Clinical validation of genomic functional screen data: Analysis of observed BRCA1 variants in an unselected population cohort.

Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.

Clinical outcomes of a genomic screening program for actionable genetic conditions.

PURPOSE: Three genetic conditions-hereditary breast and ovarian cancer syndrome, Lynch syndrome, and familial hypercholesterolemia-have tier 1 evidence for interventions that reduce morbidity and mortality, prompting proposals to screen unselected populations for these conditions. We examined the impact of genomic screening on risk management and early detection in an unselected population. METHODS: Observational study of electronic health records (EHR) among individuals in whom a pathogenic/likely pathogenic variant in a tier 1 gene was discovered through Geisinger's MyCode project. EHR of all eligible participants was evaluated for a prior genetic diagnosis and, among participants without such a diagnosis, relevant personal/family history, postdisclosure clinical diagnoses, and postdisclosure risk management. RESULTS: Eighty-seven percent of participants (305/351) did not have a prior genetic diagnosis of their tier 1 result. Of these, 65% had EHR evidence of relevant personal and/or family history of disease. Of 255 individuals eligible to have risk management, 70% (n = 179) had a recommended risk management procedure after results disclosure. Thirteen percent of participants (41/305) received a relevant clinical diagnosis after results disclosure. CONCLUSION: Genomic screening programs can identify previously unrecognized individuals at increased risk of cancer and heart disease and facilitate risk management and early cancer detection.

Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants.

Importance: Detection of disease-associated variants in the BRCA1 and BRCA2 (BRCA1/2) genes allows for cancer prevention and early diagnosis in high-risk individuals. Objectives: To identify pathogenic and likely pathogenic (P/LP) BRCA1/2 variants in an unselected research cohort, and to characterize the features associated with P/LP variants. Design, Setting, and Participants: This is a cross-sectional study of adult volunteers (n = 50 726) who underwent exome sequencing at a single health care system (Geisinger Health System, Danville, Pennsylvania) from January 1, 2014, to March 1, 2016. Participants are part of the DiscovEHR cohort and were identified through the Geisinger MyCode Community Health Initiative. They consented to a research protocol that included sequencing and return of actionable test results. Clinical data from electronic health records and clinical visits were correlated with variants. Comparisons were made between those with (cases) and those without (controls) P/LP variants in BRCA1/2. Main Outcomes: Prevalence of P/LP BRCA1/2 variants in cohort, proportion of variant carriers not previously ascertained through clinical testing, and personal and family history of relevant cancers among BRCA1/2 variant carriers and noncarriers. Results: Of the 50 726 health system patients who underwent exome sequencing, 50 459 (99.5%) had no expected pathogenic BRCA1/2 variants and 267 (0.5%) were BRCA1/2 carriers. Of the 267 cases (148 [55.4%] were women and 119 [44.6%] were men with a mean [range] age of 58.9 [23-90] years), 183 (68.5%) received clinically confirmed results in their electronic health record. Among the 267 participants with P/LP BRCA1/2 variants, 219 (82.0%) had no prior clinical testing, 95 (35.6%) had BRCA1 variants, and 172 (64.4%) had BRCA2 variants. Syndromic cancer diagnoses were present in 11 (47.8%) of the 23 deceased BRCA1/2 carriers and in 56 (20.9%) of all 267 BRCA1/2 carriers. Among women, 31 (20.9%) of 148 variant carriers had a personal history of breast cancer, compared with 1554 (5.2%) of 29 880 noncarriers (odds ratio [OR], 5.95; 95% CI, 3.88-9.13; P < .001). Ovarian cancer history was present in 15 (10.1%) of 148 variant carriers and in 195 (0.6%) of 29 880 variant noncarriers (OR, 18.30; 95% CI, 10.48-31.4; P < .001). Among 89 BRCA1/2 carriers without prior testing but with comprehensive personal and family history data, 44 (49.4%) did not meet published guidelines for clinical testing. Conclusions and Relevance: This study found that compared with previous clinical care, exome sequencing-based screening identified 5 times as many individuals with P/LP BRCA1/2 variants. These findings suggest that genomic screening may identify BRCA1/2-associated cancer risk that might otherwise remain undetected within health care systems and may provide opportunities to reduce morbidity and mortality in patients.

Analysis of DNA methylation in a three-generation family reveals widespread genetic influence on epigenetic regulation.

The methylation of cytosines in CpG dinucleotides is essential for cellular differentiation and the progression of many cancers, and it plays an important role in gametic imprinting. To assess variation and inheritance of genome-wide patterns of DNA methylation simultaneously in humans, we applied reduced representation bisulfite sequencing (RRBS) to somatic DNA from six members of a three-generation family. We observed that 8.1% of heterozygous SNPs are associated with differential methylation in cis, which provides a robust signature for Mendelian transmission and relatedness. The vast majority of differential methylation between homologous chromosomes (>92%) occurs on a particular haplotype as opposed to being associated with the gender of the parent of origin, indicating that genotype affects DNA methylation of far more loci than does gametic imprinting. We found that 75% of genotype-dependent differential methylation events in the family are also seen in unrelated individuals and that overall genotype can explain 80% of the variation in DNA methylation. These events are under-represented in CpG islands, enriched in intergenic regions, and located in regions of low evolutionary conservation. Even though they are generally not in functionally constrained regions, 22% (twice as many as expected by chance) of genes harboring genotype-dependent DNA methylation exhibited allele-specific gene expression as measured by RNA-seq of a lymphoblastoid cell line, indicating that some of these events are associated with gene expression differences. Overall, our results demonstrate that the influence of genotype on patterns of DNA methylation is widespread in the genome and greatly exceeds the influence of imprinting on genome-wide methylation patterns.

Genomic and personalized medicine: foundations and applications.

The last decade has witnessed a steady embrace of genomic and personalized medicine by senior government officials, industry leadership, health care providers, and the public. Genomic medicine, which is the use of information from genomes and their derivatives (RNA, proteins, and metabolites) to guide medical decision making-is a key component of personalized medicine, which is a rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. As medicine begins to embrace genomic tools that enable more precise prediction and treatment disease, which include "whole genome" interrogation of sequence variation, transcription, proteins, and metabolites, the fundamentals of genomic and personalized medicine will require the development, standardization, and integration of several important tools into health systems and clinical workflows. These tools include health risk assessment, family health history, and clinical decision support for complex risk and predictive information. Together with genomic information, these tools will enable a paradigm shift to a comprehensive approach that will identify individual risks and guide clinical management and decision making, all of which form the basis for a more informed and effective approach to patient care. DNA-based risk assessment for common complex disease, molecular signatures for cancer diagnosis and prognosis, and genome-guided therapy and dose selection are just among the few important examples for which genome information has already enabled personalized health care along the continuum from health to disease. In addition, information from individual genomes, which is a fast-moving area of technological development, is spawning a social and information revolution among consumers that will undoubtedly affect health care decision making. Although these and other scientific findings are making their way from the genome to the clinic, the full application of genomic and personalized medicine in health care will require dramatic changes in regulatory and reimbursement policies as well as legislative protections for privacy for system-wide adoption. Thus, there are challenges from both a scientific and a policy perspective to personalized health care; however, they will be confronted and solved with the certainty that the science behind genomic medicine is sound and the practice of medicine that it informs is evidence based.

Genomic medicine: genetic variation and its impact on the future of health care.

Advances in genome technology and other fruits of the Human Genome Project are playing a growing role in the delivery of health care. With the development of new technologies and opportunities for large-scale analysis of the genome, transcriptome, proteome and metabolome, the genome sciences are poised to have a profound impact on clinical medicine. Cancer prognostics will be among the first major test cases for a genomic medicine paradigm, given that all cancer is caused by genomic instability, and microarrays allow assessment of patients' entire expressed genomes. Analysis of breast cancer patients' expression patterns can already be highly correlated with recurrence risks. By integrating clinical data with gene expression profiles, imaging, metabolomic profiles and proteomic data, the prospect for developing truly individualized care becomes ever more real. Notwithstanding these promises, daunting challenges remain for genomic medicine. Success will require planning robust prospective trials, analysing health care economic and outcome data, assuaging insurance and privacy concerns, developing health delivery models that are commercially viable and scaling up to meet the needs of the whole population.

Human artificial chromosomes with alpha satellite-based de novo centromeres show increased frequency of nondisjunction and anaphase lag.

Human artificial chromosomes have been used to model requirements for human chromosome segregation and to explore the nature of sequences competent for centromere function. Normal human centromeres require specialized chromatin that consists of alpha satellite DNA complexed with epigenetically modified histones and centromere-specific proteins. While several types of alpha satellite DNA have been used to assemble de novo centromeres in artificial chromosome assays, the extent to which they fully recapitulate normal centromere function has not been explored. Here, we have used two kinds of alpha satellite DNA, DXZ1 (from the X chromosome) and D17Z1 (from chromosome 17), to generate human artificial chromosomes. Although artificial chromosomes are mitotically stable over many months in culture, when we examined their segregation in individual cell divisions using an anaphase assay, artificial chromosomes exhibited more segregation errors than natural human chromosomes (P < 0.001). Naturally occurring, but abnormal small ring chromosomes derived from chromosome 17 and the X chromosome also missegregate more than normal chromosomes, implicating overall chromosome size and/or structure in the fidelity of chromosome segregation. As different artificial chromosomes missegregate over a fivefold range, the data suggest that variable centromeric DNA content and/or epigenetic assembly can influence the mitotic behavior of artificial chromosomes.

An ectopic human XIST gene can induce chromosome inactivation in postdifferentiation human HT-1080 cells.

It has been believed that XIST RNA requires a discrete window in early development to initiate the series of chromatin-remodeling events that form the heterochromatic inactive X chromosome. Here we investigate four adult male HT-1080 fibrosarcoma cell lines expressing ectopic human XIST and demonstrate that these postdifferentiation cells can undergo chromosomal inactivation outside of any normal developmental context. All four clonal lines inactivated the transgene-containing autosome to varying degrees and with variable stability. One clone in particular consistently localized the ectopic XIST RNA to a discrete chromosome territory that exhibited striking hallmarks of inactivation, including long-range transcriptional inactivation. Results suggest that some postdifferentiation cell lines are capable of de novo chromosomal inactivation; however, long-term retention of autosomal inactivation was less common, which suggests that autosomal inactivation may confer a selective disadvantage. These results have fundamental significance for understanding genomic programming in early development.