Beta-lactam-induced immediate hypersensitivity reactions: A genome-wide association study of a deeply phenotyped cohort.

BACKGROUND: ß-lactam antibiotics are associated with a variety of immune-mediated or hypersensitivity reactions, including immediate (type I) reactions mediated by antigen-specific IgE. OBJECTIVE: We sought to identify genetic predisposing factors for immediate reactions to ß-lactam antibiotics. METHODS: Patients with a clinical history of immediate hypersensitivity reactions to either penicillins or cephalosporins, which were immunologically confirmed, were recruited from allergy clinics. A genome-wide association study was conducted on 662 patients (the discovery cohort) with a diagnosis of immediate hypersensitivity and the main finding was replicated in a cohort of 98 Spanish cases, recruited using the same diagnostic criteria as the discovery cohort. RESULTS: Genome-wide association study identified rs71542416 within the Class II HLA region as the top hit (P = 2 × 10-14); this was in linkage disequilibrium with HLA-DRB1∗10:01 (odds ratio, 2.93; P = 5.4 × 10-7) and HLA-DQA1∗01:05 (odds ratio, 2.93, P = 5.4 × 10-7). Haplotype analysis identified that HLA-DRB1∗10:01 was a risk factor even without the HLA-DQA1∗01:05 allele. The association with HLA-DRB1∗10:01 was replicated in another cohort, with the meta-analysis of the discovery and replication cohorts showing that HLA-DRB1∗10:01 increased the risk of immediate hypersensitivity at a genome-wide level (odds ratio, 2.96; P = 4.1 × 10-9). No association with HLA-DRB1∗10:01 was identified in 268 patients with delayed hypersensitivity reactions to ß-lactams. CONCLUSIONS: HLA-DRB1∗10:01 predisposed to immediate hypersensitivity reactions to penicillins. Further work to identify other predisposing HLA and non-HLA loci is required.

Association of Liver Injury From Specific Drugs, or Groups of Drugs, With Polymorphisms in HLA and Other Genes in a Genome-Wide Association Study.

BACKGROUND & AIMS: We performed a genome-wide association study (GWAS) to identify genetic risk factors for drug-induced liver injury (DILI) from licensed drugs without previously reported genetic risk factors. METHODS: We performed a GWAS of 862 persons with DILI and 10,588 population-matched controls. The first set of cases was recruited before May 2009 in Europe (n = 137) and the United States (n = 274). The second set of cases were identified from May 2009 through May 2013 from international collaborative studies performed in Europe, the United States, and South America. For the GWAS, we included only cases with patients of European ancestry associated with a particular drug (but not flucloxacillin or amoxicillin-clavulanate). We used DNA samples from all subjects to analyze HLA genes and single nucleotide polymorphisms. After the discovery analysis was concluded, we validated our findings using data from 283 European patients with diagnosis of DILI associated with various drugs. RESULTS: We associated DILI with rs114577328 (a proxy for A*33:01 a HLA class I allele; odds ratio [OR], 2.7; 95% confidence interval [CI], 1.9-3.8; P = 2.4 × 10-8) and with rs72631567 on chromosome 2 (OR, 2.0; 95% CI, 1.6-2.5; P = 9.7 × 10-9). The association with A*33:01 was mediated by large effects for terbinafine-, fenofibrate-, and ticlopidine-related DILI. The variant on chromosome 2 was associated with DILI from a variety of drugs. Further phenotypic analysis indicated that the association between DILI and A*33:01 was significant genome wide for cholestatic and mixed DILI, but not for hepatocellular DILI; the polymorphism on chromosome 2 was associated with cholestatic and mixed DILI as well as hepatocellular DILI. We identified an association between rs28521457 (within the lipopolysaccharide-responsive vesicle trafficking, beach and anchor containing gene) and only hepatocellular DILI (OR, 2.1; 95% CI, 1.6-2.7; P = 4.8 × 10-9). We did not associate any specific drug classes with genetic polymorphisms, except for statin-associated DILI, which was associated with rs116561224 on chromosome 18 (OR, 5.4; 95% CI, 3.0-9.5; P = 7.1 × 10-9). We validated the association between A*33:01 terbinafine- and sertraline-induced DILI. We could not validate the association between DILI and rs72631567, rs28521457, or rs116561224. CONCLUSIONS: In a GWAS of persons of European descent with DILI, we associated HLA-A*33:01 with DILI due to terbinafine and possibly fenofibrate and ticlopidine. We identified polymorphisms that appear to be associated with DILI from statins, as well as 2 non-drug-specific risk factors.

HLA-DRB1*16: 01-DQB1*05: 02 is a novel genetic risk factor for flupirtine-induced liver injury.

OBJECTIVE: Flupirtine is a nonopioid analgesic with regulatory approval in a number of European countries. Because of the risk of serious liver injury, its use is now limited to short-term pain management. We aimed to identify genetic risk factors for flupirtine-related drug-induced liver injury (DILI) as these are unknown. MATERIALS AND METHODS: Six flupirtine-related DILI patients from Germany were included in a genome-wide association study (GWAS) involving a further 614 European cases of DILI because of other drugs and 10,588 population controls. DILI was diagnosed by causality assessment and expert review. Human leucocyte antigen (HLA) and single nucleotide polymorphism genotypes were imputed from the GWAS data, with direct HLA typing performed on selected cases to validate HLA predictions. Four replication cases that were unavailable for the GWAS were genotyped by direct HLA typing, yielding an overall total of 10 flupirtine DILI cases. RESULTS: In the six flupirtine DILI cases included in the GWAS, we found a significant enrichment of the DRB1*16:01-DQB1*05:02 haplotype compared with the controls (minor allele frequency cases 0.25 and minor allele frequency controls 0.013; P=1.4 × 10(-5)). We estimated an odds ratio for haplotype carriers of 18.7 (95% confidence interval 2.5-140.5, P=0.002) using population-specific HLA control data. The result was replicated in four additional cases, also with a haplotype frequency of 0.25. In the combined cohort (six GWAS plus four replication cases), the haplotype was also significant (odds ratio 18.7, 95% confidence interval 4.31-81.42, P=6.7 × 10(-5)). CONCLUSION: We identified a novel HLA class II association for DILI, confirming the important contribution of HLA genotype towards the risk of DILI generally.

Limited contribution of common genetic variants to risk for liver injury due to a variety of drugs.

BACKGROUND AND AIMS: Drug-induced liver injury (DILI) is a serious adverse drug event that is suspected to have a heritable component. We carried out a genome-wide association study of 783 individuals of European ancestry who experienced DILI due to more than 200 implicated drugs. METHODS: DILI patients from the US-based Drug-Induced Liver Injury Network (n=401) and three international registries (n=382) were genotyped with the Illumina 1Mduo BeadChip and compared with population controls (n=3001). Potential associations were tested in 307 independent Drug-Induced Liver Injury Network cases. RESULTS: After accounting for known major histocompatibility complex risk alleles for flucloxacillin-DILI and amoxicillin/clavulanate-DILI, there were no genome-wide significant associations, including in the major histocompatibility complex region. Stratification of DILI cases according to clinical phenotypes (injury type, latency, age of onset) also did not show significant associations. An analysis of hepatocellular DILI (n=285) restricted to 193 single-nucleotide polymorphisms previously associated with autoimmune disease showed a trend association for rs7574865, in the vicinity of signal transducer and activator of transcription 4 (STAT4) (P=4.5×10(-4)). This association was replicated in an independent cohort of 168 hepatocellular DILI cases (P=0.011 and 1.5×10(-5) for combined cohorts). No significant associations were found with stratification by other clinical or demographic variables. CONCLUSION: Although not significant at the genome-wide level, the association between hepatocellular DILI and STAT4 is consistent with the emerging role of the immune system in DILI. However, the lack of genome-wide association study findings supports the idea that strong genetic determinants of DILI may be largely drug-specific or may reflect rare genetic variations, which were not assessed in our study.

Genomewide pharmacogenetics of bisphosphonate-induced osteonecrosis of the jaw: the role of RBMS3.

UNLABELLED: Bisphosphonate-related osteonecrosis of the jaw (BRONJ) is a serious adverse drug reaction. We conducted a genomewide association study to search for genetic variants with a large effect size that increase the risk for BRONJ. METHODS: We ascertained BRONJ cases according to the diagnostic criteria of the American Association of Oral and Maxillofacial Surgeons. We genotyped cases and a set of treatment-matched controls using Illumina Human Omni Express 12v1 chip (733,202 markers). To maximize the power of the study, we expanded the initial control set by including population and treatment-tolerant controls from publicly available sources. Imputation at the whole-genome level was performed to increase the number of single nucleotide polymorphisms (SNPs) investigated. Tests of association were carried out by logistic regression, adjusting for population structure. We also examined a list of candidate genes comprising genes potentially involved in the pathogenesis of BRONJ and genes related to drug absorption, distribution, metabolism, and excretion. RESULTS: Based on principal component analysis, we initially analyzed 30 white cases and 17 treatment-tolerant controls. We subsequently expanded the control set to include 60 genetically matched controls per case. Association testing identified a significant marker in the RBMS3 gene, rs17024608 (p-value < 7 × 10(-8)); individuals positive for the SNP were 5.8× more likely to develop BRONJ (odds ratio, 5.8; 95% confidence interval, 3.1-11.1). Candidate gene analysis further identified SNPs in IGFBP7 and ABCC4 as potentially implicated in BRONJ risk. CONCLUSION: Our findings suggest that genetic susceptibility plays a role in the pathophysiology of BRONJ, with RBMS3 having a significant effect in the risk.

Susceptibility to amoxicillin-clavulanate-induced liver injury is influenced by multiple HLA class I and II alleles.

BACKGROUND & AIMS: Drug-induced liver injury (DILI), especially from antimicrobial agents, is an important cause of serious liver disease. Amoxicillin-clavulanate (AC) is a leading cause of idiosyncratic DILI, but little is understood about genetic susceptibility to this adverse reaction. METHODS: We performed a genome-wide association study using 822,927 single nucleotide polymorphism (SNP) markers from 201 White European and US cases of DILI following AC administration (AC-DILI) and 532 population controls, matched for genetic background. RESULTS: AC-DILI was associated with many loci in the major histocompatibility complex. The strongest effect was with an HLA class II SNP (rs9274407, P=4.8×10(-14)), which correlated with rs3135388, a tag SNP of HLA-DRB1*1501-DQB1*0602 that was previously associated with AC-DILI. Conditioned on rs3135388, rs9274407 is still significant (P=1.1×10(-4)). An independent association was observed in the class I region (rs2523822, P=1.8×10(-10)), related to HLA-A*0201. The most significant class I and II SNPs showed statistical interaction (P=.0015). High-resolution HLA genotyping (177 cases and 219 controls) confirmed associations of HLA-A*0201 (P=2×10(-6)) and HLA-DQB1*0602 (P=5×10(-10)) and their interaction (P=.005). Additional, population-dependent effects were observed in HLA alleles with nominal significance. In an analysis of autoimmune-related genes, rs2476601 in the gene PTPN22 was associated (P=1.3×10(-4)). CONCLUSIONS: Class I and II HLA genotypes affect susceptibility to AC-DILI, indicating the importance of the adaptive immune response in pathogenesis. The HLA genotypes identified will be useful in studies of the pathogenesis of AC-DILI but have limited utility as predictive or diagnostic biomarkers because of the low positive predictive values.

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer.

Background and Aims: Individuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown. Methods: Multiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences. Results: We demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called "master transcriptional regulators" (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups. Conclusion: Our study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

A curated collection of human vaccination response signatures.

Recent advances in high-throughput experiments and systems biology approaches have resulted in hundreds of publications identifying "immune signatures". Unfortunately, these are often described within text, figures, or tables in a format not amenable to computational processing, thus severely hampering our ability to fully exploit this information. Here we present a data model to represent immune signatures, along with the Human Immunology Project Consortium (HIPC) Dashboard ( www.hipc-dashboard.org ), a web-enabled application to facilitate signature access and querying. The data model captures the biological response components (e.g., genes, proteins, cell types or metabolites) and metadata describing the context under which the signature was identified using standardized terms from established resources (e.g., HGNC, Protein Ontology, Cell Ontology). We have manually curated a collection of >600 immune signatures from >60 published studies profiling human vaccination responses for the current release. The system will aid in building a broader understanding of the human immune response to stimuli by enabling researchers to easily access and interrogate published immune signatures.

The Immune Signatures data resource, a compendium of systems vaccinology datasets.

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

geWorkbench: an open source platform for integrative genomics.

SUMMARY: geWorkbench (genomics Workbench) is an open source Java desktop application that provides access to an integrated suite of tools for the analysis and visualization of data from a wide range of genomics domains (gene expression, sequence, protein structure and systems biology). More than 70 distinct plug-in modules are currently available implementing both classical analyses (several variants of clustering, classification, homology detection, etc.) as well as state of the art algorithms for the reverse engineering of regulatory networks and for protein structure prediction, among many others. geWorkbench leverages standards-based middleware technologies to provide seamless access to remote data, annotation and computational servers, thus, enabling researchers with limited local resources to benefit from available public infrastructure. AVAILABILITY: The project site (http://www.geworkbench.org) includes links to self-extracting installers for most operating system (OS) platforms as well as instructions for building the application from scratch using the source code [which is freely available from the project's SVN (subversion) repository]. geWorkbench support is available through the end-user and developer forums of the caBIG Molecular Analysis Tools Knowledge Center, https://cabig-kc.nci.nih.gov/Molecular/forums/

Shared Genetic Risk Factors Across Carbamazepine-Induced Hypersensitivity Reactions.

Carbamazepine (CBZ) causes life-threating T-cell-mediated hypersensitivity reactions, including serious cutaneous adverse reactions (SCARs) and drug-induced liver injury (CBZ-DILI). In order to evaluate shared or phenotype-specific genetic predisposing factors for CBZ hypersensitivity reactions, we performed a meta-analysis of two genomewide association studies (GWAS) on a total of 43 well-phenotyped Northern and Southern European CBZ-SCAR cases and 10,701 population controls and a GWAS on 12 CBZ-DILI cases and 8,438 ethnically matched population controls. HLA-A*31:01 was identified as the strongest genetic predisposing factor for both CBZ-SCAR (odds ratio (OR) = 8.0; 95% CI 4.10-15.80; P = 1.2 × 10-9 ) and CBZ-DILI (OR = 7.3; 95% CI 2.47-23.67; P = 0.0004) in European populations. The association with HLA-A*31:01 in patients with SCAR was mainly driven by hypersensitivity syndrome (OR = 12.9; P = 2.1 × 10-9 ) rather than by Stevens-Johnson syndrome/toxic epidermal necrolysis cases, which showed an association with HLA-B*57:01. We also identified a novel risk locus mapping to ALK only for CBZ-SCAR cases, which needs replication in additional cohorts and functional evaluation.

CTD2 Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network.

Database URL: https://ctd2-dashboard.nci.nih.gov/.

Dictionary-driven protein annotation.

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

Identification of candidate genes for familial early-onset essential tremor.

Essential tremor (ET) is one of the most common causes of tremor in humans. Despite its high heritability and prevalence, few susceptibility genes for ET have been identified. To identify ET genes, whole-exome sequencing was performed in 37 early-onset ET families with an autosomal-dominant inheritance pattern. We identified candidate genes for follow-up functional studies in five ET families. In two independent families, we identified variants predicted to affect function in the nitric oxide (NO) synthase 3 gene (NOS3) that cosegregated with disease. NOS3 is highly expressed in the central nervous system (including cerebellum), neurons and endothelial cells, and is one of three enzymes that converts l-arginine to the neurotransmitter NO. In one family, a heterozygous variant, c.46G>A (p.(Gly16Ser)), in NOS3, was identified in three affected ET cases and was absent in an unaffected family member; and in a second family, a heterozygous variant, c.164C>T (p.(Pro55Leu)), was identified in three affected ET cases (dizygotic twins and their mother). Both variants result in amino-acid substitutions of highly conserved amino-acid residues that are predicted to be deleterious and damaging by in silico analysis. In three independent families, variants predicted to affect function were also identified in other genes, including KCNS2 (KV9.2), HAPLN4 (BRAL2) and USP46. These genes are highly expressed in the cerebellum and Purkinje cells, and influence function of the gamma-amino butyric acid (GABA)-ergic system. This is in concordance with recent evidence that the pathophysiological process in ET involves cerebellar dysfunction and possibly cerebellar degeneration with a reduction in Purkinje cells, and a decrease in GABA-ergic tone.

ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs.

Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) represent rare but serious adverse drug reactions (ADRs). Both are characterized by distinctive blistering lesions and significant mortality rates. While there is evidence for strong drug-specific genetic predisposition related to HLA alleles, recent genome wide association studies (GWAS) on European and Asian populations have failed to identify genetic susceptibility alleles that are common across multiple drugs. We hypothesize that this is a consequence of the low to moderate effect size of individual genetic risk factors. To test this hypothesis we developed Pointer, a new algorithm that assesses the aggregate effect of multiple low risk variants on a pathway using a gene set enrichment approach. A key advantage of our method is the capability to associate SNPs with genes by exploiting physical proximity as well as by using expression quantitative trait loci (eQTLs) that capture information about both cis- and trans-acting regulatory effects. We control for known bias-inducing aspects of enrichment based analyses, such as: 1) gene length, 2) gene set size, 3) presence of biologically related genes within the same linkage disequilibrium (LD) region, and, 4) genes shared among multiple gene sets. We applied this approach to publicly available SJS/TEN genome-wide genotype data and identified the ABC transporter and Proteasome pathways as potentially implicated in the genetic susceptibility of non-drug-specific SJS/TEN. We demonstrated that the innovative SNP-to-gene mapping phase of the method was essential in detecting the significant enrichment for those pathways. Analysis of an independent gene expression dataset provides supportive functional evidence for the involvement of Proteasome pathways in SJS/TEN cutaneous lesions. These results suggest that Pointer provides a useful framework for the integrative analysis of pharmacogenetic GWAS data, by increasing the power to detect aggregate effects of multiple low risk variants. The software is available for download at https://sourceforge.net/projects/pointergsa/.

The support of human genetic evidence for approved drug indications.

Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.

Genome wide analysis of drug-induced torsades de pointes: lack of common variants with large effect sizes.

Marked prolongation of the QT interval on the electrocardiogram associated with the polymorphic ventricular tachycardia Torsades de Pointes is a serious adverse event during treatment with antiarrhythmic drugs and other culprit medications, and is a common cause for drug relabeling and withdrawal. Although clinical risk factors have been identified, the syndrome remains unpredictable in an individual patient. Here we used genome-wide association analysis to search for common predisposing genetic variants. Cases of drug-induced Torsades de Pointes (diTdP), treatment tolerant controls, and general population controls were ascertained across multiple sites using common definitions, and genotyped on the Illumina 610k or 1M-Duo BeadChips. Principal Components Analysis was used to select 216 Northwestern European diTdP cases and 771 ancestry-matched controls, including treatment-tolerant and general population subjects. With these sample sizes, there is 80% power to detect a variant at genome-wide significance with minor allele frequency of 10% and conferring an odds ratio of ≥2.7. Tests of association were carried out for each single nucleotide polymorphism (SNP) by logistic regression adjusting for gender and population structure. No SNP reached genome wide-significance; the variant with the lowest P value was rs2276314, a non-synonymous coding variant in C18orf21 (p  =  3×10(-7), odds ratio = 2, 95% confidence intervals: 1.5-2.6). The haplotype formed by rs2276314 and a second SNP, rs767531, was significantly more frequent in controls than cases (p  =  3×10(-9)). Expanding the number of controls and a gene-based analysis did not yield significant associations. This study argues that common genomic variants do not contribute importantly to risk for drug-induced Torsades de Pointes across multiple drugs.

Using systems and structure biology tools to dissect cellular phenotypes.

The Center for the Multiscale Analysis of Genetic Networks (MAGNet, http://magnet.c2b2.columbia.edu) was established in 2005, with the mission of providing the biomedical research community with Structural and Systems Biology algorithms and software tools for the dissection of molecular interactions and for the interaction-based elucidation of cellular phenotypes. Over the last 7 years, MAGNet investigators have developed many novel analysis methodologies, which have led to important biological discoveries, including understanding the role of the DNA shape in protein-DNA binding specificity and the discovery of genes causally related to the presentation of malignant phenotypes, including lymphoma, glioma, and melanoma. Software tools implementing these methodologies have been broadly adopted by the research community and are made freely available through geWorkbench, the Center's integrated analysis platform. Additionally, MAGNet has been instrumental in organizing and developing key conferences and meetings focused on the emerging field of systems biology and regulatory genomics, with special focus on cancer-related research.

HLA-B*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin.

Drug-induced liver injury (DILI) is an important cause of serious liver disease. The antimicrobial agent flucloxacillin is a common cause of DILI, but the genetic basis for susceptibility remains unclear. We conducted a genome-wide association (GWA) study using 866,399 markers in 51 cases of flucloxacillin DILI and 282 controls matched for sex and ancestry. The GWA showed an association peak in the major histocompatibility complex (MHC) region with the strongest association (P = 8.7 x 10(-33)) seen for rs2395029[G], a marker in complete linkage disequilibrium (LD) with HLA-B*5701. Further MHC genotyping, which included 64 flucloxacillin-tolerant controls, confirmed the association with HLA-B*5701 (OR = 80.6, P = 9.0 x 10(-19)). The association was replicated in a second cohort of 23 cases. In HLA-B*5701 carrier cases, rs10937275 in ST6GAL1 on chromosome 3 also showed genome-wide significance (OR = 4.1, P = 1.4 x 10(-8)). These findings provide new insights into the mechanism of flucloxacillin DILI and have the potential to substantially improve diagnosis of this serious disease.