ReviewSNP analysis to dissect human traits
Introduction
There is increasing appreciation of the role played by genetic predisposition and susceptibility in such common neurological disorders as Alzheimer's disease (AD), epilepsy, Parkinson's disease, multiple sclerosis and stroke. These disorders show familial aggregation, although the mode of inheritance is not clearly Mendelian in most cases. The role that a common genomic variant might play in susceptibility to disease is best exemplified by the role that the apolipoprotein E (APOE) ε4 allele plays in AD. The ε4 allele is highly associated with the presence of AD and with earlier age of onset of disease. It is a robust association seen in many populations studied [1]. Polymorphic variation has also been implicated in stroke and cardiovascular disease [2] and in multiple sclerosis [3]. It is increasingly clear that the risk of developing many common disorders and the metabolism of medications used to treat these conditions are substantially influenced by underlying genomic variation, although the effects of any one variant might be small.
In the 1980s, restriction enzymes were used to identify single base-pair changes in genomic DNA that result in the gain or loss of a restriction site [4]. These nucleotide variants were called ‘restriction fragment length polymorphisms’ (RFLPs) and were used in early linkage studies. In the early 1990s, RFLPs were replaced by simple tandem repeats or microsatellite markers. These markers show high levels of allelic variation, are distributed throughout the human genome, and can be efficiently amplified using PCR. Microsatellite markers have been used successfully in the positional cloning of many monogenic disease genes by linkage and allelic association [5].
In recent years, there has been a greater interest in studying the genetic basis of more common disorders, in which multiple genes of small effect are involved and for which the modes of inheritance are more complex. Standard linkage analysis using large pedigrees has only limited power to detect such small effects in these disorders [6]. Association studies using unrelated cases and controls, or using smaller family groups such as sibling pairs or ‘two parents and affected child’ trios have been proposed to be more likely to detect these small effects. Quantitative analysis and mathematical modeling have suggested that genome-wide association studies using single nucleotide polymorphisms (SNPs) are more effective than linkage analysis for identifying complex disease genes 6., 7., 8.. Such studies can then take advantage of SNPs, which are easy to type, highly abundant (found on average once per 1.3 kb in the genome) and stable (i.e. not prone to the ‘slippage’ seen with microsatellite repeats).
SNPs that are associated with disease may have a direct effect on the function of the gene in which they are located. A variant may result in an amino acid change or may alter exon–intron splicing, thereby directly modifying the relevant protein, or it may exist in a regulatory region, altering the level of expression or the stability of the mRNA. Alternatively a SNP may be in linkage disequilibrium (LD) with the ‘true’ functional variant. LD, also known as allelic association, exists when alleles at two distinct locations of the genome are more highly associated than expected. To this end, the development of SNP-based LD maps could facilitate whole-genome association studies, leading to more efficient detection of candidate susceptibility genes.
The immense interest in studies with SNPs is illustrated by a recent PubMed review of papers with the keyword ‘SNP’ from June 2000 to present: nearly 500 papers have been published. In this review, we highlight the have been published. In this review, we highlight the results from some of the most significant studies.
Section snippets
Identification and characterization of SNPs
Many different techniques can be used to identify and characterize SNPs, including single-strand conformation polymorphism analysis, heteroduplex analysis by denaturing high-performance liquid chromatography (DHPLC), direct DNA sequencing and computational methods [9•]. Thanks to the wealth of sequence information in public databases, computational tools can be used to identify SNPs in silico by aligning independently submitted sequences for a given gene (either cDNA or genomic sequences).
SNP genotyping methodologies
Association studies with SNPs typically use genomic DNA from hundreds of individuals and numerous SNPs. The development of high-throughput technologies has been vital to the widespread use of SNPs in research and industry. The most common SNP typing methods currently include hybridization, primer extension and cleavage methods. Each of these methods must be connected to an appropriate detection system. Detection technologies include fluorescent polarization [20], luminometric detection of
Linkage disequilibrium and SNP maps
As mentioned above, association studies with SNPs can be performed using SNPs that are predicted to have a direct functional consequence in a gene or by using SNPs selected randomly as a marker for LD. LD is generally defined as a measure of the degree of association between two genetic markers and can be used to identify regions of the genome associated with the disease. The construction of a SNP map for the purposes of LD has been complicated by the marked genomic variability in LD that
SNPs and candidate-gene analysis
Several hundred genes have been analyzed for their SNP content 34., 35., 36., 37., 38., 39., 40.. Although the methods and populations used differ, a consistent observation has been that changes in non-coding sequences and synonymous changes in coding sequence are generally more common than non-synonymous changes, reflecting greater selective pressure on the coding sequence. (A synonymous change refers to one that does not alter an amino acid whereas a non-synonymous change causes an amino acid
SNPs in pharmacogenetics
Pharmacogenetic initiatives try to identify genetic variants that influence a patient's response to a drug (ideally suited or likely to induce side effects) [49]. For example, gene variants in a drug-metabolizing enzyme have been linked to adverse reactions with azathioprine, mercaptopurine and thioguanine [50]. Another common SNP is associated with antibiotic-induced cardiac arrhythmia, which is clinically silent before drug exposure [51].
Patients with a variation in the core promoter of the
Conclusions
Most common diseases are thought to result from a mixture of genetic and environmental risk factors; as a result, the contribution of each gene is likely to be relatively small. Allelic association methods are more powerful in the detection of these genetic risk factors than conventional linkage approaches; however, allelic association methods require genetic markers to be very closely spaced because they rely on linkage disequilibrium between the marker and the disease allele.
Recent
Acknowledgements
This work was supported by NIH grants AG16208 and AA08403 and funding from the Leda J Sears Trust.
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
•• of outstanding interest
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Molecular genetics of Alzheimer's disease
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(2000)- et al.
Correlation of polymorphisms to coagulation and biochemical risk factors for cardiovasuclar diseases
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(2001) - et al.
Multiple sclerosis: genomic rewards
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A first high-density map of 981 biallelic markers on humane chromosome 14
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The extent of linkage disequilibrium in four populations with distinct demographic histories
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Extent and distribution of linkage disequlibrium in three genomic regions
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Significant evidence for linkage disequilibrium over a 5-cM region among Afrikaners
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Sequence diversity in 36 candidate genes for cardiovascular disorders
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SNP frequencies in human genes — an excess of rare alleles and differing modes of selection
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(2000) The essence of SNPs
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SNP association studies in Alzheimer's disease highlight problems for complex disease analysis
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SNPing away at complex diseases: analysis of single-nucleotide polymorphisms around APOE in Alzheimer disease
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Pharmacogenetics and adverse drug reactions
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Construction of a genetic linkage map in man using restriction length polymorphisms
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A physical map of 30,000 human genes
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The future of genetic studies of complex human diseases
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The use of a genetic map of biallelic markers in linkage studies
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Enabling large-scale pharmacogenetic studies by high throughput mutation detection and genotyping technologies
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Data mining: efficiency of using sequence databases for polymorphism discovery
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High-throughput development and characterization of a genome-wide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry
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High-throughput SNP detection by using DNA pooling and denaturing high performance liquid chromatography (DHPLC)
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An SNP map of the human genome generated by reduced representation shotgun sequencing
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Single nucleotide polymorphisms in the public domain: how useful are they?
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A SNP resource for human chromosome 22: extracting dense clusters of SNPs from the genomic sequence
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