Citations

AbstractObjectivesRadiocontrast nephropathy (RCN) is a known complication of procedures in which intravascular iodinated contrast material is used. The authors sought to determine the risk factors for RCN after emergency department (ED) contrast‐enhanced computerized tomography (CECT).MethodsThis was a retrospective case–control study of patients presenting to a tertiary care ED between January 1, 2004, and December 31, 2006. Inclusion criteria were CECT performed in the ED, serum creatinine measured prior to CECT, and serum creatinine measured 48 to 96 hours after CECT. Exclusion criterion was dialysis‐dependent renal failure prior to CECT. The outcome of RCN was defined as an absolute creatinine increase of greater than or equal to 0.5 mg/dL, or a 25% increase above baseline. The charts of all RCN patients and a random sample of non‐RCN patients were reviewed to document the presence or absence of potential risk factors. Univariate analysis was performed using chi‐square and multiple logistic regression applying a weighted technique to account for sampling of non‐RCN patients.ResultsAmong the 5,006 patients meeting inclusion criteria, 349 (7%) developed RCN. Multiple regression analysis demonstrated that serum creatinine > 2 mg/dL, liver disease, heart failure, hematocrit < 30%, hypertension, and diabetes were risk factors for RCN, whereas age > 75 years, vascular disease, and serum creatinine > 1.5 mg/dL were not. The area under the curve (AUC) for the model was 0.65. Although the risk of RCN increased with the number of risk factors present, we could not develop a model with sufficient diagnostic accuracy to guide clinical decision‐making.ConclusionsThe authors report risk factors for RCN in a large case–control study, but could not develop an accurate decision tool to identify patients at increased risk for RCN after ED CECT.

Objective— Matrix gla protein (MGP) inhibits arterial and cartilaginous calcification. A threonine to alanine (Thr83Ala) polymorphism (codon 83) in MGP is associated with myocardial infarction and femoral artery calcification. We examined the association of the MGP Thr83Ala polymorphism with quantity and progression of coronary artery calcification (CAC), a noninvasive measure of subclinical coronary atherosclerosis. Methods and Results— In 605 participants of the Epidemiology of Coronary Artery Calcification Study, generalized linear mixed models were fit to determine the association of MGP Thr83Ala with CAC quantity and progression. There was a significant additive relation between MGP Thr83Ala and CAC progression ( P =0.001). In the fully adjusted model, every 1 Ala83 allele increase was associated with an estimated 1.9% (95% confidence interval, 0.7%–3.0%) per year since baseline larger increase in CAC quantity. A proxy single nucleotide polymorphism for MGP Thr83Ala (rs6488724) was similarly associated with CAC progression in an independent cohort from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Conclusion— Increased risk of myocardial infarction associated with MGP ThrAla83 genotype observed elsewhere may be related to faster progression of subclinical coronary atherosclerosis. MGP genotype could be a potential candidate for identifying individuals at increased risk of atherosclerotic disease who would benefit from aggressive primary prevention strategies.

BackgroundIdentifying antibodies to HLA (anti‐HLA) by solid‐phase assays is used to screen blood donors to mitigate transfusion‐related acute lung injury risk. Various cutoffs for detection assays have been proposed in the literature; however, these do not take into consideration lot‐to‐lot variability of commercially available assays.Study Design and MethodsSamples from 93 nontransfused males were tested using five different lots of a multiplex bead‐based anti‐HLA detection kit. A subset of 17 samples was tested on 5 days using a single lot. An additional 96 samples from donations with varied anti‐HLA levels were tested using kits from two different lots. Results were reported as a normalized background (NBG) ratio.ResultsFor the 93 nontransfused donors, NBG values generated using the reference lot were significantly higher than those obtained with three of the four comparator lots. However, for the 96 samples with low‐, moderate‐, and higher‐level anti‐HLA, Class I (CL‐I) values were 1.4 times lower and Class II (CL‐II) values were 1.2 times lower using the reference versus comparator lot. For CL‐I antibodies the between‐lot standard deviation (SD) was 1.36 (95% confidence interval [CI], 1.19‐1.60), while the between‐day SD was 1.27 (95% CI, 1.08‐1.52). Similarly, for CL‐II antibodies the between‐lot SD was 0.81 (95% CI, 0.70‐0.95), while the between‐day SD was 0.50 (95% CI, 0.43‐0.60).ConclusionsThere is interlot variability in the tested HLA detection assay as well as significant bias between lots. It may be reasonable to develop a new cutoff when a new lot is obtained.

Genetic variations in metabolism of endocannabinoids and in CNR1 (gene for cannabinoid 1 receptor) are associated with symptom phenotype, colonic transit, and left colon motility in irritable bowel syndrome (IBS). Our aim was to evaluate associations between two variations in CNR1 genotype (rs806378 and [AAT]n triplets) with symptom phenotype, small bowel and colonic transit, and rectal sensations in 455 patients with IBS and 228 healthy controls. Small bowel and colonic transit were measured by scintigraphy, rectal sensation by isobaric distensions. Associations with genotype were assessed by χ2test (symptom phenotype) and ANCOVA (quantitative traits) based on a dominant genetic model. Significant association of CNR1 rs806378 (but not CNR1 [AAT]n) genotype and symptom phenotype was observed (χ2P = 0.028). There was significant association of CNR1 rs806378 ( P = 0.014; CC vs. CT/TT) with colonic transit in IBS-diarrhea (IBS-D) group; the TT group had the fastest colonic transit at 24 and 48 h. There was significant overall association of CNR1 rs806378 with sensation rating of gas ( P = 0.025), but not pain; the strongest associations for gas ratings were in IBS-D ( P = 0.002) and IBS-alternating ( P = 0.025) subgroups. For CNR1 (AAT)n, gene-by-phenotype interactions were observed for colonic transit at 24 ( P = 0.06) and 48 h ( P = 0.002) and gas ( P = 0.046, highest for IBS-D, P = 0.034), but not pain sensation; the strongest association with transit was in controls, not in IBS. These data support the hypothesis that cannabinoid receptors may play a role in control of colonic transit and sensation in humans and deserve further study as potential mediators or therapeutic targets in lower functional gastrointestinal disorders.

Abstract Background: Our genome-wide association study (GWAS) of chronic lymphocytic leukemia (CLL) identified 4 highly correlated intronic variants within the IRF8 gene that were associated with CLL. These results were further supported by a recent meta-analysis of our GWAS with two other GWAS of CLL, supporting the IRF8 gene as a strong candidate for CLL risk. Methods: To refine the genetic association of CLL risk, we conducted Sanger sequencing of IRF8 in 94 CLL cases and 96 controls. We then conducted fine mapping by genotyping 39 variants (of which 10 were identified from sequencing) in 745 CLL cases and 1,521 controls. We also assessed these associations with risk of other non-Hodgkin lymphoma (NHL) subtypes. Results: The strongest association with CLL risk was observed with a common single-nucleotide polymorphism (SNP) located within the 3′ untranslated region (UTR) of IRF8 (rs1044873, log additive OR = 0.7, P = 1.81 × 10−6). This SNP was not associated with the other NHL subtypes (all P &gt; 0.05). Conclusions: We provide evidence that rs1044873 in the IRF8 gene accounts for the initial GWAS signal for CLL risk. This association appears to be unique to CLL with little support for association with other common NHL subtypes. Future work is needed to assess functional role of IRF8 in CLL etiology. Impact: These data provide support that a functional variant within the 3′UTR of IRF8 may be driving the GWAS signal seen on 16q24.1 for CLL risk. Cancer Epidemiol Biomarkers Prev; 22(3); 461–6. ©2013 AACR.