Clinical Genetic Test Results Research Articles

Abstract 7339: Mayo Clinic breast cancer cohort: A valuable resource for breast cancer research

Abstract The Mayo Clinic Breast Disease Registry (MCBDR) was developed to serve as a cohort of newly diagnosed breast cancer patients to address questions of etiology, prognosis, and survivorship. Eligibility is limited to patients 18 years or older with a confirmed first stage 0-4 breast cancer diagnosis within the last year. Consent is completed via phone, patient portal, or in-person. Upon enrollment, a baseline questionnaire and blood collection are completed. Annual follow-up surveys that capture BC outcomes are sent to all living participants. The MCBDR cohort (N=9,215, enrolled between 2001 and 2023) is 99% female, with an average age at diagnosis of 58 years (SD=12.7). Currently, MCBDR has an average time since diagnosis of 9.8 years (SD=6.4). The participants are 94% white, and 55% live in Minnesota. At the time of baseline questionnaire completion, 77% were married, 84% had a bachelor’s degree or higher, and 8% reported financial hardship. Further, 35% reported a history of smoking, 11% consumed more than two drinks per day, and 9% reported fair or poor social relationships. Within MCBDR, 53% of the participants had stage 0 or 1 cancer at diagnosis, while 28% had stage 2, 9% stage 3, and 3% stage 4 BC. Tumors were triple negative in 9%, HER 2 positive in 9%, hormone receptor-positive and HER2 low or negative in 55%, and 27% had missing HER2 status. Pathological TNM staging was available on 98%, among which 33% were staged at T2 or higher and 27% were node-positive. Definitive BC surgery was completed at Mayo Clinic for 73%, with 35% undergoing mastectomies and 44% having lumpectomies. 74% were treated with radiation, 56% underwent chemotherapy, and 79% were treated with endocrine therapy. Clinical genetic testing results have been nurse-abstracted for 94% of the cohort. Of those known to be tested, 521 (6%) had a pathogenic or likely pathogenic mutation identified in a BC causing gene. In addition, whole exome sequencing was completed on 71% of MCBDR participants in 2020, in which 167 previously unknown pathogenic or likely pathogenic mutations were identified. After the initial diagnosis and active treatment phase, nurse abstraction identified 151 (2%) participants known to have been diagnosed with a contralateral BC diagnosis, and 4% known to have been diagnosed with a second primary other than breast. Recurrence in the same breast has been reported for 242 (3%), with 72% of those recurrences occurring within 5 years of initial diagnosis and another 19% occurring 5-10 years post diagnosis. Among the 1,262 (14%) who are deceased, 24% died from BC and 19% had distant metastases at diagnosis or a distant recurrence. Amongst all deceased, 6% died within 1 year of their diagnosis and 43% died within 5 years of diagnosis. For participants who died from BC, 10% died within 1 year of their diagnosis and 64% died within 5 years of diagnosis. MCBDR data has been used in numerous publications and is an essential resource for efficient observational research analyses. Citation Format: Nicole L. Larson, Janet Olson, Kathryn Ruddy, Fergus Couch, Denise Herman, Feven Abraha. Mayo Clinic breast cancer cohort: A valuable resource for breast cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7339.

Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine

Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.

Association of Family Cancer History With Pathogenic Variants in Specific Breast Cancer Susceptibility Genes.

Family cancer history is an important component of genetic testing guidelines that estimate which patients with breast cancer are most likely to carry a germline pathogenic variant (PV). However, we do not know whether more extensive family history is differentially associated with PVs in specific genes. All women diagnosed with breast cancer in 2013-2017 and reported to statewide SEER registries of Georgia and California were linked to clinical genetic testing results and family history from two laboratories. Family history was defined as strong (suggestive of PVs in high-penetrance genes such as BRCA1/2 or TP53, including male breast, ovarian, pancreatic, sarcoma, or multiple female breast cancers), moderate (any other cancer history), or none. Among established breast cancer susceptibility genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, RAD51C, RAD51D, and TP53), we evaluated PV prevalence according to family history extent and breast cancer subtype. We used a multivariable model to test for interaction between affected gene and family history extent for ATM, BRCA1/2, CHEK2, and PALB2. A total of 34,865 women linked to genetic results. Higher PV prevalence with increasing family history extent (P < .001) was observed only with BRCA1 (3.04% with none, 3.22% with moderate, and 4.06% with strong history) and in triple-negative breast cancer with PALB2 (0.75% with none, 2.23% with moderate, and 2.63% with strong history). In a multivariable model adjusted for age and subtype, there was no interaction between family history extent and PV prevalence for any gene except PALB2 (P = .037). Extent of family cancer history is not differentially associated with PVs across established breast cancer susceptibility genes and cannot be used to personalize genes selected for testing.

Association of Genetic Testing Results With Mortality Among Women With Breast Cancer or Ovarian Cancer.

Breast cancer and ovarian cancer patients increasingly undergo germline genetic testing. However, little is known about cancer-specific mortality among carriers of a pathogenic variant (PV) in BRCA1/2 or other genes in a population-based setting. Georgia and California Surveillance Epidemiology and End Results (SEER) registry records were linked to clinical genetic testing results. Women were included who had stages I-IV breast cancer or ovarian cancer diagnosed in 2013-2017, received chemotherapy, and were linked to genetic testing results. Multivariable Cox proportional hazard models were used to examine the association of genetic results with cancer-specific mortality. 22 495 breast cancer and 4320 ovarian cancer patients were analyzed, with a median follow-up of 41 months. PVs were present in 12.7% of breast cancer patients with estrogen and/or progesterone receptor-positive, HER2-negative cancer, 9.8% with HER2-positive cancer, 16.8% with triple-negative breast cancer, and 17.2% with ovarian cancer. Among triple-negative breast cancer patients, cancer-specific mortality was lower with BRCA1 (hazard ratio [HR] = 0.49, 95% confidence interval [CI] = 0.35 to 0.69) and BRCA2 PVs (HR = 0.60, 95% CI = 0.41 to 0.89), and equivalent with PVs in other genes (HR = 0.65, 95% CI = 0.37 to 1.13), vs noncarriers. Among ovarian cancer patients, cancer-specific mortality was lower with PVs in BRCA2 (HR = 0.35, 95% CI = 0.25 to 0.49) and genes other than BRCA1/2 (HR = 0.47, 95% CI = 0.32 to 0.69). No PV was associated with higher cancer-specific mortality. Among breast cancer and ovarian cancer patients treated with chemotherapy in the community, BRCA1/2 and other gene PV carriers had equivalent or lower short-term cancer-specific mortality than noncarriers. These results may reassure newly diagnosed patients, and longer follow-up is ongoing.

Modernizing family health history: achievable strategies to reduce implementation gaps.

Family health history (FHH) is a valuable yet underused healthcare tool for assessing health risks for both prevalent disorders like diabetes, cancer, and cardiovascular diseases, and for rare, monogenic disorders. Full implementation of FHH collection and analysis in healthcare could improve both primary and secondary disease prevention for individuals and, through cascade testing, make at risk family members eligible for pre-symptomatic testing and preventative interventions. In addition to risk assessment in the clinic, FHH is increasingly important for interpreting clinical genetic testing results and for research connecting health risks to genomic variation. Despite this value, diverse implementation gaps in clinical settings undermine its potential clinical value and limit the quality of connected health and genomic data. The NHGRI Family Health History Group, an open-membership, US-based group with international members, believes that integrating FHH in healthcare and research is more important than ever, and that achievable implementation advances, including education, are urgently needed to boost the pace of translational utility in genomic medicine. An inventory of implementation gaps and proposed achievable strategies to address them, representing a consensus developed in meetings from 2019-2020, is presented here. The proposed measures are diverse, interdisciplinary, and are guided by experience and ongoing implementation and research efforts.

Abstract 16552: Chromosomal Microarray Abnormalities in More Than 1300 Patients With Congenital Heart Disease Provide Novel Clinical and Etiological Insights

Introduction: The genetic basis of congenital heart disease (CHD) is incompletely understood. Approximately 10-20% of infants with CHD have abnormal chromosome microarray (CMA) results, however, the spectrum of genomic and phenotypic abnormalities remains incompletely characterized. Methods: All study patients had abnormal CMA on clinical testing and abnormal cardiac findings on echocardiogram, as identified at 9 pediatric cardiac centers. Clinical genetic testing results, diagnoses, and echocardiogram reports for detailed cardiac phenotyping were collected. CMA results were denoted as abnormal for any reported findings that included copy number variants (CNVs) and/or regions of homozygosity. Cardiac classification was performed with minor modification to National Birth Defect Prevention Study methods. Recurrent CNVs were identified algorithmically. Functional enrichment analysis of genes predicted to be intolerant of loss-of-function (LOF) in CNVs and genes located in monogenic CNVs was performed using ToppGene. Results: The study included 1369 patients. Genetic syndromes highly associated with CHD such as Trisomy 21, Turner syndrome, and 22q11.2 deletion syndrome among others were identified in 401 patients and elucidated less recognized cardiac phenotypes in these groups. Analyzing genes known to be causative of CHD in the remaining patients (N=968) showed enrichment in CNVs &lt; 5 megabases (N=51; 7%). Common recurrent loci included duplications in 15q13.2-13.3 (N=16 patients) and 16p11.13 (N=12; 8 with left-sided cardiac lesion), and deletions in 15q11.2 (N=14; 6 with total anomalous pulmonary venous return) and 2q13 (N=10; 8 with conotruncal defect). Genes predicted to be intolerant of LOF (495 genes) or located in monogenic CNVs (137 genes) were enriched for neuronal processes. Conclusions: The consortium provides the largest data set of abnormal clinical CMA results in patients with detailed CHD phenotyping to our knowledge. The findings provide novel understanding of CHD phenotypes, a roadmap of recurrent loci, and pathways and candidate genes in CNV-associated CHD. The consortium’s data will lead to improved genetic understanding and clinical care of patients with CHD.

Research participant understanding and engagement in an institutional, self-consent biobank model.

The number of institutional and governmental biobanks and the target enrollment sizes of modern biobanks are increasing, affording more opportunities for the public to participate in biobanking efforts. In parallel with these expansions are pressures to increase the efficiency of obtaining informed consent using shorter consent forms that cover a broader scope of research and increasingly include provisions for return of research or clinical genetic test results to participants. Given these changes, how well these participants understand genetics, their level of understanding of what they are consenting to, and their wishes to engage longitudinally and receive biobank results are not well understood. We surveyed participants in a large, medical system-based biobank who had enrolled through a two-page, self-consent process about their baseline knowledge of genetics, understanding and recall of the consent process, wishes for future contact and engagement, and level of interest in receiving clinical genetic testing results. A total of 856 consented persons participated in the survey (67% women; 67% white). Participants' general reported genetics knowledge was relatively high (mean 11.60 of 15 questions answered correctly) as was recall of key elements from the two-page consent form. Overall participant enthusiasm for future contact by the biobank and for receiving clinical genetic testing results was high. The use of a two-page, self-consent process in a large, institutional biobank resulted in high levels of consent recall and enthusiasm for future ongoing engagement and receipt of genetic testing results by participants.

Genetic testing for inherited eye conditions in over 6,000 individuals through the eyeGENE network.

Genetic testing in a multisite clinical trial network for inherited eye conditions is described in this retrospective review of data collected through eyeGENE®, the National Ophthalmic Disease Genotyping and Phenotyping Network. Participants in eyeGENE were enrolled through a network of clinical providers throughout the United States and Canada. Blood samples and clinical data were collected to establish a phenotype:genotype database, biorepository, and patient registry. Data and samples are available for research use, and participants are provided results of clinical genetic testing. eyeGENE utilized a unique, distributed clinical trial design to enroll 6,403 participants from 5,385 families diagnosed with over 30 different inherited eye conditions. The most common diagnoses given for participants were retinitis pigmentosa (RP), Stargardt disease, and choroideremia. Pathogenic variants were most frequently reported in ABCA4 (37%), USH2A (7%), RPGR (6%), CHM (5%), and PRPH2 (3%). Among the 5,552 participants with genetic testing, at least one pathogenic or likely pathogenic variant was observed in 3,448 participants (62.1%), and variants of uncertain significance in 1,712 participants (30.8%). Ten genes represent 68% of all pathogenic and likely pathogenic variants in eyeGENE. Cross-referencing current gene therapy clinical trials, over a thousand participants may be eligible, based on pathogenic variants in genes targeted by those therapies. This article is the first summary of genetic testing from thousands of participants tested through eyeGENE, including reports from 5,552 individuals. eyeGENE provides a launching point for inherited eye research, connects researchers with potential future study participants, and provides a valuable resource to the vision community.

Abstract PR02: Using web-based tools to assess familial cancer risk in diverse populations

Abstract Introduction: The Cancer Health Risk Assessments Reaching Many (CHARM) study (NCT03426878) aims to increase access to genetic testing for hereditary cancer in low-income, low-literacy, and minority populations (hereafter referred to as “underserved”). To implement the study, we have capitalized on the availability of electronic medical record (EMR) systems, developed innovative web-based tools, and designed a novel telemedicine protocol for return of clinical genetic testing results. Methods: Patients aged 18-49 years are recruited from two centers: Kaiser Permanente Northwest (KPNW; an integrated health care system in Portland, OR) and Denver Health (DH; a federally qualified health care center in Denver, CO). Specific protocols were developed to identify potentially eligible patients from the EMR and invite them to complete a web-based family history assessment. KPNW patients were recruited using email, text messaging, and in-clinic booths; DH patients were recruited via mail, phone, and provider referral. Validated risk assessment tools for Lynch syndrome (PREMM5) and heredity breast and ovarian cancer syndrome (B-RST) were adapted for our low-literacy and bilingual (English and Spanish) target population. Genetic testing is offered to patients with greater than average risk for hereditary cancer, or where risk cannot be assessed because of unknown family history or limited family structure. Eligible patients review a multipart, multimedia online consent. Those who consent to participate provide a saliva sample for clinical exome sequencing. Genetic counselors return results by telephone using traditional (usual care active comparator) or modified, communication-focused (experimental) counseling for pathogenic variants, likely pathogenic variants, and select variants of uncertain significance in 39 genes related to cancer risk, pathogenic variants in 79 genes related to medically actionable secondary findings, and 14 genes related to carrier status. Results: In the first four months of recruitment, 258 patients have completed the risk assessment tool (48% are underserved). Of those, 180 (70%) had greater than average risk of hereditary cancer (or limited family history information) and were invited to participate (53% were underserved); 86% of underserved patients and 78% of patients who do not meet criteria for the underserved category have consented. The vast majority of participants complete enrollment without assistance from study staff, and in-person visits are not required for participation. Telephone genetic test result disclosure will begin in December 2018. Conclusions: We have successfully developed online tools for cancer risk assessment that are accessible to underserved and low-literacy populations. These tools may be a cost-effective approach for improving the capture of family history data in the EMR. It does not require a provider to gather the information and the patient gets immediate feedback on results of the risk assessment and appropriate next steps. This abstract is also being presented as Poster A37. Citation Format: Heather Spencer Feigelson, Kathleen F. Mittendorf, Tia L. Kauffman, Katherine Anderson, Sonia Okuyama, Benjamin Wilfond, Gail P. Jarvik, Laura M. Amendola, Carmit McMullen, Fances Lynch, Donna Eubanks, Elizabeth Shuster, Jake Allen, Stephanie A. Kraft, Galen Joseph, Sandra Soo-Jin Lee, Katrina A.B. Goddard. Using web-based tools to assess familial cancer risk in diverse populations [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr PR02.

Clinical Interpretation of Sequence Variants.

Clinical interpretation of DNA sequence variants is a critical step in reporting clinical genetic testing results. Application of next-generation sequencing technology in molecular genetic testing has facilitated diagnoses of genetic disorders in clinical practice. However, the large number of DNA sequence variants detected in clinical specimens, many of which have never been seen before, make clinical interpretation challenging. Recommendations by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have been widely adopted by clinical laboratories around the world to guide clinical interpretation of sequence variants. The ClinGen Sequence Variant Interpretation Working Group and various disease-specific variant curation expert panels have also developed specifications for the ACMG/AMP recommendations. Despite these efforts to standardize variant interpretation in clinical practice, different laboratories may subjectively use professional judgment to determine which criteria are applicable when classifying a variant. In addition, clinicians and researchers who are not familiar with the variant interpretation process may have difficulty understanding clinical genetic reports and communicating the clinical significance of genetic testing results. Here we provide a step-by-step protocol for clinical interpretation of sequence variants, including practical examples. By following this protocol, clinical laboratory geneticists can interpret the clinical significance of sequence variants according to the ACMG/AMP recommendations and ClinGen framework. Furthermore, this article will help clinicians and researchers to understand variant classification in clinical genetic testing reports and evaluate the quality of the reports. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Interpreting the clinical significance of sequence variants Support Protocol: Reevaluating the clinical significance of sequence variants.

A consensus on the standardization of the next generation sequencing process for the diagnosis of genetic diseases (4) - Report interpretation and genetic counseling

Clinical genetic testing results are compiled into a standardized report by genetic specialists and provided to clinicians and patients (Should the patient be intellectually disabled or under 18, the report will be provided to his/her parents or legal guardians). The content of genetic testing report should conform to relevant guidelines, industry standards and consensus. The decisions of clinicians will be made based on the report and clinical indications. Genetic counselors should provide post-test counseling to clinicians and patients or their authorized family members. A mechanism of follow-up visit after the genetic testing should be established with informed consent. Data should be shared by clinical institutions and genome sequencing institutions. As findings upon follow-up visit can help with further evaluation of the results, genome sequencing institutions should regularly re-analyze historical and follow-up data, and the updated results should be shared with clinical institutions. All activities involving reporting, genetic counselling, follow-up visiting, and re-analyzing should follow the relevant guidelines and regulations.

Abstract CS1-2: Breast cancer genetic testing and results in diverse populations

Abstract Sequencing multiple (20-100) cancer-associated genes has rapidly become the clinical standard for hereditary cancer risk assessment. In patients with breast cancer and/or ovarian cancer the BRCA1 and BRCA2 genes have been most widely tested, but a significant number of patients are now found to carry pathogenic (or likely pathogenic) variants in many other genes whose cancer risks are less well-characterized. Moreover, multiple-gene sequencing is associated with a higher rate of uncertain results (variants of uncertain significance), which are more prevalent among racial/ethnic minorities. While pathogenic variants in less well-characterized genes are prevalent, the appropriate management of carriers remains unclear. Questions remain about the magnitude of risk associated with a pathogenic variant in a specific gene; the spectrum of associated cancers; and the extent to which these factors are modified by family cancer history. Data are emerging from epidemiologic studies in various settings. However, clinical practice requires real-time decisions about whom to test, and for which cancers to screen, despite an incomplete evidence base. This lecture will review the current state of the science on genetic testing for hereditary breast and ovarian cancer risk. We have recently collaborated with genetic testing laboratories to link the results of clinical genetic testing to Surveillance, Epidemiology and End Results (SEER) registry records of &amp;gt;150,000 breast cancer and/or ovarian cancer patients. I will present results from the SEER-GeneLINK research initiative, focusing on the use, correlates and outcomes of genetic testing on the population level. Citation Format: Kurian A. Breast cancer genetic testing and results in diverse populations [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr CS1-2.

Discussion on the standard of clinical genetic testing report and the consensus of gene testing industry

The widespread application of next generation sequencing (NGS) in clinical settings has enabled testing, diagnosis, treatment and prevention of genetic diseases. However, many issues have arisen in the meanwhile. One of the most pressing issues is the lack of standards for reporting genetic test results across different service providers. The First Forum on Standards and Specifications for Clinical Genetic Testing was held to address the issue in Shenzhen, China, on October 28, 2017. Participants, including geneticists, clinicians, and representatives of genetic testing service providers, discussed problems of clinical genetic testing services across in China and shared opinions on principles, challenges, and standards for reporting clinical genetic test results. Here we summarize expert opinions presented at the seminar and report the consensus, which will serve as a basis for the development of standards and guidelines for reporting of clinical genetic testing results, in order to promote the standardization and regulation of genetic testing services in China.

Emerging public databases of clinical genetic test results: Implications for precision medicine

Emerging public databases of clinical genetic test results: Implications for precision medicine

Sample Confirmation Testing: A Short Tandem Repeat-Based Quality Assurance and Quality Control Procedure for the eyeGENE Biorepository.

Quality assurance and quality control (QA/QC) procedures are vital to good biorepository management. The National Eye Institute (NEI) core CLIA-certified laboratory of the eyeGENE(®) Network receives blood from individuals with inherited eye conditions and isolates DNA for clinical genetic diagnostic testing and research. Clinical genetic test results are returned to the affected individuals, making it imperative that sample integrity is preserved throughout laboratory processing. A clinically validated, short tandem repeat (STR)-based approach, termed Sample Confirmation Testing (SCT), was developed to ensure that no significant laboratory errors occurred during processing. SCT uses modified protocols from commercial kits to create and compare STR profiles for each participant's original blood and derived DNA. This QA/QC procedure has been performed on 47% of the more than 6000 participants in the eyeGENE Biorepository and has identified significant laboratory errors in 0.4% of samples tested. SCT improves the quality of the data returned to affected individuals and the data distributed to researchers using eyeGENE samples by ensuring the integrity of the samples and aiding in curation of the biorepository. This approach serves as a model for other repositories to improve sample quality and management procedures.

Results of clinical genetic testing of 2,912 probands with hypertrophic cardiomyopathy: expanded panels offer limited additional sensitivity.

Hypertrophic cardiomyopathy (HCM) is caused primarily by pathogenic variants in genes encoding sarcomere proteins. We report genetic testing results for HCM in 2,912 unrelated individuals with nonsyndromic presentations from a broad referral population over 10 years. Genetic testing was performed by Sanger sequencing for 10 genes from 2004 to 2007, by HCM CardioChip for 11 genes from 2007 to 2011 and by next-generation sequencing for 18, 46, or 51 genes from 2011 onward. The detection rate is ~32% among unselected probands, with inconclusive results in an additional 15%. Detection rates were not significantly different between adult and pediatric probands but were higher in females compared with males. An expanded gene panel encompassing more than 50 genes identified only a very small number of additional pathogenic variants beyond those identifiable in our original panels, which examined 11 genes. Familial genetic testing in at-risk family members eliminated the need for longitudinal cardiac evaluations in 691 individuals. Based on the projected costs derived from Medicare fee schedules for the recommended clinical evaluations of HCM family members by the American College of Cardiology Foundation/American Heart Association, our data indicate that genetic testing resulted in a minimum cost savings of about $0.7 million. Clinical HCM genetic testing provides a definitive molecular diagnosis for many patients and provides cost savings to families. Expanded gene panels have not substantively increased the clinical sensitivity of HCM testing, suggesting major additional causes of HCM still remain to be identified.

A review of the role of electronic health record in genomic research.

Electronic health record (EHR)-driven genomic research is a recent strategy used to answer research questions using EHR data linked to DNA samples. In models using EHR, after the subject's DNA is collected, a linkage between the DNA sample and the EHR data is maintained. This makes the EHR the paramount source of phenotypic information. The National Human Genome Research Institute sponsored Electronic Medical Records and Genomics (eMERGE) network began in five sites in 2007 and was expanded to nine sites in 2012. This network has developed the methods and best practices for utilizing EHR as a tool for genomic research. Therefore, it is vital to understand the configuration of EHR used to capture data in clinical practice and feasibility of integration with clinical genetic test results. We present a detailed review of the role and importance of EHR in the field of genomic research.

Clinical genomics in the world of the electronic health record

The widespread adoption of electronic health records presents a number of benefits to the field of clinical genomics. They include the ability to return results to the practitioner, to use genetic findings in clinical decision support, and to have data collected in the electronic health record that serve as a source of phenotypic information for analysis purposes. Not all electronic health records are created equal, however. They differ in their features, capabilities, and ease of use. Therefore, to understand the potential of the electronic health record, it is first necessary to understand its capabilities and the impact that implementation strategy has on usability. Specifically, we focus on the following areas: (i) how the electronic health record is used to capture data in clinical practice settings; (ii) how the implementation and configuration of the electronic health record affect the quality and availability of data; (iii) the management of clinical genetic test results and the feasibility of electronic health record integration; and (iv) the challenges of implementing an electronic health record in a research-intensive environment. This is followed by a discussion of the minimum functional requirements that an electronic health record must meet to enable the satisfactory integration of genomic results as well as the open issues that remain.

Genetic Testing for Inherited Colon Cancer

The genes associated with each of the inherited syndromes of colon cancer have now been identified, and genetic testing is available for diagnosis. These syndromes include familial adenomatous polyposis, hereditary nonpolyposis colorectal cancer, Peutz-Jeghers syndrome, juvenile polyposis syndrome, and, possibly, Cowden's syndrome. Clinical genetic testing approaches have been developed for each of these syndromes and are now a part of accepted clinical care. Disease-causing mutations can be found in the majority of families affected with one of the inherited syndromes, and, most importantly, once a mutation is found in an index case of the family, relatives can be tested for the presence or absence of that mutation with near 100% accuracy. Cancer screening and management in syndrome families is then based on the results of genetic testing. For the physician to order and properly interpret genetic tests, a basic understanding of the types of mutations that lead to inherited disease and the methods for detecting them is vital. These issues will be presented. Additional clinical issues somewhat unique to genetic testing include genetic counseling and informed consent for genetic testing, both of which will also be reviewed. Often the most difficult aspect of genetic testing is deciding which patients and families should undergo the testing. Furthermore, this issue is quite specific for each of the syndromes. Thus, following presentation of general principles of selection for genetic testing, a detailed approach for identifying persons who should undergo testing for each of the individual syndromes will be given, together with relevant descriptions of the syndromes. Finally, the ongoing work to discover new and possibly more common but less penetrant colon cancer susceptibility genes that cause common familial colon cancer will be presented.