Contribution of Genetic Background, Traditional Risk Factors, and HIV-Related Factors to Coronary Artery Disease Events in HIV-Positive Persons

Background Persons infected with human immunodeficiency virus (HIV) have increased rates of coronary artery disease (CAD). The relative contribution of genetic background, HIV-related factors, antiretroviral medications, and traditional risk factors to CAD has not been fully evaluated in the setting of HIV infection. Methods In the general population, 23 common single-nucleotide polymorphisms (SNPs) were shown to be associated with CAD through genome-wide association analysis. Using the Metabochip, we genotyped 1875 HIV-positive, white individuals enrolled in 24 HIV observational studies, including 571 participants with a first CAD event during the 9-year study period and 1304 controls matched on sex and cohort. Results A genetic risk score built from 23 CAD-associated SNPs contributed significantly to CAD (P = 2.9×10−4). In the final multivariable model, participants with an unfavorable genetic background (top genetic score quartile) had a CAD odds ratio (OR) of 1.47 (95% confidence interval [CI], 1.05–2.04). This effect was similar to hypertension (OR = 1.36; 95% CI, 1.06–1.73), hypercholesterolemia (OR = 1.51; 95% CI, 1.16–1.96), diabetes (OR = 1.66; 95% CI, 1.10–2.49), ≥1 year lopinavir exposure (OR = 1.36; 95% CI, 1.06–1.73), and current abacavir treatment (OR = 1.56; 95% CI, 1.17–2.07). The effect of the genetic risk score was additive to the effect of nongenetic CAD risk factors, and did not change after adjustment for family history of CAD. Conclusions In the setting of HIV infection, the effect of an unfavorable genetic background was similar to traditional CAD risk factors and certain adverse antiretroviral exposures. Genetic testing may provide prognostic information complementary to family history of CAD.

Impact of single nucleotide polymorphisms and of clinical risk factors on new-onset diabetes mellitus in HIV-infected individuals

Background. Metabolic complications, including cardiovascular events and diabetes mellitus (DM), are a major long-term concern in human immunodeficienc virus (HIV)-infected individuals. Recent genome-wide association studies have reliably associated multiple single nucleotide polymorphisms (SNPs) to DM in the general population. Methods. We evaluated the contribution of 22 SNPs identifie in genome-wide association studies and of longitudinally measured clinical factors to DM. We genotyped all 94 white participants in the Swiss HIV Cohort Study who developed DM from 1 January 1999 through 31 August 2009 and 550 participants without DM. Analyses were based on 6054 person-years of follow-up and 13,922 measurements of plasma glucose. Results. The contribution to DM risk explained by SNPs (14% of DM variability) was larger than the contribution to DM risk explained by current or cumulative exposure to different antiretroviral therapy combinations (3% of DM variability). Participants with the most unfavorable genetic score (representing 12% and 19% of the study population, respectively, when applying 2 different genetic scores) had incidence rate ratios for DM of 3.80 (95% confidenc interval [CI], 2.05–7.06) and 2.74 (95% CI, 1.53–4.88), respectively, compared with participants with a favorable genetic score. However, addition of genetic data to clinical risk factors that included body mass index only slightly improved DM prediction. Conclusions. In white HIV-infected persons treated with antiretroviral therapy, the DM effect of genetic variants was larger than the potential toxic effects of antiretroviral therapy. SNPs contributed significantl to DM risk, but their addition to a clinical model improved DM prediction only slightly, similar to studies in the general population.

Contribution of 20 single nucleotide polymorphisms of 13 genes to dyslipidemia associated with antiretroviral therapy

BACKGROUND: HIV-1 infected individuals have an increased cardiovascular risk which is partially mediated by dyslipidemia. Single nucleotide polymorphisms in multiple genes involved in lipid transport and metabolism are presumed to modulate the risk of dyslipidemia in response to antiretroviral therapy. METHODS: The contribution to dyslipidemia of 20 selected single nucleotide polymorphisms of 13 genes reported in the literature to be associated with plasma lipid levels (ABCA1, ADRB2, APOA5, APOC3, APOE, CETP, LIPC, LIPG, LPL, MDR1, MTP, SCARB1, and TNF) was assessed by longitudinally modeling more than 4400 plasma lipid determinations in 438 antiretroviral therapy-treated participants during a median period of 4.8 years. An exploratory genetic score was tested that takes into account the cumulative contribution of multiple gene variants to plasma lipids. RESULTS: Variants of ABCA1, APOA5, APOC3, APOE, and CETP contributed to plasma triglyceride levels, particularly in the setting of ritonavir-containing antiretroviral therapy. Variants of APOA5 and CETP contributed to high-density lipoprotein-cholesterol levels. Variants of CETP and LIPG contributed to non-high-density lipoprotein-cholesterol levels, a finding not reported previously. Sustained hypertriglyceridemia and low high-density lipoprotein-cholesterol during the study period was significantly associated with the genetic score. CONCLUSIONS: Single nucleotide polymorphisms of ABCA1, APOA5, APOC3, APOE, and CETP contribute to plasma triglyceride and high-density lipoprotein-cholesterol levels during antiretroviral therapy exposure. Genetic profiling may contribute to the identification of patients at risk for antiretroviral therapy-related dyslipidemia.

Comparative expression profiling of E. coli and S. aureus inoculated primary mammary gland cells sampled from cows with different genetic predispositions for somatic cell score

BACKGROUND: During the past ten years many quantitative trait loci (QTL) affecting mastitis incidence and mastitis related traits like somatic cell score (SCS) were identified in cattle. However, little is known about the molecular architecture of QTL affecting mastitis susceptibility and the underlying physiological mechanisms and genes causing mastitis susceptibility. Here, a genome-wide expression analysis was conducted to analyze molecular mechanisms of mastitis susceptibility that are affected by a specific QTL for SCS on Bos taurus autosome 18 (BTA18). Thereby, some first insights were sought into the genetically determined mechanisms of mammary gland epithelial cells influencing the course of infection. METHODS: Primary bovine mammary gland epithelial cells (pbMEC) were sampled from the udder parenchyma of cows selected for high and low mastitis susceptibility by applying a marker-assisted selection strategy considering QTL and molecular marker information of a confirmed QTL for SCS in the telomeric region of BTA18. The cells were cultured and subsequently inoculated with heat-inactivated mastitis pathogens Escherichia coli and Staphylococcus aureus, respectively. After 1, 6 and 24 h, the cells were harvested and analyzed using the microarray expression chip technology to identify differences in mRNA expression profiles attributed to genetic predisposition, inoculation and cell culture. RESULTS: Comparative analysis of co-expression profiles clearly showed a faster and stronger response after pathogen challenge in pbMEC from less susceptible animals that inherited the favorable QTL allele 'Q' than in pbMEC from more susceptible animals that inherited the unfavorable QTL allele 'q'. Furthermore, the results highlighted RELB as a functional and positional candidate gene and related non-canonical Nf-kappaB signaling as a functional mechanism affected by the QTL. However, in both groups, inoculation resulted in up-regulation of genes associated with the Ingenuity pathways 'dendritic cell maturation' and 'acute phase response signaling', whereas cell culture affected biological processes involved in 'cellular development'. CONCLUSIONS: The results indicate that the complex expression profiling of pathogen challenged pbMEC sampled from cows inheriting alternative QTL alleles is suitable to study genetically determined molecular mechanisms of mastitis susceptibility in mammary epithelial cells in vitro and to highlight the most likely functional pathways and candidate genes underlying the QTL effect.

Refining abacavir hypersensitivity diagnoses using a structured clinical assessment and genetic testing in the Swiss HIV Cohort Study

BACKGROUND: We aimed to assess the value of a structured clinical assessment and genetic testing for refining the diagnosis of abacavir hypersensitivity reactions (ABC-HSRs) in a routine clinical setting. METHODS: We performed a diagnostic reassessment using a structured patient chart review in individuals who had stopped ABC because of suspected HSR. Two HIV physicians blinded to the human leukocyte antigen (HLA) typing results independently classified these individuals on a scale between 3 (ABC-HSR highly likely) and -3 (ABC-HSR highly unlikely). Scoring was based on symptoms, onset of symptoms and comedication use. Patients were classified as clinically likely (mean score > or =2), uncertain (mean score > or = -1 and < or = 1) and unlikely (mean score < or = -2). HLA typing was performed using sequence-based methods. RESULTS: From 131 reassessed individuals, 27 (21%) were classified as likely, 43 (33%) as unlikely and 61 (47%) as uncertain ABC-HSR. Of the 131 individuals with suspected ABC-HSR, 31% were HLA-B*5701-positive compared with 1% of 140 ABC-tolerant controls (P < 0.001). HLA-B*5701 carriage rate was higher in individuals with likely ABC-HSR compared with those with uncertain or unlikely ABC-HSR (78%, 30% and 5%, respectively, P < 0.001). Only six (7%) HLA-B*5701-negative individuals were classified as likely HSR after reassessment. CONCLUSIONS: HLA-B*5701 carriage is highly predictive of clinically diagnosed ABC-HSR. The high proportion of HLA-B*5701-negative individuals with minor symptoms among individuals with suspected HSR indicates overdiagnosis of ABC-HSR in the era preceding genetic screening. A structured clinical assessment and genetic testing could reduce the rate of inappropriate ABC discontinuation and identify individuals at high risk for ABC-HSR.

The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

Novel genetic markers associate with atrial fibrillation risk in Europeans and Japanese

OBJECTIVES This study sought to identify nonredundant atrial fibrillation (AF) genetic susceptibility signals and examine their cumulative relations with AF risk. BACKGROUND AF-associated loci span broad genomic regions that may contain multiple susceptibility signals. Whether multiple signals exist at AF loci has not been systematically explored. METHODS We performed association testing conditioned on the most significant, independently associated genetic markers at 9 established AF loci using 2 complementary techniques in 64,683 individuals of European ancestry (3,869 incident and 3,302 prevalent AF cases). Genetic risk scores were created and tested for association with AF in Europeans and an independent sample of 11,309 individuals of Japanese ancestry (7,916 prevalent AF cases). RESULTS We observed at least 4 distinct AF susceptibility signals on chromosome 4q25 upstream of PITX2, but not at the remaining 8 AF loci. A multilocus score comprised 12 genetic markers demonstrated an estimated 5-fold gradient in AF risk. We observed a similar spectrum of risk associated with these markers in Japanese. Regions containing AF signals on chromosome 4q25 displayed a greater degree of evolutionary conservation than the remainder of the locus, suggesting that they may tag regulatory elements. CONCLUSIONS The chromosome 4q25 AF locus is architecturally complex and harbors at least 4 AF susceptibility signals in individuals of European ancestry. Similar polygenic AF susceptibility exists between Europeans and Japanese. Future work is necessary to identify causal variants, determine mechanisms by which associated loci predispose to AF, and explore whether AF susceptibility signals classify individuals at risk for AF and related morbidity.

Contribution of Genetic Background and Clinical Risk Factors to Low-Trauma Fractures in Human Immunodeficiency Virus (HIV)-Positive Persons: The Swiss HIV Cohort Study.

Background.  The impact of human genetic background on low-trauma fracture (LTF) risk has not been evaluated in the context of human immunodeficiency virus (HIV) and clinical LTF risk factors. Methods.  In the general population, 6 common single-nucleotide polymorphisms (SNPs) associate with LTF through genome-wide association study. Using genome-wide SNP arrays and imputation, we genotyped these SNPs in HIV-positive, white Swiss HIV Cohort Study participants. We included 103 individuals with a first, physician-validated LTF and 206 controls matched on gender, whose duration of observation and whose antiretroviral therapy start dates were similar using incidence density sampling. Analyses of nongenetic LTF risk factors were based on 158 cases and 788 controls. Results.  A genetic risk score built from the 6 LTF-associated SNPs did not associate with LTF risk, in both models including and not including parental hip fracture history. The contribution of clinical LTF risk factors was limited in our dataset. Conclusions.  Genetic LTF markers with a modest effect size in the general population do not improve fracture prediction in persons with HIV, in whom clinical LTF risk factors are prevalent in both cases and controls.