To evaluate systematically in real clinical settings whether functional genetic variations in drug metabolizing enzymes influence optimized doses, efficacy, and safety of antipsychotic medications.
DNA was collected from 750 patients with chronic schizophrenia treated with five antipsychotic drugs (olanzapine, quetiapine, risperidone, ziprasidone and perphenazine) as part of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Doses for each of the medicines were optimized to 1, 2, 3, or 4x units in identically-appearing capsules in a double blind design. We analyzed 25 known functional genetic variants in the major and minor metabolizing enzymes for each medication. These variants were tested for association with optimized dose and other relevant clinical outcomes.
None of the tested variants showed a nominally significant main effect in association with any of the tested phenotypes in European-Americans, African-Americans or all patients. Even after accounting for potential covariates no genetic variant was found to be associated with dosing, efficacy, overall tolerability, or tardive dyskinesia.
There are no strong associations between common functional genetic variants in drug metabolizing enzymes and dosing, safety or efficacy of leading antipsychotics, strongly suggesting merely modest effects on the use of these medicines in most patients in typical clinical settings.
Pharmacogenetics; CYP 450; Drug Metabolizing Enzymes; Antipsychotics; Personalized Medicine
Multifactor Dimensionality Reduction (MDR) has been widely applied to detect gene-gene (GxG) interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk) from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account.
We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR) method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX) that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy.
The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi) are proposed to detect multiple GxG interactions.
A-MDR; Epistasis enriched risk score; Epistasis enriched gene network; pRR; pOR; pChi
carbamazepine; cytochrome P450 metabolizing enzymes; HLA-B; pharmacogenomics; pharmacokinetics
Despite the frequent utilization of biomarkers in medical practice, there is a relative paucity of information regarding validated pediatric biomarkers. Frequently, biomarkers found to be efficacious in adults are extrapolated to the pediatric clinical setting without considering that the pathogenesis of many diseases is distinctly different in children, and ontogeny directly influences disease evolution and therapeutic response in children. New and innovative approaches are necessary to provide reliable, validated biomarkers that can be used to improve and advance pediatric medical care.
biomarker; children; development; genomics; ontogeny; pediatrics; pharmacogenomics
CYP2C19; CYP2C9; HLA-B; pathway; pharmacogenomic; pharmacokinetics; phenytoin; SCN1A
Multifactor Dimensionality Reduction (MDR) is a popular and successful data mining method developed to characterize and detect nonlinear complex gene-gene interactions (epistasis) that are associated with disease susceptibility. Because MDR uses a combinatorial search strategy to detect interaction, several filtration techniques have been developed to remove genes (SNPs) that have no interactive effects prior to analysis. However, the cutoff values implemented for these filtration methods are arbitrary, therefore different choices of cutoff values will lead to different selections of genes (SNPs).
We suggest incorporating a global test of p-values to filtration procedures to identify the optimal number of genes/SNPs for further MDR analysis and demonstrate this approach using a ReliefF filter technique. We compare the performance of different global testing procedures in this context, including the Kolmogorov-Smirnov test, the inverse chi-square test, the inverse normal test, the logit test, the Wilcoxon test and Tippett’s test. Additionally we demonstrate the approach on a real data application with a candidate gene study of drug response in Juvenile Idiopathic Arthritis.
Extensive simulation of correlated p-values show that the inverse chi-square test is the most appropriate approach to be incorporated with the screening approach to determine the optimal number of SNPs for the final MDR analysis. The Kolmogorov-Smirnov test has high inflation of Type I errors when p-values are highly correlated or when p-values peak near the center of histogram. Tippett’s test has very low power when the effect size of GxG interactions is small.
The proposed global tests can serve as a screening approach prior to individual tests to prevent false discovery. Strong power in small sample sizes and well controlled Type I error in absence of GxG interactions make global tests highly recommended in epistasis studies.
P-value; Global tests; ReliefF; Multifactor dimensionality reduction
Betaine-homocysteine methyltransferase (BHMT) catalyzes the remethylation of homocysteine. BHMT is highly expressed in the human liver. In the liver, BHMT catalyzes up to 50% of homocysteine metabolism. Understanding the relationship between BHMT genetic polymorphisms and function might increase our understanding of the role of this reaction in homocysteine remethylation and in S-adenosylmethionine-dependent methylation. To help achieve those goals, we measured levels of BHMT enzyme activity and immunoreactive protein in 268 human hepatic surgical biopsy samples from adult subjects as well as 73 fetal hepatic tissue samples obtained at different gestational ages. BHMT protein levels were correlated significantly (p<0.001) with levels of enzyme activity in both fetal and adult tissue, but both were decreased in fetal tissue when compared with levels in the adult hepatic biopsies. To determine possible genotype-phenotype correlations, 12 tag SNPs for BHMT and the closely related BHMT2 gene were selected from SNPs observed during our own gene resequencing studies as well as from HapMap data were used to genotype DNA from the adult hepatic surgical biopsy samples, and genotype-phenotype association analysis was performed. Three SNPs (rs41272270, rs16876512, and rs6875201), located 28 kb upstream, in the 5′-UTR and in intron 1 of BHMT, respectively, were significantly correlated with both BHMT activity (p=3.41E-8, 2.55E-9 and 2.46E-10, respectively) and protein levels (p=5.78E-5, 1.08E-5 and 6.92E-6, respectively). We also imputed 230 additional SNPs across the BHMT and BHMT2 genes, identifying an additional imputed SNP, rs7700790, that was also highly associated with hepatic BHMT enzyme activity and protein. However, none of the 3 genotyped or one imputed SNPs displayed a “shift” during electrophoretic mobility shift assays. These observations may help us to understand individual variation in the regulation of BHMT in the human liver and its possible relationship to variation in methylation.
Betaine-homocysteine methyltransferase; BHMT; BHMT2; single nucleotide polymorphisms; SNPs; genotype-phenotype correlation; hepatic tissue
Toll-like receptors (TLRs) are critical components of the innate immune system, acting as pattern recognition molecules and triggering an inflammatory response. TLR associated gene products are of interest in modulating inflammatory related pulmonary diseases of the neonate. The ontogeny of TLR related genes in human fetal lung has not been previously described and could elucidate additional functions and identify strategies for attenuating the effects of fetal inflammation. We examined the expression of 84 TLR related genes on 23 human fetal lung samples from three groups with estimated ages of 60 (57-59d), 90 (89-91d), and 130 (117-154d) days. Using a false detection rate algorithm, we identified 32 genes displaying developmental regulation with TLR2 having the greatest up-regulation of TLR genes (9.2 fold increase) and TLR4 unchanged. We confirmed the TLR2 up-regulation by examining an additional 133 fetal lung tissue samples with a fluorogenic polymerase chain reaction assay (TaqMan®) and found an exponential best-fit curve over the time studied. The best-fit curve predicts a 6.1 fold increase from 60d to 130d. We conclude that TLR2 is developmentally expressed from the early pseudoglandular stage of lung development to the canalicular stage.
Adverse drug reactions are a concern for all clinicians who utilize medications to treat adults and children; however, the frequency of adult and pediatric adverse drug reactions is likely to be under-reported. In this age of genomics and personalized medicine, identifying genetic variation that results in differences in drug biotransformation and response has contributed to significant advances in the utilization of several commonly used medications in adults. In order to better understand the variability of drug response in children however, we must not only consider differences in genotype, but also variation in gene expression during growth and development, namely ontogeny. In this article, recommendations for systematically approaching pharmacogenomic studies in children are discussed, and several examples of studies that investigate the genomic and developmental contribution to adverse drug reactions in children are reviewed.
adverse drug reactions; genetic variants; methotrexate; pediatrics; pharmacogenomics
Little is known about the role of most asthma susceptibility genes during human lung development. Genetic determinants for normal lung development are not only important early in life, but also for later lung function.
To investigate the role of expression patterns of well-defined asthma susceptibility genes during human and murine lung development. We hypothesized that genes influencing normal airways development would be over-represented by genes associated with asthma.
Asthma genes were first identified via comprehensive search of the current literature. Next, we analyzed their expression patterns in the developing human lung during the pseudoglandular (gestational age, 7-16 weeks) and canalicular (17-26 weeks) stages of development, and in the complete developing lung time series of 3 mouse strains: A/J, SW, C57BL6.
In total, 96 genes with association to asthma in at least two human populations were identified in the literature. Overall, there was no significant over-representation of the asthma genes among genes differentially expressed during lung development, although trends were seen in the human (Odds ratio, OR 1.22, confidence interval, CI 0.90-1.62) and C57BL6 mouse (OR 1.41, CI 0.92-2.11) data. However, differential expression of some asthma genes was consistent in both developing human and murine lung, e.g. NOD1, EDN1, CCL5, RORA and HLA-G. Among the asthma genes identified in genome wide association studies, ROBO1, RORA, HLA-DQB1, IL2RB and PDE10A were differentially expressed during human lung development.
Our data provide insight about the role of asthma susceptibility genes during lung development and suggest common mechanisms underlying lung morphogenesis and pathogenesis of respiratory diseases.
Asthma; Development; Expression; Genetics; Lung
Rationale: Current understanding of the molecular regulation of lung development is limited and derives mostly from animal studies.
Objectives: To define global patterns of gene expression during human lung development.
Methods: Genome-wide expression profiling was used to measure the developing lung transcriptome in RNA samples derived from 38 normal human lung tissues at 53 to 154 days post conception. Principal component analysis was used to characterize global expression variation and to identify genes and bioontologic attributes contributing to these variations. Individual gene expression patterns were verified by quantitative reverse transcriptase–polymerase chain reaction analysis.
Measurements and Main Results: Gene expression analysis identified attributes not previously associated with lung development, such as chemokine-immunologic processes. Lung characteristics attributes (e.g., surfactant function) were observed at an earlier-than-anticipated age. We defined a 3,223 gene developing lung characteristic subtranscriptome capable of describing a majority of the process. In gene expression space, the samples formed a time-contiguous trajectory with transition points correlating with histological stages and suggesting the existence of novel molecular substages. Induction of surfactant gene expression characterized a pseudoglandular “molecular phase” transition. Individual gene expression patterns were independently validated. We predicted the age of independent human lung transcriptome profiles with a median absolute error of 5 days, supporting the validity of the data and modeling approach.
Conclusions: This study extends our knowledge of key gene expression patterns and bioontologic attributes underlying early human lung developmental processes. The data also suggest the existence of molecular phases of lung development.
microarrays; surfactant; principal component analysis
Polymorphic expression of CYP2D6 contributes to the wide range of activity observed for this clinically important drug metabolizing enzyme. In this report we describe novel CYP2D7/2D6 hybrid genes encoding non-functional and functional CYP2D6 protein and a CYP2D7 variant that mimics a CYP2D7/2D6 hybrid gene. Five-kilobyte-long PCR products encompassing the novel genes were entirely sequenced. A quantitative assay probing in different gene regions was employed to determine CYP2D6 and 2D7 copy number variations and the relative position of the hybrid genes within the locus was assessed by long-range PCR. In addition to the previously known CYP2D6*13 and *66 hybrids, we describe three novel non-functional CYP2D7-2D6 hybrids with gene switching in exon 2 (CYP2D6*79), intron 2 (CYP2D6*80), and intron 5 (CYP2D6*67). A CYP2D7-specific T-ins in exon 1 causes a detrimental frame shift. One subject revealed a CYP2D7 conversion in the 5′-flanking region of a CYP2D6*35 allele, was otherwise unaffected (designated CYP2D6*35B). Finally, three DNAs revealed a CYP2D7 gene with a CYP2D6-like region downstream of exon 9 (designated CYP2D7[REP6]). Quantitative copy number determination, sequence analyses, and long-range PCR mapping were in agreement and excluded the presence of additional gene units. Undetected hybrid genes may cause over-estimation of CYP2D6 activity (CYP2D6*1/*1 vs *1/hybrid, etc), but may also cause results that may interfere with the genotype determination. Detection of hybrid events, “single” and tandem, will contribute to more accurate phenotype prediction from genotype data.
CYP2D6; hybrid genes; CYP2D6*35B; CYP2D6*67; CYP2D6*79; CYP2D6*80; CYP2D6 poor metabolizer
Although methotrexate is widely used in clinical practice there remains significant lack of understanding of its mechanisms of action and the factors that contribute to the variability in toxicity and response seen clinically. In addition to differences in drug administration, factors that affect pharmacokinetics and pharmacodynamics such as genetic variation may explain individual differences in drug biotransformation. However, the pediatric population has an additional factor to consider, namely the ontogeny of gene expression which may result in variation throughout growth and development. We review the current understanding of methotrexate biotransformation and the concept of ontogeny, with further discussion of how to implement a developmental pharmacogenomics approach in future studies.
Carbamazepine (CBZ) is a widely prescribed anticonvulsant whose use is often associated with idiosyncratic hypersensitivity. Sera of CBZ-hypersensitive patients often contain anti-CYP3A antibodies, including those to a CYP3A23 K-helix peptide that is also modified during peroxidative CYP3A4 heme-fragmentation. We explored the possibility that cytochromes P450 (P450s) such as CYP3A4 bioactivate CBZ to reactive metabolite(s) that irreversibly modify the P450 protein. Such CBZ-P450 adducts, if stable in vivo, could engender corresponding serum P450 autoantibodies. Incubation with CBZ not only failed to inactivate functionally reconstituted, purified recombinant CYP3A4 or CYP3A4 Supersomes in a time-dependent manner, but the inclusion of CBZ (0–1 mM) also afforded a concentration-dependent protection to CYP3A4 from inactivation by NADPH-induced oxidative uncoupling. Incubation of CYP3A4 Supersomes with 3H-CBZ resulted in its irreversible binding to CYP3A4 protein with a stoichiometry of 1.58 ± 0.15 pmol 3H-CBZ bound/pmol CYP3A4. Inclusion of glutathione (1.5 mM) in the incubation reduced this level to 1.09. Similar binding (1.0 ± 0.4 pmol 3H-CBZ bound/pmol CYP3A4) was observed after 3H-CBZ incubation with functionally reconstituted, purified recombinant CYP3A4(His)6. The CBZ-modified CYP3A4 retained its functional activity albeit at a reduced level, but its testosterone 6β-hydroxylase kinetics were altered from sigmoidal (a characteristic profile of substrate cooperativity) to near-hyperbolic (Michaelis-Menten) type, suggesting that CBZ may have modified CYP3A4 within its active site.
Conversion of the carbamazepine metabolite, 3-hydroxycarbamazepine (3-OHCBZ), to the catechol, 2,3-dihydroxycarbamazepine (2,3-diOHCBZ), followed by subsequent oxidation to a reactive o-quinone species has been proposed as a possible bioactivation pathway in the pathogenesis of carbamazepine-induced hypersensitivity. Initial in vitro phenotyping studies implicated CYP3A4 as a primary catalyst of 2,3-diOHCBZ formation: 2-hydroxylation of 3-OHCBZ correlated significantly (r2≥0.929, P<0.001) with CYP3A4/5 activities in a panel of human liver microsomes (n=14) and was markedly impaired by CYP3A inhibitors (>80%), but not by inhibitors of other cytochrome P450 enzymes (≤20%). However, in the presence of troleandomycin, the rate of 2,3-diOHCBZ formation correlated significantly with CYP2C19 activity (r2=0.893, P<0.001) in the panel of human liver microsomes. Studies with a panel of cDNA-expressed enzymes revealed that CYP2C19 and CYP3A4 were high (S50=30 μM) and low (S50=203 μM) affinity enzymes, respectively, for 2,3-diOHCBZ formation and suggested that CYP3A4, but not CYP2C19, might be inactivated by a metabolite formed from 3-OHCBZ. Subsequent experiments demonstrated that preincubation of 3-OHCBZ with human liver microsomes or recombinant CYP3A4 led to decreased CYP3A4 activity, which was both preincubation time- and concentration-dependent, but not inhibited by inclusion of glutathione or N-acetylcysteine. CYP3A4, CYP3A5, CYP3A7, CYP2C19 and CYP1A2 converted [14C]3-OHCBZ into protein-reactive metabolites, but CYP3A4 was the most catalytically active enzyme. The results of this study suggest that CYP3A4-dependent secondary oxidation of 3-OHCBZ represents a potential carbamazepine bioactivation pathway via formation of reactive metabolites capable of inactivating CYP3A4, potentially generating a neo-antigen that may play a role in the etiology of carbamazepine-induced idiosyncratic toxicity.
CYP2J2 metabolizes arachidonic acid to 20-HETE and EETs which play a critical role in the regulation of renal, pulmonary, cardiac and vascular function. However, the contribution of CYP2J2 to EET formation in the liver remains poorly characterized. Similarly, information is sparse regarding the extent and variability of CYP2J2 expression during human development. This investigation was undertaken to characterize the variability of CYP2J2 expression in fetal liver, heart, kidney, lung, intestine and brain and postnatal liver samples. CYP2J2 mRNA expression was measured using quantitative PCR, and immunoreactive CYP2J2 was examined using two anti-CYP2J2 antibodies. CYP2J2 mRNA was ubiquitously expressed in pre- and postnatal samples. Fetal hepatic mRNA expression varied 127-fold (1351 ± 717 transcripts/ng total RNA), but this variation was reduced to 8-fold after exclusion of four samples with extremely low levels of mRNA. Amounts of immunoreactive protein also varied substantially among samples without an apparent relationship with transcript number or genotype. Western blot analysis revealed a different protein pattern between prenatal and postnatal liver samples. DNA resequencing of selected subjects identified a single novel SNP (CYP2J2*10), which was found in only one subject and therefore did not explain the large variability in CYP2J2 protein content. In vitro expression suggests that the protein product of CYP2J2*10 confers reduced enzymatic activity. Aberrant splicing produces three minor transcripts which were present in all samples tested. Due to premature termination codons none encodes functional protein. The mechanisms leading to variable amounts of immunoreactive protein and distinct pre- and postnatal CYP2J2 protein patterns warrant further investigation.
QUESTION Recently a newborn died from morphine poisoning when hismother used codeine while breastfeeding. Many patients receive codeine for postlabour pain. Is it safe to prescribe codeine for nursing mothers?
ANSWER When a mother is an ultrarapid metabolizer of cytochrome P450 2D6, she produces much more morphine when taking codeine than most people do. In this situation, newborns might be exposed to toxic levels of morphine when breastfeeding. Options to reduce this risk include discontinuing codeine after 2 to 3 days of use and being aware of symptoms of potential opioid toxicity in both mothers and newborns.
Cytochrome P4502D6 (CYP2D6) genotyping reliably predicts poor metabolizer phenotype in Caucasians, but is less accurate in African Americans. To evaluate discordance we have observed in phenotype to genotype correlation studies, select African American subjects were chosen for complete resequencing of the CYP2D6 gene including 4.2 kb of the CYP2D7-2D6 intergenic region. Comparisons were made to a CYP2D6*1 reference sequence revealing novel SNPs in the upstream, coding and intervening sequences. These sequence variations, defining four functional alleles (CYP2D6*41B, *45A and B and *46), were characterized for their ability to influence splice site strength, transcription level or catalytic protein activity. Furthermore, their frequency was determined in a population of 251 African Americans. A −692TGTG deletion (CYP2D6*45B) did not significantly decrease gene expression, nor could any other upstream SNP explain a genotype-discordant case. CYP2D6*45 and *46 have a combined frequency of 4% and can be identified by a common SNP. Carriers are predicted to exhibit an extensive or intermediate CYP2D6 phenotype.
CYP2D6; SNPs; haplotype; dextromethorphan; African American
We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined) weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices.
Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths.
Delila-Genome was used to scan the human genome sequence with information weight matrices of transcription factor binding sites, including PXR/RXRα, AHR and NF-κB p50/p65, and matrices for RNA binding sites including splice donor, acceptor, and SC35 recognition sites. Comparisons of genome scans with the original and refined PXR/RXRα information weight matrices indicate that the refined model more accurately predicts the strengths of known binding sites and is more sensitive for detection of novel binding sites.
With the recent development of microarray technologies, the comparability of gene expression data obtained from different platforms poses an important problem. We evaluated two widely used platforms, Affymetrix U133 Plus 2.0 and the Illumina HumanRef-8 v2 Expression Bead Chips, for comparability in a biological system in which changes may be subtle, namely fetal lung tissue as a function of gestational age.
We performed the comparison via sequence-based probe matching between the two platforms. "Significance grouping" was defined as a measure of comparability. Using both expression correlation and significance grouping as measures of comparability, we demonstrated that despite overall cross-platform differences at the single gene level, increased correlation between the two platforms was found in genes with higher expression level, higher probe overlap, and lower p-value. We also demonstrated that biological function as determined via KEGG pathways or GO categories is more consistent across platforms than single gene analysis.
We conclude that while the comparability of the platforms at the single gene level may be increased by increasing sample size, they are highly comparable ontologically even for subtle differences in a relatively small sample size. Biologically relevant inference should therefore be reproducible across laboratories using different platforms.