Personal genomics: information can be harmful

Neutral, Negative, or Negligible? Changes in Patient Perceptions of Disease Risk Following Receipt of a Negative Genomic Screening Result

Most individuals who undergo genomic screening will receive negative results or results not sufficient to warrant a clinical response. Even though a majority of individuals receive negative results, little is known about how negative results may impact individuals' perception of disease risk. Changes in risk perception (specifically reductions in perceived risk) may affect both probands and their family members if inaccurate information is communicated to family members. We surveyed patients who received negative results as part of their participation in a genomic screening study and assessed their perceptions of disease risk following receipt of results. Participants had either hyperlipidemia or colon polyps (or both) and received their negative genomic screening results by mail. Of 1712 total individuals recruited, 1442 completed the survey (84.2% completion rate). Approximately one quarter of individuals believed their risk for heart disease to be lower and approximately one third of individuals believed their risk for colon cancer to be lower after receiving and evaluating their negative genomic screening result. 78% of those who believed their risk for one or both diseases had declined had already shared or intended to share their result with family members. Our study suggests patients may interpret a negative genomic screening result as implying a reduction in their overall disease risk.

Proposed guidelines to evaluate scientific validity and evidence for genotype-based dietary advice

Nutrigenetic research examines the effects of inter-individual differences in genotype on responses to nutrients and other food components, in the context of health and of nutrient requirements. A practical application of nutrigenetics is the use of personal genetic information to guide recommendations for dietary choices that are more efficacious at the individual or genetic subgroup level relative to generic dietary advice. Nutrigenetics is unregulated, with no defined standards, beyond some commercially adopted codes of practice. Only a few official nutrition-related professional bodies have embraced the subject, and, consequently, there is a lack of educational resources or guidance for implementation of the outcomes of nutrigenetic research. To avoid misuse and to protect the public, personalised nutrigenetic advice and information should be based on clear evidence of validity grounded in a careful and defensible interpretation of outcomes from nutrigenetic research studies. Evidence requirements are clearly stated and assessed within the context of state-of-the-art 'evidence-based nutrition'. We have developed and present here a draft framework that can be used to assess the strength of the evidence for scientific validity of nutrigenetic knowledge and whether 'actionable'. In addition, we propose that this framework be used as the basis for developing transparent and scientifically sound advice to the public based on nutrigenetic tests. We feel that although this area is still in its infancy, minimal guidelines are required. Though these guidelines are based on semi-quantitative data, they should stimulate debate on their utility. This framework will be revised biennially, as knowledge on the subject increases.

Waste, Leaks, and Failures in the Biomarker Pipeline

BACKGROUND

The large, expanding literature on biomarkers is characterized by almost ubiquitous significant results, with claims about the potential importance, but few of these discovered biomarkers are used in routine clinical care.

CONTENT

The pipeline of biomarker development includes several specific stages: discovery, validation, clinical translation, evaluation, implementation (and, in the case of nonutility, deimplementation). Each of these stages can be plagued by problems that cause failures of the overall pipeline. Some problems are nonspecific challenges for all biomedical investigation, while others are specific to the peculiarities of biomarker research. Discovery suffers from poor methods and incomplete and selective reporting. External independent validation is limited. Selection for clinical translation is often shaped by nonrational choices. Evaluation is sparse and the clinical utility of many biomarkers remains unknown. The regulatory environment for biomarkers remains weak and guidelines can reach biased or divergent recommendations. Removing inefficient or even harmful biomarkers that have been entrenched in clinical care can meet with major resistance.

SUMMARY

The current biomarker pipeline is too prone to failures. Consideration of clinical needs should become a starting point for the development of biomarkers. Improvements can include the use of more stringent methodology, better reporting, larger collaborative studies, careful external independent validation, preregistration, rigorous systematic reviews and umbrella reviews, pivotal randomized trials, and implementation and deimplementation studies. Incentives should be aligned toward delivering useful biomarkers.

An Insufferable Business: Ethics, Nonhuman Animals and Biomedical Experiments

Each year millions of nonhuman animals suffer in biomedical experiments for human health benefits. Clinical ethics demand that nonhuman animals are used in the development of pharmaceuticals and vaccines. Nonhuman animals are also used for fundamental biomedical research. Biomedical research that uses nonhuman animals is big business but the financial gains are generally occluded. This paper explores how such research generates profits and gains for those associated with the industry. Research establishments, scientists, laboratories, companies that sell nonhuman animal subjects, that supply equipment for the research, and corporations that market the resulting products are among those that benefit financially. Given the complex articulation of ethical codes, enormous corporate profits that are secured and personal returns that are made, the accepted moral legitimacy of such experiments is compromised. In order to address this, within the confines of the moral orthodoxy, more could to be done to ensure transparency and to extricate the vested financial interests from the human health benefits. But such a determination would not address the fundamental issues that should be at the heart of human actions in respect of the nonhuman animals who are used in experiments. The paper concludes with such an address by calling for an end to the denigration of nonhuman animals as experimental subjects who can be used as commodities for profit-maximisation and as tools in experiments for human health benefits, and the implementation of a more inclusive ethic that is informed by universal concern about the suffering of and compassion for all oppressed beings.

Effects of genetic and environmental risk assessment feedback on colorectal cancer screening adherence

Little is known about the impact of genetic and environmental risk assessment (GERA) feedback on colorectal cancer (CRC) screening. In a recently completed randomized trial, primary care patients received GERA feedback based on a blood test for genetic polymorphisms and serum folate level (GERA Group) versus usual care (Control Group). Subsequently, participants were offered CRC screening. Among participants who received GERA feedback, being at elevated risk was negatively associated with prospective CRC screening adherence. Secondary analyses of data from this study were performed to identify independent predictors of adherence among participants who received GERA feedback. We obtained baseline survey, follow-up survey, and endpoint medical records data on sociodemographic background, knowledge, psychosocial characteristics, risk status, and adherence for 285 GERA Group participants. Univariate and multivariable analyses were performed to identify predictors of CRC screening adherence. Following a 6-month outcomes observation period, we also conducted two focus groups with GERA Group participants to assess their perceptions of GERA risk feedback and screening. Content analyses of focus group data were evaluated to gain insights into participant response to risk feedback. Overall, half of GERA Group participants adhered to screening within 6 months after randomization. Multivariable analyses showed a statistically significant interaction between race and GERA feedback status relative to screening adherence (p = 0.043). Among participants who received average risk feedback, adherence was comparable among whites (49.7 %) and nonwhites (54.1 %); however, among those at elevated risk, adherence was substantially higher among whites (66.7 %) compared to nonwhites (33.3 %). Focus group findings suggest that whites were more likely than nonwhites to view elevated risk feedback as a prompt to screen. In response to receiving elevated risk feedback, nonwhites were more likely than whites to report feeling anxiety about the likelihood of being diagnosed with CRC. Further research is needed to explore race-related CRC screening differences in response to GERA feedback.

Genetic and environmental risk assessment and colorectal cancer screening in an average-risk population: a randomized trial

BACKGROUND

New methods are needed to improve health behaviors, such as adherence to colorectal cancer (CRC) screening. Personalized genetic information to guide medical decisions is increasingly available. Whether such information motivates behavioral change is unknown.

OBJECTIVE

To determine whether individualized genetic and environmental risk assessment (GERA) of CRC susceptibility improves adherence to screening in average-risk persons.

DESIGN

2-group, randomized, controlled trial. (ClinicalTrials.gov: NCT0087360).

SETTING

4 medical school-affiliated primary care practices.

PARTICIPANTS

783 participants at average risk for CRC who were not adherent to screening at study entry.

INTERVENTION

Participants were randomly assigned to usual care or GERA, which evaluated methylenetetrahydrofolate reductase polymorphisms and serum folate levels. On the basis of prespecified combinations of polymorphisms and serum folate levels, GERA recipients were told that they were at elevated or average risk for CRC.

MEASUREMENTS

The primary outcome was CRC screening within 6 months of study entry.

RESULTS

Overall screening rates for CRC did not statistically significant differ between the usual care (35.7%) and GERA (33.1%) groups. After adjustment for baseline participant factors, the odds ratio for screening completion for GERA versus usual care was 0.88 (95% CI, 0.64 to 1.22). Within the GERA group, screening rates did not significantly differ between average-risk (38.1%) and elevated-risk (26.9%) participants. Odds ratios for elevated- versus average-risk participants remained nonsignificant after adjustment for covariates (odds ratio, 0.75 [CI, 0.39 to 1.42]).

LIMITATION

Only 1 personalized genetic and environmental interaction and 1 health behavior (CRC screening) were assessed.

CONCLUSION

In average-risk persons, CRC screening uptake was not positively associated with feedback from a single personalized GERA. Additional studies will be required to evaluate whether other approaches to providing GERA affect screening utilization differently. These findings raise concern about the effectiveness of moderately predictive assessment of genetic risk to promote favorable health care behavior.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Translational genomics

The term "Translational Genomics" reflects both title and mission of this new journal. "Translational" has traditionally been understood as "applied research" or "development", different from or even opposed to "basic research". Recent scientific and societal developments have triggered a re-assessment of the connotation that "translational" and "basic" are either/or activities: translational research nowadays aims at feeding the best science into applications and solutions for human society. We therefore argue here basic science to be challenged and leveraged for its relevance to human health and societal benefits. This more recent approach and attitude are catalyzed by four trends or developments: evidence-based solutions; large-scale, high dimensional data; consumer/patient empowerment; and systems-level understanding.

Cancer screening and genetics: a tale of two paradigms

The long-standing medical tradition to "first do no harm" is reflected in population-wide evidence-based recommendations for cancer screening tests that focus primarily on reducing morbidity and mortality. The conventional cancer screening process is predicated on finding early-stage disease that can be treated effectively; yet emerging genetic and genomic testing technologies have moved the target earlier in the disease development process to identify a probabilistic predisposition to disease. Genetic risk information can have varying implications for the health and well-being of patients and their relatives, and has raised important questions about the evaluation and value of risk information. This article explores the paradigms that are being applied to the evaluation of conventional cancer screening tests and emerging genetic and genomic tests of cancer susceptibility, and how these perspectives are shifting and evolving in response to advances in our ability to detect cancer risks. We consider several challenges germane to the evaluation of both categories of tests, including defining benefits and harms in terms of personal and clinical utility, addressing healthcare consumers' information preferences, and managing scientific uncertainty. We encourage research and dialogue aimed at developing a better understanding of the value of all risk information, nongenetic and genetic, to people's lives. Cancer Epidemiol Biomarkers Prev; 23(6); 909-16. ©2014 AACR.

Quantification of population benefit in evaluation of biomarkers: practical implications for disease detection and prevention

BACKGROUND

With the rapid development of "-omic" technologies, an increasing number of purported biomarkers have been identified for cancer and other diseases. The process of identifying those that are most promising and validating them for use at the population level for prevention and early detection is a critical next step in achieving significant health benefits.

METHODS

In this paper, we propose that in order to effectively translate biomarkers for practical clinical use, it is important to distinguish and quantify the differences between the use of biomarkers and other risk factors to identify preventive interventions versus their use in disease risk prediction and early detection. We developed mathematical models for quantitatively evaluating risk and benefit in use of biomarkers for disease prevention or early detection. Simple numerical examples were used to demonstrate the potential applications of the models for various types of data.

RESULTS

We propose an index which takes into account potential adverse consequences of biomarker-driven interventions - the 'naïve' ratio of population benefit (RPB) - to facilitate evaluating the potential impact of biomarkers on cancer prevention and personalized medicine. The index RPB is developed for both binary and continuous biomarkers/risk factors. Examples with computational analyses are presented in the paper to contrast the differences in using biomarkers/risk factors for prevention and early detection.

CONCLUSIONS

Integrating epidemiologic knowledge into clinical decision making is a key step to translate new biomarkers/risk factors into practical use to achieve health benefits. The RPB proposed in this paper considers the absolute risk of a disease in intervention, and takes into account the risk-benefit effects simultaneously for a marker/exposure at the population level. The RPB illustrates a unique approach to quantitatively assess the risk and potential benefits of using a biomarker/risk factor for intervention in both early detection and prevention.

Impact of delivery models on understanding genomic risk for type 2 diabetes

BACKGROUND

Genetic information, typically communicated in-person by genetic counselors, can be challenging to comprehend; delivery of this information online--as is becoming more common--has the potential of increasing these challenges.

METHODS

To address the impact of the mode of delivery of genomic risk information, 300 individuals were recruited from the general public and randomized to receive genomic risk information for type 2 diabetes mellitus in-person from a board-certified genetic counselor or online through the testing company's website.

RESULTS

Participants were asked to indicate their genomic risk and overall lifetime risk as reported on their test report as well as to interpret their genomic risk (increased, decreased, or same as population). For each question, 59% of participants correctly indicated their risk. Participants who received their results in-person were more likely than those who reviewed their results on-line to correctly interpret their genomic risk (72 vs. 47%, p = 0.0002) and report their actual genomic risk (69 vs. 49%, p = 0.002).

CONCLUSIONS

The delivery of personal genomic risk through a trained health professional resulted in significantly higher comprehension. Therefore, if the online delivery of genomic test results is to become more widespread, further evaluation of this method of communication may be needed to ensure the effective presentation of results to promote comprehension.

Neither as harmful as feared by critics nor as empowering as promised by providers: risk information offered direct to consumer by personal genomics companies

In this paper, I investigate ethical and policy aspects of the genetic services and web-rhetoric of companies offering genetic information direct to consumer, and I do so with a special focus on genetic risk information. On their websites, the companies stress that genetic risk testing for multifactorial complex medical conditions such as cardiovascular disease and cancer may empower the consumer and provide valuable input to personal identity. Critics maintain, on the other hand, that testing can be psychologically harmful, is of limited clinical and preventive value, and vulnerable to misinterpretation. I stress the importance of empirical studies in assessing the pros and cons of direct-to-consumer testing and point out that recent empirical studies indicate that this testing is neither as harmful as feared by critics nor as empowering as promised by the companies. However, the testing is not entirely harmless. Remaining problems include testing of third parties without consent and ownership of genotypic and phenotypic information. Moreover, the testing, although not particularly empowering, may still provide input to self-understanding that some people find valuable. Regarding policy-making, I suggest that self-regulation in terms of best practice guidelines may play an important role, but I also stress that national and international regulation may be necessary.

Issues surrounding the health economic evaluation of genomic technologies

AIM

Genomic interventions could enable improved disease stratification and individually tailored therapies. However, they have had a limited impact on clinical practice to date due to a lack of evidence, particularly economic evidence. This is partly because health economists are yet to reach consensus on whether existing methods are sufficient to evaluate genomic technologies. As different approaches may produce conflicting adoption decisions, clarification is urgently required. This article summarizes the methodological issues associated with conducting economic evaluations of genomic interventions.

MATERIALS & METHODS

A structured literature review was conducted to identify references that considered the methodological challenges faced when conducting economic evaluations of genomic interventions.

RESULTS

Methodological challenges related to the analytical approach included the choice of comparator, perspective and timeframe. Challenges in costing centered around the need to collect a broad range of costs, frequently, in a data-limited environment. Measuring outcomes is problematic as standard measures have limited applicability, however, alternative metrics (e.g., personal utility) are underdeveloped and alternative approaches (e.g., cost-benefit analysis) underused. Effectiveness data quality is weak and challenging to incorporate into standard economic analyses, while little is known about patient and clinician behavior in this context. Comprehensive value of information analyses are likely to be helpful.

CONCLUSION

Economic evaluations of genomic technologies present a particular challenge for health economists. New methods may be required to resolve these issues, but the evidence to justify alternative approaches is yet to be produced. This should be the focus of future work in this field.

“It’s our DNA, we deserve the right to test!” A content analysis of a petition for the right to access direct-to-consumer genetic testing

Aims: Various companies are currently advertising or selling genetic tests over the internet using a model of provision referred to as ‘direct-to-consumer’ (DTC). This commercial offer of DTC genetic testing (GT) has fueled a number of scientific, ethical and policy debates. To date there have been few studies published regarding the users’ perspective. This study aimed to obtain information regarding the issues raised by individuals who signed a petition in support of DTC GT and the ‘unrestricted’ access to their genetic information. Materials & methods: We conducted qualitative content analysis of comments written by individuals who signed a public online petition initiated by DIYgenomics (CA, USA) to support “personal access to genetic information”. Results: Of the 523 individuals who signed the petition sponsored by DIYgenomics, 247 individuals also wrote individual comments. A content analysis of these comments reveals that petitioners raised six main issues in support of unrestricted access to DTC GT: that their ownership of their DNA should allow them to have unrestricted access to their genomic information; that they should have the right to their genomic information; that the government has no place in (further) regulating DTC GT; that healthcare professionals should not be placed as intermediaries when purchasing DTC GT services; that many petioners who had already obtained DTC GT had positive experiences with this model of provision; and that genealogy or ancestry DNA testing is one of the main activities petitioners wish to have ‘unrestricted’ or ‘direct’ access. Conclusion: These results give insight into why individuals may support unrestricted access to their genomic information and confirm some of the motivations of users for purchasing DTC GT. Our analysis also brings to the forefront themes that have been raised less often in empirical studies involving motivations to purchase DTC GT services; these include the strongly held beliefs of some petitioners that, since they own their DNA, they should have the right to access the information without (further) government control or physician involvement. Interestingly, the comments left by petitioners also reveal a certain distrust of governmental agencies and healthcare professionals. This urges us to further study the public’s views of these services and the potential impact of these views in order to responsibly address the ongoing debate on DTC GT.

Limitations of medical research and evidence at the patient-clinician encounter scale

We explore some philosophical and scientific underpinnings of clinical research and evidence at the patient-clinician encounter scale. Insufficient evidence and a common failure to use replicable and sound research methods limit us. Both patients and health care may be, in part, complex nonlinear chaotic systems, and predicting their outcomes is a challenge. When trustworthy (credible) evidence is lacking, making correct clinical choices is often a low-probability exercise. Thus, human (clinician) error and consequent injury to patients appear inevitable. Individual clinician decision-makers operate under the philosophical influence of Adam Smith's "invisible hand" with resulting optimism that they will eventually make the right choices and cause health benefits. The presumption of an effective "invisible hand" operating in health-care delivery has supported a model in which individual clinicians struggle to practice medicine, as they see fit based on their own intuitions and preferences (and biases) despite the obvious complexity, errors, noise, and lack of evidence pervading the system. Not surprisingly, the "invisible hand" does not appear to produce the desired community health benefits. Obtaining a benefit at the patient-clinician encounter scale requires human (clinician) behavior modification. We believe that serious rethinking and restructuring of the clinical research and care delivery systems is necessary to assure the profession and the public that we continue to do more good than harm. We need to evaluate whether, and how, detailed decision-support tools may enable reproducible clinician behavior and beneficial use of evidence.

Should genetic findings from genome research be reported back to the participants?

BACKGROUND

Today, new and powerful sequencing technology is being used in biomedical research. In parallel, an intense ethical debate has arisen regarding the handling of the information which is generated through such comprehensive analyses. The conflict concerns whether any findings made during research, intended or incidental, should be reported back to the individual research participant. KNOWLEDGE BASIS: We reviewed international academic literature that has addressed the issue of feedback from genetic studies. The arguments in favour and against providing individual information from genome research to research participants were reviewed. Key arguments in this debate are presented and commented on.

RESULTS

A growing number of voices argue in favour of return of research-generated genetic information with reference to key values such as autonomy, respect, charity, mutuality and reciprocity. The counter-arguments are not as easily accessible, but concern the fundamental distinction between research and treatment, which indicates that researchers are not obliged to provide individual information to participants. Partly, the counter-arguments focus on the possible unfortunate consequences that such feedback may have for individuals, research and society as a whole.

INTERPRETATION

We are standing at a crossroads with regard to assessing whether returning research-generated genetic risk information at the individual level is a moral imperative. Here, individually based research ethics run up against concerns of social medicine and research-based obligations. The right balance has probably not yet been found.

Informed consent for whole-genome sequencing studies in the clinical setting. Proposed recommendations on essential content and process

The development of new massive sequencing techniques has now made it possible to significantly reduce the time and costs of whole-genome sequencing (WGS). Although WGS will soon become a routine testing tool, new ethical issues have surfaced. In light of these concerns, a systematic review of papers published by expert authors on IC or specific ethical issues related to IC for WGS analysis in the clinical setting has been conducted using the Pubmed, Embase and Cochrane Library databases. Additionally, a search was conducted for international ethical guidelines for genetic studies published by scientific societies and ethical boards. Based on these documents, a minimum set of information to be provided to patients in the IC form was determined. Fourteen and seven documents from the database search and from scientific societies, respectively, were selected. A very high level of consistency between them was found regarding the recommended IC form content. Pre-test counselling and general information common to all genetic tests should be included in the IC form for WGS for diagnostic purposes, but additional information addressing specific issues on WGS are proposed, such as a plan for the ethical, clinically oriented return of incidental findings. Moreover, storage of additional information for future use should also be agreed upon with the patient in advance. Recommendations for WGS studies in the clinical setting concerning both the elements of information and the process of obtaining the IC as well as how to handle the results obtained are proposed.

Systems genetics in "-omics" era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP-SNP genetic interactions, LD block-block interactions, miRNA-mRNA interactions, DNA-protein interactions, protein-protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate "-omics" datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.

Genetic prediction of common diseases. Still no help for the clinical diabetologist!

Genome-wide association studies (GWAS) have identified several loci associated with many common, multifactorial diseases which have been recently used to market genetic testing directly to the consumers. We here addressed the clinical utility of such GWAS-derived genetic information in predicting type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) in diabetic patients. In addition, the development of new statistical approaches, novel technologies of genome sequencing and ethical, legal and social aspects related to genetic testing have been also addressed. Available data clearly show that, similarly to what reported for most common diseases, genetic testing offered today by commercial companies cannot be used as predicting tools for T2DM and CAD. Further studies taking into account the complex interaction between genes as well as between genetic and non-genetic factors, including age, obesity and glycemic control which seem to modify genetic effects on the risk of T2DM and CAD, might mitigate such negative conclusions. Also, addressing the role of relatively rare variants by next generation sequencing may help identify novel and strong genetic markers with an important role in genetic prediction. Finally, statistical tools concentrated on reclassifying patients might be a useful application of genetic information for predicting many common diseases. By now, prediction of such diseases, including those of interest for the clinical diabetologist, have to be pursued by using traditional clinical markers which perform well and are not costly.

Comparison of family history and SNPs for predicting risk of complex disease

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)–based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%–30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history–based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP–based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis.

In clinical practice, obtaining a detailed family history is often considered the standard-of-care for characterizing the inherited component of an individual's disease risk. Recently, genetic risk assessments based on the cumulative effect of known single nucleotide polymorphism (SNP) disease associations have been proposed as another potentially useful source of information. To date, however, little is known regarding the predictive power of each approach. In this study, we develop models based on quantitative genetic theory to analyze and compare family history and SNP–based models. Our models explain the impact of disease frequency and heritability on performance for each method, and reveal a wide range of scenarios (16 out of the 23 diseases considered) where SNP associations may already be better predictors of risk than family history. Our results confirm the difficulty of obtaining accurate prediction when SNP or family history–based methods are used alone, and they show the benefits of combining information from the two approaches. They also suggest that, in some situations, SNP associations may be potentially useful as supporting evidence alongside other types of clinical information. To our knowledge, this study is the first broad comparison of family history– and SNP–based methods across a wide range of health conditions.

Implementation of proteomic biomarkers: making it work

While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare.

Consistency of genome-wide associations across major ancestral groups

It is not well known whether genetic markers identified through genome-wide association studies (GWAS) confer similar or different risks across people of different ancestry. We screened a regularly updated catalog of all published GWAS curated at the NHGRI website for GWAS-identified associations that had reached genome-wide significance (p ≤ 5 × 10(-8)) in at least one major ancestry group (European, Asian, African) and for which replication data were available for comparison in at least two different major ancestry groups. These groups were compared for the correlation between and differences in risk allele frequencies and genetic effects' estimates. Data on 108 eligible GWAS-identified associations with a total of 900 datasets (European, n = 624; Asian, n = 217; African, n = 60) were analyzed. Risk-allele frequencies were modestly correlated between ancestry groups, with >10% absolute differences in 75-89% of the three pairwise comparisons of ancestry groups. Genetic effect (odds ratio) point estimates between ancestry groups correlated modestly (pairwise comparisons' correlation coefficients: 0.20-0.33) and point estimates of risks were opposite in direction or differed more than twofold in 57%, 79%, and 89% of the European versus Asian, European versus African, and Asian versus African comparisons, respectively. The modest correlations, differing risk estimates, and considerable between-association heterogeneity suggest that differential ancestral effects can be anticipated and genomic risk markers may need separate further evaluation in different ancestry groups.

"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.

How comparative effectiveness research can help advance 'personalized medicine' in cancer treatment

The use of biomarkers to "personalize" cancer treatment--identifying discrete genes, proteins, or other indicators that can differentiate one type of cancer from another and enable the use of highly tailored therapies--offers tremendous potential for improved outcomes and lower treatment costs. However, the rapid development of cancer biomarker, or genomic, tests--combined with a paucity of evidence to support the effectiveness of the tests--presents a challenge for patients, clinicians, and other stakeholders. In this article we propose that comparative effectiveness research be used to strengthen what is now a haphazard process for developing and marketing cancer biomarker tests. We suggest novel funding approaches and a systematic process for moving from regulatory approval to the generation of evidence that meets the needs of stakeholders and, ultimately, patients.

You never call, you never write: why return of 'omic' results to research participants is both a good idea and a moral imperative

The rapid emergence of whole-genome and whole-exome sequencing of research participants has helped to revive the debate about whether genetic and other 'omic' data should be returned to research participants, and if so, which data, under what circumstances and by whom. While partial disclosure of such data has been justified in cases where participants' lives and health are threatened, full disclosure appears to remain beyond the pale for most researchers and bioethicists. I argue that it should not be and that the objections to full disclosure short-sightedly favor near-term considerations over long-term benefits. Return of genomic data to those who want it, even if a difficult undertaking and even if the meaning of the data is unclear, engages participants in science and the research enterprise, and positions them to be better stewards of their own health and wellbeing.

A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: "leukocyte activation and differentiation", "pattern-recognition receptor signaling pathway", and "chemokines and their receptors".These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.

Next-generation sequencing applied to molecular diagnostics

Next-generation sequencing technologies have begun to revolutionize the field of cancer genetics through rapid and accurate assessment of a patient's DNA makeup with minimal cost. These technologies have already led to the realization of the inter- and intra-tumor genetic heterogeneity and the identification of novel mutations and chimeric genes, however, several challenges lie ahead. Given the low number of recurrent somatic genetic aberrations in common types of cancer, the identification of 'driver' genetic aberrations has proven challenging. Furthermore, implementation of next-generation sequencing and/or some of its derivatives into routine practice as diagnostic tests will require in-depth understanding of the pitfalls of these technologies and a great degree of bioinformatic expertise. This article focuses on the contribution of next-generation sequencing technologies to diagnosis and cancer prognostication and prediction.

Direct-to-consumer personalized genomic testing

Over the past 18 months, there have been notable developments in the direct-to-consumer (DTC) genomic testing arena, in particular with regard to issues surrounding governmental regulation in the USA. While commentaries continue to proliferate on this topic, actual empirical research remains relatively scant. In terms of DTC genomic testing for disease susceptibility, most of the research has centered on uptake, perceptions and attitudes toward testing among health care professionals and consumers. Only a few available studies have examined actual behavioral response among consumers, and we are not aware of any studies that have examined response to DTC genetic testing for ancestry or for drug response. We propose that further research in this area is desperately needed, despite challenges in designing appropriate studies given the rapid pace at which the field is evolving. Ultimately, DTC genomic testing for common markers and conditions is only a precursor to the eventual cost-effectiveness and wide availability of whole genome sequencing of individuals, although it remains unclear whether DTC genomic information will still be attainable. Either way, however, current knowledge needs to be extended and enhanced with respect to the delivery, impact and use of increasingly accurate and comprehensive individualized genomic data.

Motivations and perceptions of early adopters of personalized genomics: perspectives from research participants

BACKGROUND/AIMS

To predict the potential public health impact of personal genomics, empirical research on public perceptions of these services is needed. In this study, 'early adopters' of personal genomics were surveyed to assess their motivations, perceptions and intentions.

METHODS

Participants were recruited from everyone who registered to attend an enrollment event for the Coriell Personalized Medicine Collaborative, a United States-based (Camden, N.J.) research study of the utility of personalized medicine, between March 31, 2009 and April 1, 2010 (n = 369). Participants completed an Internet-based survey about their motivations, awareness of personalized medicine, perceptions of study risks and benefits, and intentions to share results with health care providers.

RESULTS

Respondents were motivated to participate for their own curiosity and to find out their disease risk to improve their health. Fewer than 10% expressed deterministic perspectives about genetic risk, but 32% had misperceptions about the research study or personal genomic testing. Most respondents perceived the study to have health-related benefits. Nearly all (92%) intended to share their results with physicians, primarily to request specific medical recommendations.

CONCLUSION

Early adopters of personal genomics are prospectively enthusiastic about using genomic profiling information to improve their health, in close consultation with their physicians. This suggests that early users (i.e. through direct-to-consumer companies or research) may follow up with the health care system. Further research should address whether intentions to seek care match actual behaviors.

Users' motivations to purchase direct-to-consumer genome-wide testing: an exploratory study of personal stories

The relatively rapid growth of the direct-to-consumer (DTC) genetic testing market in the last few years has led to increasing attention from both the scientific community and policy makers. One voice often missing in these debates, however, is that of the actual user of these genetic testing services. In order to gain a better picture of the motivations and expectations that propel individuals to purchase DTC genome-wide testing, we conducted an exploratory study based on users' personal stories. Through qualitative content analysis of users' personal stories found on Internet blogs and DTC genetic testing companies' websites, we identified five major sets of motivations and expectations towards DTC genome-wide testing. These themes are related to (1) health, (2) curiosity and fascination, (3) genealogy, (4) contributing to research, and (5) recreation. Obtaining such information can help us to understand how users consider genome-wide testing and forms the basis for further research.

Personal genetics: regulatory framework in Europe from a service provider's perspective

The purpose of this article is to give an overview and discuss the relevant regulations in place, or under consideration, regarding healthcare-related personal genetics services in Europe - this is a rapidly evolving field and in most European Union (EU) countries the regulatory framework is not yet clear. The review will be framed from the perspective of potential service providers (companies, health services and practitioners, including medical, nutritional, complementary, etc), the growing number of which will need to be aware of potential regulatory hurdles existing now and that may arise in the future. The main conclusion from the survey is that strict regulations regarding practitioner-delivered personal genetic-testing services are unlikely to be enforced over the next 5 years in most EU countries, with the exception of Germany. There is broad-based, but by no means universal, support for a strong voluntary code of practice as an alternative to government regulations to protect consumers and to enable all stakeholders to recognise serious and reputable service providers. On the other hand, there are influential bodies calling for strict regulation. As genotyping costs rapidly fall, it is likely that it will become routine and a major challenge that does not seem to be addressed by current debate on regulations is the emergence of companies offering/selling personal genetic services based on a customer's pre-existing genetic results and therefore no actual laboratory testing involved.

Current priorities for public health practice in addressing the role of human genomics in improving population health

In spite of accelerating human genome discoveries in a wide variety of diseases of public health significance, the promise of personalized health care and disease prevention based on genomics has lagged behind. In a time of limited resources, public health agencies must continue to focus on implementing programs that can improve health and prevent disease now. Nevertheless, public health has an important and assertive leadership role in addressing the promise and pitfalls of human genomics for population health. Such efforts are needed not only to implement what is known in genomics to improve health but also to reduce potential harm and create the infrastructure needed to derive health benefits in the future.

Personalized medicine and comparative effectiveness research in an era of fixed budgets

For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability. Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine. The purpose of this paper is to explore the potential and the limitations of CER. While the analytic methods and data used for CER overcome many of the disadvantages of randomized controlled trials, there are significant barriers, including lack of routinely collected genetic information, patient-reported outcomes and information on new and emerging technologies. Recommendations for using CER include augmenting current data with genetic information, promoting the collection of uniform health outcomes, using value of information analysis to guide development of new technologies, and greater use of decision analysis. Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

Genome-wide association studies and genetic risk assessment of liver diseases

Genetic tests can help clinicians to diagnose rare monogenic liver diseases. For most common liver diseases, however, multiple gene variants that have small to moderate individual phenotypic effects contribute to the overall risk of disease. An individual's level of risk depends on interactions between environmental factors and a wide range of modifier genes, which are yet to be identified systematically. The latest genome-wide association studies in large cohorts of patients with gallstones, fatty liver disease, viral hepatitis, chronic cholestatic liver diseases or drug-induced liver injury have provided new insights into the pathophysiology of these illnesses and have suggested the contribution of previously unsuspected pathogenic pathways. Studies in mouse models have identified further susceptibility genes for several complex liver diseases. As a result, in the future polygenic risk scores might help to define subgroups of patients at risk of developing liver diseases who would benefit from preventative measures and/or personalized therapy. Now that whole-genome sequencing is possible, comprehensive strategies for integrating genomic data and counseling of patients need to be developed.

Being more realistic about the public health impact of genomic medicine

Wayne Hall and colleagues discuss the limitations of genomic risk prediction for population-level preventive health care.

Biomarkers and their consequences for the biomedical profession: a social science perspective

Although biomarkers are not altogether new, they are gaining a new life in our postgenomic present. This article takes this as a good reason to explore biomarkers in depth and to speculate about the consequences that biomarkers might engender in clinical practices. First, the article ventures into an endeavor of ordering the dynamic field of biomarkers, suggesting a possible classification of biomarkers, and then argues that we are currently witnessing a 'biomarkerization' of health and disease - defined as an ongoing future-oriented process that seeks to solve biomedical as well as public health problems through investments into biomarker research at the present time. Subsequently, this article reflects on some possible consequences of this phenomenon. It argues that while the movement of candidate biomarkers into the clinic is arduous, biomarkers might develop a life of their own once they arrive in the clinic. This article outlines the direction of two such possible consequences. It suggests that biomarkers might be involved in a change of the actors that order and categorize diseases, as well as trigger transformations in our understanding of what counts as disease in the first place. Hence, this article seeks to shed light on the paradox that while biomarkers are designed to add more evidence into clinical practice, they might actually increase uncertainty and ambiguity.

A compendium of genome-wide associations for cancer: critical synopsis and reappraisal

Since 2007, genome-wide association (GWA) studies have identified numerous well-supported, novel genetic risk loci for common cancers; however, there are concerns that this technology is reaching its limits. We provide an overview of GWA-identified genetic associations with solid tumors. We simulated the distribution of population risk alleles for colorectal, prostate, testicular, and thyroid cancers based on genetic variants identified in GWA studies. We also evaluated whether statistical power to detect typical genetic effects could be improved with studies performing GWA analyses of all available samples rather than multistage designs. Fifty-six eligible articles yielded 92 eligible associations between cancer phenotypes and genetic variants with a median per-allele odds ratio (OR) of 1.22 (interquartile range = 1.15-1.36). Half of the associations pertained to prostate, colorectal, or breast cancer. Individuals at the upper quartile of simulated risk had only 2.1- to 4.2-fold higher relative risk than those in the lower quartile. Comprehensive evaluation of currently available samples with GWA platforms would yield few additional variants with per-allele OR = 1.4, but many more variants with OR = 1.2 could be detected; statistical power to detect weak associations (OR = 1.07) would still be negligible. The GWA approach is effective in identifying common genetic variants with moderate effect; however, identifying loci with very small effects and rare variants will require major new efforts. At present, the utility of GWA-identified risk loci in risk stratification for cancer is limited.