Biomedical subjects

Jinko Graham

Publications and source records attributed to Jinko Graham.

5 recordsLinked to original sources

PubMed2006

MHC class I chain-related gene-A is associated with IA2 and IAA but not GAD in Swedish type 1 diabetes mellitus.

In type 1 diabetes mellitus (T1DM), the frequency of antibodies against insulin (IAA), glutamic acid decarboxylase-65 (GAD65), ICA512/IA2 (IA2), and islet cell antigens (ICA) vary with human leukocyte antigen (HLA) composition of the patient. IAA, IA2 autoantibodies, and ICA are increased in DQ8 positives; GAD65 antibodies are increased in DQ2 positives. MHC class I chain-related gene-A (MICA) is another genetic marker that has been proposed to be associated with T1DM. In this article, we looked at microsatellite polymorphism of MICA and its association with autoantibodies (IAA, IA2, and GAD65) in Swedish T1DM patients and if the association explains its importance in early events in autoimmune response. We studied 635 T1DM patients between 0-35 years. Frequency of MICA5/5 was positively associated with the formation of IAA and IA2 antibodies considered individually or in combination (odds ratio [OR], 95% CI, Pc: [IAA+ versus IAA-]: 4.94, 2.09-11.62, <0.0005; [IA2+ versus IA2-]: 2.65, 1.52-4.59, 0.0015; [IAA and/or IA2+ versus rest]: 9.83, 2.37-40.78, <0.0015; [IAA and IA2+ versus rest]: 3.51, 2.01-6.15, <0.0015). Also, -5.1/5.1 was increased in IAA+ patients compared to IAA- patients (2.82, 1.64-4.83, <0.0005). All patients positive for -5/5 developed at least one of the three antibodies. Frequency of MICA5.1 was decreased in IAA+ (0.54, 0.36-0.81, 0.017), in IA2A+ (0.63, 0.45-0.88, 0.04), in IAA and/or IA2A+ (0.52, 0.33-0.84, 0.044), and in IAA and IA2A+ (0.55, 0.39-0.78, 0.0055) patients when compared with patients negative for corresponding antibodies. Frequency of MICA9, 5/5.1, and 5.1/9 was decreased in IAA+ compared to IAA- patients (0.51, 0.32-0.79, 0.021; 0.22, 0.11-0.44, <0.005; and 0.39, 0.22-0.69, 0.026, respectively). Frequency of MICA9 and -5.1/9 was also decreased in IAA and/or IA2 antibody-positive patients while MICA5/5.1 decreased in patients positive for IAA and IA2 antibody both together. IAA and IA2 antibodies are believed to appear early during the autoimmune reaction against beta cells. Thus, according to our data, MICA-5/5 and -5.1/5.1 is associated with early autoimmunity in T1DM patients. Our study suggests that MICA gene polymorphism is associated with autoantibody formation and that the polymorphism especially MICA5/5 and -5.1/5.1 are important in early events of autoimmune reaction.

Adolescent↗

PubMed2005

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.

Genetic Techniques↗

PubMed2004

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.

Algorithms↗

PubMed2004

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.

Algorithms↗

PubMed2002

Genetic effects on age-dependent onset and islet cell autoantibody markers in type 1 diabetes.

Age-dependent associations between type 1 diabetes risk genes HLA, INS VNTR, and CTLA-4 and autoantibodies to GAD65 (GADAs), ICA512/IA-2, insulin, and islet cells were determined by logistic regression analysis in 971 incident patients with type 1 diabetes and 702 control subjects aged 0-34 years. GADAs were associated with HLA-DQ2 in young but not in older patients (P = 0.009). Autoantibodies to insulin were negatively associated with age (P < 0.0001) but positively associated with DQ8 (P = 0.03) and with INS VNTR (P = 0.04), supporting possible immune tolerance induction. ICA512/IA-2 were negatively associated with age (P < 0.0001) and with DQ2 (P < 0.0001) but positively associated with DQ8 (P = 0.04). Males were more likely than females to be negative for GADA (P < 0.0001), autoantibodies to islet cells (P = 0.04), and all four autoantibody markers (P = 0.004). The CTLA-4 3' end microsatellite marker was not associated with any of the autoantibodies. We conclude that age and genetic factors such as HLA-DQ and INS VNTR need to be combined with islet autoantibody markers when evaluating the risk for type 1 diabetes development.

Adolescent↗