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PURPOSEThe terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation, and to support variant classification within the ACMG/AMP framework.METHODSTerminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition (GenCC) members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.RESULTSWe present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both sequence ontology (SO) and human phenotype ontology (HPO) ontologies. GenCC member groups intend to use or map to these terms in their respective resources.CONCLUSIONThe terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection.METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis.RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives.CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.).

Clinical validity assessments of gene-disease associations underpin analysis and reporting in diagnostic genomics, and yet wide variability exists in practice, particularly in use of these assessments for virtual gene panel design and maintenance. Harmonization efforts are hampered by the lack of agreed terminology, agreed gene curation standards, and platforms that can be used to identify and resolve discrepancies at scale. We undertook a systematic comparison of the content of 80 virtual gene panels used in two healthcare systems by multiple diagnostic providers in the United Kingdom and Australia. The process was enabled by a shared curation platform, PanelApp, and resulted in the identification and review of 2,144 discordant gene ratings, demonstrating the utility of sharing structured gene-disease validity assessments and collaborative discordance resolution in establishing national and international consensus.

T-cell non-Hodgkin’s lymphomas develop following transformation of tissue resident T-cells. We performed a meta-analysis of whole exome sequencing data from 403 patients with eight subtypes of T-cell non-Hodgkin’s lymphoma to identify mutational signatures and associated recurrent gene mutations. Signature 1, indicative of age-related deamination, was prevalent across all T-cell lymphomas, reflecting the derivation of these malignancies from memory T-cells. Adult T-cell leukemia-lymphoma was specifically associated with signature 17, which was found to correlate with the IRF4 K59R mutation that is exclusive to Adult T-cell leukemia-lymphoma. Signature 7, implicating UV exposure was uniquely identified in cutaneous T-cell lymphoma (CTCL), contributing 52% of the mutational burden in mycosis fungoides and 23% in Sezary syndrome. Importantly this UV signature was observed in CD4 + T-cells isolated from the blood of Sezary syndrome patients suggesting extensive re-circulation of these T-cells through skin and blood. Analysis of non-Hodgkin’s T-cell lymphoma cases submitted to the national 100,000 WGS project confirmed that signature 7 was only identified in CTCL strongly implicating UV radiation in the pathogenesis of cutaneous T-cell lymphoma.

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.

BACKGROUND: Repeat expansion disorders affect about 1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in underdiagnosis of people who have atypical clinical presentations, especially in paediatric patients without a previous positive family history. Whole genome sequencing is increasingly used as a first-line test for other rare genetic disorders, and we aimed to assess its performance in the diagnosis of patients with neurological repeat expansion disorders.METHODS: We retrospectively assessed the diagnostic accuracy of whole genome sequencing to detect the most common repeat expansion loci associated with neurological outcomes (AR, ATN1, ATXN1, ATXN2, ATXN3, ATXN7, C9orf72, CACNA1A, DMPK, FMR1, FXN, HTT, and TBP) using samples obtained within the National Health Service in England from patients who were suspected of having neurological disorders; previous PCR test results were used as the reference standard. The clinical accuracy of whole genome sequencing to detect repeat expansions was prospectively examined in previously genetically tested and undiagnosed patients recruited in 2013-17 to the 100 000 Genomes Project in the UK, who were suspected of having a genetic neurological disorder (familial or early-onset forms of ataxia, neuropathy, spastic paraplegia, dementia, motor neuron disease, parkinsonian movement disorders, intellectual disability, or neuromuscular disorders). If a repeat expansion call was made using whole genome sequencing, PCR was used to confirm the result.FINDINGS: The diagnostic accuracy of whole genome sequencing to detect repeat expansions was evaluated against 793 PCR tests previously performed within the NHS from 404 patients. Whole genome sequencing correctly classified 215 of 221 expanded alleles and 1316 of 1321 non-expanded alleles, showing 97·3% sensitivity (95% CI 94·2-99·0) and 99·6% specificity (99·1-99·9) across the 13 disease-associated loci when compared with PCR test results. In samples from 11 631 patients in the 100 000 Genomes Project, whole genome sequencing identified 81 repeat expansions, which were also tested by PCR: 68 were confirmed as repeat expansions in the full pathogenic range, 11 were non-pathogenic intermediate expansions or premutations, and two were non-expanded repeats (16% false discovery rate).INTERPRETATION: In our study, whole genome sequencing for the detection of repeat expansions showed high sensitivity and specificity, and it led to identification of neurological repeat expansion disorders in previously undiagnosed patients. These findings support implementation of whole genome sequencing in clinical laboratories for diagnosis of patients who have a neurological presentation consistent with a repeat expansion disorder.FUNDING: Medical Research Council, Department of Health and Social Care, National Health Service England, National Institute for Health Research, and Illumina.

PURPOSESeveral groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease, and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.METHODSThe GenCC drafted harmonized definitions for differing levels of gene-disease validity based on existing resources, and performed a modified Delphi survey with three rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members.RESULTSBased on 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contains 15,241 gene-disease assertions on 4,569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%.CONCLUSIONTerminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

A fundamental problem in rare-disease diagnostics is the lack of consensus as to which genes have sufficient evidence to attribute causation. To address this issue, we have created PanelApp ( https://panelapp.genomicsengland.co.uk ), a publicly available knowledge base of curated virtual gene panels.

Hannu Laaksovirta konsortion jäsenenä. The Genomics England Research Consortium, The International ALS/FTD Genomics Consortium (iAFGC), The International FTD Genetics Consortium (IFGC), The International LBD Genomics Consortium (iLBDGC), The NYGC ALS Consortium, The PROSPECT Consortium,17 James B. Rowe,17 Luisa Benussi,18 Giuliano Binetti,18,19 Roberta Ghidoni,18 Edwin Jabbari,20,21 Coralie Viollet,22 Jonathan D. Glass,23 Andrew B. Singleton,24 Vincenzo Silani,25,26 Owen A. Ross,27 Mina Ryten,8,28,29 Ali Torkamani,30 Toshiko Tanaka,31 Luigi Ferrucci,31 Susan M. Resnick,32 We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40?64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington?s disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered. We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40?64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington?s disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered.

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target–disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive.

BackgroundRepeat expansion (RE) disorders affect ~1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in under diagnosis of atypical clinical presentations, especially in paediatric patients without a prior positive family history. Whole genome sequencing (WGS) is emerging as a first-line test for rare genetic disorders, but until recently REs were thought to be undetectable by this approach.MethodsWGS pipelines for RE disorder detection were deployed by the 100,000 Genomes Project and Illumina Clinical Services Laboratory. Performance was retrospectively assessed across the 13 most common neurological RE loci using 793 samples with prior orthogonal testing (182 with expanded alleles and 611 with alleles within normal size) and prospectively interrogated in 13,331 patients with suspected genetic neurological disorders.FindingsWGS RE detection showed minimum 97·3% sensitivity and 99·6% specificity across all 13 disease-associated loci. Applying the pipeline to patients from the 100,000 Genomes Project identified pathogenic repeat expansions which were confirmed in 69 patients, including seven paediatric patients with no reported family history of RE disorders, with a 0.09% false positive rate.InterpretationWe show here for the first time that WGS enables the detection of causative repeat expansions with high sensitivity and specificity, and that it can be used to resolve previously undiagnosed neurological disorders. This includes children with no prior suspicion of a RE disorder. These findings are leading to diagnostic implementation of this analytical pipeline in the NHS Genomic Medicine Centres in England.FundingMedical Research Council, Department of Health and Social Care, National Health Service England, National Institute for Health Research, Illumina Inc

SOX6 belongs to a family of 20 SRY-related HMG-box-containing (SOX) genes that encode transcription factors controlling cell fate and differentiation in many developmental and adult processes. For SOX6, these processes include, but are not limited to, neurogenesis and skeletogenesis. Variants in half of the SOX genes have been shown to cause severe developmental and adult syndromes, referred to as SOXopathies. We here provide evidence that SOX6 variants also cause a SOXopathy. Using clinical and genetic data, we identify 19 individuals harboring various types of SOX6 alterations and exhibiting developmental delay and/or intellectual disability; the individuals are from 17 unrelated families. Additional, inconstant features include attention-deficit/hyperactivity disorder (ADHD), autism, mild facial dysmorphism, craniosynostosis, and multiple osteochondromas. All variants are heterozygous. Fourteen are de novo, one is inherited from a mosaic father, and four offspring from two families have a paternally inherited variant. Intragenic microdeletions, balanced structural rearrangements, frameshifts, and nonsense variants are predicted to inactivate the SOX6 variant allele. Four missense variants occur in residues and protein regions highly conserved evolutionarily. These variants are not detected in the gnomAD control cohort, and the amino acid substitutions are predicted to be damaging. Two of these variants are located in the HMG domain and abolish SOX6 transcriptional activity in vitro. No clear genotype-phenotype correlations are found. Taken together, these findings concur that SOX6 haploinsufficiency leads to a neurodevelopmental SOXopathy that often includes ADHD and abnormal skeletal and other features.

Pharmacogenomics (PGx) can be seen as a model for biomedical studies: it includes all disease areas of interest and spans in vitro studies to clinical trials, while focusing on the relationships between genes and drugs and the resulting phenotypes. This review will examine different characteristics of PGx study publications and provide examples of excellence in framing PGx questions and reporting their resulting data in a way that maximizes the knowledge that can be built on them.

Although over 150 unique mutations affecting the coding sequence of CHM have been identified in patients with the X-linked chorioretinal disease choroideremia (CHM), no regulatory mutations have been reported, and indeed the promoter has not been defined. Here, we describe two independent families affected by CHM bearing a mutation outside the gene's coding region at position c.-98: C>A and C>T, which segregated with the disease. The male proband of family 1 was found to lack CHM mRNA and its gene product Rab escort protein 1, whereas whole-genome sequencing of an affected male in family 2 excluded the involvement of any other known retinal genes. Both mutations abrogated luciferase activity when inserted into a reporter construct, and by further employing the luciferase reporter system to assay sequences 5' to the gene, we identified the CHM promoter as the region encompassing nucleotides c.-119 to c.-76. These findings suggest that the CHM promoter region should be examined in patients with CHM who lack coding sequence mutations, and reveals, for the first time, features of the gene's regulation.

Background and aims Between July 2016 and September 2018, NHS Genomic Medicine Centres (GMCs) recruited families with specified rare diseases to the 100,000 Genomes Project for whole genome sequencing (WGS), and linkage to phenotypic information from NHS Health Records. Methods Genomics England protocols were followed for disease nominations, data model generation based on human phenotype ontology (HPO) terms,1 and development/review of PanelApp gene panels.2 Genomics England performed all WGS, data alignments, and initial variant tiering. This incorporated appropriate familial segregation patterns for variants in genes known to cause the patient‘s disease (Tier 1: clear loss of function variants, Tier2: other variants), and clear loss of function or de novo variants in other genes (Tier 3). The Respiratory GeCIP (Clinical Interpretation Partnership) was established to analyse full WGS/phenotypic datasets. Results Six respiratory diseases were nominated and passed through 100K pipelines: primary ciliary dyskinesia (PCD), familial pulmonary fibrosis (FPF), aggressive non-CF bronchiectasis, pulmonary arteriovenous malformations (PAVMs), hereditary haemorrhagic telangiectasia (HHT) and familial pneumothorax. National and international networks were established for each, including a focus on patient/public engagement. Patient results were returned to UK GMCs from August 2017. Recruited participants with recessive and dominant diseases each had 0–2 Tier 1 variants, 0–2 Tier 2 variants and up to 536 Tier 3 variants. Genomic diagnoses have been fed back to 57 respiratory families for 15 different genes in PCD, FPF, non-CF bronchiectasis, and PAVMs/HHT, already modifying PanelApp, with validations in two potentially new ciliopathy genes in progress. Full WGS results have been released quarterly to the Research Data Embassy at steadily increasing numbers. HPO term capture identifies further patients; for example, there are data on 269 families recruited with bronchiectasis plus another 27 with relevant HPO terms. Respiratory GeCIP Data Embassy access and Projects were secured through 2018–2019. New analytic resources available through the Data Embassy (particularly LabKey and IVA 2.0) enable >90 Domain members to identify annotated variants through indexed systems. Custom scripts are being used to access variant information from the whole genome. Conclusions The Respiratory GeCIP has established a collaborative resource for the advancement of NHS Respiratory Genomics. References http://human-phenotype-ontology.github.io/ https://bioinfo.extge.co.uk/crowdsourcing/PanelApp

Cilia are highly specialized cellular organelles that serve multiple functions in human development and health. Their central importance in the body is demonstrated by the occurrence of a diverse range of developmental disorders that arise from defects of cilia structure and function, caused by a range of different inherited mutations found in more than 150 different genes. Genetic analysis has rapidly advanced our understanding of the cell biological basis of ciliopathies over the past two decades, with more recent technological advances in genomics rapidly accelerating this progress. The 100,000 Genomes Project was launched in 2012 in the UK to improve diagnosis and future care for individuals affected by rare diseases like ciliopathies, through whole genome sequencing (WGS). In this review we discuss the potential promise and medical impact of WGS for ciliopathies and report on current progress of the 100,000 Genomes Project, reviewing the medical, technical and ethical challenges and opportunities that new, large scale initiatives such as this can offer.

Background: Highly accurate next-generation sequencing (NGS) of genetic variants is key to many areas of science and medicine, such as cataloguing population genetic variation and diagnosing patients with genetic diseases. Certain genomic loci and regions can be prone to higher rates of systematic sequencing and alignment bias that pose a challenge to achieving high accuracy, resulting in false positive variant calls. Current standard practices to differentiate between loci that can and cannot be sequenced with high confidence utilise consensus between different sequencing methods as a proxy for sequencing confidence. This assumption is not accurate in cases where all sequencing pipelines have consensus on the same errors due to similar systematic biases in sequencing. Alternative methods are therefore required to identify systematic biases. Methods: We have developed a novel statistical method based on summarising sequenced reads from whole genome clinical samples and cataloguing them in "Incremental Databases" (IncDBs) that maintain individual confidentiality. Variant statistics were analysed and catalogued for each genomic position that consistently showed systematic biases with the corresponding sequencing pipeline. Results: We have demonstrated that systematic errors in NGS data are widespread, with persistent low-fraction alleles present at 1.26-2.43% of the human autosomal genome across three different Illumina-based pipelines, each consisting of at least 150 patient samples. We have identified a variety of genomic regions that are more or less prone to systematic biases, such as GC-rich regions (OR = 6.47-8.19) and the NIST high-confidence genomic regions (OR = 0.154-0.191). We have verified our predictions on a gold-standard reference genome and have shown that these systematic biases can lead to suspect variant calls at clinically important loci, including within introns and exons. Conclusions: Our results recommend increased caution to minimise the effect of systematic biases in whole genome sequencing and alignment. This study supports the utility of a statistical approach to enhance quality control of clinically sequenced samples in order to flag up variant calls made at known suspect loci for further analysis or exclusion, using anonymised summary databases from which individual patients cannot be re-identified, so that results can be shared more widely.

Ivacaftor [VX-770; N-(2,4-Di-tert-butyl-5-hydroxyphenyl)-4-oxo-1,4-dihydroquinoline-3-carboxamide] is one of the first drugs developed to treat an underlying cause of cystic fibrosis (CF) rather than the symptoms. It is a selective small molecule potentiator of the Cystic Fibrosis Transmembrane Conductance Regulator protein (CFTR). Potentiators are a new drug class of CFTR modulators designed to restore CFTR function [1]. The Food and Drug Administration (FDA) has granted ivacaftor orphan drug status because it is indicated in a subset of patients with particular CFTR variants, specifically class III variants. Approximately 30,000 people have CF in the United States, which is below the 200,000 patient threshold for orphan drugs in the United States [1]. CF is an autosomal recessive disorder characterized by sweat chloride concentration above 60 mmol/L, leading to progressive obstructive lung disease and premature mortality, as well as problems in the liver, pancreas, vas deferens, and intestine [2]. CF affects approximately 70,000 people worldwide [3], including approximately 1 of every 3500 infants born in the United States [4], and is caused by inheriting two detrimental copies of the CFTR gene. The CFTR protein is a chloride channel, which maintains ion and water balance intra- and extra-cellularly [5]. The channel opens and closes through ATP binding, hydrolysis, and phosphorylation, which changes the protein conformation to allow chloride ions to flow through the ion gradient between the intracellular and extracellular regions [2]. Defective CFTR function prevents the flow of chloride ions across epithelial cells, which leads to the mucus buildup, infection, inflammation, and progressively decreasing lung function that is characteristic of cystic fibrosis [5].

To facilitate precision medicine and neuroscience research, we developed a machine-learning technique that scores the likelihood that a gene, when mutated, will cause a neurological phenotype. We analysed 1126 genes relating to 25 subtypes of Mendelian neurological disease defined by Genomics England (March 2017) together with 154 gene-specific features capturing genetic variation, gene structure and tissue-specific expression and co-expression. We randomly re-sampled genes with no known disease association to develop bootstrapped decision-tree models, which were integrated to generate a decision tree-based ensemble for each disease subtype. Genes generating larger numbers of distinct transcripts and with higher probability of having missense mutations in normal individuals were significantly more likely to cause neurological diseases. Using mouse-mutant phenotypic data we tested the accuracy of gene-phenotype predictions and found that for 88% of all disease subtypes there was a significant enrichment of relevant phenotypic abnormalities when predicted genes were mutated in mice and in many cases mutations produced specific and matching phenotypes. Furthermore, using only newly identified genes included in the Genomics England November 2017 release, we assessed our gene-phenotype predictions and showed an 8.3 fold enrichment relative to chance for correct predictions. Thus, we demonstrate both the explanatory and predictive power of machine-learning-based models in neurological disease.

As pharmacogenomics becomes integrated into clinical practice, curation of published studies becomes increasingly important. At the Pharmacogenomics Knowledgebase (PharmGKB; www.pharmgkb.org), pharmacogenetic associations reported in published articles are manually curated and evaluated.[1] Standard terminologies are used, making findings uniform and unambiguous. Lack of information, clarity, or standards in the original report can make it difficult or impossible to curate. We provide 10 rules to help authors ensure that their results are accurately captured and integrated.

Glucose‐6‐phosphate dehydrogenase (G6PD) deficiency is associated with development of acute hemolytic anemia (AHA) induced by a number of drugs. We provide guidance as to which G6PD genotypes are associated with G6PD deficiency in males and females. Rasburicase is contraindicated in G6PD‐deficient patients due to the risk of AHA and possibly methemoglobinemia. Unless preemptive genotyping has established a positive diagnosis of G6PD deficiency, quantitative enzyme assay remains the mainstay of screening prior to rasburicase use. The purpose of this article is to help interpret the results of clinical G6PD genotype tests so that they can guide the use of rasburicase. Detailed guidelines on other aspects of the use of rasburicase, including analyses of cost‐effectiveness, are beyond the scope of this document. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines are published and updated periodically on https://www.pharmgkb.org/page/cpic to reflect new developments in the field.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines.

The many uses of methylene blue Methylene blue (methylthioninium chloride) is a ‘jack of all trades’ with a litany of clinical uses. In vivo, it is indicated for use as a therapy for drug-induced methemoglobinemia [1-3], can be used for the treatment of infections, pathologies, or poisoning, and as a dye for diagnostics. It is also commonly used as a dye in vitro – for example, as a component in staining of cells, tissues, DNA, parasites, and bacteria [4-6]. In the 1890s, Ehrlich demonstrated its use to target the malarial parasite, and more recently it has been reinvestigated for inclusion in antimalarial regimens in the wake of parasite drug resistance [7-9]. Further examples of its clinical use include treatment of ifosfamide-induced neurotoxicity (although treatment has been reported ineffective), an antidote for cyanide poisoning, visualization of fallopian tubes or ruptured membranes, a marker of tumors, and even as a potential therapy for septic shock and ischemic brain injury [5,8,10-18]. In phase II clinical trials, a modified version of methylene blue is reported to slow cognitive decline in mild–moderate Alzheimer’s disease patients compared to placebo, and phase III trials are planned, although these results remain unpublished [19]. The mechanism of action is unclear – possibly by preventing tau protein aggregation or increasing amyloid-β clearance by enhancing proteasome activities [19,20]. As a photodynamic therapy, methylene blue could be used to treat psoriasis, West Nile virus infection, AIDS-related Kaposi’s sarcoma, antibiotic-resistant bacterial strains and decontaminate blood before transfusion [5,21-25]. Methylene blue has also contributed to drug development, forming the structural chemical basis of other therapeutic drugs, including the antimalarial drug, chloroquine; the antihistamine, promethazine; and the antipsychotic, chlorpromazine [5]. Acknowledging the many uses of methylene blue, this article focuses on the pharmacodynamics of methylene blue in the context of methemoglobinemia treatment and the pathways surrounding this, due to known pharmacogenetic associations that relate to these pathways.

The drug-metabolizing enzyme thiopurine methyltransferase (TPMT) has become one of the best examples of pharmacogenomics to be translated into routine clinical practice. TPMT metabolizes the thiopurines 6-mercaptopurine, 6-thioguanine, and azathioprine, drugs that are widely used for treatment of acute leukemias, inflammatory bowel diseases, and other disorders of immune regulation. Since the discovery of genetic polymorphisms in the TPMT gene, many sequence variants that cause a decreased enzyme activity have been identified and characterized. Increasingly, to optimize dose, pretreatment determination of TPMT status before commencing thiopurine therapy is now routine in many countries. Novel TPMT sequence variants are currently numbered sequentially using PubMed as a source of information; however, this has caused some problems as exemplified by two instances in which authors’ articles appeared on PubMed at the same time, resulting in the same allele numbers given to different polymorphisms. Hence, there is an urgent need to establish an order and consensus to the numbering of known and novel TPMT sequence variants. To address this problem, a TPMT nomenclature committee was formed in 2010, to define the nomenclature and numbering of novel variants for the TPMT gene. A website (http://www.imh.liu.se/tpmtalleles) serves as a platform for this work. Researchers are encouraged to submit novel TPMT alleles to the committee for designation and reservation of unique allele numbers. The committee has decided to renumber two alleles: nucleotide position 106 (G > A) from TPMT*24 to TPMT*30 and position 611 (T > C, rs79901429) from TPMT*28 to TPMT*31. Nomenclature for all other known alleles remains unchanged.

Although over 150 unique mutations affecting the coding sequence of CHM have been identified in patients with the X-linked chorioretinal disease choroideremia (CHM), no regulatory mutations have been reported, and indeed the promoter has not been defined. Here, we describe two independent families affected by CHM bearing a mutation outside the gene's coding region at position c.-98: CA and CT, which segregated with the disease. The male proband of family 1 was found to lack CHM mRNA and its gene product Rab escort protein 1, whereas whole-genome sequencing of an affected male in family 2 excluded the involvement of any other known retinal genes. Both mutations abrogated luciferase activity when inserted into a reporter construct, and by further employing the luciferase reporter system to assay sequences 5' to the gene, we identified the CHM promoter as the region encompassing nucleotides c.-119 to c.-76. These findings suggest that the CHM promoter region should be examined in patients with CHM who lack coding sequence mutations, and reveals, for the first time, features of the gene's regulation.

The Pharmacogenomics Knowledgebase (PharmGKB) is a resource that collects, curates, and disseminates information about the impact of human genetic variation on drug responses. It provides clinically relevant information, including dosing guidelines, annotated drug labels, and potentially actionable gene–drug associations and genotype–phenotype relationships. Curators assign levels of evidence to variant–drug associations using well-defined criteria based on careful literature review. Thus, PharmGKB is a useful source of high-quality information supporting personalized medicine–implementation projects.

Departments of Genetics, Bioengineering, Stanford University Medical Center, Stanford, California, USA and Division of Clinical Pharmacology, Karolinska Institute, Stockholm, Sweden Correspondence to Dr Teri E. Klein, PhD, Department of Genetics, Stanford University Medical Center, 300 Pasteur D. Lane L301, Mail Code 5120, Stanford, CA 94305-5120, USA Tel: + 1 650 725 0659; fax: + 1 650 725 3863; e-mail: feedback@pharmgkb.org

Glucose-6-phosphate dehydrogenase (G6PD) was one of the first genes found to be associated with variable drug response. It is also very polymorphic, with G6PD deficiency found in more than 300 million people worldwide [1]. Here, we provide an overview of G6PD as a very important pharmacogene, and detail genetic variants and haplotypes associated with drug response (Although most G6PD variants are caused by single nucleotide polymorphisms (SNPs) in the coding region of the G6PD gene at the X chromosome, due to the heterogeneity of alleles causing G6PD deficiency; here, we use the term ‘haplotype’ to define the set of linked SNPs in a G6PD variant that are inherited together and that may or may not produce G6PD deficiency). A more in-depth report, with interactive links to individual literature annotations, can be found at http://www.pharmgkb.org/gene/PA28469.

In partnership with NHS England, Genomics England’s ambitious plans to embed genomic medicine into routine patient care are well underway. Clare Turnbull and colleagues discuss its progress

The chemokine CXCL4/platelet factor-4 is released by activated platelets in micromolar concentrations and is a chemoattractant for leukocytes via an unidentified receptor. Recently, a variant of the human chemokine receptor CXCR3 (CXCR3-B) was described, which transduced apoptotic but not chemotactic signals in microvascular endothelial cells following exposure to high concentrations of CXCL4. Here, we show that CXCL4 can induce intracellular calcium release and the migration of activated human T lymphocytes. CXCL4-induced chemotaxis of T lymphocytes was inhibited by a CXCR3 antagonist and pretreatment of cells with pertussis toxin (PTX), suggestive of CXCR3-mediated G-protein signaling via Gαi-sensitive subunits. Specific binding by T lymphocytes of the CXCR3 ligand CXCL10 was not effectively competed by CXCL4, suggesting that the two are allotopic ligands. We subsequently used expression systems to dissect the potential roles of each CXCR3 isoform in mediating CXCL4 function. Transient expression of the CXCR3-A and CXCR3-B isoforms in the murine pre-B cell L1.2 produced cells that migrated in response to CXCL4 in a manner sensitive to PTX and a CXCR3 antagonist. Binding of radiolabeled CXCL4 to L1.2 CXCR3 transfectants was of low affinity and appeared to be mediated chiefly by glycosaminoglycans (GAGs), as no specific CXCL4 binding was observed in GAG-deficient 745-Chinese hamster ovary cells stably expressing CXCR3. We suggest that following platelet activation, the CXCR3/CXCL4 axis may play a role in T lymphocyte recruitment and the subsequent amplification of inflammation observed in diseases such as atherosclerosis. In such a setting, antagonism of the CXCR3/CXCL4 axis may represent a useful, therapeutic intervention.

The application of surgical treatments is greatly enhanced by the availability of anesthetic agents, such as neuromuscular blockers. Succinylcholine chloride (2,2′-[(1,4-dioxo-1, 4-butanediyl) bis (oxy)] bis [N, N, N-trimethylethanaminium] dichloride), also known as suxamethonium chloride, is a depolarizing neuromuscular blocking agent (NMBA) on the World Health Organization's List of Essential Medicines. Because of its rapid onset of action and short half-life, it is commonly used in medical procedures that require short-term skeletal muscle paralysis, including rapid intubation in emergency medical situations. The clinical application of succinylcholine (SCH) is tempered by the occurrence of rare, but dramatic adverse reactions and some were the earliest known examples of pharmacogenetics. In many cases, patients with functionally characterized single nucleotide polymorphisms (SNPs) in specific genes in either the pharmacokinetic (PK) or pharmacodynamic (PD) pathways of SCH are at increased risk of these adverse reactions. The ubiquity of SCH in medical procedures makes understanding the pharmacogenomics of SCH critical for identifying susceptible patients such that suitable interventions and alternatives may be utilized. Figure 1 illustrates the PD and PK pathways of SCH and a fully interactive version of these pathways can be accessed at PharmGKB (https://www.pharmgkb.org/pathway/PA166122732). Figure 1 Stylized cells depicting the metabolism and mechanism of action of succinylcholine. Note: the star symbol on the DHPR indicates that it has been activated by depolarization of the t-tubules. A fully interactive version is available at PharmGKB http://www.pharmgkb.org/pathway/PA166122732 ... Pharmacodynamics Structurally, SCH consists of two acetylcholine (ACh) molecules linked end to end by their acetyl groups [1, 2]. ACh is the endogenous agonist of the nicotinic acetylcholine receptor (nAChR), a ligand-gated, non-specific cation channel that is formed by five sub-units organized around a central pore. There are two α1 subunits, and one β1, δ, and e sub-units. Each sub-unit of the nACHR is encoded by one of four genes (α1 is encoded by CHRNA1, β1 is encoded by CHRNB1, δ is encoded by CHRND, and e is encoded by CHRNE) (Figure 1). The nAChR is located on the motor end plate of neuromuscular junction (NMJ) of the skeletal muscle membrane, also known as the sarcolemma. Binding of an agonist, such as ACh or SCH, promotes the open state of the channel. When the nAChR opens, sodium ions rush into the cell and potassium ions rush out resulting in membrane depolarization and generation of an action potential. In myocytes, depolarization stimulates muscle contraction [3-5]. L-type voltage gated calcium channels, also known as dihydropyridine receptors (DHPR), are located on invaginations of the sarcolemma called the transverse tubules (T-tubules). The DHPR is a complex of four sub-units (α1, α2δ, β, γ) and a distinct gene encodes each sub-unit. CACNA1S encodes the α1 sub-unit (also called Cav1.1), the primary sub-unit of the channel that contains the voltage sensor, gating apparatus and channel pore of DHPR [6]. The DHPR is mechanically coupled to the ryanodine receptor (RYR1), a homotetrameric voltage gated calcium channel that is located on the sarcoplasmic reticulum (SR) and encoded by the RYR1 gene [7] (Figure 1). When skeletal muscles are at rest, the troponin complex allosterically inhibits the formation of a cross-bridge between myosin and actin. When calcium is released into the myoplasm, it binds the troponin complex and allows myosin to bind to actin to initiate muscle contraction and continues for as long as ATP is freely available [8]. Upon depolarization of the sarcolemma, the DHPR undergoes a conformational change and transmits a signal to RYR1, which opens to release SR calcium stores into the myoplasm to initiate muscle contraction. Muscle relaxation occurs when calcium ATPases on the sarcoplasmic reticulum (SERCA) remove calcium from the myoplasm and pump it back into the SR [9]. Because it is a depolarizing NMBA, SCH first induces muscle fasiculations followed by flaccid muscle paralysis. SCH takes effect within 60 seconds of intravenous administration and paralysis lasts between 4-6 minutes during which time patients are monitored with an electric nerve stimulator [1]. Because of its short half-life SCH is indicated for medical procedures requiring short-term muscle paralysis, such as endotracheal intubation, neuromuscular surgery, and electroconvulsive therapy. Because SCH paralyzes the respiratory muscles, patients require mechanical ventilation and close monitoring for the duration of paralysis. It has no direct effect on smooth or cardiac muscle contraction. SCH is often administered in combination with other anesthetics, analgesics and narcotics because although it blocks muscle contraction it has no effect on pain perception [1, 2, 10].

The Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for HLA-B*58:01 Genotype and Allopurinol Dosing was originally published in February 2013. We reviewed the recent literature and concluded that none of the evidence would change the therapeutic recommendations in the original guideline; therefore, the original publication remains clinically current. However, we have updated the Supplemental Material and included additional resources for applying CPIC guidelines into the electronic health record. Up-to-date information can be found at PharmGKB (http://www.pharmgkb.org).

The cystic fibrosis transmembrane conductance regulator (CFTR, ATP-binding cassette sub-family C, member 7, ABCC7) protein is 1480 amino acids in length. It is encoded by a single large gene with 27 exons spanning around 250kbp on chromosome 7q31.2, identified in the search to find the gene underlying cystic fibrosis (CF) disease [1–4]. The protein structure is made up of two units, each with six transmembrane helices and an intracellular nucleotide-binding domain (NBD) that can interact with adenosine triphosphate (ATP). A regulatory “R” domain connects the two units and contains sites for protein kinase phosphorylation [1]. The structure creates a channel in the plasma membrane through which anions can flow, and the gate is thought to be opened and closed by ATP binding and hydrolysis (NBDs) and phosphorylation mechanisms (R domain) which alter the protein’s conformation [1, 5, 6]. CFTR is expressed predominantly in epithelial tissues, but is also found in other cell types such as smooth muscle, cardiac myocytes, macrophages, and erythrocytes [1]. CFTR is multi-functional. It is an anion channel that transports chloride (Cl−) and bicarbonate. It is also involved in the regulation of a range of transporters including the epithelial sodium channel (ENaC encoded by SCNN1A, SCNN1B, SCNN1D and SCNN1G) and outwardly rectifying chloride channels (ORCC) [1, 7–10]. In addition, CFTR has been proposed to be a hub for signaling pathways and may regulate a variety of other physiological processes including exocytosis and endocytosis, ATP export, proinflammatory cytokine expression and intracellular pH [1, 10]. Defective CFTR therefore results in widespread cellular homeostasis dysfunction [10]. CF is an autosomal recessive disease resulting from a defect-causing variant on each CFTR allele. More than 1800 variants in the CFTR gene have been reported [11]. Despite a large collection of variants, there is a gap in our knowledge regarding which cause CF disease. To address this, the Clinical and Functional Translation of CFTR project was established to collect information regarding the functional consequences and resulting phenotypes associated with CFTR variants [12, 13]. Data for 39,696 subjects from 25 CF patient registries or specialty clinics were collected for the database, and an initial set of 159 CFTR variants (those with a frequency of ≥0.01% in the CFTR2 database) was evaluated for whether they cause CF disease by both clinical phenotype and functional analysis [12]. A variant was defined clinically as causing CF if mean sweat chloride concentration was ≥60mM for at least three individuals with the variant or >90mM if only 2 individuals with the variant were available; 140 variants met the clinical criteria to be CF-causing. The variants were sorted by their predicted functional effect, and 77 were investigated further using in vitro assays appropriate to the genetic variant (

Disorders involving uric acid including gout, hyperuricemia and resultant kidney failure are prevalent. There are three main groups of pharmaceuticals used for modulating uric acid: 1. Drugs that reduce the generation of uric acid (allopurinol and febuxistat), 2. Those that increase the removal of uric acid (rasburicase, pegloticase), (both depicted in Figure 1) or 3. Those that inhibit the reabsorption of uric acid (depicted in Figure 3). This summary briefly describes the mechanisms of action and the candidate genes and genetic variants associated with response to these drugs. Clinically relevant genetic variants have been identified for allopurinol and rasburicase, and CPIC guidelines have been published that recommend selection of alternative treatments for some individuals. A more extensive description and interactive version can be found for each pathway at www.pharmgkb.org. Figure 1 Uric acid-lowering drugs pathway, Pharmacodynamics Figure 3 Uricosurics pathway, Pharmacodynamics 1) Drugs that reduce the generation of uric acid: allopurinol and febuxostat Pharmacodynamics Allopurinol is a drug indicated for the treatment of gout, prophylaxis of hyperuricemia in patients undergoing chemotherapy, and prevention of kidney stones recurrence [1]. Allopurinol and its metabolite oxypurinol are analogues of hypoxanthine and xanthine, respectively, and work by binding to and inhibiting xanthine dehydrogenase (XDH), preventing the formation of uric acid (Figure 1) [1–5]. Hypoxanthine and xanthine are cleared in the urine or reutilized in the synthesis of nucleotides and nucleic acids [1, 6]. Febuxostat (Uloric®) is a non-purine inhibitor of XDH that can bind to and inhibit both oxidized or reduced forms of XDH (Figure 1) [2, 7, 8]. It is indicated for the treatment of hyperuricemia in patients with gout (but not for asymptomatic hyperuricemia) [9], and is an alternative therapy for patients where allopurinol has been contraindicated due to allergic responses [7, 8, 10]. A downside to allopurinol/febuxostat treatment is that existing high levels of plasma uric acid are not cleared and, as xanthine is less soluble than uric acid, xanthine kidney stones or xanthine nephropathy may result [3, 6].

Cystic fibrosis (CF) is a life-shortening disease arising as a consequence of mutations within the CFTR gene. Novel therapeutics for CF are emerging that target CF transmembrane conductance regulator protein (CFTR) defects resulting from specific CFTR variants. Ivacaftor is a drug that potentiates CFTR gating function and is specifically indicated for CF patients with a particular CFTR variant, G551D-CFTR (rs75527207). Here, we provide therapeutic recommendations for ivacaftor based on preemptive CFTR genotype results.