Search

Paraoxonase-1 (PON1) is associated with high-density lipoprotein (HDL) particles and is believed to contribute to antiatherogenic properties of HDLs. We assessed the determinants of PON1 activity variation using different substrates of the enzyme. PON1 activity in serum samples from 922 participants in the San Antonio Family Heart Study was assayed using a reliable microplate format with three substrates: paraoxon, phenyl acetate and the lactone dihydrocoumarin. There were major differences among results from the three substrates in degree of effect by various environmental and genetic factors, suggesting that knowledge of one substrate activity alone may not provide a complete sense of PON1 metabolism. Three significant demographic covariates (age, smoking status and contraceptive usage) together explained 1–6% of phenotypic variance, whereas four metabolic covariates representing lipoprotein metabolism (apoAII, apoAI, triglycerides and non-HDL cholesterol) explained 4–19%. Genes explained 65–92% of phenotypic variance and the dominant genetic effect was exerted by a locus mapping at or near the protein structural locus (PON1) on chromosome 7. Additional genes influencing PON1 activity were localized to chromosomes 3 and 14. Our study identified environmental and genetic determinants of PON1 activity that accounted for 88–97% of total phenotypic variance, suggesting that few, if any, major biological determinants are unrepresented in the models.Heredity (2009) 102, 147–154; doi:10.1038/hdy.2008.110; published online 29 October 2008 [ABSTRACT FROM AUTHOR]

Background: Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology., Methods: Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits., Results: Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD=3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD=2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg=0.550-0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD=3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD=3.425)., Conclusions: This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)

Objective: CD4(+) T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis., Methods: We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore™ software was conducted to characterize known interaction among coded proteins., Results: Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h(2)=0.278, P=4.72×10(-4)). Linkage analyses yielded significant evidence (LOD≥2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10(-2)-1.03×10(-14)). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ρ(G)=0 rejected at FDR≤0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r([ρP],)([ρG])=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins., Conclusions: We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)