreasing costs and increasing efficacy of association studies.

Analysis of Clinically Relevant Single-Nucleotide Polymorphisms by Use of Microelectronic Array Technology

Background: Microelectronic DNA chip devices represent an emerging technology for genotyping. We developed methods for detection of single-nucleotide polymorphisms (SNPs) in clinically relevant genes.

Methods: Primer pairs, with one containing a 5′-biotin group, were used to PCR-amplify the region encompassing the SNP to be interrogated. After denaturation, the biotinylated strand was electronically targeted to discrete sites on streptavidin-coated gel pads surfaces by use of a Nanogen Molecular Workstation. Allele-specific dye-labeled oligonucleotide reporters were used for detection of wild-type and variant sequences. Methods were developed for SNPs in genes, including factor VII, β-globin, and the RET protooncogene. We genotyped 331 samples for five DNA variations in the factor VII gene, &gt;600 samples from patients with β-thalassemia, and 15 samples for mutations within the RET protooncogene. All samples were previously typed by various methods, including DNA sequence analysis, allele-specific PCR, and/or restriction enzyme digestion of PCR products.

Results: Analysis of amplified DNA required 4–6 h. After mismatched DNA was removed, signal-to-noise ratios were &gt;5. More than 940 samples were typed with the microelectronic array platform, and results were totally concordant with results obtained previously by other genotyping methods.

Conclusions: The described protocols detect SNPs of clinical interest with results comparable to those of other genotyping methods.

Single nucleotide polymorphism of the human high affinity choline transporter alters transport rate

High affinity choline uptake plays a critical role in the regulation of acetylcholine synthesis in cholinergic neurons. Recently, we succeeded in molecular cloning of the high affinity choline transporter (CHT1), which is specifically expressed in cholinergic neurons. Here we demonstrate the presence of functionally relevant, nonsynonymous single nucleotide polymorphism in the human CHT1 gene by comprehensive sequence analysis of the exons and the intron/exon boundaries including the transcription start site. The deduced amino acid change for the polymorphism is isoleucine to valine at amino acid 89 (I89V) located within the third transmembrane domain of the protein. The allele frequency of I89V was 6% for Ashkenazi Jews. Functional assessment of the I89V transporter in mammalian cell lines revealed a 40-50% decrease in V(max) for choline uptake rate compared with the wild type, whereas there was no alteration in the apparent affinities for choline, sodium, chloride, and the specific inhibitor hemicholinum-3. There also was no change in the specific hemicholinum-3 binding activity. The decreased choline uptake was not associated with the surface expression level of the protein as assessed by biotinylation assay. These results suggest an impaired substrate translocation in the I89V transporter. The Caenorhabditis elegans ortholog of CHT1 has a valine residue at the corresponding position and a single replacement from valine to isoleucine caused a decrease in the choline uptake rate by 40%, suggesting that this hydrophobic residue is generally critical in the choline transport rate in CHT1. This polymorphism in the allelic CHT1 gene may represent a predisposing factor for cholinergic dysfunction.

Murine pharmacogenomics: using the mouse to understand the genetics of drug therapy

Pharmacogenomics seeks to understand the genetic basis of interindividual differences in drug disposition and effects. Differential drug response is likely to most often be a complex trait, in which multiple genes contribute with varying strengths to the therapeutic phenotype. Due to technical and economic limitations, pharmacogenomic studies in humans are mainly limited to a small number of candidate genes with relatively major influences on drug response. This review discusses the problems involved in mapping genes underlying drug response in humans and highlights the theoretical and applied uses of mouse genetics to address these important issues.

Distribution of recombination crossovers and the origin of haplotype blocks: the interplay of population history, recombination, and mutation

Recent studies suggest that haplotypes are arranged into discrete blocklike structures throughout the human genome. Here, we present an alternative haplotype block definition that assumes no recombination within each block but allows for recombination between blocks, and we use it to study the combined effects of demographic history and various population genetic parameters on haplotype block characteristics. Through extensive coalescent simulations and analysis of published haplotype data on chromosome 21, we find that (1) the combined effects of population demographic history, recombination, and mutation dictate haplotype block characteristics and (2) haplotype blocks can arise in the absence of recombination hot spots. Finally, we provide practical guidelines for designing and interpreting studies investigating haplotype block structure.

DNA sequence variation in a 3.7-kb noncoding sequence 5' of the CYP1A2 gene: implications for human population history and natural selection

CYP1A2 is a cytochrome P450 gene that is involved in human physiological responses to a variety of drugs and toxins. To investigate the role of population history and natural selection in shaping genetic diversity in CYP1A2, we sequenced a 3.7-kb region 5' from CYP1A2 in a diverse collection of 113 individuals from three major continental regions of the Old World (Africa, Asia, and Europe). We also examined sequences in the 90-member National Institutes of Health DNA Polymorphism Discovery Resource (PDR). Eighteen single-nucleotide polymorphisms (SNPs) were found. Most of the high-frequency SNPs found in the Old World sample were also found in the PDR sample. However, six SNPs were detected in the Old World sample but not in the PDR sample, and two SNPs found in the PDR sample were not found in the Old World sample. Most pairs of SNPs were in complete linkage disequilibrium with one another, and there was no indication of a decline of disequilibrium with physical distance in this region. The average +/- SD nucleotide diversity in the Old World sample was 0.00043+/-0.00026. The African population had the highest level of nucleotide diversity and the lowest level of linkage disequilibrium. Two distinct haplotype clusters with broadly overlapping geographical distributions were present. Of the 17 haplotypes found in the Old World sample, 12 were found in the African sample, 8 were found in Indians, 5 were found in non-Indian Asians, and 5 were found in Europeans. Haplotypes found outside Africa were mostly a subset of those found within Africa. These patterns are all consistent with an African origin of modern humans. Seven SNPs were singletons, and the site-frequency spectrum showed a significant departure from neutral expectations, suggesting population expansion and/or natural selection. Comparison with outgroup species showed that four derived SNPs have achieved high (>0.90) frequencies in human populations, a trend consistent with the action of positive natural selection. These patterns have a number of implications for disease-association studies in CYP1A2 and other genes.

Molecular genetic studies of schizophrenia: challenges and insights

Schizophrenia (SCZ) is a mental disease that affects approximately 1% of the population with life-long devastating consequences. Based on evidence for a major contribution of genetic factors, a decade of extensive efforts has been dedicated to the search of DNA sequence variations that increase the risk to SCZ. Search for genes in rare multiplex SCZ families with a large number of affected individuals and quasi-Mendelian mode of inheritance using genetic linkage methodology has been one of the favorite strategies in psychiatric genetics. Although several genomic regions were suggested for linkage to SCZ, not a single gene causing or predisposing to SCZ has been identified thus far. Furthermore, it is not clear whether the genes of familial SCZ are also involved in sporadic cases that represent the overwhelming majority of SCZ patients. For sporadic cases, genetic association studies comparing the distribution of allelic frequencies of candidate genes in SCZ patients and controls have been performed but the outcome of such studies has also been quite modest. Several factors such as possible involvement of numerous interactive genes of minor effect, yet unknown environmental effects and diagnostic ambiguities of the disease have made genetic studies in SCZ quite unproductive. In terms of future studies, a genome-wide association search is a promising approach; however, this approach requires genotyping of thousands of genetic markers in large samples. In addition, a detailed analysis of the genes, expression of which changes under the influence of environmental factors, can indicate good candidates for genetic association studies. In this connection, investigations of the epigenetic regulation of genes and not only the DNA sequence variation, may be necessary for complete understanding of the etiopathogenic mechanisms of SCZ.

Single nucleotide polymorphism seeking long term association with complex disease

Successful investigation of common diseases requires advances in our understanding of the organization of the genome. Linkage disequilibrium provides a theoretical basis for performing candidate gene or whole-genome association studies to analyze complex disease. However, to constructively interrogate SNPs for these studies, technologies with sufficient throughput and sensitivity are required. A plethora of suitable and reliable methods have been developed, each of which has its own unique advantage. The characteristics of the most promising genotyping and polymorphism scanning technologies are presented. These technologies are examined both in the context of complex disease investigation and in their capacity to face the unique physical and molecular challenges (allele amplification, loss of heterozygosity and stromal contamination) of solid tumor research.

Finding genes influencing susceptibility to complex diseases in the post-genome era

During the last decade, hundreds of genes that harbor mutations causing simple Mendelian disorders have been identified using a combination of linkage analysis and positional cloning techniques. Traditional approaches to gene mapping have been largely unsuccessful in mapping genes influencing so-called 'complex' genetic diseases, however, because of low power and other factors. Complex genetic diseases do not display simple Mendelian patterns of inheritance, although genes do have an influence and close relatives of probands consequently have an increased risk. These disorders are thought to be due to the combined effects of variation at multiple interacting genes and the environment. Complex diseases have a significant impact on human health because of their high population incidence (unlike simple Mendelian disorders, which tend to be rare). New techniques are being developed aimed specifically at mapping genes conferring susceptibility to complex diseases. A project aimed at mapping genes influencing susceptibility to a complex disease may be undertaken in several stages: establishing a genetic basis for the disease in one or more populations; measuring the distribution of gene effects; studying statistical power using models; carrying out marker-based mapping studies using linkage or association. Quantitative genetic models can be used to estimate the heritability of a complex (polygenic) disease, as well as to predict the distribution of gene effects and to test whether one or more quantitative trait loci (QTLs) exist. Such models can be used to predict the power of different mapping approaches, but are often unrealistic and therefore provide only approximate predictions. Linkage analyses, association studies and family-based association tests are all hindered by low power and other specific problems. Association studies tend to be more powerful but can generate spurious associations due to population admixture. Alternative strategies for association mapping include the use of recent founder populations or unique isolated populations that are genetically homogeneous, and the use of unlinked markers (so-called genomic controls) to assign different regions of the genome of an admixed individual to particular source populations. Linkage disequilibrium observed in a sample of unrelated affected and normal individuals can also be used to fine-map a disease susceptibility locus in a candidate region. New Bayesian strategies make use of an annotated human genome sequence to further refine the position of a candidate disease susceptibility locus.

Genome screening for susceptibility loci in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a complex, multigenic autoimmune disease with a wide spectrum of clinical manifestations. Much of the pathology is attributed to deposition to various tissues of immune complexes continuously formed with autoantibodies; thus, the pathogenesis is related to dysregulation of self-reactive B cells. Recent family linkage studies and allele-sharing linkage analyses of affected sibling pairs have advanced genome screening for susceptibility loci in SLE, and a considerable number of chromosomal intervals with significant or suggestive linkage to SLE have been identified. However, there are still several inherent difficulties in precisely identifying loci and genes, as the complexity of polygenic inheritance of SLE phenotypes is considerable. One must note that each specific aspect of diverse SLE phenotypes (clinical manifestations and immunological abnormalities) is mostly controlled separately by a different set of susceptibility loci. Involvement of positive and negative epistatic gene interactions often puzzles genetic analyses. Studies on SLE using murine lupus models are ongoing to solve some of these difficulties. Comparative studies have identified several syntenic chromosomal intervals with susceptibility loci in both mouse models and humans. Thus, combining knowledge derived from both human and murine studies is vital. The ultimate identification of susceptibility genes and their functions will probably depend largely on studies using genetically manipulated mutant mice, including those with homologous recombination of potent polymorphic target genes. The up-coming completion of genomic sequences in mice and humans is predicted to limit the numbers of potent candidate genes in particular genomic intervals and accelerates this line of studies. Such knowledge will lead to elucidation of genetic and cellular mechanisms involved in the dysregulation of self-reactive lymphocytes in the pathogenesis of SLE. Prophylactic and therapeutic clinical approaches can then be better designed.