ADME pharmacogenetics: investigation of the pharmacokinetics of the antiretroviral agent lopinavir coformulated with ritonavir.

BACKGROUND: An ADME (absorption, distribution, metabolism and excretion)-pharmacogenetics association study may identify functional variants relevant to the pharmacokinetics of lopinavir co-formulated with ritonavir (LPV/r), a first-line anti-HIV agent. METHODS: An extensive search of literature and web resources helped select ADME genes and single nucleotide polymorphisms (SNPs, functional and HapMap tagging SNPs) with a proven or potentially relevant role in LPV/r pharmacokinetics. The study followed a two-stage design. Stage 1 (discovery) considered a Caucasian population (n=638) receiving LPV/r, where we selected 117 individuals with low LPV clearance (cases) and 90 individuals with high clearance (controls). Genotyping was performed by a 1536-SNP customized GoldenGate Illumina BeadArray. Stage 2 (confirmation) represented a replication study of candidate SNPs from the stage 1 in 148 individuals receiving LPV/r. The analysis led to formal population pharmacokinetic-pharmacogenetic modeling of demographic, environmental and candidate SNP effects. RESULTS: One thousand three hundred and eighty SNPs were successfully genotyped. Nine SNPs prioritized by the stage 1 analysis were brought to replication. Stage 2 confirmed the contribution of two functional SNPs in SLCO1B1, one functional SNP in ABCC2 and a tag SNP of the CYP3A locus in addition to body weight effect and ritonavir coadministration. According to the population pharmacokinetic-pharmacogenetic model, genetic variants explained 5% of LPV variability. Individuals homozygous rs11045819 (SLCO1B1*4) had a clearance of 12.6 l/h, compared with 5.4 l/h in the reference group, and 3.9 l/h in individuals with two or more variant alleles of rs4149056 (SLCO1B1*5), rs717620 (ABCC2) or rs6945984 (CYP3A). A subanalysis confirmed that although a significant part of the variance in LPV clearance was attributed to fluctuation in ritonavir levels, genetic variants had an additional effect on LPV clearance. CONCLUSION: The two-stage strategy successfully identified genetic variants affecting LPV/r pharmacokinetics. Such a general approach of ADME pharmacogenetics should be generalized to other drugs.

APOBEC3G genetic variants and their influence on the progression to AIDS.

The cytosine deaminase APOBEC3G, in the absence of the human immunodeficiency virus type 1 (HIV-1) accessory gene HIV-1 viral infectivity factor (vif), inhibits viral replication by introducing G-->A hypermutation in the newly synthesized HIV-1 DNA negative strand. We tested the hypothesis that genetic variants of APOBEC3G may modify HIV-1 transmission and disease progression. Single nucleotide polymorphisms were identified in the promoter region (three), introns (two), and exons (two). Genotypes were determined for 3,073 study participants enrolled in six HIV-AIDS prospective cohorts. One codon-changing variant, H186R in exon 4, was polymorphic in African Americans (AA) (f = 37%) and rare in European Americans (f < 3%) or Europeans (f = 5%). For AA, the variant allele 186R was strongly associated with decline in CD4 T cells (CD4 slope on square root scale: -1.86, P = 0.009), The 186R allele was also associated with accelerated progression to AIDS-defining conditions in AA. The in vitro antiviral activity of the 186R enzyme was not inferior to that of the common H186 variant. These studies suggest that there may be a modifying role of variants of APOBEC3G on HIV-1 disease progression that warrants further investigation.

Séquelles radio-induites et tests prédictifs [Radiation-induced sequelae: toward an individual profile]

The impact of curative radiotherapy depends mainly on the total dose delivered homogenously in the targeted volume. Nevertheless, the dose delivery is limited by the tolerated dose of the surrounding healthy tissues. Two different side effects (acute and late) can occur during and after radiotherapy. Of particular interest are the radiation-induced sequelae due to their irreversibility and the potential impact on daily quality of life. In a population treated in one center with the same technique, it appears that individual radiosensitivity clearly exists. In the hypothesis that genetic is involved in this area of research, lymphocytes seem to be the tissue of choice due to easy accessibility. Recently, low percentage of CD4 and CD8 lymphocyte apoptosis were shown to be correlated with high grade of sequelae. In addition, recent data suggest that patients with severe radiation-induced late side effects possess four or more SNP in candidate genes (ATM, SOD2, TGFB1, XRCC1 et XRCC3) and low radiation-induced CD8 lymphocyte apoptosis in vitro.

Influence of HLA-C expression level on HIV control.

A variant upstream of human leukocyte antigen C (HLA-C) shows the most significant genome-wide effect on HIV control in European Americans and is also associated with the level of HLA-C expression. We characterized the differential cell surface expression levels of all common HLA-C allotypes and tested directly for effects of HLA-C expression on outcomes of HIV infection in 5243 individuals. Increasing HLA-C expression was associated with protection against multiple outcomes independently of individual HLA allelic effects in both African and European Americans, regardless of their distinct HLA-C frequencies and linkage relationships with HLA-B and HLA-A. Higher HLA-C expression was correlated with increased likelihood of cytotoxic T lymphocyte responses and frequency of viral escape mutation. In contrast, high HLA-C expression had a deleterious effect in Crohn's disease, suggesting a broader influence of HLA expression levels in human disease.

Six new loci associated with body mass index highlight a neuronal influence on body weight regulation.

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

Schizophrenia and oxidative stress: glutamate cysteine ligase modifier as a susceptibility gene.

Oxidative stress could be involved in the pathophysiology of schizophrenia, a major psychiatric disorder. Glutathione (GSH), a redox regulator, is decreased in patients' cerebrospinal fluid and prefrontal cortex. The gene of the key GSH-synthesizing enzyme, glutamate cysteine ligase modifier (GCLM) subunit, is strongly associated with schizophrenia in two case-control studies and in one family study. GCLM gene expression is decreased in patients' fibroblasts. Thus, GSH metabolism dysfunction is proposed as one of the vulnerability factors for schizophrenia.

Approches de gene silencing pour le traitement de la maladie de Huntington [Gene silencing approaches for the treatment of Huntington's disease].

Huntington's disease is a rare neurodegenerative disease caused by a pathologic CAG expansion in the exon 1 of the huntingtin (HTT) gene. Aggregation and abnormal function of the mutant HTT (mHTT) cause motor, cognitive and psychiatric symptoms in patients, which lead to death in 15-20 years. Currently, there is no treatment for HD. Experimental approaches based on drug, cell or gene therapy are developed and reach progressively to the clinic. Among them, mHTT silencing using small non-coding nucleic acids display important physiopathological benefit in HD experimental models.

Association of PCK1 with Body Mass Index and Other Metabolic Features in Patients With Psychotropic Treatments.

Weight gain is a major health problem among psychiatric populations. It implicates several receptors and hormones involved in energy balance and metabolism. Phosphoenolpyruvate carboxykinase 1 is a rate-controlling enzyme involved in gluconeogenesis, glyceroneogenesis and cataplerosis and has been related to obesity and diabetes phenotypes in animals and humans. The aim of this study was to investigate the association of phosphoenolpyruvate carboxykinase 1 polymorphisms with metabolic traits in psychiatric patients treated with psychotropic drugs inducing weight gain and in general population samples. One polymorphism (rs11552145G > A) significantly associated with body mass index in the psychiatric discovery sample (n = 478) was replicated in 2 other psychiatric samples (n1 = 168, n2 = 188), with AA-genotype carriers having lower body mass index as compared to G-allele carriers. Stronger associations were found among women younger than 45 years carrying AA-genotype as compared to G-allele carriers (-2.25 kg/m, n = 151, P = 0.009) and in the discovery sample (-2.20 kg/m, n = 423, P = 0.0004). In the discovery sample for which metabolic parameters were available, AA-genotype showed lower waist circumference (-6.86 cm, P = 0.008) and triglycerides levels (-5.58 mg/100 mL, P < 0.002) when compared to G-allele carriers. Finally, waist-to-hip ratio was associated with rs6070157 (proxy of rs11552145, r = 0.99) in a population-based sample (N = 123,865, P = 0.022). Our results suggest an association of rs11552145G > A polymorphism with metabolic-related traits, especially in psychiatric populations and in women younger than 45 years.

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.

Genomic and transcriptomic analysis of the streptomycin-dependent Mycobacterium tuberculosis strain 18b.

The ability of Mycobacterium tuberculosis to establish a latent infection (LTBI) in humans confounds the treatment of tuberculosis. Consequently, there is a need to discover new therapeutic agents that can kill M. tuberculosis both during active disease and LTBI. The streptomycin-dependent strain of M. tuberculosis, 18b, provides a useful tool for this purpose since upon removal of streptomycin (STR) it enters a non-replicating state that mimics latency both in vitro and in animal models. The 4.41 Mb genome sequence of M. tuberculosis 18b was determined and this revealed the strain to belong to clade 3 of the ancient ancestral lineage of the Beijing family. STR-dependence was attributable to insertion of a single cytosine in the 530 loop of the 16S rRNA and to a single amino acid insertion in the N-terminal domain of initiation factor 3. RNA-seq was used to understand the genetic programme activated upon STR-withdrawal and hence to gain insight into LTBI. This revealed reconfiguration of gene expression and metabolic pathways showing strong similarities between non-replicating 18b and M. tuberculosis residing within macrophages, and with the core stationary phase and microaerophilic responses. The findings of this investigation confirm the validity of 18b as a model for LTBI, and provide insight into both the evolution of tubercle bacilli and the functioning of the ribosome.

Impact of genetic SLC28 transporter and ITPA variants on ribavirin 21 serum level, hemoglobin drop and therapeutic response in patients with HCV infection

Background: T reatment o f chronic hepatitis C i s evolving, a nd direct acting antivirals ( DAAs) are now a dded to p egylated interferon-α ( Peg- INF-α) and ribavirin (RBV) for the treatment o f hepatitis C v irus ( HCV) genotype 1 infection. DAAs c ause d ifferent side effects and can even worsen RBV induced hemolytic anemia. T herefore, identifying host genetic d eterminants of R BV bioavailability and therapeutic e fficacy will remain crucial for individualized treatment. Recent d ata showed associations between R BV induced h emolytic anemia and genetic polymorphisms o f concentrative nucleoside transporters s uch as C NT3 (SLC28A3) and i nosine t riphosphatase (ITPA). T o analyze t he association of genetic variants of SLC28 transporters and ITPA with RBV induced hemolytic anemia and treatment o utcome. Methods: I n our study, 173 patients f rom t he S wiss Hepatitis C C ohort Study and 2 2 patients from Swiss Association for the Study of the Liver study 24 (61% HCV g enotype 1, 3 9% genotypes 2 o r 3) were analyzed for SLC28A2 single nucleotide p olymorphism (SNP) rs11854484, SLC28A3 rs56350726 and SLC28A3 rs10868138 as well as ITPA SNPs rs1127354 and rs7270101. RBV serum levels during treatment were measured in 49 patients. Results: SLC28A2 r s11854484 genotype TT was associated with significantly higher dosage- and body weight-adjusted RBV levels as compared to genotypes TC and CC (p=0.04 and p=0.02 at weeks 4 and 8, respectively). ITPA SNPs rs1127354 and rs7270101 were associated with h emolytic a nemia both in genotype as w ell as i n allelic a nalyses. SLC28A3 rs56350726 genotype TT (vs. AT/AA, RR=2.1; 95% CI 1.1-4.1) as well as the T allele (vs. A; RR=1.8, 95% CI 1.1-3.2) were associated with increased SVR rates. The combined analysis of overall ITPA activity and SLC28 v ariants together revealed n o significant a dditive effects on either treatment-related anemia or SVR. Conclusions: T he newly identified association between RBV serum levels a nd SLC28A2 rs11854484 genotype as well as the replicated association of ITPA and SLC28A3 g enetic p olymorphisms w ith RBV induced hemolytic anemia and treatment r esponse underpin the need for further studies on host genetic d eterminants of R BV bioavailability and therapeutic e fficacy f or individualized treatment of chronic hepatitis C.

IFN stimulated gene expression in the liver is a better predictor of treatment response in chronic hepatitis c than the IL28b (IFN lambda 3) genotype

Background: Therapy of chronic hepatitis C (CHC) with pegIFNa/ribavirin achieves sustained virologic response (SVR) in ~55%. Pre-activation of the endogenous interferon system in the liver is associated non-response (NR). Recently, genome-wide association studies described associations of allelic variants near the IL28B (IFNλ3) gene with treatment response and with spontaneous clearance of the virus. We investigated if the IL28B genotype determines the constitutive expression of IFN stimulated genes (ISGs) in the liver of patients with CHC. Methods: We genotyped 93 patients with CHC for 3 IL28B single nucleotide polymorphisms (SNPs, rs12979860, rs8099917, rs12980275), extracted RNA from their liver biopsies and quantified the expression of IL28B and of 8 previously identified classifier genes which discriminate between SVR and NR (IFI44L, RSAD2, ISG15, IFI22, LAMP3, OAS3, LGALS3BP and HTATIP2). Decision tree ensembles in the form of a random forest classifier were used to calculate the relative predictive power of these different variables in a multivariate analysis. Results: The minor IL28B allele (bad risk for treatment response) was significantly associated with increased expression of ISGs, and, unexpectedly, with decreased expression of IL28B. Stratification of the patients into SVR and NR revealed that ISG expression was conditionally independent from the IL28B genotype, i.e. there was an increased expression of ISGs in NR compared to SVR irrespective of the IL28B genotype. The random forest feature score (RFFS) identified IFI27 (RFFS = 2.93), RSAD2 (1.88) and HTATIP2 (1.50) expression and the HCV genotype (1.62) as the strongest predictors of treatment response. ROC curves of the IL28B SNPs showed an AUC of 0.66 with an error rate (ERR) of 0.38. A classifier with the 3 best classifying genes showed an excellent test performance with an AUC of 0.94 and ERR of 0.15. The addition of IL28B genotype information did not improve the predictive power of the 3-gene classifier. Conclusions: IL28B genotype and hepatic ISG expression are conditionally independent predictors of treatment response in CHC. There is no direct link between altered IFNλ3 expression and pre-activation of the endogenous system in the liver. Hepatic ISG expression is by far the better predictor for treatment response than IL28B genotype.

Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study.

AIMS/HYPOTHESIS: Several susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors. METHODS: We constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals. RESULTS: The clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8-4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles. CONCLUSIONS/INTERPRETATION: In this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.

Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1)H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8)) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44)) and lysine (rs8101881, P = 1.2×10(-33)), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.