Genetic Testing Reference Material Coordination Research Articles

Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip.

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

The Genetic Testing Reference Materials Coordination Program: Over 10 Years of Support for Pharmacogenomic Testing

The Genetic Testing Reference Materials Coordination Program: Over 10 Years of Support for Pharmacogenomic Testing

Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing.

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

Characterization of Reference Materials for TPMT and NUDT15: A GeT-RM Collaborative Project

Pharmacogenetic testing is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the TPMT and NUDT15 variants included in clinical tests. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention-based Genetic Testing Reference Material (GeT-RM) coordination program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 19 DNA samples derived from Coriell cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using a variety of commercially available and laboratory developed tests and/or Sanger sequencing. Of the 12 samples characterized for TPMT, newly identified variants include TPMT∗2, ∗6, ∗12, ∗16, ∗21, ∗24, ∗32, ∗33, and ∗40; for the 7 NUDT15 reference material samples, newly identified variants are NUDT15∗2, ∗3, ∗4, ∗5, ∗6, and ∗9. In addition, a novel haplotype, TPMT∗46, was identified in this study. Preexisting data on an additional 11 Coriell samples, as well as some supplemental testing, were used to create comprehensive reference material panels for TPMT and NUDT15. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

Automated Pharmacogenomic Reports for Clinical Genome Sequencing

Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.

StellarPGx: A Nextflow Pipeline for Calling Star Alleles in Cytochrome P450 Genes.

Bioinformatics pipelines for calling star alleles (haplotypes) in cytochrome P450 (CYP) genes are important for the implementation of precision medicine. Genotyping CYP genes using high throughput sequencing data is complicated, e.g., by being highly polymorphic, not to mention the structural variations especially in CYP2D6, CYP2A6, and CYP2B6. Genome graph-based variant detection approaches have been shown to be reliable for genotyping HLA alleles. However, their application to enhancing star allele calling in CYP genes has not been extensively explored. We present StellarPGx, a Nextflow pipeline for accurately genotyping CYP genes by combining genome graph-based variant detection, read coverage information from the original reference-based alignments, and combinatorial diplotype assignments. The implementation of StellarPGx using Nextflow facilitates its portability, reproducibility, and scalability on various user platforms. StellarPGx is currently able to genotype 12 important pharmacogenes belonging to the CYP1, 2, and 3 families. For purposes of validation, we use CYP2D6 as a model gene owing to its high degree of polymorphisms (over 130 star alleles defined to date, including complex structural variants) and clinical importance. We applied StellarPGx and three existing callers to 109 whole genome sequenced samples for which the Genetic Testing Reference Material Coordination Program (GeT-RM) has recently provided consensus truth CYP2D6 diplotypes. StellarPGx had the highest CYP2D6 diplotype concordance (99%) with GeT-RM compared with Cyrius (98%), Aldy (82%), and Stargazer (84%). This exemplifies the high accuracy of StellarPGx and highlights its importance for both research and clinical pharmacogenomics applications. The StellarPGx pipeline is open-source and available from https://github.com/SBIMB/StellarPGx.

Characterization of Reference Materials for Spinal Muscular Atrophy Genetic Testing: A Genetic Testing Reference Materials Coordination Program Collaborative Project

Spinal muscular atrophy (SMA) is an autosomal recessive disorder predominately caused by bi-allelic loss of the SMN1 gene. Increased copies of SMN2, a low functioning nearly identical paralog, are associated with a less severe phenotype. SMA was recently recommended for inclusion in newborn screening. Clinical laboratories must accurately measure SMN1 and SMN2 copy number to identify SMA patients and carriers, and to identify individuals likely to benefit from therapeutic interventions. Having publicly available and appropriately characterized reference materials with various combinations of SMN1 and SMN2 copy number variants is critical to assure accurate SMA clinical testing. To address this need, the CDC-based Genetic Testing Reference Materials Coordination Program, in collaboration with members of the genetic testing community and the Coriell Institute for Medical Research, has characterized 15 SMA reference materials derived from publicly available cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using three different methods. The characterized samples had zero to four copies of SMN1 and zero to five copies SMN2. The samples also contained clinically important allele combinations (eg, zero copies SMN1, three copies SMN2), and several had markers indicative of an SMA carrier. These and other reference materials characterized by the Genetic Testing Reference Materials Coordination Program are available from the Coriell Institute and are proposed to support the quality of clinical laboratory testing.

Phased Haplotype Resolution of the SLC6A4 Promoter Using Long-Read Single Molecule Real-Time (SMRT) Sequencing.

The SLC6A4 gene has been implicated in psychiatric disorder susceptibility and antidepressant response variability. The SLC6A4 promoter is defined by a variable number of homologous 20–24 bp repeats (5-HTTLPR), and long (L) and short (S) alleles are associated with higher and lower expression, respectively. However, this insertion/deletion variant is most informative when considered as a haplotype with the rs25531 and rs25532 variants. Therefore, we developed a long-read single molecule real-time (SMRT) sequencing method to interrogate the SLC6A4 promoter region. A total of 120 samples were subjected to SLC6A4 long-read SMRT sequencing, primarily selected based on available short-read sequencing data. Short-read genome sequencing from the 1000 Genomes (1KG) Project (~5X) and the Genetic Testing Reference Material Coordination Program (~45X), as well as high-depth short-read capture-based sequencing (~330X), could not identify the 5-HTTLPR short (S) allele, nor could short-read sequencing phase any identified variants. In contrast, long-read SMRT sequencing unambiguously identified the 5-HTTLPR short (S) allele (frequency of 0.467) and phased SLC6A4 promoter haplotypes. Additionally, discordant rs25531 genotypes were reviewed and determined to be short-read errors. Taken together, long-read SMRT sequencing is an innovative and robust method for phased resolution of the SLC6A4 promoter, which could enable more accurate pharmacogenetic testing for both research and clinical applications.

Development and Analytical Validation of a 29 Gene Clinical Pharmacogenetic Genotyping Panel: Multi‐Ethnic Allele and Copy Number Variant Detection

To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single‐base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation‐dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi‐ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.

Pharmacogenomics Clinical Annotation Tool (PharmCAT).

Pharmacogenomics (PGx) decision support and return of results is an active area of precision medicine. One challenge of implementing PGx is extracting genomic variants and assigning haplotypes in order to apply prescribing recommendations and information from the Clinical Pharmacogenetics Implementation Consortium (CPIC), the US Food and Drug Administration (FDA), the Pharmacogenomics Knowledgebase (PharmGKB), etc. Pharmacogenomics Clinical Annotation Tool (PharmCAT) (i) extracts variants specified in guidelines from a genetic data set derived from sequencing or genotyping technologies, (ii) infers haplotypes and diplotypes, and (iii) generates a report containing genotype/diplotype‐based annotations and guideline recommendations. We describe PharmCAT and a pilot validation project comparing results for 1000 Genomes Project sequences of Coriell samples with corresponding Genetic Testing Reference Materials Coordination Program (GeT‐RM) sample characterization. PharmCAT was highly concordant with the GeT‐RM data. PharmCAT is available in GitHub to evaluate, test, and report results back to the community. As precision medicine becomes more prevalent, our ability to consistently, accurately, and clearly define and report PGx annotations and prescribing recommendations is critical.

Characterizing the pharmacogenome using molecular inversion probes for targeted next-generation sequencing.

Aim: This study assesses the technical performance and cost of a targeted next-generation sequencing (NGS) multigene pharmacogenetic (PGx) test. Materials & methods: A genetic test was developed for 21 PGx genes using molecular inversion probes to generate library fragments for NGS. Performance of this test was assessed using 53 unique reference control cell lines from the Genetic Testing Reference Materials Coordination Program (GeT-RM). Results: 93.7% of variants were successfully called and the repeatability rate was 99.9%. Reference calls were available for 78.4% of diplotype calls resulting from PGx testing, and concordance for the test was 85.7%. Cost per sample was $32-$56. Conclusion: A targeted NGS assay using molecular inversion probe technology is able to characterize the pharmacogenome efficiently.

Characterization of Reference Materials for Genetic Testing of CYP2D6 Alleles: A GeT-RM Collaborative Project

Pharmacogenetic testing increasingly is available from clinical and research laboratories. However, only a limited number of quality control and other reference materials currently are available for the complex rearrangements and rare variants that occur in the CYP2D6 gene. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Cell Repositories (Camden, NJ), has characterized 179 DNA samples derived from Coriell cell lines. Testing included the recharacterization of 137 genomic DNAs that were genotyped in previous Genetic Testing Reference Material Coordination Program studies and 42 additional samples that had not been characterized previously. DNA samples were distributed to volunteer testing laboratories for genotyping using a variety of commercially available and laboratory-developed tests. These publicly available samples will support the quality-assurance and quality-control programs of clinical laboratories performing CYP2D6 testing.

Calling Star Alleles With Stargazer in 28 Pharmacogenes With Whole Genome Sequences.

Variation in the enzymatic activity of pharmacogenes is defined by star alleles (haplotypes) comprised of single‐nucleotide variants, small insertion‐deletions, and large structural variants. We recently developed Stargazer, a next‐generation sequencing‐based tool to call star alleles for the clinically important CYP2D6 gene. Here, we present the utility of extending Stargazer to call star alleles for 28 pharmacogenes using whole genome sequencing (WGS) data. We applied Stargazer to WGS data from 70 ethnically diverse samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM). These reference samples were extensively characterized by GeT‐RM using multiple pharmacogenetic testing assays. In all 28 genes, Stargazer recalled 100% of star alleles (N = 92) present in GeT‐RM's consensus genotypes (N = 1,559). Stargazer also detected star alleles not previously reported by GeT‐RM, including complex structural variants. Our results demonstrate that combining WGS data and Stargazer enables automated, accurate, and comprehensive genotyping of pharmacogenes in the human genome.

P060 Characterization of 108 genomic DNA reference materials for 11 HLA LOCI: A GeT-RM collaborative project

Improve availability of publicly available, renewable, and well-characterized genomic DNA reference materials to support molecular HLA typing assay development, validation and verification, quality control, and proficiency testing. The Centers for Disease Control and Prevention’s (CDC) Genetic Testing Reference Materials Coordination Program (GeT-RM) together with three clinical laboratories and the Coriell Cell Repositories characterized genomic DNA from 108 cell lines for HLA-A, B, C, DRB1, DRB3, DRB4, DRB5, DQA1, DQB1, DPA1, and DPB1. DNA was isolated by the Coriell Cell Repositories and distributed to the 3 laboratories. Methodologies used were: PCR-SSO-LABType® SSO (One Lambda, Canoga Park, CA), SSP – Olerup SSP® (Stockholm, Sweden), SBT-AlleleSEQR® HLA-SBT (Abbott Molecular, Des Plaines, IL) and NGS - HoloType HLA™ kits (Omixon Inc., Budapest, Hungary). Each of the 11 genes was tested by 2 or 3 methods. Consensus genotype was the NGS result, which provided the highest level of resolution, and was consistent with the results obtained by the parallel testing using other methods. HLA typing results using SBT, SSP, SSO and NGS were 99.95 % concordant. Of the 1905 alleles typed, only one discrepancy was observed. The discrepant result was found to be due to an error in SBT/SSO typing. Five unique novel alleles with differences in exonic regions were identified and three were submitted to the WHO Nomenclature Committee. Ambiguities persisted in 50/1905 allele calls, most due to alternative cis/trans combinations of exons 2 and 3 of DPB1 (n = 21 pairs: 42 alleles) and 8 caused by polymorphisms in a non-covered region (exon1) of the DRB1and DPB1 genes. Thirty HLA-A, 54-B, 30-C, 36-DRB1, 4-DRB3, 4-DRB4, 3-DRB5, 19-DQA1, 17-DQB1, 10-DPA1 and 29-DPB1 alleles are represented in the panel. These alleles cover a high percentage of HLA specificities present in five ancestry groups in the USA population. These genomic DNA samples are publicly available from the National Institutes of General Medical Science (NIGMS) Repository at the Coriell Cell Repositories. M. Bettinotti: 3. Speaker’s Bureau; Company/Organization; One Lambda Thermo Fisher. D. Ferriola: 7. Other (Identify); Company/Organization; Licensing proceeds of the HLA-NGS protocol by CHOP to Omixon. J.L. Duke: 7. Other (Identify); Company/Organization; receiving proceeds from the licensing of the HLA-NGS protocol by CHOP to Omixon. D. Monos: 4. Scientific/Medical Advisor; Company/Organization; Omixon. 7. Other (Identify); Company/Organization; receiving proceeds from the licensing of the HLA-NGS protocol by CHOP to Omixon.

Characterization of 108 Genomic DNA Reference Materials for 11 Human Leukocyte Antigen Loci: A GeT-RM Collaborative Project

The highly polymorphic human leukocyte antigen (HLA) genes, located in the human major histocompatibility complex, encode the class I and II antigen-presenting molecules, which are centrally involved in the immune response. HLA typing is used for several clinical applications, such as transplantation, pharmacogenetics, and diagnosis of autoimmune disease. HLA typing is highly complex because of the homology of HLA genes and pseudogenes and the extensive polymorphism in the population. The Centers for Disease Control and Prevention established the Genetic Testing Reference Materials Coordination Program (GeT-RM) in partnership with the genetics community to improve theavailability of genomic DNA reference materials necessary for quality assurance of genetic laboratory testing. The GeT-RM together with three clinical laboratories and the Coriell Cell Repositories have characterized genomic DNA obtained from a panel of 108 cell lines for all HLA classic polymorphic loci: HLA-A, B, C, DRB1, DRB3, DRB4, DRB5, DQA1, DQB1, DPA1, and DPB1. The goal was to develop a publicly available and renewable source of well-characterized genomic DNA reference materials to support molecular HLA typing assay development, validation, and verification, quality control, and proficiency testing. These genomic DNA samples are publicly available from the National Institutes of General Medical Science Repository at the Coriell Cell Repositories.

Development and Characterization of Reference Materials for Genetic Testing: Focus on Public Partnerships.

Characterized reference materials (RMs) are needed for clinical laboratory test development and validation, quality control procedures, and proficiency testing to assure their quality. In this article, we review the development and characterization of RMs for clinical molecular genetic tests. We describe various types of RMs and how to access and utilize them, especially focusing on the Genetic Testing Reference Materials Coordination Program (Get-RM) and the Genome in a Bottle (GIAB) Consortium. This review also reinforces the need for collaborative efforts in the clinical genetic testing community to develop additional RMs.

Characterization of 137 Genomic DNA Reference Materials for 28 Pharmacogenetic Genes: A GeT-RM Collaborative Project

Pharmacogenetic testing is increasingly available from clinical laboratories. However, only a limited number of quality control and other reference materials are currently available to support clinical testing. To address this need, the Centers for Disease Control and Prevention-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing community and the Coriell Cell Repositories, has characterized 137 genomic DNA samples for 28 genes commonly genotyped by pharmacogenetic testing assays (CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, CYP4F2, DPYD, GSTM1, GSTP1, GSTT1, NAT1, NAT2, SLC15A2, SLC22A2, SLCO1B1, SLCO2B1, TPMT, UGT1A1, UGT2B7, UGT2B15, UGT2B17, and VKORC1). One hundred thirty-seven Coriell cell lines were selected based on ethnic diversity and partial genotype characterization from earlier testing. DNA samples were coded and distributed to volunteer testing laboratories for targeted genotyping using a number of commercially available and laboratory developed tests. Through consensus verification, we confirmed the presence of at least 108 variant pharmacogenetic alleles. These samples are also being characterized by other pharmacogenetic assays, including next-generation sequencing, which will be reported separately. Genotyping results were consistent among laboratories, with most differences in allele assignments attributed to assay design and variability in reported allele nomenclature, particularly for CYP2D6, UGT1A1, and VKORC1. These publicly availablesamples will help ensure the accuracy of pharmacogenetic testing.

Development of a Genomic DNA Reference Material Panel for Rett Syndrome (MECP2-Related Disorders) Genetic Testing

Rett syndrome is a dominant X-linked disorder caused by point mutations (approximately 80%) or by deletions or insertions (approximately 15% to 18%) in the MECP2 gene. It is most common in females but lethal in males, with a distinctly different phenotype. Rett syndrome patients have severe neurological and behavioral problems. Clinical genetic testing laboratories commonly use characterized genomic DNA reference materials to assure the quality of the testing process; however, none are commercially available for MECP2 genetic testing. The Centers for Disease Control and Prevention's Genetic Testing Reference Material Coordination Program, in collaboration with the genetic testing community and the Coriell Cell Repositories, established 27 new cell lines and characterized the MECP2 mutations in these and in 8 previously available cell lines. DNA samples from the 35 cell lines were tested by eight clinical genetic testing laboratories using DNA sequence analysis and methods to assess copy number (multiplex ligation-dependent probe amplification, semiquantitative PCR, or array-based comparative genomic hybridization). The eight common point mutations known to cause approximately 60% of Rett syndrome cases were identified, as were other MECP2 variants, including deletions, duplications, and frame shift and splice-site mutations. Two of the 35 samples were from males with MECP2 duplications. These MECP2 and other characterized genomic DNA samples are publicly available from the NIGMS Repository at the Coriell Cell Repositories.

Development of a Genomic DNA Reference Material Panel for Myotonic Dystrophy Type 1 (DM1) Genetic Testing

Myotonic dystrophy type 1 (DM1) is caused by expansion of a CTG triplet repeat in the 3' untranslated region of the DMPK gene that encodes a serine-threonine kinase. Patients with larger repeats tend to have a more severe phenotype. Clinical laboratories require reference and quality control materials for DM1 diagnostic and carrier genetic testing. Well-characterized reference materials are not available. To address this need, the Centers for Disease Control and Prevention-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the genetic testing community, the National Registry of Myotonic Dystrophy and Facioscapulohumeral Muscular Dystrophy Patients and Family Members, and the Coriell Cell Repositories, has established and characterized cell lines from patients with DM1 to create a reference material panel. The CTG repeats in genomic DNA samples from 10 DM1 cell lines were characterized in three clinical genetic testing laboratories using PCR and Southern blot analysis. DMPK alleles in the samples cover four of five DM1 clinical categories: normal (5 to 34 repeats), mild (50 to 100 repeats), classical (101 to 1000 repeats), and congenital (>1000 repeats). We did not identify or establish Coriell cell lines in the premutation range (35 to 49 repeats). These samples are publicly available for quality control, proficiency testing, test development, and research and should help improve the accuracy of DM1 testing.