Emmanuel Farber: In Memoriam (1918–2014)

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Targeted next generation sequencing as a tool for precision medicine

Background: Targeted next-generation sequencing (NGS) enables rapid identification of common and rare genetic variation. The detection of variants contributing to therapeutic drug response or adverse effects is essential for implementation of individualized pharmacotherapy. Successful application of short-read based NGS to pharmacogenes with high sequence homology, nearby pseudogenes and complex structure has been previously shown despite anticipated technical challenges. However, little is known regarding the utility of such panels to detect copy number variation (CNV) in the highly polymorphic cytochrome P450 (CYP) 2D6 gene, or to identify the promoter (TA)7 TAA repeat polymorphism UDP glucuronosyltransferase (UGT) 1A1∗28. Here we developed and validated PGxSeq, a targeted exome panel for pharmacogenes pertinent to drug disposition and/or response. Methods: A panel of capture probes was generated to assess 422 kb of total coding region in 100 pharmacogenes. NGS was carried out in 235 subjects, and sequencing performance and accuracy of variant discovery validated in clinically relevant pharmacogenes. CYP2D6 CNV was determined using the bioinformatics tool CNV caller (VarSeq). Identified SNVs were assessed in terms of population allele frequency and predicted functional effects through in silico algorithms. Results: Adequate performance of the PGxSeq panel was demonstrated with a depth-of-coverage (DOC) ≥ 20× for at least 94% of the target sequence. We showed accurate detection of 39 clinically relevant gene variants compared to standard genotyping techniques (99.9% concordance), including CYP2D6 CNV and UGT1A1∗28. Allele frequency of rare or novel variants and predicted function in 235 subjects mirrored findings from large genomic datasets. A large proportion of patients (78%, 183 out of 235) were identified as homozygous carriers of at least one variant necessitating altered pharmacotherapy. Conclusions: PGxSeq can serve as a comprehensive, rapid, and reliable approach for the detection of common and novel SNVs in pharmacogenes benefiting the emerging field of precision medicine

Clinical and pharmacogenetic predictors of circulating atorvastatin and rosuvastatin concentrations in routine clinical care

Background-A barrier to statin therapy is myopathy associated with elevated systemic drug exposure. Our objective was to examine the association between clinical and pharmacogenetic variables and statin concentrations in patients. Methods and Results-In total, 299 patients taking atorvastatin or rosuvastatin were prospectively recruited at an outpatient referral center. The contribution of clinical variables and transporter gene polymorphisms to statin concentration was assessed using multiple linear regression. We observed 45-fold variation in statin concentration among patients taking the same dose. After adjustment for sex, age, body mass index, ethnicity, dose, and time from last dose, SLCO1B1 c.521T\u3eC (P\u3c0.001) and ABCG2 c.421C\u3eA (P\u3c0.01) were important to rosuvastatin concentration (adjusted R2=0.56 for the final model). Atorvastatin concentration was associated with SLCO1B1 c.388A\u3eG (P\u3c0.01) and c.521T\u3eC (P\u3c0.05) and 4β-hydroxycholesterol, a CYP3A activity marker (adjusted R2=0.47). A second cohort of 579 patients from primary and specialty care databases were retrospectively genotyped. In this cohort, genotypes associated with statin concentration were not differently distributed among dosing groups, implying providers had not yet optimized each patient\u27s risk-benefit ratio. Nearly 50% of patients in routine practice taking the highest doses were predicted to have statin concentrations greater than the 90th percentile. Conclusions-Interindividual variability in statin exposure in patients is associated with uptake and efflux transporter polymorphisms. An algorithm incorporating genomic and clinical variables to avoid high atorvastatin and rosuvastatin levels is described; further study will determine whether this approach reduces incidence of statin myopathy. © 2013 American Heart Association, Inc

International consensus guideline for reporting transmission electron microscopy results in the diagnosis of Primary Ciliary Dyskinesia (BEAT PCD TEM Criteria)

Primary Ciliary Dyskinesia (PCD) is a heterogeneous genetic condition. European and North American diagnostic guidelines recommend transmission electron microscopy (TEM) as one of a combination of tests to confirm a diagnosis. However, there is no definition of what constitutes a defect or consensus on reporting terminology. The aim of this project was to provide an internationally agreed ultrastructural classification for PCD diagnosis by TEM. A consensus guideline was developed by PCD electron microscopy experts representing 18 centres in 14 countries. An initial meeting and discussion were followed by a Delphi consensus process. The agreed guideline was then tested, modified and retested through exchange of samples and electron micrographs between the 18 diagnostic centres. The final guideline a) Provides agreed terminology and a definition of class 1 defects which are diagnostic for PCD; b) Identifies class 2 defects which can indicate a diagnosis of PCD in combination with other supporting evidence; c) Describes features which should be included in a ciliary ultrastructure report to assist multidisciplinary diagnosis of PCD d) Defines adequacy of a diagnostic sample. This tested and externally validated statement provides a clear guideline for the diagnosis of PCD by TEM which can be used to standardise diagnosis internationally.</p

Targeted copy number variant identification across the neurodegenerative disease spectrum

Background: Although genetic factors are known to contribute to neurodegenerative disease susceptibility, there remains a large amount of heritability unaccounted for across the diagnoses. Copy number variants (CNVs) contribute to these phenotypes, but their presence and influence on disease state remains relatively understudied. Methods: Here, we applied a depth of coverage approach to detect CNVs in 80 genes previously associated with neurodegenerative disease within participants of the Ontario Neurodegenerative Disease Research Initiative (n = 519). Results: In total, we identified and validated four CNVs in the cohort, including: (1) a heterozygous deletion of exon 5 in OPTN in an Alzheimer\u27s disease participant; (2) a duplication of exons 1–5 in PARK7 in an amyotrophic lateral sclerosis participant; (3) a duplication of \u3e3 Mb, which encompassed ABCC6, in a cerebrovascular disease (CVD) participant; and (4) a duplication of exons 7–11 in SAMHD1 in a mild cognitive impairment participant. We also identified 43 additional CNVs that may be candidates for future replication studies. Conclusion: The identification of the CNVs suggests a portion of the apparent missing heritability of the phenotypes may be due to these structural variants, and their assessment is imperative for a thorough understanding of the genetic spectrum of neurodegeneration

A Common CNR1 (Cannabinoid Receptor 1) Haplotype Attenuates the Decrease in HDL Cholesterol That Typically Accompanies Weight Gain

We have previously shown that genetic variability in CNR1 is associated with low HDL dyslipidemia in a multigenerational obesity study cohort of Northern European descent (209 families, median  = 10 individuals per pedigree). In order to assess the impact of CNR1 variability on the development of dyslipidemia in the community, we genotyped this locus in all subjects with class III obesity (body mass index >40 kg/m2) participating in a population-based biobank of similar ancestry. Twenty-two haplotype tagging SNPs, capturing the entire CNR1 gene locus plus 15 kb upstream and 5 kb downstream, were genotyped and tested for association with clinical lipid data. This biobank contains data from 645 morbidly obese study subjects. In these subjects, a common CNR1 haplotype (H3, frequency 21.1%) is associated with fasting TG and HDL cholesterol levels (p = 0.031 for logTG; p = 0.038 for HDL-C; p = 0.00376 for log[TG/HDL-C]). The strength of this relationship increases when the data are adjusted for age, gender, body mass index, diet and physical activity. Mean TG levels were 160±70, 155±70, and 120±60 mg/dL for subjects with 0, 1, and 2 copies of the H3 haplotype. Mean HDL-C levels were 45±10, 47±10, and 48±9 mg/dL, respectively. The H3 CNR1 haplotype appears to exert a protective effect against development of obesity-related dyslipidemia