Reference materials are critical for many activities in clinical laboratories, including quality control, development and validation of tests, proficiency testing, validating variant calling algorithms, and inter-laboratory standardization, and are needed to comply with regulations, accreditation standards, and professional guidance^1–5 (American College of Medical Genetics and Genomics https://www.acmg.net/PDFLibrary/ACMG%20Technical%20Lab%20Standards%20Section%20G.pdf, last accessed 7/12/2024, Washington State Legislature, http://app.leg.wa.gov/WAC/default.aspx?cite=246-338-090, last accessed 7/12/2024, College of American Pathologists (Northfield, IL) https://www.cap.org/ last accessed 7/12/2024, New York State Clinical Laboratory Evaluation Program, https://www.wadsworth.org/regulatory/clep, last accessed 7/12/2024, MMWR https://www.cdc.gov/mmwr/preview/mmwrhtml/rr5806a1.htm, last accessed 7/12/2024).

Clinical laboratories often develop pharmacogenetic and other genetic tests as laboratory developed tests or procedures (LDT or LDP), and use residual patient samples, genomic DNA from cell lines, or synthetic DNA containing variants of interest as reference materials. However, despite the regulatory and professional guidelines requiring their use, there are few, if any, publicly available reference materials for most clinical genetic tests.

To address this issue, the CDC created the Genetic Testing Reference Materials Program (GeT-RM) in 2004 (GeT-RM, https://www.cdc.gov/lab-quality/php/get-rm/index.html, last accessed 11/4/2024).⁶ The GeT-RM is a collaborative program whose goal is to improve the availability of genomic DNA reference materials for genetic testing. GeT-RM works with a variety of partners, including clinical and research laboratories, in vitro diagnostics (IVD) manufacturers, professional organizations, patient advocacy groups, and the Coriell Institute for Medical Research to identify reference material needs and create publicly available and renewable genomic DNA reference materials.

GeT-RM has created cell-line based genomic DNA reference materials for a large number of clinically important genes for hereditary genetic disorders, including cystic fibrosis, fragile X, Rett syndrome, and Duchenne muscular dystrophy^7–10, 11 Human Leukocyte Antigen (HLA) loci¹¹, and many pharmacogenes and loci.^12–19 Each sample is experimentally characterized in two or more laboratories using a variety of analytical methods, including targeted genotyping and Sanger sequencing. For some genes, experimental testing also includes copy number variants (CNVs) and structural variation (SVs) analysis or phasing of variants into star alleles.²⁰ In addition, publicly available high-coverage (30x) whole genome sequencing (WGS) data from the 1000 Genomes Project (1kGP)²¹ or 10x Genomics Linked-Read data (Illumina https://github.com/Illumina/Polaris/wiki/HiSeqX-PGx-Cohort last accessed 8/19/2024) was also analyzed. Results were assessed for quality, discordances, and determination of a consensus genotype for each sample. All characterized genomic DNA samples are publicly available from the National Institute of General Medical Sciences (NIGMS) Human Genetic Cell Repository or the National Human Genome Research Institute (NHGRI) Sample Repository for Human Genetic Research, which are both housed at the Coriell Institute for Medical Research.

The GeT-RM has conducted nine studies over the last 14 years to create reference materials for pharmacogenetic and HLA testing.^11–19 In many cases, samples were reanalyzed for the same gene(s) in subsequent studies using more comprehensive and sensitive methods and panels with additional single nucleotide variants (SNVs) and/or star alleles that were not included in previous characterizations along with other data that became publicly available. This approach allowed updating and expanding consensus genotypes for a considerable number of samples. Often, additional samples were added in later characterization studies to identify SNVs and star alleles that were defined after the original study. In addition, samples characterized during the earliest studies may also have been assigned outdated designations as allele definitions evolve over time and new alleles are identified frequently. These allele designations were updated during subsequent studies.

We created two resources, the GeT-RM Consolidated PGx and HLA Table as well as a searchable database tool, GeT-RM PGx Search, to provide the most up to date pharmacogenetic genotypes for each characterized sample. Both resources provide information about 363 DNA samples that were characterized during nine GeT-RM PGx or HLA studies for 34 genes/loci including CYP2C9, CYP2C19, CYP3A4, CYP3A5, CYP2D6, TPMT, NUDT15, DPYD, and 11 HLA loci.^11–19

The GeT-RM Consolidated PGx and HLA Table (https://www.cdc.gov/lab-quality/php/get-rm/reference-materials.html, last accessed 11/4/2024) shows consensus genotypes determined during the nine GeT-RM PGx studies for all 363 samples in an Excel format. This table was used to develop an interactive, web-based search tool, “GeT-RM PGx Search”, which is available on the Coriell Institute for Medical Research website (https://www.coriell.org/GetRM/PGxSearch, last accessed 8/13/2024). Each gene is given a unique key in a Structured Query Language (SQL) Server relational database that is linked to sample level data. Users can query GeT-RM PGx Search using a web-based interface and select a gene of interest from the dropdown menu (Figure 2). GeT-RM PGx Search returns the following: links to PharmVar annotations (https://www.pharmvar.org/, last accessed 7/22/2024), and the NCBI gene entry (if available) (NCBI https://www.ncbi.nlm.nih.gov/gene/?term=, last accessed 8/13/2024), additional documentation regarding allele information and allele definitions, an option to export annotations for the chosen gene to an Excel spreadsheet, and an interactive data display (Figure 3). The number of samples viewable in the interactive table can be adjusted to the user’s preference, and the annotated samples can be sorted by sample ID, description, gene, genotype, reference, product, source, or genetic sex. Each sample ID is hyperlinked to a sample-specific page that includes the detailed overview, characterizations, associated data and publications, and related external links. In addition, the viewable samples can be filtered by star allele, variant(s), or genotype.

Reference material organizations including the National Institute of Standards and Technology (NIST, https://www.nist.gov/, last accessed 1/3/2025), the National Institute for Biological Standards and Control (NIBSC, Hertfordshire UK) and the Joint Research Centre (Geel, Belgium) as well as commercial vendors produce reference materials and standards for product control and forensic testing. Availability of reference materials encompassing a range of human genetic variation, however, has been an ongoing challenge for clinical laboratorians. This limited availability has negatively impacted the ability to develop and validate new tests and provide quality control and ongoing quality assurance for existing tests. To address this gap, the GeT-RM has characterized hundreds of publicly available and renewable genomic DNA reference materials, many of these for pharmacogenetic testing. Unlike other PGx annotation approaches^22–24, the GeT-RM requires that each sample be experimentally characterized in two or more laboratories using a variety of analytical methods. These reference materials can then be used by laboratories as they implement clinical practice guidelines such as those developed by the Association for Molecular Pathology PGx Working Group.^25–30

Most pharmacogenes are highly polymorphic^{31, 32} with new alleles and haplotypes still being discovered, especially in non-European poulations;^{33, 34} thus the catalog of haplotype-based (i.e., star allele) definitions continues to grow and is anticipated to be updated regularly.^{20, 35, 36} In addition, there has been a rapid evolution of the technologies and methods available to perform pharmacogenetic testing. Over the last 15 years, pharmacogenetic tests, which started as targeted genotyping and Sanger sequencing assays, have come to incorporate more comprehensive analyses³⁷ including testing for copy number variation, as well as short and long-read NGS.^{38, 39} This has enhanced our understanding of many pharmacogenetic loci, such as CYP2D6, which often requires extensive analysis to resolve its many structural variants.⁴⁰ Historically, simpler assays were only able to detect full CYP2D6 gene deletions, duplications and multiplications, while recent more advanced assays can also detect hybrid genes and more comprehensively characterize complex genotypes. These higher resolution analyses have resulted in the identification and naming of many new CYP2D6 star alleles by PharmVar. While copy number analysis is now commonly performed for CYP2D6, testing for copy number variation is not widely used for other loci. For example, the most recent GeT-RM study utilized copy number analysis and identified a relatively common intragenic deletion in DPYD.¹⁹ Finally, at present, the phase of most pharmacogene variants is determined empirically. As single molecule long read NGS becomes more widely available, it is anticipated that previously analyzed samples may be re-tested to determine phase, which may require further updates to the “gold standard” genotype data in GeT-RM for some samples. Although the reference material DNA does not change over time, the ability to precisely characterize genotype continues to improve.

Since 2010, GeT-RM has performed eight studies characterizing genomic DNA samples for pharmacogenetic loci^12–19 and one study for 11 HLA loci.¹¹ Due to the changing nature of PGx testing and the identification of important new alleles, reference materials for many of the commonly tested PGx genes, including CYP2C9, CYP2C19, CYP2D6, and DPYD, have been characterized in more than one GeT-RM study.^12–19 Some samples were characterized for the same gene during multiple studies, and their consensus genotype was revised based on the information gleaned from analyses using more comprehensive assays. This has resulted in some sample genotypes seeming to change between GeT-RM studies, which may have been interpreted as being “discrepant” and caused confusion amongst users of the reference material samples.

Assignment of PGx genotypes during GeT-RM studies is dependent on the assays used for sample characterization as well as the PharmVar star allele definitions existing at the time of the study. Newly available assay technologies can be used to recharacterize samples to overcome limitations of assays used during earlier studies. For example, genotyping assays, Sanger or short read NGS assays employed in previous studies could often not resolve the phase of variants. This limitation may now be overcome by single molecule long read NGS technologies. In addition, PharmVar may have revised allele definitions and added new star alleles since samples were first characterized. GeT-RM aims to not only update reported genotypes of previously characterized samples by testing with new technologies, but also identify samples with newly discovered star alleles. It is important to note that genotypes listed in the GeT-RM Consolidated PGx and HLA Table are based on the nomenclature available at the time of analysis and may not be consistent with current nomenclature. This explains, for example, why some genotypes contain “letter” extensions (e.g., for CYP1A2). Furthermore, NAT2 was only transferred to PharmVar in 2024 and its nomenclature underwent substantial changes. Future recharacterization of sample materials for NAT2 will not only include testing for many additional star alleles with the latest technologies but will also report genotypes using PharmVar’s current star allele definitions.

There are several bioinformatic tools that can be used to call PGx variants and star alleles for the 1000 Genomes Project samples^{22–24, 41, 42}. These tools can be useful to identify publicly available samples that may contain PGx variants of interest, however the variants in these samples should be confirmed using orthogonal methods prior to use as reference materials.

The GeT-RM Consolidated PGx and HLA Table and the GeT-RM PGx Search tool were created to provide an easily accessible and searchable resource with up-to-date information about publicly available, well-characterized reference DNA samples that can be used to support quality assurance programs of laboratories performing clinical PGx and HLA testing. The GeT-RM Consolidated PGx and HLA Table and GeT-RM PGx Search tool will be updated and synchronized as additional GeT-RM PGx studies are completed. All reference materials characterized by GeT-RM are publicly available from the NIGMS and NHGRI Repositories at the Coriell Institute for Medical Research.