Lack of association between genetic polymorphisms within DUSP12 - ATF6 locus and glucose metabolism related traits in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Genome-wide linkage studies in multiple ethnic populations found chromosome 1q21-q25 was the strongest and most replicable linkage signal in the human chromosome. Studies in Pima Indian, Caucasians and African Americans identified several SNPs in <it>DUSP12 </it>and <it>ATF6</it>, located in chromosome 1q21-q23, were associated with type 2 diabetes.</p> <p>Methods</p> <p>We selected 19 single nucleotide polymorphisms (SNPs) that could tag 98% of the SNPs with minor allele frequencies over 0.1 within <it>DUSP12-ATF6 </it>region. These SNPs were genotyped in a total of 3,700 Chinese Han subjects comprising 1,892 type 2 diabetes patients and 1,808 controls with normal glucose regulation.</p> <p>Results</p> <p>None of the SNPs and haplotypes showed significant association to type 2 diabetes in our samples. No association between the SNPs and quantitative traits was observed either.</p> <p>Conclusions</p> <p>Our data suggests common SNPs within <it>DUSP12</it>-<it>ATF6 </it>locus may not play a major role in glucose metabolism in the Chinese.</p

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

BACKGROUND: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. METHODS: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. RESULTS: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. CONCLUSIONS: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Variation in CHI3LI in Relation to Type 2 Diabetes and Related Quantitative Traits

CHI3LI encoding the inflammatory glycoprotein YKL-40 is located on chromosome 1q32.1. YKL-40 is involved in inflammatory processes and patients with Type 2 Diabetes (T2D) have elevated circulating YKL-40 levels which correlate with their level of insulin resistance. Interestingly, it has been reported that rs10399931 (-329 G/A) of CHI3LI contributes to the inter-individual plasma YKL-40 levels in patients with sarcoidosis, and that rs4950928 (-131 C/G) is a susceptibility polymorphism for asthma and a decline in lung function. We hypothesized that single nucleotide polymorphisms (SNPs) or haplotypes thereof the CHI3LI locus might influence risk of T2D. The aim of the present study was to investigate the putative association between SNPs and haplotype blocks of CHI3LI and T2D and T2D related quantitative traits.Eleven SNPs of CHI3LI were genotyped in 6514 individuals from the Inter99 cohort and 2924 individuals from the outpatient clinic at Steno Diabetes Center. In cas-control studies a total of 2345 T2D patients and 5302 individuals with a normal glucose tolerance test were examined. We found no association between rs10399931 (OR, 0.98 (CI, 0.88-1.10), p = 0.76), rs4950928 (0.98 (0.87-1.10), p = 0.68) or any of the other SNPs with T2D. Similarly, we found no significant association between any of the 11 tgSNPs and T2D related quantitative traits, all p>0.14. None of the identified haplotype blocks of CHI3LI showed any association with T2D, all p>0.16.None of the examined SNPs or haplotype blocks of CHI3LI showed any association with T2D or T2D related quantitative traits. Estimates of insulin resistance and dysregulated glucose homeostasis in T2D do not seem to be accounted for by the examined variations of CHI3LI

Effects of interacting networks of cardiovascular risk genes on the risk of type 2 diabetes mellitus (the CODAM study)

Background: Genetic dissection of complex diseases requires innovative approaches for identification of disease-predisposing genes. A well-known example of a human complex disease with a strong genetic component is Type 2 Diabetes Mellitus (T2DM). Methods: We genotyped normal-glucose-tolerant subjects (NGT; n = 54), subjects with an impaired glucose metabolism (IGM; n = 111) and T2DM (n = 142) subjects, in an assay (designed by Roche Molecular Systems) for detection of 68 polymorphisms in 36 cardiovascular risk genes. Using the single-locus logistic regression and the so-called haplotype entropy, we explored the possibility that (1) common pathways underlie development of T2DM and cardiovascular disease which would imply enrichment of cardiovascular risk polymorphisms in "pre-diabetic" (IGM) and diabetic (T2DM) populations- and (2) that gene-gene interactions are relevant for the effects of risk polymorphisms. Results: In single-locus analyses, we showed suggestive association with disturbed glucose metabolism (i.e. subjects who were either IGM or had T2DM), or with T2DM only. Moreover, in the haplotype entropy analysis, we identified a total of 14 pairs of polymorphisms (with a false discovery rate of 0.125) that may confer risk of disturbed glucose metabolism, or T2DM only, as members of interacting networks of genes. We substantiated gene-gene interactions by showing that these interacting networks can indeed identify potential "disease-predisposing allele-combinations". Conclusion: Gene-gene interactions of cardiovascular risk polymorphisms can be detected in prediabetes and T2DM, supporting the hypothesis that common pathways may underlie development of T2DM and cardiovascular disease. Thus, a specific set of risk polymorphisms, when simultaneously present, increases the risk of disease and hence is indeed relevant in the transfer of risk

The genetic profile of RF-positive polyarticular juvenile idiopathic arthritis (JIA) resembles adult rheumatoid arthritis (RA)

OBJECTIVE: Juvenile idiopathic arthritis (JIA) is comprised of seven heterogeneous categories of chronic childhood arthritides. About 5% of children with JIA have rheumatoid factor (RF) positive arthritis, which phenotypically resembles adult rheumatoid arthritis (RA). Our objective was to compare and contrast the genetics of RF-positive polyarticular JIA with RA, and selected other JIA categories, to more fully understand the pathophysiological relationships of inflammatory arthropathies. METHODS: RF-positive polyarticular JIA cases (n=340) and controls (n=14,412) were genotyped using the Immunochip array. Single nucleotide polymorphisms (SNPs) were tested for association using a logistic regression model adjusting for admixture proportions. Weighted genetic risk scores (wGRS) of published RA and JIA risk loci were calculated and their ability to predict RF-positive polyarticular JIA were compared. RESULTS: As expected, the HLA region was strongly associated with RF-positive polyarticular JIA (p=5.51x10-31). Nineteen of 44 RA risk loci and 6 of 27 oligoarticular/RF-negative polyarticular JIA risk loci were associated (p70 years. CONCLUSIONS: RF-positive polyarticular JIA is genetically more similar to adult RA than to the most common JIA categories and thus appears to be a childhood-onset presentation of autoantibody positive RA. These findings suggest common disease mechanisms, which could lead to novel therapeutic targets and shared treatment strategies. This article is protected by copyright. All rights reserved

Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia

Fibrotic idiopathic interstitial pneumonias (fIIP) are a group of fatal lung diseases with largely unknown etiology and without definitive treatment other than lung transplant to prolong life. There is strong evidence for the importance of both rare and common genetic risk alleles in familial and sporadic disease. We have previously used genome-wide single nucleotide polymorphism data to identify 10 risk loci for fIIP. Here we extend that work to imputed genome-wide genotypes and conduct new RNA sequencing studies of lung tissue to identify and characterize new fIIP risk loci. Results: We performed genome-wide genotype imputation association analyses in 1616 non-Hispanic white (NHW) cases and 4683 NHW controls followed by validation and replication (878 cases, 2017 controls) genotyping and targeted gene expression in lung tissue. Following meta-analysis of the discovery and replication populations, we identified a novel fIIP locus in the HLA region of chromosome 6 (rs7887 Pmeta = 3.7 × 10-09). Imputation of classic HLA alleles identified two in high linkage disequilibrium that are associated with fIIP (DRB1 15:01 P = 1.3 × 10-7 and DQB1 06:02 P = 6.1 × 10-8). Targeted RNA-sequencing of the HLA locus identified 21 genes differentially expressed between fibrotic and control lung tissue (Q < 0.001), many of which are involved in immune and inflammatory response regulation. In addition, the putative risk alleles, DRB1 15:01 and DQB1 06:02, are associated with expression of the DQB1 gene among fIIP cases (Q < 1 × 10-16)

Genetic architecture distinguishes systemic juvenile idiopathic arthritis from other forms of juvenile idiopathic arthritis: clinical and therapeutic implications

OBJECTIVES: Juvenile idiopathic arthritis (JIA) is a heterogeneous group of conditions unified by the presence of chronic childhood arthritis without an identifiable cause. Systemic JIA (sJIA) is a rare form of JIA characterised by systemic inflammation. sJIA is distinguished from other forms of JIA by unique clinical features and treatment responses that are similar to autoinflammatory diseases. However, approximately half of children with sJIA develop destructive, long-standing arthritis that appears similar to other forms of JIA. Using genomic approaches, we sought to gain novel insights into the pathophysiology of sJIA and its relationship with other forms of JIA. METHODS: We performed a genome-wide association study of 770 children with sJIA collected in nine countries by the International Childhood Arthritis Genetics Consortium. Single nucleotide polymorphisms were tested for association with sJIA. Weighted genetic risk scores were used to compare the genetic architecture of sJIA with other JIA subtypes. RESULTS: The major histocompatibility complex locus and a locus on chromosome 1 each showed association with sJIA exceeding the threshold for genome-wide significance, while 23 other novel loci were suggestive of association with sJIA. Using a combination of genetic and statistical approaches, we found no evidence of shared genetic architecture between sJIA and other common JIA subtypes. CONCLUSIONS: The lack of shared genetic risk factors between sJIA and other JIA subtypes supports the hypothesis that sJIA is a unique disease process and argues for a different classification framework. Research to improve sJIA therapy should target its unique genetics and specific pathophysiological pathways

PPARα L162V underlies variation in serum triglycerides and subcutaneous fat volume in young males

<p>Abstract</p> <p>Background</p> <p>Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50–80% of population variation). Studies defining genetic predispositions have typically focused on older populations with metabolic syndrome and/or type 2 diabetes. We hypothesized that the study of younger populations would mitigate many confounding variables, and allow us to better define genetic predisposition loci for metabolic syndrome.</p> <p>Methods</p> <p>We studied 610 young adult volunteers (average age 24 yrs) for metabolic syndrome markers, and volumetric MRI of upper arm muscle, bone, and fat pre- and post-unilateral resistance training.</p> <p>Results</p> <p>We found the PPARα L162V polymorphism to be a strong determinant of serum triglyceride levels in young White males, where carriers of the V allele showed 78% increase in triglycerides relative to L homozygotes (LL = 116 ± 11 mg/dL, LV = 208 ± 30 mg/dL; p = 0.004). Men with the V allele showed lower HDL (LL = 42 ± 1 mg/dL, LV = 34 ± 2 mg/dL; p = 0.001), but women did not. Subcutaneous fat volume was higher in males carrying the V allele, however, exercise training increased fat volume of the untrained arm in V carriers, while LL genotypes significantly decreased in fat volume (LL = -1,707 ± 21 mm³, LV = 17,617 ± 58 mm³; p = 0.002), indicating a systemic effect of the V allele on adiposity after unilateral training. Our study suggests that the primary effect of PPARα L162V is on serum triglycerides, with downstream effects on adiposity and response to training.</p> <p>Conclusion</p> <p>Our results on association of PPARα and triglycerides in males showed a much larger effect of the V allele than previously reported in older and less healthy populations. Specifically, we showed the V allele to increase triglycerides by 78% (p = 0.004), and this single polymorphism accounted for 3.8% of all variation in serum triglycerides in males (p = 0.0037).</p