High-throughput genotyping of single nucleotide polymorphisms with rolling circle amplification

BACKGROUND: Single nucleotide polymorphisms (SNPs) are the foundation of powerful complex trait and pharmacogenomic analyses. The availability of large SNP databases, however, has emphasized a need for inexpensive SNP genotyping methods of commensurate simplicity, robustness, and scalability. We describe a solution-based, microtiter plate method for SNP genotyping of human genomic DNA. The method is based upon allele discrimination by ligation of open circle probes followed by rolling circle amplification of the signal using fluorescent primers. Only the probe with a 3' base complementary to the SNP is circularized by ligation. RESULTS: SNP scoring by ligation was optimized to a 100,000 fold discrimination against probe mismatched to the SNP. The assay was used to genotype 10 SNPs from a set of 192 genomic DNA samples in a high-throughput format. Assay directly from genomic DNA eliminates the need to preamplify the target as done for many other genotyping methods. The sensitivity of the assay was demonstrated by genotyping from 1 ng of genomic DNA. We demonstrate that the assay can detect a single molecule of the circularized probe. CONCLUSIONS: Compatibility with homogeneous formats and the ability to assay small amounts of genomic DNA meets the exacting requirements of automated, high-throughput SNP scoring

'Aspirin resistance' or treatment non-compliance: Which is to blame for cardiovascular complications?

Aspirin is one of the 'cornerstone' drugs in our current management of cardiovascular disorders. However, despite the prescription of aspirin recurrent vascular events still occur in 10–20% of patients. These, data together with the observations of diminished antiaggregatory response to aspirin in some subjects have provided the basis of the current debate on the existence of so-called "aspirin resistance". Unfortunately, many of the tests employed to define 'aspirin resistance' lack sufficient sensitivity, specificity, and reproducibility. The prevalence of 'aspirin resistance' as defined by each test varies widely, and furthermore, the value of a single point estimate measure of aspirin resistance is questionable. The rate of 'aspirin resistance' is law if patients observed to ingest aspirin, with large proportion of patients to be pseudo-'aspirin resistant', due to non-compliance. What are the implications for clinical practice? Possible non-adherence to aspirin prescription should also be carefully considered before changing to higher aspirin doses, other antiplatelet drugs (e.g. clopidogrel) or even combination antiplatelet drug therapy. Given the multifactorial nature of atherothrombotic disease, it is not surprising that only about 25% of all cardiovascular complications can usually be prevented by any single medication. We would advocate against routine testing of platelet sensitivity to aspirin (as an attempt to look for 'aspirin resistance') but rather, to highlight the importance of clinicians and public attention to the problem of treatment non-compliance

Exhaustive prediction of disease susceptibility to coding base changes in the human genome

<p>Abstract</p> <p>Background</p> <p>Single Nucleotide Polymorphisms (SNPs) are the most abundant form of genomic variation and can cause phenotypic differences between individuals, including diseases. Bases are subject to various levels of selection pressure, reflected in their inter-species conservation.</p> <p>Results</p> <p>We propose a method that is not dependant on transcription information to score each coding base in the human genome reflecting the disease probability associated with its mutation. Twelve factors likely to be associated with disease alleles were chosen as the input for a support vector machine prediction algorithm. The analysis yielded 83% sensitivity and 84% specificity in segregating disease like alleles as found in the Human Gene Mutation Database from non-disease like alleles as found in the Database of Single Nucleotide Polymorphisms. This algorithm was subsequently applied to each base within all known human genes, exhaustively confirming that interspecies conservation is the strongest factor for disease association. For each gene, the length normalized average disease potential score was calculated. Out of the 30 genes with the highest scores, 21 are directly associated with a disease. In contrast, out of the 30 genes with the lowest scores, only one is associated with a disease as found in published literature. The results strongly suggest that the highest scoring genes are enriched for those that might contribute to disease, if mutated.</p> <p>Conclusion</p> <p>This method provides valuable information to researchers to identify sensitive positions in genes that have a high disease probability, enabling them to optimize experimental designs and interpret data emerging from genetic and epidemiological studies.</p

A Simple Method for Analyzing Exome Sequencing Data Shows Distinct Levels of Nonsynonymous Variation for Human Immune and Nervous System Genes

To measure the strength of natural selection that acts upon single nucleotide variants (SNVs) in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs) per nonsynonymous site and synonymous SNVs (sSNVs) per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv) in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs), nervous system genes (NSGs), randomly sampled genes (RSGs), and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30–40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system

Statins but Not Aspirin Reduce Thrombotic Risk Assessed by Thrombin Generation in Diabetic Patients without Cardiovascular Events: The RATIONAL Trial

The systematic use of aspirin and statins in patients with diabetes and no previous cardiovascular events is controversial. We sought to assess the effects of aspirin and statins on the thrombotic risk assessed by thrombin generation (TG) among patients with type II diabetes mellitus and no previous cardiovascular events.Prospective, randomized, open, blinded to events evaluation, controlled, 2×2 factorial clinical trial including 30 patients randomly allocated to aspirin 100 mg/d, atorvastatin 40 mg/d, both or none. Outcome measurements included changes in TG levels after treatment (8 to 10 weeks), assessed by a calibrated automated thrombogram. At baseline all groups had similar clinical and biochemical profiles, including TG levels. There was no interaction between aspirin and atorvastatin. Atorvastatin significantly reduced TG measured as peak TG with saline (85.09±55.34 nmol vs 153.26±75.55 nmol for atorvastatin and control groups, respectively; p = 0.018). On the other hand, aspirin had no effect on TG (121.51±81.83 nmol vs 116.85±67.66 nmol, for aspirin and control groups, respectively; p = 0.716). The effects of treatments on measurements of TG using other agonists were consistent.While waiting for data from ongoing large clinical randomized trials to definitively outline the role of aspirin in primary prevention, our study shows that among diabetic patients without previous vascular events, statins but not aspirin reduce thrombotic risk assessed by TG.ClinicalTrials.gov NCT00793754

Genetic Variation in the Proximal Promoter of ABC and SLC Superfamilies: Liver and Kidney Specific Expression and Promoter Activity Predict Variation

Membrane transporters play crucial roles in the cellular uptake and efflux of an array of small molecules including nutrients, environmental toxins, and many clinically used drugs. We hypothesized that common genetic variation in the proximal promoter regions of transporter genes contribute to observed variation in drug response. A total of 579 polymorphisms were identified in the proximal promoters (−250 to +50 bp) and flanking 5′ sequence of 107 transporters in the ATP Binding Cassette (ABC) and Solute Carrier (SLC) superfamilies in 272 DNA samples from ethnically diverse populations. Many transporter promoters contained multiple common polymorphisms. Using a sliding window analysis, we observed that, on average, nucleotide diversity (π) was lowest at approximately 300 bp upstream of the transcription start site, suggesting that this region may harbor important functional elements. The proximal promoters of transporters that were highly expressed in the liver had greater nucleotide diversity than those that were highly expressed in the kidney consistent with greater negative selective pressure on the promoters of kidney transporters. Twenty-one promoters were evaluated for activity using reporter assays. Greater nucleotide diversity was observed in promoters with strong activity compared to promoters with weak activity, suggesting that weak promoters are under more negative selective pressure than promoters with high activity. Collectively, these results suggest that the proximal promoter region of membrane transporters is rich in variation and that variants in these regions may play a role in interindividual variation in drug disposition and response

Clique-based data mining for related genes in a biomedical database

<p>Abstract</p> <p>Background</p> <p>Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph.</p> <p>Results</p> <p>We constructed a graph whose nodes were gene or disease pages, and edges were the hyperlink connections between those pages in the Online Mendelian Inheritance in Man (OMIM) database. We obtained over 20,000 sets of related genes (called 'gene modules') by enumerating cliques computationally. The modules included genes in the same family, genes for proteins that form a complex, and genes for components of the same signaling pathway. The results of experiments using 'metabolic syndrome'-related gene modules show that the gene modules can be used to get a coherent holistic picture helpful for interpreting relations among genes.</p> <p>Conclusion</p> <p>We presented a data mining approach extracting related genes by enumerating cliques. The extracted gene sets provide a holistic picture useful for comprehending complex disease mechanisms.</p

Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: association with major depression and antidepressant response in Mexican-Americans

We studied seven genes that reflect events relevant to antidepressant action at four sequential levels: (1) entry into the brain, (2) binding to monoaminergic transporters, and (3) distal effects at the transcription level, resulting in (4) changes in neurotrophin and neuropeptide receptors. Those genes are ATP-binding cassette subfamily B member 1 (ABCB1), the noradrenaline, dopamine, and serotonin transporters (SLC6A2, SLC6A3 and SLC6A4), cyclic AMP-responsive element binding protein 1 (CREB1), corticotropin-releasing hormone receptor 1 (CRHR1) and neurotrophic tyrosine kinase type 2 receptor (NTRK2). Sequence variability for those genes was obtained in exonic and flanking regions. A total of 56 280 000 bp across were sequenced in 536 unrelated Mexican Americans from Los Angeles (264 controls and 272 major depressive disorder (MDD)). We detected in those individuals 419 single nucleotide polymorphisms (SNPs); the nucleotide diversity was 0.00054±0.0001. Of those, a total of 204 novel SNPs were identified, corresponding to 49% of all previously reported SNPs in those genes: 72 were in untranslated regions, 19 were in coding sequences of which 7 were non-synonymous, 86 were intronic and 27 were in upstream/downstream regions. Several SNPs or haplotypes in ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1 and NTRK2 were associated with MDD, and in ABCB1, SLC6A2 and NTRK2 with antidepressant response. After controlling for age, gender and baseline 21-item Hamilton Depression Rating Scale (HAM-D21) score, as well as correcting for multiple testing, the relative reduction of HAM-D21 score remained significantly associated with two NTRK2-coding SNPs (rs2289657 and rs56142442) and the haplotype CAG at rs2289658 (splice site), rs2289657 and rs2289656. Further studies in larger independent samples will be needed to confirm these associations. Our data indicate that extensive assessment of sequence variability may contribute to increase understanding of disease susceptibility and drug response. Moreover, these results highlight the importance of direct re-sequencing of key candidate genes in ethnic minority groups in order to discover novel genetic variants that cannot be simply inferred from existing databases

Allellic variants in regulatory regions of cyclooxygenase-2: association with advanced colorectal adenoma

Cyclooxygenase 2 (Cox-2) is upregulated in colorectal adenomas and carcinomas. Polymorphisms in the Cox-2 gene may influence its function and/or its expression and may modify the protective effect of nonsteroidal anti-inflammatory drugs (NSAIDs), thereby impacting individuals' risk of developing colorectal cancer and response to prevention/intervention strategies. In a nested case–control study, four polymorphisms in the Cox-2 gene (two in the promoter, −663 insertion/deletion, GT/(GT) and −798 A/G; one in intron 5-5229, T/G; one in 3′untranslated region (UTR)-8494, T/C) were genotyped in 726 cases of colorectal adenomas and 729 age- and gender-matched controls in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial. There was no significant association between the Cox-2 polymorphisms and adenoma development in the overall population. However, in males, the relatively rare heterozygous genotype GT/(GT) at −663 in the promoter and the variant homozygous genotype G/G at intron 5-5229 appeared to have inverse associations (odds ratio (OR)=0.59, confidence interval (CI): 0.34–1.02 and OR=0.48, CI: 0.24–0.99, respectively), whereas the heterozygous genotype T/C at 3′UTR-8494 had a positive association (OR=1.31, CI: 1.01–1.71) with adenoma development. Furthermore, the haplotype carrying the risk-conferring 3′UTR-8494 variant was associated with a 35% increase in the odds for adenoma incidence in males (OR=1.35, CI: 1.07–1.70), but the one with a risk allele at 3′UTR-8494 and a protective allele at intron 5-5229 had no effect on adenoma development (OR=0.85, CI: 0.66–1.09). Gender-related differences in adenoma risk were also noted with tobacco usage and protective effects of NSAIDs. Our analysis underscores the significance of the overall allelic architecture of Cox-2 as an important determinant for risk assessment

Distribution and Effects of Nonsense Polymorphisms in Human Genes

BACKGROUND: A great amount of data has been accumulated on genetic variations in the human genome, but we still do not know much about how the genetic variations affect gene function. In particular, little is known about the distribution of nonsense polymorphisms in human genes despite their drastic effects on gene products. METHODOLOGY/PRINCIPAL FINDINGS: To detect polymorphisms affecting gene function, we analyzed all publicly available polymorphisms in a database for single nucleotide polymorphisms (dbSNP build 125) located in the exons of 36,712 known and predicted protein-coding genes that were defined in an annotation project of all human genes and transcripts (H-InvDB ver3.8). We found a total of 252,555 single nucleotide polymorphisms (SNPs) and 8,479 insertion and deletions in the representative transcripts in these genes. The SNPs located in ORFs include 40,484 synonymous and 53,754 nonsynonymous SNPs, and 1,258 SNPs that were predicted to be nonsense SNPs or read-through SNPs. We estimated the density of nonsense SNPs to be 0.85x10(-3) per site, which is lower than that of nonsynonymous SNPs (2.1x10(-3) per site). On average, nonsense SNPs were located 250 codons upstream of the original termination codon, with the substitution occurring most frequently at the first codon position. Of the nonsense SNPs, 581 were predicted to cause nonsense-mediated decay (NMD) of transcripts that would prevent translation. We found that nonsense SNPs causing NMD were more common in genes involving kinase activity and transport. The remaining 602 nonsense SNPs are predicted to produce truncated polypeptides, with an average truncation of 75 amino acids. In addition, 110 read-through SNPs at termination codons were detected. CONCLUSION/SIGNIFICANCE: Our comprehensive exploration of nonsense polymorphisms showed that nonsense SNPs exist at a lower density than nonsynonymous SNPs, suggesting that nonsense mutations have more severe effects than amino acid changes. The correspondence of nonsense SNPs to known pathological variants suggests that phenotypic effects of nonsense SNPs have been reported for only a small fraction of nonsense SNPs, and that nonsense SNPs causing NMD are more likely to be involved in phenotypic variations. These nonsense SNPs may include pathological variants that have not yet been reported. These data are available from Transcript View of H-InvDB and VarySysDB (http://h-invitational.jp/varygene/)