Jinko Graham

IA-2 autoantibodies in incident type I diabetes patients are associated with a polyadenylation signal polymorphism in GIMAP5

In a large case-control study of Swedish incident type I diabetes patients and controls, 0–34 years of age, we tested the hypothesis that the GIMAP5 gene, a key genetic factor for lymphopenia in spontaneous BioBreeding rat diabetes, is associated with type I diabetes; with islet autoantibodies in incident type I diabetes patients or with age at clinical onset in incident type I diabetes patients. Initial scans of allelic association were followed by more detailed logistic regression modeling that adjusted for known type I diabetes risk factors and potential confounding variables. The single nucleotide polymorphism (SNP) rs6598, located in a polyadenylation signal of GIMAP5, was associated with the presence of significant levels of IA-2 autoantibodies in the type I diabetes patients. Patients with the minor allele A of rs6598 had an increased prevalence of IA-2 autoantibody levels compared to patients without the minor allele (OR=2.2; Bonferroni-corrected P=0.003), after adjusting for age at clinical onset (P=8.0 × 10−13) and the numbers of HLA-DQ A1*0501-B1*0201 haplotypes (P=2.4 × 10−5) and DQ A1*0301-B1*0302 haplotypes (P=0.002). GIMAP5 polymorphism was not associated with type I diabetes or with GAD65 or insulin autoantibodies, ICA, or age at clinical onset in patients. These data suggest that the GIMAP5 gene is associated with islet autoimmunity in type I diabetes and add to recent findings implicating the same SNP in another autoimmune disease.

A Note on Inference of Trait Associations with SNP Haplotypes and Other Attributes in Generalized Linear Models

Recently, Lake et al. [Human Heredity 2003;55:56–65] have proposed an approach based on the EM algorithm for maximum-likelihood inference of trait associations with haplotypes and environmental cofactors in generalized linear models. In this short report, we describe an extension to accommodate missing SNP genotype information. We also discuss differences in the calculation of standard errors between their implementation and our own. Finally, we present results indicating that inference is robust to low levels of dependence between haplotypes and nongenetic factors, but that biased inference can result when there is moderate to strong dependence. Overall, the method is found to perform well in the models we considered.

Cell culture-induced aberrant methylation of the imprinted IG DMR in human lymphoblastoid cell lines

DNA methylation patterns are often poorly conserved through cell culturing. To determine the effect of cell immortalization and culture on DNA methylation profiles, we analyzed methylation in the differentially methylated regions (DMR) of five imprinted domains: the intergenic (IG) DMR on chromosome 14q32; potassium voltage-gated channel, KQT-like subfamily, member 1, (KCNQ1); small nuclear ribonucleoprotein polypeptide N (SNRPN), mesoderm specific transcript homolog (MEST); and H19 in lymphoblastoid cell lines (LCLs). In the IG DMR we found an aberrant methylation pattern that was consistent through all the cell lines tested, and significantly different from that of noncultured peripheral blood cells. Using a generalized linear mixed model to compare methylation profiles, we show that recently derived LCLs significantly differ from the CEPH LCLs. This implies a gradual cell-culture related deterioration of DNA methylation in the IG DMR with at least two steps that may be identified: loss of methylation at CG sites 1 and 8; and loss of allelic differences in DNA methylation. The IG DMR methylation profile also confirms the high level of clonality of the CEPH LCLs. We conclude that non-transformed primary cells may be less susceptible to epigenetic anomalies and therefore may provide a more accurate reflection of gene expression in vivo.

The length of the CTLA-4 microsatellite (AT)N-repeat affects the risk for type 1 diabetes. Diabetes Incidence in Sweden Study Group.

CTLA-4 is important to down-regulating T cell responses and has been implicated in type 1 (insulin dependent) diabetes mellitus in both linkage and association studies. The aim of our study was to relate the polymorphic (AT)n microsatellite in the 3′ untranslated sequence of the CTLA-4 gene to diabetes risk. We studied 616 consecutively diagnosed 0-34 year-old Swedish patients and 502 matched controls by PCR-based genotyping to determine the length of the 3′-end (AT)n repeat region of the CTLA-4 gene and categorizing alleles as predominantly monomorphic short (S) or highly polymorphic (in length) long (L) alleles. The odds of type 1 diabetes of subjects with the L/L genotype was estimated to be 1.84 times that of subjects with the S/S genotype (95% CI 1.44-2.73, p=0.002). Further analysis of the long alleles, partitioned into intermediate (I) length and very long (VL) alleles, suggested that L alleles act recessively in conferring diabetes risk (p=0.0009). This study suggests that the 3′-end (AT)n repeat region of the CTLA-4 gene represents a recessive risk factor for type 1 diabetes

A discovery study of daunorubicin induced cardiotoxicity in a sample of acute myeloid leukemia patients prioritizes P450 oxidoreductase polymorphisms as a potential risk factor

Anthracyclines are very effective chemotherapeutic agents; however, their use is hampered by the treatment-induced cardiotoxicity. Genetic variants that help define patients sensitivity to anthracyclines will greatly improve the design of optimal chemotherapeutic regimens. However, identification of such variants is hampered by the lack of analytical approaches that address the complex, multi-genic character of anthracycline induced cardiotoxicity (AIC). Here, using a multi-SNP based approach, we examined 60 genes coding for proteins involved in drug metabolism and efflux and identified the P450 oxidoreductase (POR) gene to be most strongly associated with daunorubicin induced cardiotoxicity in a population of acute myeloid leukemia (AML) patients (FDR adjusted p-value of 0.15). In this sample of cancer patients, variation in the POR gene is estimated to account for some 11.6% of the variability in the drop of left ventricular ejection fraction (LVEF) after daunorubicin treatment, compared to the estimated 13.2% accounted for by the cumulative dose and ethnicity. In post-hoc analysis, this association was driven by 3 SNPs—the rs2868177, rs13240755, and rs4732513—through their linear interaction with cumulative daunorubicin dose. The unadjusted odds ratios (ORs) and confidence intervals (CIs) for rs2868177 and rs13240755 were estimated to be 1.89 (95% CI: 0.7435–4.819; p = 0.1756) and 3.18 (95% CI: 1.223–8.27; p = 0.01376), respectively. Although the contribution of POR variants is expected to be overestimated due to the multiple testing performed in this small pilot study, given that cumulative anthracycline dose is virtually the only factor used clinically to predict the risk of cardiotoxicity, the contribution that genetic analyses of POR can make to the assessment of this risk is worthy of follow up in future investigations.

Genetic variation in cell death genes and risk of non-Hodgkin lymphoma.

Background Non-Hodgkin lymphomas are a heterogeneous group of solid tumours that constitute the 5th highest cause of cancer mortality in the United States and Canada. Poor control of cell death in lymphocytes can lead to autoimmune disease or cancer, making genes involved in programmed cell death of lymphocytes logical candidate genes for lymphoma susceptibility. Materials and Methods We tested for genetic association with NHL and NHL subtypes, of SNPs in lymphocyte cell death genes using an established population-based study. 17 candidate genes were chosen based on biological function, with 123 SNPs tested. These included tagSNPs from HapMap and novel SNPs discovered by re-sequencing 47 cases in genes for which SNP representation was judged to be low. The main analysis, which estimated odds ratios by fitting data to an additive logistic regression model, used European ancestry samples that passed quality control measures (569 cases and 547 controls). A two-tiered approach for multiple testing correction was used: correction for number of tests within each gene by permutation-based methodology, followed by correction for the number of genes tested using the false discovery rate. Results Variant rs928883, near miR-155, showed an association (OR per A-allele: 2.80 [95% CI: 1.63–4.82]; pF = 0.027) with marginal zone lymphoma that is significant after correction for multiple testing. Conclusions This is the first reported association between a germline polymorphism at a miRNA locus and lymphoma.

Stepwise detection of recombination breakpoints in sequence alignments

MOTIVATION We propose a stepwise approach to identify recombination breakpoints in a sequence alignment. The approach can be applied to any recombination detection method that uses a permutation test and provides estimates of breakpoints. RESULTS We illustrate the approach by analyses of a simulated dataset and alignments of real data from HIV-1 and human chromosome 7. The presented simulation results compare the statistical properties of one-step and two-step procedures. More breakpoints are found with a two-step procedure than with a single application of a given method, particularly for higher recombination rates. At higher recombination rates, the additional breakpoints were located at the cost of only a slight increase in the number of falsely declared breakpoints. However, a large proportion of breakpoints still go undetected. AVAILABILITY A makefile and C source code for phylogenetic profiling and the maximum chi2 method, tested with the gcc compiler on Linux and WindowsXP, are available at http://stat-db.stat.sfu.ca/stepwise/ CONTACT jgraham@stat.sfu.ca.

Single nucleotide polymorphisms in aldo-keto and carbonyl reductase genes are not associated with acute cardiotoxicity after daunorubicin chemotherapy.

Background: Evidence suggests that interpatient variability in anthracycline metabolic rate may contribute to the cardiotoxicity associated with anthracycline-based chemotherapy. Therefore, polymorphisms in the anthracycline metabolizing enzymes have been proposed as potential biomarkers of anthracycline-induced cardiotoxicity (AIC). Methods: We have previously shown that 13 of the naturally occurring nonsynonymous single-nucleotide polymorphisms (nsSNP) in the aldo–keto reductases (AKR) and carbonyl reductases (CBR) reduce anthracycline metabolic rate in vitro. Here, we test these SNPs individually and jointly for association with daunorubicin-induced cardiotoxicity in patients with acute myeloid leukemia (AML). Results: Five of the 13 nsSNPs exhibiting an in vitro effect on anthracycline metabolism were detected among the 185 patients with AML. No association was found between the SNPs and daunorubicin-induced cardiotoxicity in either individual or joint effect analyses. Conclusions: Despite the shown in vitro effect of nsSNPs in reductase genes on anthracycline metabolic rate, on their own these SNPs do not explain enough variability in cardiotoxicity to be useful markers of this adverse event. Impact: The results of this study provide important information for biomarker studies on side effects of anthracycline chemotherapy. Cancer Epidemiol Biomarkers Prev; 21(11); 2118–20. ©2012 AACR.

Age-dependent variation of genotypes in MHC II transactivator gene (CIITA) in controls and association to type 1 diabetes.

The major histocompatibility complex class II transactivator (CIITA) gene (16p13) has been reported to associate with susceptibility to multiple sclerosis, rheumatoid arthritis and myocardial infarction, recently also to celiac disease at genome-wide level. However, attempts to replicate association have been inconclusive. Previously, we have observed linkage to the CIITA region in Scandinavian type 1 diabetes (T1D) families. Here we analyze five Swedish T1D cohorts and a combined control material from previous studies of CIITA. We investigate how the genotype distribution within the CIITA gene varies depending on age, and the association to T1D. Unexpectedly, we find a significant difference in the genotype distribution for markers in CIITA (rs11074932, P=4 × 10−5 and rs3087456, P=0.05) with respect to age, in the collected control material. This observation is replicated in an independent cohort material of about 2000 individuals (P=0.006, P=0.007). We also detect association to T1D for both markers, rs11074932 (P=0.004) and rs3087456 (P=0.001), after adjusting for age at sampling. The association remains independent of the adjacent T1D risk gene CLEC16A. Our results indicate an age-dependent variation in CIITA allele frequencies, a finding of relevance for the contrasting outcomes of previously published association studies.

A comparison of five methods for selecting tagging single-nucleotide polymorphisms

Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai). In two disease-associated regions from the Genetic Analysis Workshop 14 simulated data, we tested the association between tagSNP genotype and disease over the tagSNP sets chosen by each method for each sampling scheme. This was repeated for 100 replicates to estimate power. The two allelic methods chose essentially all SNPs in the region and had nearly optimal power. The two haplotypic methods chose about half as many SNPs. The haplotypic methods had poor performance compared to the allelic methods in both regions. We expected an improvement in power when the selection sample contained cases; however, there was only moderate variation in power between the sampling approaches for each method. Finally, when compared to the haplotypic methods, the reference method performed as well or worse in the region with ancestral disease haplotype structure.