Background: Preterm birth (PTB) is a complex disorder associated with significant neonatal mortality and morbidity and long-term adverse health consequences. Multiple lines of evidence suggest that genetic factors play an important role in its etiology. This study was designed to identify genetic variation associated with PTB in oxytocin pathway genes whose role in parturition is well known. Methods: To identify common genetic variants predisposing to PTB, we genotyped 16 single nucleotide polymorphisms (SNPs) in the oxytocin (OXT), oxytocin receptor (OXTR), and leucyl/cystinyl aminopeptidase (LNPEP) genes in 651 case infants from the U.S. and one or both of their parents. In addition, we examined the role of rare genetic variation in susceptibility to PTB by conducting direct sequence analysis of OXTR in 1394 cases and 1112 controls from the U.S., Argentina, Denmark, and Finland. This study was further extended to maternal triads (maternal grandparents-mother of a case infant, N=309). We also performed in vitro analysis of selected rare OXTR missense variants to evaluate their functional importance. Results: Maternal genetic effect analysis of the SNP genotype data revealed four SNPs in LNPEP that show significant association with prematurity. In our case–control sequence analysis, we detected fourteen coding variants in exon 3 of OXTR, all but four of which were found in cases only. Of the fourteen variants, three were previously unreported novel rare variants. When the sequence data from the maternal triads were analyzed using the transmission disequilibrium test, two common missense SNPs (rs4686302 and rs237902) in OXTR showed suggestive association for three gestational age subgroups. In vitro functional assays showed a significant difference in ligand binding between wild-type and two mutant receptors. Conclusions: Our study suggests an association between maternal common polymorphisms in LNPEP and susceptibility to PTB. Maternal OXTR missense SNPs rs4686302 and rs237902 may have gestational age-dependent effects on prematurity. Most of the OXTR rare variants identified do not appear to significantly contribute to the risk of PTB, but those shown to affect receptor function in our in vitro study warrant further investigation. Future studies with larger sample sizes are needed to confirm the findings of this study.
14 March 2012 in American Journal of Medical Genetics Part A
DNASE1L3, an enzyme highly expressed in DCs, is functionally important for regulating autoimmune responses to self-DNA and chromatin. Deficiency of DNASE1L3 leads to development of autoimmune diseases in both humans and mice. However, despite the well-established causal relationship between DNASE1L3 and immunity, little is known about the involvement of DNASE1L3 in regulation of antitumor immunity, the foundation of modern antitumor immunotherapy. In this study, we identify DNASE1L3 as a potentially new regulator of antitumor immunity and a tumor suppressor in colon cancer. In humans, DNASE1L3 is downregulated in tumor-infiltrating DCs, and this downregulation is associated with poor patient prognosis and reduced tumor immune cell infiltration in many cancer types. In mice, Dnase1l3 deficiency in the tumor microenvironment enhances tumor formation and growth in several colon cancer models. Notably, the increased tumor formation and growth in Dnase1l3 -deficient mice are associated with impaired antitumor immunity, as evidenced by a substantial reduction of cytotoxic T cells and a unique subset of DCs. Consistently, Dnase1l3 -deficient DCs directly modulate cytotoxic T cells in vitro. To our knowledge, our study unveils a previously unknown link between DNASE1L3 and antitumor immunity and further suggests that restoration of DNASE1L3 activity may represent a potential therapeutic approach for anticancer therapy.
BACKGROUND: HMG-CoA reductase inhibitors (statins) are prescribed to millions of people. Statins are antiinflammatory independent of their cholesterol-reducing effects. To date, most reports on the immune effects of statins have assayed a narrow array of variables and have focused on cell lines, rodent models, or patient cohorts. We sought to define the effect of rosuvastatin on the “immunome” of healthy, normocholesterolemic subjects. METHODS: We conducted a prospective study of rosuvastatin (20 mg/d × 28 days) in 18 statin-naive adults with LDL cholesterol 180 immune/biochemical/endocrinologic variables was measured at baseline and on days 14, 28, and 42 (14 days after drug withdrawal). Drug effect was evaluated using linear mixed-effects models. Potential interactions between drug and baseline high-sensitivity C-reactive protein (hsCRP) were evaluated. RESULTS: A wide array of immune measures changed (nominal P < 0.05) during rosuvastatin treatment, although the changes were modest in magnitude, and few met an FDR of 0.05. Among changes noted were a concordant increase in proinflammatory cytokines (IFN-γ, IL-1β, IL-5, IL-6, and TNF-α) and peripheral blood neutrophil frequency, and a decline in activated Treg frequency. Several drug effects were significantly modified by baseline hsCRP, and some did not resolve after drug withdrawal. Among other unexpected rosuvastatin effects were changes in erythrocyte indices, glucose-regulatory hormones, CD8 + T cells, and haptoglobin. CONCLUSION: Rosuvastatin induces modest changes in immunologic and metabolic measures in normocholesterolemic subjects, with several effects dependent on baseline CRP. Future, larger studies are warranted to validate these changes and their physiological significance. TRIAL REGISTRATION: ClinicalTrials.gov NCT01200836. FUNDING: This research was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01 ES102005), and the trans-NIH Center for Human Immunology.
Cleft palate only is a common birth defect with high heritability. Only a small fraction of this heritability is explained by the genetic variants identified so far, underscoring the need to investigate other disease mechanisms, such as gene-environment (GxE) interactions and parent-of-origin (PoO) effects. Furthermore, PoO effects may vary across exposure levels (PoOxE effects). Such variation is the focus of this study. We upgraded the R-package Haplin to enable direct tests of PoOxE effects at the genome-wide level. From a previous GWAS, we had genotypes for 550 case-parent trios, of mainly European and Asian ancestry, and data on three maternal exposures (smoking, alcohol, and vitamins). Data were analyzed for Europeans and Asians separately, and also for all ethnicities combined. To account for multiple testing, a false discovery rate method was used, where q-values were generated from the p-values. In the Europeans-only analyses, interactions with maternal smoking yielded the lowest q-values. Two SNPs in the ‘Interactor of little elongation complex ELL subunit 1’ (ICE1) gene had a q-value of 0.14, and five of the 20 most significant SNPs were in the ‘N-acetylated alpha-linked acidic dipeptidase-like 2’ (NAALADL2) gene. No evidence of PoOxE effects was found in the other analyses. The connections to ICE1 and NAALADL2 are novel and warrant further investigation. More generally, the new methodology presented here is easily applicable to other traits and exposures in which a family-based study design has been implemented.
To evaluate statistical methods for genome-wide genetic analyses, one needs to be able to simulate realistic genotypes. We here describe a method, applicable to a broad range of association study designs, that can simulate autosome-wide single-nucleotide polymorphism data with realistic linkage disequilibrium and with spiked in, user-specified, single or multi-SNP causal effects. Our construction uses existing genome-wide association data from unrelated case-parent triads, augmented by including a hypothetical complement triad for each triad (same parents but with a hypothetical offspring who carries the non-transmitted parental alleles). We assign offspring qualitative or quantitative traits probabilistically through a specified risk model and show that our approach destroys the risk signals from the original data. Our method can simulate genetically homogeneous or stratified populations and can simulate case-parents studies, case-control studies, case-only studies, or studies of quantitative traits. We show that allele frequencies and linkage disequilibrium structure in the original genome-wide association sample are preserved in the simulated data. We have implemented our method in an R package (TriadSim) which is freely available at the comprehensive R archive network. We have proposed a method for simulating genome-wide SNP data with realistic linkage disequilibrium. Our method will be useful for developing statistical methods for studying genetic associations, including higher order effects like epistasis and gene by environment interactions.