Triallelic single nucleotide polymorphisms and genotyping error in genetic epidemiology studies: MDR1 (ABCB1) G2677/T/A as an example

An almost infinite sites model

MOTIVATION

A main challenge in molecular evolution is to find computationally efficient mutation models with flexible assumptions that properly reflect genetic variation. The infinite sites model assumes that each mutation event occurs at a site never previously mutant, i.e. it does not allow recurrent mutations. This is reasonable for low mutation rates and makes statistical inference much more tractable. However, recurrent mutations are common enough to be observable from genetic variation data, even in species with low per-site mutation rates such as humans. The finite sites model on the other hand allows for recurrent mutations but is computationally unfeasible to work with in most cases. In this work, we bridge these two approaches by developing a novel molecular evolution model, the almost infinite sites model, that both admits recurrent mutations and is tractable. We provide a recursive characterization of the likelihood of our proposed model under complete linkage and outline a parsimonious approximation scheme for computing it.

RESULTS

We show the usefulness of our model in simulated and human mitochondrial data. Our results show that the AISM, in combination with a constraint on the total number of mutation events, can recover accurate approximations to the maximum likelihood estimator of the mutation rate.

AVAILABILITY AND IMPLEMENTATION

An implementation of our model is freely available along with code for reproducing our computational experiments at https://github.com/Cronjaeger/almost-infinite-sites-recursions.

FLT4 gene polymorphisms influence isolated ventricular septal defect predisposition in a Southwest China population

BACKGROUND

Ventricular septal defect (VSD) is the most common congenital heart disease. Although a small number of genes associated with VSD have been found, the genetic factors of VSD remain unclear. In this study, we evaluated the association of 10 candidate single nucleotide polymorphisms (SNPs) with isolated VSD in a population from Southwest China.

METHODS

Based on the results of 34 congenital heart disease whole-exome sequencing and 1000 Genomes databases, 10 candidate SNPs were selected. A total of 618 samples were collected from the population of Southwest China, including 285 VSD samples and 333 normal samples. Ten SNPs in the case group and the control group were identified by SNaPshot genotyping. The chi-square (χ2) test was used to evaluate the relationship between VSD and each candidate SNP. The SNPs that had significant P value in the initial stage were further analysed using linkage disequilibrium, and haplotypes were assessed in 34 congenital heart disease whole-exome sequencing samples using Haploview software. The bins of SNPs that were in very strong linkage disequilibrium were further used to predict haplotypes by Arlequin software. ViennaRNA v2.5.1 predicted the haplotype mRNA secondary structure. We evaluated the correlation between mRNA secondary structure changes and ventricular septal defects.

RESULTS

The χ2 results showed that the allele frequency of FLT4 rs383985 (P = 0.040) was different between the control group and the case group (P < 0.05). FLT4 rs3736061 (r2 = 1), rs3736062 (r2 = 0.84), rs3736063 (r2 = 0.84) and FLT4 rs383985 were in high linkage disequilibrium (r2 > 0.8). Among them, rs3736061 and rs3736062 SNPs in the FLT4 gene led to synonymous variations of amino acids, but predicting the secondary structure of mRNA might change the secondary structure of mRNA and reduce the free energy.

CONCLUSIONS

These findings suggest a possible molecular pathogenesis associated with isolated VSD, which warrants investigation in future studies.

Association study of FLT4 and HYDIN single nucleotide polymorphisms with atrial septal defect susceptibility in the Han Chinese population of Southwest China

BACKGROUND

Atrial septal defect (ASD) is a common form of congenital heart disease. Although several genes related to ASD have been found, the genetic factors of ASD remain unclear. This study aimed to evaluate the correlation between 10 candidate single nucleotide polymorphisms (SNPs) and sporadic atrial septal defects.

METHODS

Based on the results of 34 individual whole exome sequences, 10 candidate SNPs were selected. In total, 489 ASD samples and 420 normal samples were collected. The 10 SNPs in the case group and the control group were identified through Snapshot genotyping technology. The χ2-test and unconditional regression model were used to evaluate the relationship between ASD and each candidate SNP. Haploview software was used to perform linkage disequilibrium and haplotype analysis.

RESULTS

The χ2 results showed that the FLT4 rs383985 (P = 0.003, OR = 1.115-1.773), HYDIN rs7198975 (P = 0.04621, OR = 1.003-1.461), and HYDIN rs1774266 (P = 0.04621, OR = 1.003-1.461) alleles were significantly different between the control group and the case group (P < 0.05). Only the association with the FLT4 polymorphism was statistically significant after adjustment for multiple comparisons.

CONCLUSION

These findings suggest that a possible molecular pathogenesis associated with sporadic ASD is worth exploring in future studies.

The arithmetic topology of genetic alignments

We propose a novel mathematical paradigm for the study of genetic variation in sequence alignments. This framework originates from extending the notion of pairwise relations, upon which current analysis is based on, to k-ary dissimilarity. This dissimilarity naturally leads to a generalization of simplicial complexes by endowing simplices with weights, compatible with the boundary operator. We introduce the notion of k-stances and dissimilarity complex, the former encapsulating arithmetic as well as topological structure expressing these k-ary relations. We study basic mathematical properties of dissimilarity complexes and show how this approach captures watershed moments of viral dynamics in the context of SARS-CoV-2 and H1N1 flu genomic data.

Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance

The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

Candidate adaptive genes associated with lineage divergence: identifying SNPs via next-generation targeted resequencing in mule deer (Odocoileus hemionus)

Mule deer (Odocoileus hemionus) are an excellent nonmodel species for empirically testing hypotheses in landscape and population genomics due to their large population sizes (low genetic drift), relatively continuous distribution, diversity of occupied habitats and phenotypic variation. Because few genomic resources are currently available for this species, we used exon data from a cattle (Bos taurus) reference genome to direct targeted resequencing of 5935 genes in mule deer. We sequenced approximately 3.75 Mbp at minimum 20X coverage in each of the seven mule deer, identifying 23 204 single nucleotide polymorphisms (SNPs) within, or adjacent to, 6886 exons in 3559 genes. We found 91 SNP loci (from 69 genes) with putatively fixed allele frequency differences between the two major lineages of mule deer (mule deer and black-tailed deer), and our estimate of mean genetic divergence (genome-wide FST  = 0.123) between these lineages was consistent with previous findings using microsatellite loci. We detected an over-representation of gamete generation and amino acid transport genes among the genes with SNPs exhibiting potentially fixed allele frequency differences between lineages. This targeted resequencing approach using exon capture techniques has identified a suite of loci that can be used in future research to investigate the genomic basis of adaptation and differentiation between black-tailed deer and mule deer. This study also highlights techniques (and an exon capture array) that will facilitate population genomic research in other cervids and nonmodel organisms.

Genetic risk factors for clozapine-induced neutropenia and agranulocytosis in a Dutch psychiatric population

Prescription of clozapine is complicated by the occurrence of clozapine-induced reduction of neutrophils. The aim of this study was to identify genetic risk factors in a population of 310 Dutch patients treated with clozapine, including 38 patients developing neutropenia and 31 patients developing agranulocytosis. NQO2 1541AA (NRH quinone oxidoreductase 2; protects cells against oxidative metabolites) was present at a higher frequency in agranulocytosis patients compared with control (23% versus 7%, P=0.03), as was ABCB1 (ABC-transporter-B1; drug efflux transporter) 3435TT (32% versus 20%, P=0.05). In patients developing neutropenia, ABCB1 3435TT and homozygosity for GSTT1^null (glutathione-S-transferase; conjugates reactive clozapine metabolites into glutathione) were more frequent compared with control (34% versus 20%, P=0.05 and 31% versus 14%, P=0.03), whereas GSTM1^null was less frequent in these patients (31% versus 52%, P=0.03). To investigate whether combinations of the identified genetic risk factors have a higher predictive value, should be confirmed in a larger case-control study.

Risk of Misdiagnosis Due to Allele Dropout and False-Positive PCR Artifacts in Molecular Diagnostics: Analysis of 30,769 Genotypes

Quality control is a complex issue for clinical molecular diagnostic applications. In the case of genotyping assays, artifacts such as allele dropout represent a risk of misdiagnosis for amplification-based methods. However, its frequency of occurrence in PCR-based diagnostic assays remains unknown. To maximize the likelihood of detecting allele dropout, our clinical genotyping PCR-based assays are designed with two independent assays for each allele (nonoverlapping primers on each DNA strand). To estimate the incidence of allelic dropout, we took advantage of the capacity of our clinical assays to detect such events. We retrospectively studied their occurrence in the initial PCR assay for 30,769 patient reports for mutations involved in four diseases produced over 8 years. Ninety-three allele dropout events were detected and all were solved before reporting. In addition, 42 cases of artifacts caused by amplification of an allele ultimately confirmed to not be part of the genotype (drop-in events) were detected and solved. These artifacts affected 1:227 genotypes, 94% of which were due to nonreproducible PCR failures rather than sequence variants interfering with the assay, suggesting that careful primer design cannot prevent most of these errors. This provides a quantitative estimate for clinical laboratories to take this phenomenon into account in quality management and to favor assay designs that can detect (and minimize) occurrence of these artifacts in routine clinical use.

Comparing variant calling algorithms for target-exon sequencing in a large sample

BACKGROUND

Sequencing studies of exonic regions aim to identify rare variants contributing to complex traits. With high coverage and large sample size, these studies tend to apply simple variant calling algorithms. However, coverage is often heterogeneous; sites with insufficient coverage may benefit from sophisticated calling algorithms used in low-coverage sequencing studies. We evaluate the potential benefits of different calling strategies by performing a comparative analysis of variant calling methods on exonic data from 202 genes sequenced at 24x in 7,842 individuals. We call variants using individual-based, population-based and linkage disequilibrium (LD)-aware methods with stringent quality control. We measure genotype accuracy by the concordance with on-target GWAS genotypes and between 80 pairs of sequencing replicates. We validate selected singleton variants using capillary sequencing.

RESULTS

Using these calling methods, we detected over 27,500 variants at the targeted exons; >57% were singletons. The singletons identified by individual-based analyses were of the highest quality. However, individual-based analyses generated more missing genotypes (4.72%) than population-based (0.47%) and LD-aware (0.17%) analyses. Moreover, individual-based genotypes were the least concordant with array-based genotypes and replicates. Population-based genotypes were less concordant than genotypes from LD-aware analyses with extended haplotypes. We reanalyzed the same dataset with a second set of callers and showed again that the individual-based caller identified more high-quality singletons than the population-based caller. We also replicated this result in a second dataset of 57 genes sequenced at 127.5x in 3,124 individuals.

CONCLUSIONS

We recommend population-based analyses for high quality variant calls with few missing genotypes. With extended haplotypes, LD-aware methods generate the most accurate and complete genotypes. In addition, individual-based analyses should complement the above methods to obtain the most singleton variants.

Efficiency of the inbreeding coefficient f and other estimators in detecting null alleles, as revealed by empirical data of locus oke3 across 65 populations of chum salmon Oncorhynchus keta

A survey of 65 populations of chum salmon Oncorhynchus keta across the species range revealed homozygote excess (947 homozygotes in 2954 fish) at a polymerase chain reaction (PCR)-based simple sequence repeat (SSR) locus oke3 with multiple alleles, whereas re-designed PCR primers indicated that 328 of these homozygotes were actually heterozygotes. Statistically significant high positive values of inbreeding coefficients, f, in multiple populations appeared to be a reliable predictor of null alleles. Based on these data, three methods were checked for their ability to estimate null-allele frequencies.

MDR1 gene polymorphisms and imatinib response in chronic myeloid leukemia: a meta-analysis

BACKGROUND

MDR1 gene polymorphisms were demonstrated to be associated with interindividual variability of imatinib response for chronic myeloid leukemia (CML) patients in several studies; however, the results have been inconclusive.

MATERIALS & METHODS

To clarify the effect of common MDR1 variants on clinical response to imatinib, we performed a meta-analysis to quantify the accumulated information from genetic association studies. After a thorough search of the published literature, we undertook a meta-analysis to evaluate the effect of MDR1 C1236T, G2677T and C3435T polymorphisms on imatinib response.

RESULTS

Our pooled data showed a significant association between MDR1 C1236T polymorphism and the increasing risk of imatinib resistance in Asian CML patients. However, no significant association was found for the MDR1 G2677T or C3435T polymorphisms in an Asian CML population as well as a Caucasian CML population.

CONCLUSION

The synonymous MDR1 C1236T polymorphism might be a risk factor for nonoptimal clinical response to imatinib in Asian CML patients.

Clinical SNP detection by the SmartAmp method

For advancing personalized medicine, it is important to incorporate pharmacogenomics data into routine clinical practice. The SmartAmp method enables us to detect genetic polymorphisms or mutations in target genes within 30-40 min without DNA isolation and PCR amplification. The SmartAmp method has been developed based on the concept that DNA amplification per se is the signal for the presence of a specific target sequence. Differing from the widely used PCR, the SmartAmp reaction is an isothermal DNA amplification, where the initial step of copying a target sequence from the template DNA is critically important. For clinical applications, we have created SmartAmp primers and clinical device that detect genetic polymorphisms of human genes involved in drug-induced toxicity or disease risk. This chapter addresses both the basic molecular mechanism underlying the SmartAmp method and its practical applications to detect clinically important single nucleotide polymorphisms (SNPs).

General triallelic frequency spectrum under demographic models with variable population size

It is becoming routine to obtain data sets on DNA sequence variation across several thousands of chromosomes, providing unprecedented opportunity to infer the underlying biological and demographic forces. Such data make it vital to study summary statistics that offer enough compression to be tractable, while preserving a great deal of information. One well-studied summary is the site frequency spectrum-the empirical distribution, across segregating sites, of the sample frequency of the derived allele. However, most previous theoretical work has assumed that each site has experienced at most one mutation event in its genealogical history, which becomes less tenable for very large sample sizes. In this work we obtain, in closed form, the predicted frequency spectrum of a site that has experienced at most two mutation events, under very general assumptions about the distribution of branch lengths in the underlying coalescent tree. Among other applications, we obtain the frequency spectrum of a triallelic site in a model of historically varying population size. We demonstrate the utility of our formulas in two settings: First, we show that triallelic sites are more sensitive to the parameters of a population that has experienced historical growth, suggesting that they will have use if they can be incorporated into demographic inference. Second, we investigate a recently proposed alternative mechanism of mutation in which the two derived alleles of a triallelic site are created simultaneously within a single individual, and we develop a test to determine whether it is responsible for the excess of triallelic sites in the human genome.

CXCR3/CCR5 pathways in metastatic melanoma patients treated with adoptive therapy and interleukin-2

Background:

Adoptive therapy with tumour-infiltrating lymphocytes (TILs) induces durable complete responses (CR) in ∼20% of patients with metastatic melanoma. The recruitment of T cells through CXCR3/CCR5 chemokine ligands is critical for immune-mediated rejection. We postulated that polymorphisms and/or expression of CXCR3/CCR5 in TILs and the expression of their ligands in tumour influence the migration of TILs to tumours and tumour regression.

Methods:

Tumour-infiltrating lymphocytes from 142 metastatic melanoma patients enrolled in adoptive therapy trials were genotyped for CXCR3 rs2280964 and CCR5-Δ32 deletion, which encodes a protein not expressed on the cell surface. Expression of CXCR3/CCR5 in TILs and CXCR3/CCR5 and ligand genes in 113 available parental tumours was also assessed. Tumour-infiltrating lymphocyte data were validated by flow cytometry (N=50).

Results:

The full gene expression/polymorphism model, which includes CXCR3 and CCR5 expression data, CCR5-Δ32 polymorphism data and their interaction, was significantly associated with both CR and overall response (OR; P=0.0009, and P=0.007, respectively). More in detail, the predicted underexpression of both CXCR3 and CCR5 according to gene expression and polymorphism data (protein prediction model, PPM) was associated with response to therapy (odds ratio=6.16 and 2.32, for CR and OR, respectively). Flow cytometric analysis confirmed the PPM. Coordinate upregulation of CXCL9, CXCL10, CXCL11, and CCL5 in pretreatment tumour biopsies was associated with OR.

Conclusion:

Coordinate overexpression of CXCL9, CXCL10, CXCL11, and CCL5 in pretreatment tumours was associated with responsiveness to treatment. Conversely, CCR5-Δ32 polymorphism and CXCR3/CCR5 underexpression influence downregulation of the corresponding receptors in TILs and were associated with likelihood and degree of response.

Nutrigenomics and nutrigenetics in inflammatory bowel diseases

Inflammatory bowel diseases (IBD) including ulcerative colitis and Crohn's disease are chronically relapsing, immune-mediated disorders of the gastrointestinal tract. A major challenge in the treatment of IBD is the heterogenous nature of these pathologies. Both, ulcerative colitis and Crohn's disease are of multifactorial etiology and feature a complex interaction of host genetic susceptibility and environmental factors such as diet and gut microbiota. Genome-wide association studies identified disease-relevant single-nucleotide polymorphisms in approximately 100 genes, but at the same time twin studies also clearly indicated a strong environmental impact in disease development. However, attempts to link dietary factors to the risk of developing IBD, based on epidemiological observations showed controversial outcomes. Yet, emerging high-throughput technologies implying complete biological systems might allow taking nutrient-gene interactions into account for a better classification of patient subsets in the future. In this context, 2 new scientific fields, "nutrigenetics" and "nutrigenomics" have been established. "Nutrigenetics," studying the effect of genetic variations on nutrient-gene interactions and "Nutrigenomics," describing the impact of nutrition on physiology and health status on the level of gene transcription, protein expression, and metabolism. It is hoped that the integration of both research areas will promote the understanding of the complex gene-environment interaction in IBD etiology and in the long-term will lead to personalized nutrition for disease prevention and treatment. This review briefly summarizes data on the impact of nutrients on intestinal inflammation, highlights nutrient-gene interactions, and addresses the potential of applying "omic" technologies in the context of IBD.

Limitations of the human reference genome for personalized genomics

Data from the 1000 genomes project (1KGP) and Complete Genomics (CG) have dramatically increased the numbers of known genetic variants and challenge several assumptions about the reference genome and its uses in both clinical and research settings. Specifically, 34% of published array-based GWAS studies for a variety of diseases utilize probes that overlap unanticipated single nucleotide polymorphisms (SNPs), indels, or structural variants. Linkage disequilibrium (LD) block length depends on the numbers of markers used, and the mean LD block size decreases from 16 kb to 7 kb,when HapMap-based calculations are compared to blocks computed from1KGP data. Additionally, when 1KGP and CG variants are compared, 19% of the single nucleotide variants (SNVs) reported from common genomes are unique to one dataset; likely a result of differences in data collection methodology, alignment of reads to the reference genome, and variant-calling algorithms. Together these observations indicate that current research resources and informatics methods do not adequately account for the high level of variation that already exists in the human population and significant efforts are needed to create resources that can accurately assess personal genomics for health, disease, and predict treatment outcomes.

Genetic analysis of cytomegalovirus in malignant gliomas

Human cytomegalovirus (HCMV) has been found in malignant gliomas at variable frequencies with efforts to date focused on characterizing the role(s) of single gene products in disease. Here, we reexamined the HCMV prevalence in malignant gliomas using different methods and began to dissect the genetics of HCMV in tumors. HCMV DNA was found in 16/17 (94%) tumor specimens. Viral DNA copy numbers were found to be low and variable, ranging from 10(2) to 10(6) copies/500 ng of total DNA. The tumor tissues had incongruences between viral DNA copy numbers and protein levels. However, nonlatent protein expression was detected in many tumors. The viral UL83 gene, encoding pp65, was found to segregate into five cancer-associated genotypes with a bias for amino acid changes in glioblastoma multiforme (GBM) in comparison to the low-grade tumors. Deep sequencing of a GBM-associated viral population resulted in 81,224 bp of genome coverage. Sequence analysis revealed the presence of intact open reading frames and higher numbers of high-frequency variations within the repeat long region compared to the unique long region, which harbors many core genes, and the unique short region (P = 0.001). This observation was in congruence with phylogenetic analyses across replication-competent viral strains in databases. The tumor-associated viral population was less variable (π = 0.1% and π(AA) = 0.08%) than that observed in other clinical infections. Moreover, 42/46 (91.3%) viral genes analyzed had dN/dS scores of <1, which is indicative of high amino acid sequence conservation. Taken together, these findings raise the possibility that replication-competent HCMV may exist in malignant gliomas.

Genetic variations and patient-reported quality of life among patients with lung cancer

PURPOSE

Recent evidence has suggested a relationship between the baseline quality of life (QOL) self-reported by patients with cancer and genetic disposition. We report an analysis exploring relationships among baseline QOL assessments and candidate genetic variations in a large cohort of patients with lung cancer.

PATIENTS AND METHODS

QOL data were provided by 1,299 patients with non-small-cell lung cancer observed at the Mayo Clinic between 1997 and 2007. Overall QOL and subdomains were assessed by either Lung Cancer Symptom Scale or Linear Analog Self Assessment measures; scores were transformed to a scale of 0 to 10, with higher scores representing better status. Baseline QOL scores assessed within 1 year of diagnosis were dichotomized as clinically deficient (CD) or not. A total of 470 single nucleotide polymorphisms (SNPs) in 56 genes of three biologic pathways were assessed for association with QOL measures. Logistic regression with training/validation samples was used to test the association of SNPs with CD QOL.

RESULTS

Six SNPs on four genes were replicated using our split schemes. Three SNPs in the MGMT gene (adjusted analysis, rs3858300; unadjusted analysis, rs10741191 and rs3852507) from DNA repair pathway were associated with overall QOL. Two SNPs (rs2287396 [GSTZ1] and rs9524885 [ABCC4]) from glutathione metabolic pathway were associated with fatigue in unadjusted analysis. In adjusted analysis, two SNPs (rs2756109 [ABCC2] and rs9524885 [ABCC4]) from glutathione metabolic pathway were associated with pain.

CONCLUSION

We identified three SNPs in three glutathione metabolic pathway genes and three SNPs in two DNA repair pathway genes associated with QOL measures in patients with non-small-cell lung cancer.

ALG: automated genotype calling of Luminex assays

Single nucleotide polymorphisms (SNPs) are the most commonly used polymorphic markers in genetics studies. Among the different platforms for SNP genotyping, Luminex is one of the less exploited mainly due to the lack of a robust (semi-automated and replicable) freely available genotype calling software. Here we describe a clustering algorithm that provides automated SNP calls for Luminex genotyping assays. We genotyped 3 SNPs in a cohort of 330 childhood leukemia patients, 200 parents of patient and 325 healthy individuals and used the Automated Luminex Genotyping (ALG) algorithm for SNP calling. ALG genotypes were called twice to test for reproducibility and were compared to sequencing data to test for accuracy. Globally, this analysis demonstrates the accuracy (99.6%) of the method, its reproducibility (99.8%) and the low level of no genotyping calls (3.4%). The high efficiency of the method proves that ALG is a suitable alternative to the current commercial software. ALG is semi-automated, and provides numerical measures of confidence for each SNP called, as well as an effective graphical plot. Moreover ALG can be used either through a graphical user interface, requiring no specific informatics knowledge, or through command line with access to the open source code. The ALG software has been implemented in R and is freely available for non-commercial use either at http://alg.sourceforge.net or by request to mathieu.bourgey@umontreal.ca

Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level

BACKGROUND

Targeted re-sequencing of candidate genes in individuals at the extremes of a quantitative phenotype distribution is a method of choice to gain information on the contribution of rare variants to disease susceptibility. The endocannabinoid system mediates signaling in the brain and peripheral tissues involved in the regulation of energy balance, is highly active in obese patients, and represents a strong candidate pathway to examine for genetic association with body mass index (BMI).

RESULTS

We sequenced two intervals (covering 188 kb) encoding the endocannabinoid metabolic enzymes fatty-acid amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal controls and 142 extremely obese cases. After applying quality filters, we called 1,393 high quality single nucleotide variants, 55% of which are rare, and 143 indels. Using single marker tests and collapsed marker tests, we identified four intervals associated with BMI: the FAAH promoter, the MGLL promoter, MGLL intron 2, and MGLL intron 3. Two of these intervals are composed of rare variants and the majority of the associated variants are located in promoter sequences or in predicted transcriptional enhancers, suggesting a regulatory role. The set of rare variants in the FAAH promoter associated with BMI is also associated with increased level of FAAH substrate anandamide, further implicating a functional role in obesity.

CONCLUSIONS

Our study, which is one of the first reports of a sequence-based association study using next-generation sequencing of candidate genes, provides insights into study design and analysis approaches and demonstrates the importance of examining regulatory elements rather than exclusively focusing on exon sequences.

Methodological issues of genetic association studies

Genetic association studies explore the association between genetic polymorphisms and a certain trait, disease or predisposition to disease. It has long been acknowledged that many genetic association studies fail to replicate their initial positive findings. This raises concern about the methodological quality of these reports. Case-control genetic association studies often suffer from various methodological flaws in study design and data analysis, and are often reported poorly. Flawed methodology and poor reporting leads to distorted results and incorrect conclusions. Many journals have adopted guidelines for reporting genetic association studies. In this review, some major methodological determinants of genetic association studies will be discussed.

Scientific imperatives, clinical implications, and theoretical underpinnings for the investigation of the relationship between genetic variables and patient-reported quality-of-life outcomes

Objectives

There is emerging evidence for a genetic basis of patient-reported quality-of-life (QOL) outcomes that can ultimately be incorporated into clinical research and practice. Objectives are (1) to provide arguments for the timeliness of investigating the genetic basis of QOL given the scientific advances in genetics and patient-reported QOL research; (2) to describe the clinical implications of such investigations; (3) to present a theoretical foundation for investigating the genetic underpinnings of QOL; and (4) to describe a series of papers resulting from the GENEQOL Consortium that was established to move this work forward.

Methods

Discussion of scientific advances based on relevant literature.

Results

In genetics, technological advances allow for increases in speed and efficiency and decreases in costs in exploring the genetic underpinnings of disease processes, drug metabolism, treatment response, and survival. In patient-based research, advances yield empirically based and stringent approaches to measurement that are scientifically robust. Insights into the genetic basis of QOL will ultimately allow early identification of patients susceptible to QOL deficits and to target care. The Wilson and Cleary model for patient-reported outcomes was refined by incorporating the genetic underpinnings of QOL.

Conclusions

This series of papers provides a path for QOL and genetics researchers to work together to move this field forward and to unravel the intricate interplay of the genetic underpinnings of patient-reported QOL outcomes. The ultimate result will be a greater understanding of the process relating disease, patient, and doctor that will have the potential to lead to improved survival, QOL, and health services delivery.

Rapid and cost-effective SNP detection method: application of SmartAmp2 to pharmacogenomics research

Pharmacogenomics data can facilitate our understanding of the sources of variability in drug response, which can potentially lead to improved safety and efficacy of drug therapy for individual patients. A key requirement for the development of individualized medicine or personalized therapy is the ability to rapidly and conveniently test patients for genetic polymorphisms and/or mutations. However, in today's world, genotyping technology remains a bottleneck in clinical applications because of its slow speed and high cost. Therefore, we have recently developed a rapid and cost-effective method for SNP detection, named Smart Amplification Process 2 (SmartAmp2), which enables us to detect genetic polymorphisms or mutations in 30-45 min under isothermal conditions without DNA isolation and PCR amplification. This article presents the SNP detection method and its underlying molecular mechanism as well as clinical research applications.

An extended IUPAC nomenclature code for polymorphic nucleic acids

The International Union of Pure and Applied Chemistry (IUPAC) code specified nearly 25 years ago provides a nomenclature for incompletely specified nucleic acids. However, no system currently exists that allows for the informatics representation of the relative abundance at polymorphic nucleic acids (e.g. single nucleotide polymorphisms) in a single specified character, or a string of characters. Here, I propose such an information code as a natural extension to the IUPAC nomenclature code, and present some potential uses and limitations to such a code. The primary anticipated use of this extended nomenclature code is to assist in the representation of the rapidly growing space of information in human genetic variation.

CONTACT

johnsonad2@nhlbi.nih.gov

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of single-nucleotide polymorphisms relevant to inflammatory bowel disease in commonly used gastrointestinal cell lines

BACKGROUND

The era of genome-wide association studies (GWAS) has led to the identification of many inflammatory bowel disease (IBD)-associated single-nucleotide polymorphisms (SNPs) with unknown function. The next step would be to identify the functional consequences of these polymorphisms in order to target them efficiently for therapeutic purposes. One way to study this type of genetic variation is the use of cell line models. However, to characterize the functional effect of a SNP, it is important to know if the selected cell line model itself carries the studied genetic variation. Here, we genotyped 50 IBD markers across 32 susceptibility genes in 9 commonly used gastrointestinal cell lines.

METHODS

We used Sequenom, TaqMan, and DNA sequencing for the genotyping. To determine the expression profile of the selected genes, we conducted real-time RT-PCR.

RESULTS

We found variant SNPs in all analyzed cell lines. Almost every minor allele was carried by at least one of the tested cell lines. We analyzed the effect of 4 SNPs in more detail using quantitative real-time RT-PCR (qRT-PCR) comprising genes ATG16L1, CD14, MDR1, and OCTN2. According to our data, only 2 of the commonly studied SNPs in MDR1 and CD14 have an impact on gene expression.

CONCLUSIONS

We have identified genotype variants in all analyzed cell lines. Some of them are functional and alter the response to drugs (MDR1) or affect bacterial recognition (TLR4, NOD2). Our results highlight that the genotype should not be neglected in experimental design when using model cell lines.

Current software for genotype imputation

Genotype imputation for single nucleotide polymorphisms (SNPs) has been shown to be a powerful means to include genetic markers in exploratory genetic association studies without having to genotype them, and is becoming a standard procedure. A number of different software programs are available. In our experience, user-friendliness is often the deciding factor in the choice of software to solve a particular task. We therefore evaluated the usability of three publicly available imputation programs: BEAGLE, IMPUTE and MACH. We found all three programs to perform well with HapMap reference data, with little effort needed for data preparation and subsequent association analysis. Each of them has different strengths and weaknesses, however, and none is optimal for all situations.

Genotyping error detection in samples of unrelated individuals without replicate genotyping

OBJECTIVE

Identifying genotyping errors is an important issue in genetic research, yet it has been relatively less studied in samples consisting of unrelated individuals. In this article, we consider several models of genotyping errors, which were originally proposed for pedigree data, for unrelated population samples with single nucleotide polymorphism (SNP) genotype data. The mathematical constraints are investigated for detecting genotyping errors without resampling replicates or genotyping relatives.

METHODS

For the various proposed genotyping error models, we unveil the conditions under which the parameters are identifiable. These results are verified through applications to simulated and real SNP data.

RESULTS

We show that, with constraints, two particular models provide both identifiable error rate and allele frequencies of an SNP for unrelated population data. The simulation study shows that these two models present unbiased estimates for the allele frequencies. One of the models also gives an unbiased estimate for the genotyping error rate.

CONCLUSION

While the Hardy-Weinberg equilibrium test can be used to detect genotyping errors, a key advantage of these models is the explicit estimates of genotyping error rates and allele frequencies. This work may help researchers to estimate error rates and to use the estimates in their analysis to increase power and decrease bias, without the extra work of genotyping family members or replicates.

Genetic variation in Transaldolase 1 and risk of squamous cell carcinoma of the head and neck

BACKGROUND

The Pentose Phosphate Pathway (PPP) is involved in the body's protection against oxidative stress and resistance/susceptibility to apoptosis and thus has been implicated in tumor development and progression. Here we present data examining the association of genetic variation in one of the key enzymes of the PPP, Transaldolase 1 (TALDO1) with squamous cell carcinoma of the head and neck (SCCHN).

METHODS

We performed sequencing analysis to identify common genetic variations in TALDO1 and then investigated their association with SCCHN using samples from a population-based case/control study with both European American (EA) and African American (AA) former and current smokers.

RESULTS

We identified three polymorphisms in TALDO1 that were associated with SCCHN risk in our EA study population. Specifically the 5' upstream variant -490C>G or T (rs10794338), which we identified as tri-allelic, showed a reduced risk compared with any presence of the common allele, odds ratio (OR) [95% confidence interval (95% CI)]: 0.57 (0.38-0.86). Additionally two intronic high frequency polymorphisms demonstrated a positive association with disease, with the presence of the variant IVS1+1874T>A (rs3901233), 1.76 (1.19-2.61) and IVS4+2187A>C (rs4963163), 1.71 (1.16-2.53).

CONCLUSION

These results provide preliminary evidence that genetic polymorphisms in TALDO1 are associated with SCCHN.

Association of a polymorphism of ABCB1 with obesity in Japanese individuals

The aim of the present study was to identify gene polymorphisms that confer susceptibility to obesity. A total of 5448 unrelated Japanese individuals from two independent populations were examined: subject panel A comprised 4252 individuals who visited participating hospitals; subject panel B comprised 1196 community-dwelling elderly individuals. The genotypes for 95 polymorphisms of 67 candidate genes were determined. The chi(2) test revealed that six polymorphisms were related (p<0.05) to the prevalence of obesity in subject panel A; after application of Bonferroni's correction, however, only the 2677G --> A/T polymorphism (rs2032582) of the ATP-binding cassette, subfamily B, member 1 gene (ABCB1) was significantly associated (p=0.0003) with obesity. Subsequent multivariable logistic regression analysis also revealed that the 2677G --> A/T polymorphism of ABCB1 was significantly associated with obesity. For validation of this association, the 2677G --> A/T polymorphism of ABCB1 was examined in subject panel B and again found to be significantly associated with obesity. Body mass index was significantly (p=0.01) greater for individuals with the variant T allele of this polymorphism than for those with the GG genotype in the combined subject panels A and B. Our results suggest that the ABCB1 genotype may prove informative for assessment of genetic risk for obesity in Japanese individuals.