The future is now: Technology's impact on the practice of genetic counseling.

Smartphones, artificial intelligence, automation, digital communication, and other types of technology are playing an increasingly important role in our daily lives. It is no surprise that technology is also shaping the practice of medicine, and more specifically the practice of genetic counseling. While digital tools have been part of the practice of medical genetics for decades, such as internet- or CD-ROM-based tools like Online Mendelian Inheritance in Man and Pictures of Standard Syndromes and Undiagnosed Malformations in the 1980s, the potential for emerging tools to change how we practice and the way patients consume information is startling. Technology has the potential to aid in at-risk patient identification, assist in generating a differential diagnosis, improve efficiency in medical history collection and risk assessment, provide educational support for patients, and streamline follow-up. Here we review the historic and current uses of technology in genetic counseling, identify challenges to integration, and propose future applications of technology that can shape the practice of genetic counseling.

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

The molecular epidemiology of Huntington disease is related to intermediate allele frequency and haplotype in the general population.

Huntington disease (HD) is the most common monogenic neurodegenerative disorder in populations of European ancestry, but occurs at lower prevalence in populations of East Asian or black African descent. New mutations for HD result from CAG repeat expansions of intermediate alleles (IAs), usually of paternal origin. The differing prevalence of HD may be related to the rate of new mutations in a population, but no comparative estimates of IA frequency or the HD new mutation rate are available. In this study, we characterize IA frequency and the CAG repeat distribution in fifteen populations of diverse ethnic origin. We estimate the HD new mutation rate in a series of populations using molecular IA expansion rates. The frequency of IAs was highest in Hispanic Americans and Northern Europeans, and lowest in black Africans and East Asians. The prevalence of HD correlated with the frequency of IAs by population and with the proportion of IAs found on the HD-associated A1 haplotype. The HD new mutation rate was estimated to be highest in populations with the highest frequency of IAs. In European ancestry populations, one in 5,372 individuals from the general population and 7.1% of individuals with an expanded CAG repeat in the HD range are estimated to have a molecular new mutation. Our data suggest that the new mutation rate for HD varies substantially between populations, and that IA frequency and haplotype are closely linked to observed epidemiological differences in the prevalence of HD across major ancestry groups in different countries.

Outcomes of a Randomized Controlled Trial of Genomic Counseling for Patients Receiving Personalized and Actionable Complex Disease Reports.

There has been very limited study of patients with chronic disease receiving potentially actionable genomic based results or the utilization of genetic counselors in the online result delivery process. We conducted a randomized controlled trial on 199 patients with chronic disease each receiving eight personalized and actionable complex disease reports online. Primary study aims were to assess the impact of in-person genomic counseling on 1) causal attribution of disease risk, 2) personal awareness of disease risk, and 3) perceived risk of developing a particular disease. Of 98 intervention arm participants (mean age = 57.8; 39% female) randomized for in-person genomic counseling, 76 (78%) were seen. In contrast, control arm participants (n = 101; mean age = 58.5; 54% female) were initially not offered genomic counseling as part of the study protocol but were able to access in-person genomic counseling, if they requested it, 3-months post viewing of at least one test report and post-completion of the study-specific follow-up survey. A total of 64 intervention arm and 59 control arm participants completed follow-up survey measures. We found that participants receiving in-person genomic counseling had enhanced objective understanding of the genetic variant risk contribution for multiple complex diseases. Genomic counseling was associated with lowered participant causal beliefs in genetic influence across all eight diseases, compared to control participants. Our findings also illustrate that for the majority of diseases under study, intervention arm participants believed they knew their genetic risk status better than control arm subjects. Disease risk was modified for the majority during genomic counseling, due to the assessment of more comprehensive family history. In conclusion, for patients receiving personalized and actionable genomic results through a web portal, genomic counseling enhanced their objective understanding of the genetic variant risk contribution to multiple common diseases. These results support the development of additional genomic counseling interventions to ensure a high level of patient comprehension and improve patient-centered health outcomes.

Genetic Counselors in Startup Companies: Redefining the Genetic Counselor Role.

Genetic counselors (GCs) have recently begun moving into non-clinic based roles in increasing numbers. A relatively new role for GCs is working for startup companies. Startups are newly established companies in the phase of developing and researching new scalable businesses. This article explores the experiences of four GCs working at different startup companies and aims to provide resources for GCs interested in learning more about these types of roles. The article describes startup culture, including a relatively flat organizational structure, quick product iterations, and flexibility, among other unique cultural characteristics. Financial considerations are described, including how to understand and evaluate a company's financial status, along with a brief explanation of alternate forms of compensation including stock options and equity. Specifically, the article details the uncertainties and rewards of working in a fast-paced startup environment that affords opportunities to try new roles and use the genetic counseling skill set in new ways. This article aims to aid GCs in determining whether a startup environment would be a good fit, learning how to evaluate a specific startup, and understanding how to market themselves for positions at startups.

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Using the Coriell Personalized Medicine Collaborative Data to conduct a genome-wide association study of sleep duration.

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome-wide association studies (GWAS). However, genome-wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self-reported sleep duration, demographic and lifestyle variables, and genome-wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self-reported data collected through the CPMC are robust, and our genome-wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep.

Characterizing genetic variants for clinical action.

Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome-scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.

A randomized trial of the clinical utility of genetic testing for obesity: design and implementation considerations.

BACKGROUND: Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts. Currently, testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies. Despite the availability of this type of testing, there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses. PURPOSE: We describe the key issues in the design and implementation of a randomized controlled trial examining the clinical utility of providing genetic risk information for obesity. METHODS: Participants are being recruited from the Coriell Personalized Medicine Collaborative, an ongoing, longitudinal research cohort study designed to determine the utility of personal genome information in health management and clinical decision making. The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity, which are based on lifestyle risk factors. The trial employs a 2 × 2 factorial design in order to examine the effects of providing genetic risk information for obesity, alone or in combination with lifestyle risk information, on participants' psychological responses, behavioral intentions, health behaviors, and weight. RESULTS: The factorial design generated four experimental arms based on communication of estimated risk to participants: (1) no risk feedback (control), (2) genetic risk only, (3) lifestyle risk only, and (4) both genetic and lifestyle risk (combined). Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical standards and methodological rigor. Following the launch of the trial in September 2011, implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol. Although monitoring of these efforts is ongoing, initial observations show a doubling of enrollment and reduced attrition. LIMITATIONS: The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months. This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases. This nesting in a larger study may attenuate the effects of obesity risk information and has implications for the generalizability of study findings. CONCLUSIONS: This randomized trial examines value of obesity genetic information, both when provided independently and when combined with lifestyle risk assessment, to motivate individuals to engage in healthy lifestyle behaviors. Study findings will guide future intervention efforts to effectively communicate genetic risk information.

Assessing the integration of genomic medicine in genetic counseling training programs.

Medical genetics has entered a period of transition from genetics to genomics. Genetic counselors (GCs) may take on roles in the clinical implementation of genomics. This study explores the perspectives of program directors (PDs) on including genomic medicine in GC training programs, as well as the status of this integration. Study methods included an online survey, an optional one-on-one telephone interview, and an optional curricula content analysis. The majority of respondents (15/16) reported that it is important to include genomic medicine in program curricula. Most topics of genomic medicine are either "currently taught" or "under development" in all participating programs. Interview data from five PDs and one faculty member supported the survey data. Integrating genomics in training programs is challenging, and it is essential to develop genomics resources for curricula.

Personalized genomic results: analysis of informational needs.

Use of genomic information in healthcare is increasing; however data on the needs of consumers of genomic information is limited. The Coriell Personalized Medicine Collaborative (CPMC) is a longitudinal study investigating the utility of personalized medicine. Participants receive results reflecting risk of common complex conditions and drug-gene pairs deemed actionable by an external review board. To explore the needs of individuals receiving genomic information we reviewed all genetic counseling sessions with CPMC participants. A retrospective qualitative review of notes from 157 genetic counseling inquiries was conducted. Notes were coded for salient themes. Five primary themes; "understanding risk", "basic genetics", "complex disease genetics", "what do I do now?" and "other" were identified. Further review revealed that participants had difficulty with basic genetic concepts, confused relative and absolute risks, and attributed too high a risk burden to individual single nucleotide polymorphisms (SNPs). Despite these hurdles, counseled participants recognized that behavior changes could potentially mitigate risk and there were few comments alluding to an overly deterministic or fatalistic interpretation of results. Participants appeared to recognize the multifactorial nature of the diseases for which results were provided; however education to understand the complexities of genomic risk information was often needed.

"It's not like judgment day": public understanding of and reactions to personalized genomic risk information.

The value of genomic risk assessment depends upon patients making appropriate behavioral changes in response to increased risk leading to disease prevention and early detection. To date, few studies have investigated consumers' response to personalized genomic disease risk information. To address this gap, we conducted semi-structured interviews with 60 adults participating in the Coriell Personalized Medicine Collaborative. The interviews took place after receiving results providing genomic and other risk information for up to eight common complex diseases. We found that participants were most likely to recall results which conferred an increased risk or those of particular personal interest. Participants understood the multi-factorial nature of common complex disease, and generally did not have negative emotional responses or overly deterministic perceptions of their results. Although most participants expressed a desire to use results to improve their health, a minority had actually taken action (behavior change or shared results with their doctor) at the time of the interview. These results suggest that participants have a reasonable understanding of genomic risk information and that provision of genomic risk information may motivate behavior change in some individuals; however additional work is needed to better understand the lack of change seen in the majority of participants.

Genetic risk estimation in the Coriell Personalized Medicine Collaborative.

PURPOSE: Recent genome wide-association studies have identified hundreds of single nucleotide polymorphisms associated with common complex diseases. With the momentum of these discoveries comes a need to communicate this information to individuals. METHODS: The Coriell Personalized Medicine Collaborative is an observational research study designed to evaluate the utility of personalized genomic information in health care. Participants provide saliva samples for genotyping and complete extensive on-line medical history, family history, and lifestyle questionnaires. Only results for diseases deemed potentially actionable by an independent advisory board are reported. RESULTS: We present our methodology for developing personalized reports containing risks for both genetic and nongenetic factors. Risk estimates are given as relative risk, derived or reported from representative peer-reviewed publications. Estimates of disease prevalence are also provided. Presenting risk as relative risk allows for consistent reporting across multiple diseases and across genetic and nongenetic factors. Using this approach eliminates the need for assumptions regarding population lifetime risk estimates. Publications used for risk reporting are selected based on the strength of the design and study quality. CONCLUSION: Coriell Personalized Medicine Collaborative risk reports demonstrate an approach to communicating risk of complex disease via the web that encompasses risks due to genetic variants along with risks caused by family history and lifestyle factors.

Genetic and clinical heterogeneity in eIF2B-related disorder.

Eukaryotic initiation factor 2B (eIF2B)-related disorders are heritable white matter disorders with a variable clinical phenotype (including vanishing white matter disease and ovarioleukodystrophy) and an equally heterogeneous genotype. We report 9 novel mutations in the EIF2B genes in our subject population, increasing the number of known mutations to more than 120. Using homology modeling, we have analyzed the impact of novel mutations on the 5 subunits of the eIF2B protein. Although recurrent mutations have been found at CpG dinucleotides in the EIF2B genes, the high incidence of private or low frequency mutations increases the challenge of providing rapid genetic confirmation of this disorder, and limits the application of EIF2B screening in cases of undiagnosed leukodystrophy.

Precision Military Medicine: Conducting a multi-site clinical utility study of genomic and lifestyle risk factors in the United States Air Force.

Following several years enrolling disease-specific and otherwise healthy cohorts into the Coriell Personalized Medicine Collaborative, a prospective study aimed at evaluating the clinical utility of personal genomic information for common complex disease and pharmacogenomics, the Coriell Personalized Medicine Collaborative expanded to create a military cohort, specifically, the United States Air Force. Initial recruitment focused on Air Force Medical Service personnel and later expanded to include all Active Duty Air Force members and beneficiaries. Now in its 6th year, the study has produced a wide variety of insights, including optimal study design for military-sponsored genomic research, and discussion on genetic information sharing between and amongst Air Force study participants, civilian and military researchers, and the United States Department of Defense. Over the longer term, analyses will further contribute to the development of policies and processes relevant to clinical decision support and data sharing within the US military, and on-going work with the Air Force Medical Service sub-cohort will generate critical insights into how best to deploy useful genomic information in clinical care. Here we discuss challenges faced and critical success factors for military-civilian collaborations around genomic research.

Huntington disease reduced penetrance alleles occur at high frequency in the general population.

OBJECTIVE: To directly estimate the frequency and penetrance of CAG repeat alleles associated with Huntington disease (HD) in the general population. METHODS: CAG repeat length was evaluated in 7,315 individuals from 3 population-based cohorts from British Columbia, the United States, and Scotland. The frequency of ≥36 CAG alleles was assessed out of a total of 14,630 alleles. The general population frequency of reduced penetrance alleles (36-39 CAG) was compared to the prevalence of patients with HD with genetically confirmed 36-39 CAG from a multisource clinical ascertainment in British Columbia, Canada. The penetrance of 36-38 CAG repeat alleles for HD was estimated for individuals ≥65 years of age and compared against previously reported clinical penetrance estimates. RESULTS: A total of 18 of 7,315 individuals had ≥36 CAG, revealing that approximately 1 in 400 individuals from the general population have an expanded CAG repeat associated with HD (0.246%). Individuals with CAG 36-37 genotypes are the most common (36, 0.096%; 37, 0.082%; 38, 0.027%; 39, 0.000%; ≥40, 0.041%). General population CAG 36-38 penetrance rates are lower than penetrance rates extrapolated from clinical cohorts. CONCLUSION: HD alleles with a CAG repeat length of 36-38 occur at high frequency in the general population. The infrequent diagnosis of HD at this CAG length is likely due to low penetrance. Another important contributing factor may be reduced ascertainment of HD in those of older age.

A randomized trial Examining The Impact Of Communicating Genetic And Lifestyle Risks For Obesity.

OBJECTIVE: Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. METHODS: A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. RESULTS: A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

The genetics of muscle atrophy and growth: the impact and implications of polymorphisms in animals and humans.

Much of the vast diversity we see in animals and people is governed by genetic loci that have quantitative effects of phenotype (quantitative trait loci; QTLs). Here we review the current knowledge of the genetics of atrophy and hypertrophy in both animal husbandry (meat quantity and quality), and humans (muscle size and performance). The selective breeding of animals for meat has apparently led to a few genetic loci with strong effects, with different loci in different animals. In humans, muscle quantitative trait loci (QTLs) appear to be more complex, with few "major" loci identified to date, although this is likely to change in the near future. We describe how the same phenotypic traits we see as positive, greater lean muscle mass in cattle or a better exercise results in humans, can also have negative "side effects" given specific environmental challenges. We also discuss the strength and limitations of single nucleotide polymorphisms (SNP) association studies; what the reader should look for and expect in a published study. Lastly we discuss the ethical and societal implications of this genetic information. As more and more research into the genetic loci that dictate phenotypic traits become available, the ethical implications of testing for these loci become increasingly important. As a society, most accept testing for genetic diseases or susceptibility, but do we as easily accept testing to determine one's athletic potential to be an Olympic endurance runner, or quarterback on the high school football team.

Nondisease genetic testing: reporting of muscle SNPs shows effects on self-concept and health orientation scales.

The purpose of this study was to assess the impact of genetic self-knowledge (nondisease genotype information) on individual self-concept and Health Orientation Scale (HOS). Adult volunteers (n=257) were recruited from an ongoing genetic association study identifying muscle quantitative trait loci (QTLs). Participants completed psychosocial assessments before and after 12 weeks of resistance training of the nondominant arm. At study exit, a genetic counselor informed participants of genetic test results on three to four genes that have an association with muscle-related traits, and counseled subjects on the potential significance of these findings. The second psychosocial assessment was performed immediately following this counseling session. The Tennessee Self-Concept Scale v.2 (TSCS:2) and the HOS showed female subjects to have a significantly greater positive change between first and second assessments, relative to male subjects. Most self-concept subscales improved significantly, when 'neutral' genotypes (no anticipated beneficial or deleterious impact) were reported, compared to positive genotypes. TSCS:2 subscales showing improvement included: total (P=0.013); physical (P=0.004); satisfaction (P=0.019); and behavioral (P=0.047). HOS subscales showing improvement included health image concern (P=0.006); and health expectations (P=0.047). In conclusion, these results suggest that genetic self-knowledge affects self-concept, consistent with the 'attribution' theory. Individuals who received neutral genetic information attributed positive changes from the exercise program to their own abilities, while those who received positive information were more likely to attribute positive changes to their genetics. This study is limited by the ability to determine the direction of the impact of nondisease genetic information presented to participants.