Single nucleotide polymorphisms and the future of genetic epidemiology

Shrunken methodology to genome-wide SNPs selection and construction of SNPs networks

BACKGROUND

Recent development of high-resolution single nucleotide polymorphism (SNP) arrays allows detailed assessment of genome-wide human genome variations. There is increasing recognition of the importance of SNPs for medicine and developmental biology. However, SNP data set typically has a large number of SNPs (e.g., 400 thousand SNPs in genome-wide Parkinson disease data set) and a few hundred of samples. Conventional classification methods may not be effective when applied to such genome-wide SNP data.

RESULTS

In this paper, we use shrunken dissimilarity measure to analyze and select relevant SNPs for classification problems. Examples of HapMap data and Parkinson disease (PD) data are given to demonstrate the effectiveness of the proposed method, and illustrate it has a potential to become a useful analysis tool for SNP data sets. We use Parkinson disease data as an example, and perform a whole genome analysis. For the 367440 SNPs with less than 1% missing percentage from all 22 chromosomes, we can select 357 SNPs from this data set. For the unique genes that those SNPs are located in, a gene-gene similarity value is computed using GOSemSim and gene pairs that has a similarity value being greater than a threshold are selected to construct several groups of genes. For the SNPs that involved in these groups of genes, a statistical software PLINK is employed to compute the pair-wise SNP-SNP interactions, and SNPs with significance of P < 0.01 are chosen to identify SNPs networks based on their P values. Here SNPs networks are constructed based on Gene Ontology knowledge, and therefore each SNP network plays a role in the biological process. An analysis shows that such networks have relationships directly or indirectly to Parkinson disease.

CONCLUSIONS

Experimental results show that our approach is suitable to handle genetic variations, and provide useful knowledge in a genome-wide SNP study.

Endothelial nitric oxide synthase gene variation associated with chronic kidney disease after liver transplant

OBJECTIVE

To identify single nucleotide polymorphisms (SNPs) associated with risk of developing chronic kidney disease (CKD), a prevalent comorbidity, after liver transplant (LT).

PATIENTS AND METHODS

This study consists of a cohort of adult (> or =18 years) primary-LT recipients who had normal renal function before LT and who survived 1 year or more after LT at a high-volume US LT program between January 1, 1990, and December 31, 2000. Patients with adequate renal function (estimated glomerular filtration rate, > or =40 mL/min per 1.73 m(2) during follow-up; n=308) and patients with incident CKD (estimated glomerular filtration rate, <40 mL/min per 1.73 m(2) after LT; n=92) were identified. To investigate the association of 6 candidate genes with post-LT CKD, we selected SNPs that have been associated with renal function in the literature. Hazard ratios were estimated using Cox regression, adjusted for potential confounding variables.

RESULTS

The variant allele (298Asp) of the Glu298Asp SNP in the endothelial nitric oxide synthase gene (NOS3) was significantly associated with CKD after LT (P=.05; adjusted for multiple comparisons). The 5-year incidence of CKD was 70% among patients homozygous for the NOS3 variant allele (298Asp) compared with 42% among those not homozygous for the NOS3 variant allele. Specifically, homozygosity for the NOS3 variant allele conferred a 2.5-fold increased risk of developing CKD after LT (P=.005, adjusted for confounding variables).

CONCLUSION

Homozygosity for the variant allele of NOS3 (298Asp) is associated with CKD after LT and may be useful for identifying recipients at higher risk of post-LT CKD.

A single molecular beacon probe is sufficient for the analysis of multiple nucleic acid sequences

Molecular beacon (MB) probes are dual-labeled hairpin-shaped oligodeoxyribonucleotides that are extensively used for real-time detection of specific RNA/DNA analytes. In the MB probe, the loop fragment is complementary to the analyte: therefore, a unique probe is required for the analysis of each new analyte sequence. The conjugation of an oligonucleotide with two dyes and subsequent purification procedures add to the cost of MB probes, thus reducing their application in multiplex formats. Here we demonstrate how one MB probe can be used for the analysis of an arbitrary nucleic acid. The approach takes advantage of two oligonucleotide adaptor strands, each of which contains a fragment complementary to the analyte and a fragment complementary to an MB probe. The presence of the analyte leads to association of MB probe and the two DNA strands in quadripartite complex. The MB probe fluorescently reports the formation of this complex. In this design, the MB does not bind the analyte directly; therefore, the MB sequence is independent of the analyte. In this study one universal MB probe was used to genotype three human polymorphic sites. This approach promises to reduce the cost of multiplex real-time assays and improve the accuracy of single-nucleotide polymorphism genotyping.

A comprehensive in silico analysis of the functional and structural impact of SNPs in the IGF1R gene

Insulin-like growth factor 1 receptor (IGF1R) acts as a critical mediator of cell proliferation and survival. Many single nucleotide polymorphisms (SNPs) found in the IGF1R gene have been associated with various diseases, including both breast and prostate cancer. The genetics of these diseases could be better understood by knowing the functions of these SNPs. In this study, we performed a comprehensive analysis of the functional and structural impact of all known SNPs in this gene using publicly available computational prediction tools. Out of a total of 2412 SNPs in IGF1R retrieved from dbSNP, we found 32 nsSNPs, 58 sSNPs, 83 mRNA 3' UTR SNPs, and 2225 intronic SNPs. Among the nsSNPs, a total of six missense nsSNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (PolyPhen), and one nonsense nsSNP was found. Further, we modeled mutant proteins and compared the total energy values with the native IGF1R protein, and showed that a mutation from arginine to cysteine at position 1216 (rs61740868) on the surface of the protein caused the greatest impact on stability. Also, the FASTSNP tool suggested that 31 sSNPs and 3 intronic SNPs might affect splicing regulation. Based on our investigation, we report potential candidate SNPs for future studies on IGF1R mutations.

Fine mapping the soybean aphid resistance gene Rag1 in soybean

The soybean aphid (Aphis glycines Matsumura) is an important soybean [Glycine max (L.) Merr.] pest in North America. The dominant aphid resistance gene Rag1 was previously mapped from the cultivar 'Dowling' to a 12 cM marker interval on soybean chromosome 7 (formerly linkage group M). The development of additional genetic markers mapping closer to Rag1 was needed to accurately position the gene to improve the effectiveness of marker-assisted selection (MAS) and to eventually clone it. The objectives of this study were to identify single nucleotide polymorphisms (SNPs) near Rag1 and to position these SNPs relative to Rag1. To generate a fine map of the Rag1 interval, 824 BC(4)F(2) and 1,000 BC(4)F(3) plants segregating for the gene were screened with markers flanking Rag1. Plants with recombination events close to the gene were tested with SNPs identified in previous studies along with new SNPs identified from the preliminary Williams 82 draft soybean genome shotgun sequence using direct re-sequencing and gene-scanning melt-curve analysis. Progeny of these recombinant plants were evaluated for aphid resistance. These efforts resulted in the mapping of Rag1 between the two SNP markers 46169.7 and 21A, which corresponds to a physical distance on the Williams 82 8x draft assembly (Glyma1.01) of 115 kilobase pair (kb). Several candidate genes for Rag1 are present within the 115-kb interval. The markers identified in this study that are closely linked to Rag1 will be a useful resource in MAS for this important aphid resistance gene.

An electrochemical sensor for single nucleotide polymorphism detection in serum based on a triple-stem DNA probe

We report here an electrochemical approach that offers, for the first time, single-step, room-temperature single nucleotide polymorphism (SNP) detection directly in complex samples (such as blood serum) without the need for target modification, postwashing, or the addition of exogenous reagents. This sensor, which is sensitive, stable, and reusable, is comprised of a single, self-complementary, methylene blue-labeled DNA probe possessing a triple-stem structure. This probe takes advantage of the large thermodynamic changes in enthalpy and entropy that result from major conformational rearrangements that occur upon binding a perfectly matched target, resulting in a large-scale change in the faradaic current. As a result, the discrimination capabilities of this sensor greatly exceed those of earlier single- and double-stem electrochemical sensors and support rapid (minutes), single-step, reagentless, room-temperature detection of single nucleotide substitutions. To elucidate the theoretical basis of the sensor's selectivity, we present a comparative thermodynamic analysis among single-, double-, and triple-stem probes.

Applications of computational tools to predict functional SNPs effects in human ErbB genes

Understanding the functions of single nucleotide polymorphisms (SNPs) can greatly help to understand the genetic basis of human complex diseases such as cancer. However, identifying functional SNPs among the huge number of available SNPs is challenging. In this study, we analyzed the genetic variations that can alter the expression and function of ErbB proteins using different computational tools. For noncoding SNP, we found that one SNP located in 59UTR of ErbB1 gene might change protein expression level and two SNPS located in regulatory regions might affect transcriptional regulation of Erbb1 and Erbb4. For coding SNPs we predicted that 25 nonsynonymous SNPs (most of them in ErbB1 gene) might disrupt the protein function among which 22 might alter protein structure. Prediction regarding the potential effect of the SNPs showed that 13 of them located within the tyrosine kinase or the ligand binding domain are likely to be associated with cancer.

Oligonucleotide hybridization and free-solution electrokinetic separation in a nanofluidic device

There is significant interest in developing on-chip DNA hybridization assays to leverage the advantages of lab-on-a-chip systems, which include smaller sample and reagent volumes, faster processing speeds, and greater opportunities for large-scale integration. While much research has explored ways to integrate DNA microarrays on-chip, little work has been done to incorporate hybridization with existing microscale separation platforms. We present the first separation of single-stranded and double-stranded oligonucleotides in a nanofluidic device. We couple this separation with free-solution hybridization to develop a simple, electrokinetic technique that detects DNA hybridization without sample labeling. The technique is used both to detect target DNA sequences and to quantitatively measure hybridization kinetics. To demonstrate the method, we measured the second order reaction coefficient of complementary 20-mer oligonucleotides as a function of sodium ion concentration, which ranged from 0.0048 mol(-1).sec(-1) at 5 mM sodium to 0.42 mol(-1).sec(-1) at 50 mM. We also distinguished between a pair of complementary oligonucleotides and a pair with a single nucleotide mismatch, observing a two-fold difference in hybridization rate. Additionally, we observed a relative change in the mobility of single-stranded and double-stranded DNA with increasing sodium concentration, suggesting that our device may provide a useful platform for studying biomolecule transport in nanochannels.

Genetic predictors of response to therapy in childhood asthma

Asthma is a common chronic condition in children, where the response to treatment can be heterogeneous within a population. Genetic variations may partly explain the inconsistent response to asthma treatment between individuals. There is a relatively small but consistent body of literature linking genetic variations to improved response to different classes of asthma treatment, including short- and long-acting beta-agonists, corticosteroids, and leukotriene modifiers. In most cases, the advantage conferred by a single genetic mutation for treatment response is relatively small; the Arg16Gly single nucleotide polymorphism of the beta2-adrenoceptor is the exception to this rule and is associated with a marked difference in response to short-acting beta-agonists. Pharmacogenetic studies have only recently been undertaken in asthmatic individuals, and much more work is required before clinical applications arise. Future genome-wide association (GWA) studies and randomized controlled trials in genetically susceptible populations will determine whether asthma treatment can be tailored to an individual based on their DNA. The aim of the present paper is to review pharmacogenetic studies concerning asthma medications, with a primary focus on studies involving children.

Genetics terminology for respiratory physicians

Genes affect our susceptibility to almost all diseases, from the rare single gene disorders such as cystic fibrosis to common multifactorial disorders such as asthma. They also influence our response to specific therapies. Scientific advances in genetics, starting with projects such as the mapping of the human genome [International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 2004; 431: 931-945] are likely to improve healthcare in the coming decades. Internationally, government initiatives have been established to address strategies to implement these changes [NHS Genetics White Paper. "Our Inheritance - Our Future": Realising the potential of Genetics in the NHS. UK: Department of Health 2003; Family Health History Initiative. National Human Genome Research Institute and Office of Surgeon General, Department of Health and Human Services. 2004]. A knowledge of basic genetic principles and familiarity with genetic 'jargon' associated with new technologies will be important for those practicing in this era of 'genomic medicine' [Collins FS, Green ED, Guttmacher AE, Guyer MS. A vision for the future of genomics research. Nature 2003; 422; April 24; 835-847]. The aim of this article is to review genetic terminology using examples from paediatric respiratory medicine.

Kinetic and thermodynamic characterization of single-mismatch discrimination using single-molecule imaging

A single-molecule detection setup based on total internal reflection fluorescence (TIRF) microscopy has been used to investigate association and dissociation kinetics of unlabeled 30mer DNA strands. Single-molecule sensitivity was accomplished by letting unlabeled DNA target strands mediate the binding of DNA-modified and fluorescently labeled liposomes to a DNA-modified surface. The liposomes, acting as signal enhancer elements, enabled the number of binding events as well as the residence time for high affinity binders (K_d < 1 nM, k_off < 0.01 s⁻¹) to be collected under equilibrium conditions at low pM concentrations. The mismatch discrimination obtained from the residence time data was shown to be concentration and temperature independent in intervals of 1–100 pM and 23–46°C, respectively. This suggests the method as a robust means for detection of point mutations at low target concentrations in, for example, single nucleotide polymorphism (SNP) analysis.

PAMAM dendrimer-enhanced DNA biosensors based on electrochemical impedance spectroscopy

A novel, simple and sensitive DNA biosensor based on DNA-poly(amidoamine) (PAMAM) dendrimer nanoconjugates was developed by using the electrochemical impedance spectroscopy (EIS) technique. In this context, the assay relies on the hybridization of the single-stranded DNA (ssDNA) probe covalently conjugated on a mercaptoacetic acid self-assembled monolayer on gold electrodes, with the generation 4.5 (G-4.5) PAMAM-target DNA complex in solution. Once the double-stranded DNA (dsDNA) formed on the gold electrodes, G-4.5 PAMAM bearing carboxyls on the periphery was anchored on the hybrids; the changes of interfacial electron-transfer resistance (R(et)) of the electrodes were measured using an Fe(CN)(6)(3-/4-) redox probe by electrochemical impedance spectroscopy. The results showed that only a complementary sequence could form a dsDNA-PAMAM with the DNA-PAMAM probe and give an obviously enlarged R(et) value. The non-complementary and three-base mismatched sequence exhibited negligible impedance change compared with the blank measurement (the blank measurement means: ssDNA probe-modified gold electrode was directly measured by EIS). The unique spherical structure combining with more negative charges on the G-4.5 PAMAM periphery anchored on the hybrids could significantly amplify the hybridization signal (R(et) value), and the detection limit for measuring the full complementary sequence is down to pM level.

In silico investigations on functional and haplotype tag SNPs associated with congenital long QT syndromes (LQTSs)

Single-nucleotide polymorphisms (SNPs) play a major role in the understanding of the genetic basis of many complex human diseases. It is still a major challenge to identify the functional SNPs in disease-related genes. In this review, the genetic variation that can alter the expression and the function of the genes, namely KCNQ1, KCNH2, SCN5A, KCNE1 and KCNE2, with the potential role for the development of congenital long QT syndrome (LQTS) was analyzed. Of the total of 3,309 SNPs in all five genes, 27 non-synonymous SNPs (nsSNPs) in the coding region and 44 SNPs in the 5' and 3' un-translated regions (UTR) were identified as functionally significant. SIFT and PolyPhen programs were used to analyze the nsSNPs and FastSNP; UTR scan programs were used to compute SNPs in the 5' and 3' untranslated regions. Of the five selected genes, KCNQ1 has the highest number of 26 haplotype blocks and 6 tag SNPs with a complete linkage disequilibrium value. The gene SCN5A has ten haplotype blocks and four tag SNPs. Both KCNE1 and KCNE2 genes have only one haplotype block and four tag SNPs. Four haplotype blocks and two tag SNPs were obtained for KCNH2 gene. Also, this review reports the copy number variations (CNVs), expressed sequence tags (ESTs) and genome survey sequences (GSS) of the selected genes. These computational methods are in good agreement with experimental works reported earlier concerning LQTS.

Cationic conjugated polyelectrolyte/molecular beacon complex for sensitive, sequence-specific, real-time DNA detection

A new fluorescence method has been developed for DNA detection at room temperature in a sensitive, selective, economical, and real-time manner that interfaces the superiority of a molecular beacon in mismatch discrimination with the light-harvesting property of water-soluble conjugated polyelectrolytes. The probe solution contains a cationic conjugated polyelectrolyte (PFP-NMe3+), a molecular beacon with a five base pairs double-stranded stem labeled at the 5'-terminus with fluorescein (DNA P-Fl), and ethidium bromide (EB, a specific intercalator of dsDNA). The electrostatic interactions between DNA P-Fl and PFP-NMe3+ keep them in close proximity, facilitating the fluorescence resonance energy transfer (FRET) from PFP-NMe3+ to fluorescein. Upon adding a complementary strand to the probe solution, the conformation of DNA P-Fl transits into dsDNA followed by the intercalation of EB into the grooves. Two-step FRET, from PFP-NMe3+ to DNA P-Fl (FRET-1), followed by FRET from DNA P-Fl to EB (FRET-2) takes place. In view of the observed fluorescein or EB emission changes, DNA can be detected in aqueous solution. Because the base mismatch in target DNA inhibits the transition of DNA P-Fl from the stem-loop to duplex structure, single nucleotide mismatch can be clearly detected.

Toll-like receptors: their roles in bacterial recognition and respiratory infections

Although respiratory infections cause significant morbidity and mortality throughout the world, the immunologic factors that mediate host susceptibility to these infections remain poorly understood. The lung contains a vast surface at the host-environment interface and acts as a crucial barrier to invading pathogens. The lung is equipped with specialized epithelial and hematopoietic cells, which express pattern recognition receptors that act as both sentinels and mediators of pulmonary innate immunity. Toll-like receptors (TLRs) mediate a particularly critical role in pathogen recognition and subsequent initiation of the host immune response. In this review, we will summarize current knowledge of TLRs and their bacterial ligands and explore their role in respiratory infections. Moreover, we will highlight recent advances in the role of TLRs in pulmonary infections from a human immunogenetics perspective.

[Research progresses on nutrigenomics]

Nutrition science is an age-old subject, and offers important theoretic instructions for human health protection and disease prevention. With the development of molecular biology, it will be a key technique in the 21 century. Combination of molecular biology and nutrition, bio-nutrition is formed. While the combination of genome and nutrition, nutrigenomics is developed. Nutrigenomics covers a wide range of areas, which studies the interactive effects between nutrients and genes expression, and predicts the expressive response to the nutrients. Genomics technology can help us to identify some dis-ease-related genes, thereby people establish individual diet and make their heath attained the best status through adjusting diet. This paper focuses on the main research technology of nutrigenomics and its application.

Direct haplotyping of bi-allelic SNPs using ARMS and RFLP analysis techniques

Haplotype analysis of single nucleotide polymorphisms (SNPs) is an important and rapidly growing approach for association studies. In recent years, statistical procedures to haplotype determination from genotypic information have employed in population studies. These procedures, even though some advantages for estimation of haplotype frequencies in large population samples, have limitations in the accuracy of the analysis. In this study, we have designed a reliable method for direct haplotyping of polymorphic sites using the amplification refractory mutation system (ARMS) and restriction fragment length polymorphism (RFLP) analysis techniques. We applied the method to determination of haplotypes composed of three SNPs within the paraoxonase1 gene promoter and found the approach can be used in many studies in population and in a variety of clinical settings.

Toll-like receptors in defense and damage of the central nervous system

Members of the Toll-like receptor (TLR) family play critical roles as regulators of innate and adaptive immune responses. TLRs function by recognizing diverse molecular patterns on the surface of invading pathogens. In the brain, microglial cells generate neuroimmune responses through production of proinflammatory mediators. The upregulation of cytokines and chemokines in response to microbial products and other stimuli has both beneficial and deleterious effects. Emerging evidence demonstrates a central role for TLRs expressed on microglia as a pivotal factor in generating these neuroimmune responses. Therefore, understanding the basis of TLR signaling in producing these responses may provide insights into how activated microglia attempt to strike a balance between defense against invading pathogens and inflicting irreparable brain damage. These insights may lead to innovative therapies for CNS infections and neuroinflammatory diseases based on the modulation of microglial cell activation through TLR signaling.

Correlating observed odds ratios from lung cancer case-control studies to SNP functional scores predicted by bioinformatic tools

Bioinformatic tools are widely utilized to predict functional single nucleotide polymorphisms (SNPs) for genotyping in molecular epidemiological studies. However, the extent to which these approaches are mirrored by epidemiological findings has not been fully explored. In this study, we first surveyed SNPs examined in case-control studies of lung cancer, the most extensively studied cancer type. We then computed SNP functional scores using four popular bioinformatics tools: SIFT, PolyPhen, SNPs3D, and PMut, and determined their predictive potential using the odds ratios (ORs) reported. Spearman's correlation coefficient (r) for the association with SNP score from SIFT, PolyPhen, SNPs3D, and PMut, and the summary ORs were r=-0.36 (p=0.007), r=0.25 (p=0.068), r=-0.20 (p=0.205), and r=-0.12 (p=0.370), respectively. By creating a combined score using information from all four tools we were able to achieve a correlation coefficient of r=0.51 (p<0.001). These results indicate that scores of predicted functionality could explain a certain fraction of the lung cancer risk detected in genetic association studies and more accurate predictions may be obtained by combining information from a variety of tools. Our findings suggest that bioinformatic tools are useful in predicting SNP functionality and may facilitate future genetic epidemiological studies.

Recent development in pharmacogenomics: from candidate genes to genome-wide association studies

Genetic diversity, most notably through single nucleotide polymorphisms and copy-number variation, together with specific environmental exposures, contributes to both disease susceptibility and drug response variability. It has proved difficult to isolate disease genes that confer susceptibility to complex disorders, and as a consequence, even fewer genetic variants that influence clinical drug responsiveness have been uncovered. As such, the candidate gene approach has largely failed to deliver and, although the family-based linkage approach has certain theoretical advantages in dealing with common/complex disorders, progress has been slower than was hoped. More recently, genome-wide association studies have gained increasing popularity, as they enable scientists to robustly associate specific variants with the predisposition for complex disease, such as age-related macular degeneration, Type 2 diabetes, inflammatory bowel disease, obesity, autism and leukemia. This relatively new methodology has stirred new hope for the mapping of genes that regulate drug response related to these conditions. Collectively, these studies support the notion that modern high-throughput single nucleotide polymorphism genotyping technologies, when applied to large and comprehensively phenotyped patient cohorts, will readily reveal the most clinically relevant disease-modifying and drug response genes. This review addresses both recent advances in the genotyping field and highlights from genome-wide association studies, which have conclusively uncovered variants that underlie disease susceptibility and/or variability in drug response in common disorders.

SNP genotyping: technologies and biomedical applications

Single nucleotide polymorphisms (SNPs) are the most frequently occurring genetic variation in the human genome, with the total number of SNPs reported in public SNP databases currently exceeding 9 million. SNPs are important markers in many studies that link sequence variations to phenotypic changes; such studies are expected to advance the understanding of human physiology and elucidate the molecular bases of diseases. For this reason, over the past several years a great deal of effort has been devoted to developing accurate, rapid, and cost-effective technologies for SNP analysis, yielding a large number of distinct approaches. This article presents a review of SNP genotyping techniques and examines their principles of genotype determination in terms of allele differentiation strategies and detection methods. Further, several current biomedical applications of SNP genotyping are discussed.

DNA base mismatch detection with bulky rhodium intercalators: synthesis and applications

This protocol describes the syntheses and applications of two metallointercalators, Rh(bpy)2(chrysi)3+ and Rh(bpy)2(phzi)3+, that target single base mismatches in DNA. The complexes bind mismatched DNA sites specifically and, upon photoactivation, promote strand scission neighboring the mismatch. Owing to their high specificity and sequence context independence, targeting mismatches with these complexes offers an attractive alternative to current mismatch- and SNP-detection methodologies. This protocol also describes the synthesis of these complexes and their use in marking mismatched sites. Irradiation of 32P-labeled duplex DNA with either intercalator followed by denaturing PAGE allows the detection of mismatches in oligonucleotides. The protocol also outlines a method for efficient detection of single nucleotide polymorphisms (SNPs) in larger genes or plasmids. Pooled genes are denatured and re-annealed to form heteroduplexes; they are then incubated with either complex, irradiated and analyzed using capillary electrophoresis to probe for mismatches (SNP sites). The synthesis of the metallointercalators requires approximately 5-7 d. The mismatch- and SNP-detection experiments each require approximately 3 d.

Automated single-nucleotide polymorphism analysis using fluorescence excitation–emission spectroscopy and one-class classifiers

We have developed a new method of highly automated SNP (single nucleotide polymorphism) analysis for identification of genotypes. The data were generated by the Taqman reaction. A total of 18 half-plates were analysed for different genes, each consisting of 48 wells, including six synthetic DNA samples, three background samples, and 39 human DNA samples. Fluorescence spectra were obtained from each well. The characteristics of the spectra depended on whether the genotype originated from one of three classes-homozygotic wild-type, mutant, or heterozygote. The main problems are: (1) spectral variation from one half-plate to another is sometimes very substantial; (2) the spectra of heterozygotic samples vary substantially; (3) outliers are common; and (4) not all possible alleles are represented on each half-plate so the number of types of spectra can vary, depending on the gene being analysed. We solved these problems by using a signal-standardisation technique (piecewise direct standardisation, PDS) and then built two one-class classifiers based on PCA models (PCA data description) to identify the two types of homozygote. The remaining samples were tested to see whether they could be approximated well by a linear combination of the spectra of two types of homozygote. If they could, they were identified as heterozygotic; if not, they were identified as outliers. The results are characterised by very low false-positive errors and 2 to 6% overall false-negative errors.

Genomics and proteomics: importance for the future of nutrition research

A huge number of genes within the human genome code for proteins that mediate and/or control nutritional processes. Although a large body of information on the number of genes, on chromosomal localisation, gene structure and function has been gathered, we are far from understanding the orchestrated way of how they make metabolism. Nevertheless, based on the genetic information emerging on a daily basis, we are offered fantastic new tools that allow us new insights into the molecular basis of human metabolism under normal as well as pathophysiological conditions. Recent technological advancements have made it possible to analyse simultaneously large sets of mRNA and/or proteins expressed in a biological sample or to define genetic heterogeneity that may be important for the individual response of an organism to changes in its nutritional environment. Applications of the new techniques of genome and proteome analysis are central for the development of nutritional sciences in the next decade and its integration into the rapidly developing era of functional genomics.

Multiple hypothesis testing strategies for genetic case-control association studies

The genetic case-control association study of unrelated subjects is a leading method to identify single nucleotide polymorphisms (SNPs) and SNP haplotypes that modulate the risk of complex diseases. Association studies often genotype several SNPs in a number of candidate genes; we propose a two-stage approach to address the inherent statistical multiple comparisons problem. In the first stage, each gene's association with disease is summarized by a single p-value that controls a familywise error rate. In the second stage, summary p-values are adjusted for multiplicity using a false discovery rate (FDR) controlling procedure. For the first stage, we consider marginal and joint tests of SNPs and haplotypes within genes, and we construct an omnibus test that combines SNP and haplotype analysis. Simulation studies show that when disease susceptibility is conferred by a SNP, and all common SNPs in a gene are genotyped, marginal analysis of SNPs using the Simes test has similar or higher power than marginal or joint haplotype analysis. Conversely, haplotype analysis can be more powerful when disease susceptibility is conferred by a haplotype. The omnibus test tracks the more powerful of the two approaches, which is generally unknown. Multiple testing balances the desire for statistical power against the implicit costs of false positive results, which up to now appear to be common in the literature.

TAMGeS: a Three-array Method for Genotyping of SNPs by a dual-colour approach

Background

Many of the most effective high-throughput protocols for SNP genotyping employ microarrays. Genotypes are assessed by comparing the signal intensities that derive from the hybridization of different allele-specific probes labelled either by using four fluorescent dyes, one for each base, or by using only two dyes and investigating the polymorphic alleles two by two on separate arrays. The employment of only two dyes makes it possible to use a dual-laser scanner, which has the advantage of being present in every microarray laboratory. However, this protocol may present some drawbacks. To infer all the six possible genotypes it is necessary to compare signals from two arrays, but this comparison not always is successful. A number of systematic errors in the experimental protocol, in fact, may differently affect signal intensities on separate arrays. Here we present TAMGeS (Three-Array Method for Genotyping of SNPs), an exhaustive method for SNP genotyping through SBE (Single Base Extension) and dual-colour microarrays, which makes the comparison of signals on distinct arrays reliable by using a third array and a data handling method for signal normalization based on bilinear regression theory.

Results

We tested the effectiveness of the proposed method by evaluating the results obtained from the direct comparison of the two arrays or by applying TAMGeS, both on experimental and synthetic data. With synthetic data, TAMGeS reduced the frequency of errors by an order of magnitude, when the incidence of systematic errors was not negligible. With the experimental data, produced by genotyping 25 SNPs in 437 subjects, TAMGeS reduced the percentage of missing genotypes from 54% (Two-Array Method) to 14.5%. Allelic and genotypic call rates were 99.3% and 99.5%, respectively. The normalization procedure takes into account also systematic errors, which can be generated by a time-delayed assay, thus making the protocol more flexible.

Conclusion

TAMGeS represents an innovative method, which proved to be very effective in producing reliable SNP genotyping data by dual-colour microarrays. The requirement of a third array is well balanced by the strong enhancement in data quality and by the greater flexibility of the experimental protocol.

SNPHunter: a versatile web-based tool for acquiring and managing single nucleotide polymorphisms

Sites in the DNA sequences where two homologous chromosomes differ at a single DNA base are called single nucleotide polymorphisms (SNPs). The human genome contains at least 10 million SNPs, making them the most abundant genetic "lampposts" for pinpointing causal variants underlying human diseases. SNP-related toolboxes and databases have become increasingly important for researchers to choose the most appropriate SNP set for attaining their research goals. This chapter introduces SNPHunter, a web-based software program that allows for SNP search (both ad hoc mode and batch mode), retrieval of SNP information, SNP management, automatic SNP selection based on customizable criteria including physical position, function class, flanking sequences at user-defined lengths, and heterozygosity from National Center for Biotechnology Information dbSNP. The SNP data extracted from dbSNP via SNPHunter can be exported and saved in plain text format for further down-stream analyses.

Resampling-based multiple hypothesis testing procedures for genetic case-control association studies

In case-control studies of unrelated subjects, gene-based hypothesis tests consider whether any tested feature in a candidate gene--single nucleotide polymorphisms (SNPs), haplotypes, or both--are associated with disease. Standard statistical tests are available that control the false-positive rate at the nominal level over all polymorphisms considered. However, more powerful tests can be constructed that use permutation resampling to account for correlations between polymorphisms and test statistics. A key question is whether the gain in power is large enough to justify the computational burden. We compared the computationally simple Simes Global Test to the min P test, which considers the permutation distribution of the minimum p-value from marginal tests of each SNP. In simulation studies incorporating empirical haplotype structures in 15 genes, the min P test controlled the type I error, and was modestly more powerful than the Simes test, by 2.1 percentage points on average. When disease susceptibility was conferred by a haplotype, the min P test sometimes, but not always, under-performed haplotype analysis. A resampling-based omnibus test combining the min P and haplotype frequency test controlled the type I error, and closely tracked the more powerful of the two component tests. This test achieved consistent gains in power (5.7 percentage points on average), compared to a simple Bonferroni test of Simes and haplotype analysis. Using data from the Shanghai Biliary Tract Cancer Study, the advantages of the newly proposed omnibus test were apparent in a population-based study of bile duct cancer and polymorphisms in the prostaglandin-endoperoxide synthase 2 (PTGS2) gene.

Design and analysis in genetic studies of human ageing and longevity

With the success of the Human Genome Project and taking advantage of the recent developments in high-throughput genotyping techniques as well as in functional genomics, it is now feasible to collect vast quantities of genetic data with the aim of deciphering the genetics of human complex traits. As a result, the amount of research on human ageing and longevity has been growing rapidly in recent years. The situation raises questions concerning efficient choice of study population, sampling schemes, and methods of data analysis. In this article, we summarize the key issues in genetic studies of human ageing and longevity ranging from research design to statistical analyses. We discuss the virtues and drawbacks of the multidisciplinary approaches including the population-based cross-sectional and cohort studies, family-based linkage analysis, and functional genomics studies. Different analytical approaches are illustrated with their performances compared. In addition, important research topics are highlighted together with experiment design and data analyzing issues to serve as references for future studies.

Phenotypic features with p53 alterations related to human papillomavirus and prognostic evaluation in cervical cancer

Cervical cancer is one of the most common tumor affecting women worldwide. Human papillomavirus (HPV) was found to have a causal relationship with cervical cancer and its precursors. The interaction between HPV E6 protein and p53 was identified in in vitro studies. The aim of the study was to evaluate the prevalence of p53 alterations related to HPV infection and the prognostic significance of p53 alterations in cervical cancer. Studies were identified by a MEDLINE search, and all relevant articles were retrieved from 1991 to March 2004. The prevalence of p53 mutations is a rare event in cervical cancer. The correlation between p53 mutations and HPV or prognosis is controversial. Loss of heterozygosity (LOH) of p53 is more commonly found in cervical cancer and is related with the prognosis of this disease. There is no significant correlation between p53 polymorphism and development of cervical cancer. The p53 mutations were not commonly found in cervical cancer. LOH of p53 may contribute to the progression of this malignancy. p53 polymorphism failed to be an independent prognostic factor in predicting the outcome of patients with cervical cancer. Further, epidemiologic surveys should be undertaken in larger populations and in different geographical regions.

CSF1 gene associated with aggressive periodontitis in the Japanese population

Aggressive periodontitis (AgP) is characterized by the early onset of the rapid and progressive destruction of the alveolar bone. We investigated the correlation of single nucleotide polymorphisms (SNPs) in candidate genes with AgP in the Japanese population in order to determine the genetic risk factors for this complex disease. Among 11 genes related to bone formation and resorption, 43 known SNPs were tested in 98 case and 88 control samples for association with AgP by using SNP genotyping techniques. Among these, three polymorphisms located in the colony stimulating factor 1 (CSF1) gene showed a positive association with AgP. This is the first case of an association between a CSF1 polymorphism and a human disease.

DNA polymorphisms and renal disease: a critical appraisal of studies presented at the annual ERA/EDTA and ASN conferences in 2004 and 2005

Countless studies try to associate single DNA polymorphisms with disease, while there is growing evidence that many of these studies are of flawed design. Based on the Journal of the American Society of Nephrology (JASN) requirements for gene-disease association study quality, the abstracts presented at the two major international nephrology conferences in 2004 and 2005 organized by the European Renal Association/European Dialysis and Transplantation Association (ERA/EDTA) and American Society of Nephrology (ASN) are analysed to show how this problem affects nephrology. Over time, average sample numbers have increased, as have the numbers of abstracts compliant with the JASN requirements. This indicates a potential beneficial effect of the published stricter guidelines on study quality. Alternative options include pre-registration of studies in dedicated databases, secondary assessment of association studies through meta-analysis and participation in network approaches, such as the Human Genome Epidemiology Network (HuGE Net) and the Renal Genome Network.

Applications of computational algorithm tools to identify functional SNPs in cytokine genes

Understanding the functions of single nucleotide polymorphisms (SNPs) can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. However, how to identify functional SNPs from a pool containing both functional and neutral SNPs is challenging. In this study, we analyzed the genetic variations that can alter the expression and function of a group of cytokine proteins using computational tools. As a result, we extracted 4552 SNPs from 45 cytokine proteins from SNPper database. Of particular interest, 828 SNPs were in the 5'UTR region, 961 SNPs were in the 3' UTR region, and 85 SNPs were non-synonymous SNPs (nsSNPs), which cause amino acid change. Evolutionary conservation analysis using the SIFT tool suggested that 8 nsSNPs may disrupt the protein function. Protein structure analysis using the PolyPhen tool suggested that 5 nsSNPs might alter protein structure. Binding motif analysis using the UTResource tool suggested that 27 SNPs in 5' or 3'UTR might change protein expression levels. Our study demonstrates the presence of naturally occurring genetic variations in the cytokine proteins that may affect their expressions and functions with possible roles in complex human disease, such as immune diseases.