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Browsing by Subject "gene-environment interaction"
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Item Cis‐acting allele specific expression (ASE) differences induced by alcohol and impacted by sex as well as parental genotype of origin(Wiley, 2018) Lo, Chiao-Ling; Lumeng, Lawrence; Bell, Richard L.; Liang, Tiebing; Lossie, Amy C.; Muir, Williams M.; Zhou, Feng C.; Anatomy and Cell Biology, School of MedicineBackground Alcohol use disorders (AUDs) are influenced by complex interactions between the genetics of the individual and their environment. We have previously identified hundreds of polygenic genetic variants between the selectively bred high and low alcohol drinking (HAD and LAD) rat lines. Here we report allele specific expression (ASE) differences, between the HAD2 and LAD2 rat lines. Methods The HAD2 and LAD2 rats which have been sequenced were reciprocally crossed to generate 10 litters of F1 progeny. For 5 of these litters, the sire was HAD2; and, for the other 5 litters, the sire was a LAD2. From these 10 litters, two males and two females were picked from each F1 litter (N = 40 total). The F1‐pups were divided, with balancing for sex and direction of cross, into an alcohol (15%) vs a water control group. Alcohol‐drinking started in the middle of adolescence (~PND 35) and lasted 9 weeks. At the end of these treatments, rats were euthanized, the nucleus accumbens was dissected, and RNA was processed for RNA‐sequencing and ASE analyses. Results Analyses revealed that adolescent ethanol drinking, individual ethanol drinking levels, parentage, and sex‐of‐animal affected ASEs of about 300 genes. The identified genes included those associated with ethanol metabolism (e.g., Aldh2); neuromodulatory function [e.g., Cckbr, Slc6a7, and Slc1a1]; ion channel activity (e.g., Kcnc3); as well as other synaptic and epigenetic function. Conclusion These data indicate that ethanol drinking differentially amplified paternal vs maternal allelic contribution to the transcriptome. We hypothesize that this was due, at least in part, to ethanol‐induced changes in cis‐regulation of polymorphisms previously identified between the HAD2 and LAD2 rat lines. This report highlights the complexity of gene‐by‐environment interactions mediating a genetic predisposition for, and/or the active development of, alcohol use disorders.Item An Investigation of Modifying Effects of Single Nucleotide Polymorphisms in Metabolism-related Genes on the Relationship between Peripheral Nerve Function and Mercury Levels in Urine and Hair(2012-02) Wang, Yi; Goodrich, Jaclyn M.; Werner, Robert; Gillespie, Brenda; Basu, Niladri; Franzblau, AlfredMercury (Hg) is a potent neurotoxicant. We hypothesized that single nucleotide polymorphisms (SNPs) in genes coding glutathione-related proteins, selenoproteins and metallothioneins may modify the relationship of mercury biomarkers with changes in peripheral nerve function. Dental professionals (n=515) were recruited in 2009 and 2010. Sensory nerve function (onset latency, peak latency and amplitude) of the median, ulnar and sural nerves was recorded. Samples of urine, hair and DNA were collected. Covariates related to demographics, nerve function and elemental and methyl-mercury exposure were also collected. Subjects included 244 dentists (47.4%) and 269 non-dentists (52.2%; mostly dental hygienists and dental assistants). The mean mercury levels in urine (1.06 μg/L) and hair (0.51 μg/g) were not significantly different from the US general population (0.95 μg/L and 0.47 μg/g, respectively). In multivariate linear models predicting nerve function adjusting for covariates, only 3 out of a total of 504 models showed stable and statistically significant interaction of SNPs with mercury biomarkers. Overall, given the possibility of false positives, the results suggested little evidence of effect modification of the SNPs on the relationship between mercury biomarkers with peripheral nerve function at exposure levels that are relevant to the general US population.Item Robust tests for gene–environment interaction in case-control and case-only designs(Elsevier, 2019-01) Zang, Yong; Fung, Wing Kam; Cao, Sha; Ng, Hon Keung Tony; Zhang, Chi; Biostatistics, School of Public HealthThe case-control and case-only designs are commonly used to detect the gene–environment (G–E) interaction. In principle, the tests based on these two designs require a pre-specified genetic model to achieve an expected power of detecting the G–E interaction. Unfortunately, for most complex diseases the underlying genetic models are unknown. It is well known that mis-specification of the genetic model can result in a substantial loss of power in the detection of the main genetic effect. However, limited effort has been dedicated to the study of G–E interaction. This issue has been investigated in this article with a conclusion that the genetic model mis-specification can not only undermine the power of detecting G–E interaction in both case-control and case-only designs but also distort the type I error rate in case-control design. To tackle this problem, a class of robust tests, namely MAX3, have been proposed for both the case-control and case-only designs. The proposed tests can well control the type I error rate and yield satisfactory power even when the genetic model is mis-specified. The asymptotic distribution and the