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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.

Producción Científica, 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 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 a human leukocyte antigen (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=0.0015). 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=0.005). Additional, population-dependent effects were observed in HLA alleles with nominal significance. In an analysis of auto-immunerelated 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.

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.

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.

In the past few years, pattern discovery has been emerging as a generic tool of choice for tackling problems from the computational biology domain. In this presentation, and after defining the problem in its generality, we review some of the algorithms that have appeared in the literature and describe several applications of pattern discovery to problems from computational biology.

MOTIVATION: The discovery of motifs in biological sequences is an important problem. RESULTS: This paper presents a new algorithm for the discovery of rigid patterns (motifs) in biological sequences. Our method is combinatorial in nature and able to produce all patterns that appear in at least a (user-defined) minimum number of sequences, yet it manages to be very efficient by avoiding the enumeration of the entire pattern space. Furthermore, the reported patterns are maximal: any reported pattern cannot be made more specific and still keep on appearing at the exact same positions within the input sequences. The effectiveness of the proposed approach is showcased on a number of test cases which aim to: (i) validate the approach through the discovery of previously reported patterns; (ii) demonstrate the capability to identify automatically highly selective patterns particular to the sequences under consideration. Finally, experimental analysis indicates that the algorithm is output sensitive, i.e. its running time is quasi-linear to the size of the generated output.

Idiosyncratic drug-induced liver injury (DILI) is a leading cause of morbidity and mortality due to medication use yet is poorly studied, in part, due to its low incidence in the general population. Identification of genetic variants associated with these uncommon and difficult to diagnose adverse events could provide clues to underlying mechanisms. Hypothesis: Common genetic variants exist that contribute to DILI susceptibility from multiple drugs. Methods: DNA obtained from 783 individuals of European ancestry who experienced DILI attributed to >200 individual drugs were genotypedwith the Illumina 1Mor 1Mduo beadchip. Source of DNA samples included the following DILI registries: DILIN (401), DILIGEN (242), EUDRAGENE (89), and Malaga (51). Genome Wide Association (GWA) was performed using population controls (n=3001). Potential associations were tested for replication in 190 independent cases from DILIN. Results: GWA revealed a strong association within the MHC region (p 108), which did not replicate in validation cohorts composed of sufficient cases due to the same drug or class. Conclusion: Our replicated association between hepatocellular DILI and STAT4 supports the emerging role of the immune system in DILI susceptibility and suggests that common genetic variation may contribute to DILI susceptibility from multiple drugs. However, the generally negative GWA results suggest that there may be a preponderance of drug-specific genetic risk factors and/or rare genetic variation underlying DILI susceptibility. Therefore, we have begun whole exome and whole genome sequencing of DILI cases caused by the most frequent drugs in our cohorts in search of rarer, high-penetrance drug-specific risk factors.

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/.