Ethical issues of predictive genetic testing for diabetes

Challenges and Legal Gaps of Genetic Profiling in the Era of Big Data

Profiling of individuals based on inborn, acquired, and assigned characteristics is central for decision making in health care. In the era of omics and big smart data, it becomes urgent to differentiate between different data governance affordances for different profiling activities. Typically, diagnostic profiling is in the focus of researchers and physicians, and other types are regarded as undesired side-effects; for example, in the connection of health care insurance risk calculations. Profiling in a legal sense is addressed, for example, by the EU data protection law. It is defined in the General Data Protection Regulation as automated decision making. This term does not correspond fully with profiling in biomedical research and healthcare, and the impact on privacy has hardly ever been examined. But profiling is also an issue concerning the fundamental right of non-discrimination, whenever profiles are used in a way that has a discriminatory effect on individuals. Here, we will focus on genetic profiling, define related notions as legal and subject-matter definitions frequently differ, and discuss the ethical and legal challenges.

Personalized medicine and genome-based treatments: Why personalized medicine ≠ individualized treatments

The sequencing of the human genome and decreasing costs of sequencing technology have led to the notion of ‘personalized medicine’. This has been taken by some authors to indicate that personalized medicine will provide individualized treatments solely based on one’s DNA sequence. We argue this is overly optimistic and misconstrues the notion of personalization. Such interpretations fail to account for economic, policy and structural constraints on the delivery of healthcare. Furthermore, notions of individualization based on genomic data potentially take us down the road of genetic reductionism obscuring the role of environmental factors in disease and ill health. We propose that one should see personalized medicine as a way of using personal genomic information to stratify individuals into subpopulations and suggest that personalized medicine be seen within a broader idea of personalized healthcare, reflecting healthcare that integrates personal genomic data into cultural, environmental and personal contexts.

Motivations of Patients with Diabetes to Participate in Research

BACKGROUND

Research on the motivations of research participants has focused primarily on vulnerable populations at risk of exploitation, and there is little research on the motivations and reasons of general medical patients participating in research. Given a significant increase in research studies recruiting participants with diabetes, we sought to better understand the motivations of patients with diabetes considering a general medical research protocol.

METHODS

The analyses presented here compare the reasoning and willingness to participate in a hypothetical research study of medically ill subjects (patients with diabetes, n=51) with non-ill (n=57) subjects. Responses on the MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR) were correlated with demographic variables and scores on the Mini-Mental State Examination (MMSE) and Short-Form-36 (SF-36).

RESULTS

Overall, 44% of the group with diabetes and 56% of the comparison group indicated a willingness to participate in the research study. The reasons diabetic and comparison groups offered for willingness or unwillingness to participate in research did not differ significantly. 75% mentioned reasons related to treatment, 63% altruism; none mentioned money. Of those patients with diabetes who would not participate in research, 94% cited risk, and 89% expressed an aversion to research.

CONCLUSIONS

The present study suggests that when research is not related to their diagnosis, persons with diabetes do not differ significantly from non-ill comparison subjects in their motivations to participate in research. Given the similarity of our subjects' motivations to those of other medically ill populations, it may be that investigators can now focus more closely on the decision-making characteristics of their patients involved in clinical research rather than their diagnoses.

Benefits and burdens of newborn screening: public understanding and decision-making

In this article we review the literature regarding the public understanding of the potential benefits and burdens of expanded newborn bloodspot screening. We draw attention to broadened notions of benefit that go beyond early identification of asymptomatic individuals and interventions to reduce morbidity or mortality, and include benefits gained by families through knowledge that may facilitate life choices, as well as gains generated by avoiding diagnostic delays. We also reflect on burdens such as increasing false-positive results and parental anxiety, together with risks of overdiagnosis when the natural history of a condition is poorly understood. We conclude that expanded notions of benefit and burden bring with them implications for parental consent and confidentiality and the secondary use of bloodspots.

Genomic counseling: next generation counseling

Personalized medicine continues to expand with the development and increasing use of genome-based testing. While these advances present new opportunities for diagnosis and risk assessment, they also present challenges to clinical delivery. Genetic counselors will play an important role in ushering in this new era of testing; however, it will warrant a shift from traditional genetic counseling to "genomic counseling." This shift will be marked by a move from reactive genetic testing for diagnosis of primarily single-gene diseases to proactive genome-based testing for multiple complex diseases for the purpose of disease prevention. It will also require discussion of risk information for a number of diseases, some of which may have low relative risks or weak associations, and thus, may not substantially impact clinical care. Additionally, genomic counselors will expand their roles, particularly in the area of health promotion to reduce disease risk. This additional role will require a style of counseling that is more directive than traditional counseling and require greater knowledge about risk reducing behaviors and disease screening.

Personalized medicine in women's obesity prevention and treatment: implications for research, policy and practice

The prevalence of obesity in America has reached epidemic proportions, and obesity among women is particularly concerning. Severe obesity (body mass index ≥35 kg m(-2) ) is more prevalent in women than men. Further, women have sex-specific risk factors that must be considered when developing preventive and therapeutic interventions. This review presents personalized medicine as a dynamic approach to obesity prevention, management and treatment for women. First, we review obesity as a complex health issue, with contributing sex-specific, demographic, psychosocial, behavioural, environmental, epigenetic and genetic/genomic risk factors. Second, we present personalized medicine as a rapidly advancing field of health care that seeks to quantify these complex risk factors to develop more targeted and effective strategies that can improve disease management and/or better minimize an individual's likelihood of developing obesity. Third, we discuss how personalized medicine can be applied in a clinical setting with current and emerging tools, including health risk assessments, personalized health plans, and strategies for increasing patient engagement. Finally, we discuss the need for additional research, training and policy that can enhance the practice of personalized medicine in women's obesity, including further advancements in the '-omics' sciences, physician training in personalized medicine, and additional development and standardization of innovative targeted therapies and clinical tools.

Impact of genetic notification on smoking cessation: systematic review and pooled-analysis

Objectives

This study aimed to evaluate the impact of genetic notification of smoking-related disease risk on smoking cessation in the general population. Secondary objectives were to assess the impact of genetic notification on intention-to-quit smoking and on emotional outcomes as well as the understanding and the recall of this notification.

Methods

A systematic review of articles from inception to August 2011 without language restriction was realized using PubMed, Embase, Scopus, Web of Science, PsycINFO and Toxnet. Other publications were identified using hand search. The pooled-analysis included only randomized trials. Comparison groups were (i) high and low genetic risk versus control, and (ii) high versus low genetic risk. For the pooled-analysis random effect models were applied and sensitivity analyses were conducted.

Results

Eight papers from seven different studies met the inclusion criteria of the review. High genetic risk notification was associated with short-term increased depression and anxiety. Four randomized studies were included in the pooled-analysis, which revealed a significant impact of genetic notification on smoking cessation in comparison to controls (clinical risk notification or no intervention) in short term follow-up less than 6 months (RR = 1.55, 95% CI 1.09–2.21).

Conclusions

In short term follow-up, genetic notification increased smoking cessation in comparison to control interventions. However, there is no evidence of long term effect (up to 12 month) on smoking cessation. Further research is needed to assess more in depth how genetic notification of smoking-related disease could contribute to smoking cessation.

Nuclear receptor variants in liver disease

This review aims to provide a snapshot of the actual state of knowledge on genetic variants of nuclear receptors (NR) involved in regulating important aspects of liver metabolism. It recapitulates recent evidence for the application of NR in genetic diagnosis of monogenic ("Mendelian") liver disease and their use in clinical diagnosis. Genetic analysis of multifactorial liver diseases such as viral hepatitis or fatty liver disease identifies key players in disease predisposition and progression. Evidence from these analyses points towards a role of NR polymorphisms in common diseases, linking regulatory networks to complex and variable phenotypes. The new insights into NR variants also offer perspectives and cautionary advice for their use as handles towards diagnosis and treatment.

Nuclear receptor variants in liver disease

This review aims to provide a snapshot of the actual state of knowledge on genetic variants of nuclear receptors (NR) involved in regulating important aspects of liver metabolism. It recapitulates recent evidence for the application of NR in genetic diagnosis of monogenic (“Mendelian”) liver disease and their use in clinical diagnosis. Genetic analysis of multifactorial liver diseases such as viral hepatitis or fatty liver disease identifies key players in disease predisposition and progression. Evidence from these analyses points towards a role of NR polymorphisms in common diseases, linking regulatory networks to complex and variable phenotypes. The new insights into NR variants also offer perspectives and cautionary advice for their use as handles towards diagnosis and treatment.

Lay perceptions of predictive testing for diabetes based on DNA test results versus family history assessment: a focus group study

BACKGROUND

This study assessed lay perceptions of issues related to predictive genetic testing for multifactorial diseases. These perceived issues may differ from the "classic" issues, e.g. autonomy, discrimination, and psychological harm that are considered important in predictive testing for monogenic disorders. In this study, type 2 diabetes was used as an example, and perceptions with regard to predictive testing based on DNA test results and family history assessment were compared.

METHODS

Eight focus group interviews were held with 45 individuals aged 35-70 years with (n = 3) and without (n = 1) a family history of diabetes, mixed groups of these two (n = 2), and diabetes patients (n = 2). All interviews were transcribed and analysed using Atlas-ti.

RESULTS

Most participants believed in the ability of a predictive test to identify people at risk for diabetes and to motivate preventive behaviour. Different reasons underlying motivation were considered when comparing DNA test results and a family history risk assessment. A perceived drawback of DNA testing was that diabetes was considered not severe enough for this type of risk assessment. In addition, diabetes family history assessment was not considered useful by some participants, since there are also other risk factors involved, not everyone has a diabetes family history or knows their family history, and it might have a negative influence on family relations. Respect for autonomy of individuals was emphasized more with regard to DNA testing than family history assessment. Other issues such as psychological harm, discrimination, and privacy were only briefly mentioned for both tests.

CONCLUSION

The results suggest that most participants believe a predictive genetic test could be used in the prevention of multifactorial disorders, such as diabetes, but indicate points to consider before both these tests are applied. These considerations differ with regard to the method of assessment (DNA test or obtaining family history) and also differ from monogenic disorders.

Preferences regarding genetic research results: comparing veterans and nonveterans responses

OBJECTIVE

Communicating genetic research results to participants presents ethical challenges. Our objectives were to examine participants' preferences in receiving future genetic research results and to compare preferences reported by veteran and nonveterans participants.

METHODS

Secondary analysis was performed on data collected in 2000-2004 from 1,575 consent forms signed by Mexican-American participants enrolled in 2 genetic family studies (GFS) in San Antonio: The Family Investigation of Nephropathy and Diabetes (FIND) and the Extended FIND (EFIND). The consent forms for these studies contained multiple-choice questions to examine participants' preferences about receiving their (1) clinical lab results and (2) future genetic research results. The FIND and EFIND databases had information on subjects' demographic characteristics and some selected clinical variables. We identified veterans using the Veterans Health Administration's (VHA's) centralized data repository. We compared veterans' and nonveterans' preferences using Student's t test for continuous variables and χ² test for discrete variables. A logistic regression analyzed subjects' preference for receiving their research results, controlling for other socio-demographic and clinical variables.

RESULTS

The sample included 275 (18%) veterans and 1,247 (82%) nonveterans. Our results indicated a strong desire among the majority of participants 1,445 (95%) in getting their clinical lab research results. Likewise, 93% expressed interest in being informed about their future genetic results. There was no significant difference in veterans' and nonveterans' preference to disclosure of the research results (χ² test; p > 0.05). Regression analysis showed no significant relationship (p = 0.449) between the outcome (receiving research results) and veterans' responses after controlling for demographics and educational levels.

CONCLUSION

Participants believed they would prefer receiving their genetic research results. Veterans are similar to nonveterans in their preferences. Offering genetic research results to participants should be based on well defined and structured plans to enhance interpretation of genetic data.

The personalized medicine for diabetes meeting summary report

Personalized medicine for diabetes is a potential method to specifically identify people who are at high risk of developing type 2 diabetes based on a combination of personal history, family history, physical examination, circulating biomarkers, and genome. High-risk individuals can then be referred to lifestyle programs for risk reduction and disease prevention. Using a personalized medicine approach, a patient with already-diagnosed type 2 diabetes can be treated individually based on information specific to that individual. The field of personalized medicine for diabetes is rapidly exploding. Diabetes Technology Society convened the Personalized Medicine for Diabetes (PMFD) Meeting March 19-20, 2009 in San Francisco. The meeting was funded through a contract from the US Air Force. Diabetes experts from the military, government, academic, and industry communities participated. The purpose was to reach a consensus about PMFD in type 2 diabetes to (a) establish screening programs, (b) diagnose cases at an early stage, and (c) monitor and treat the disease with specific measures. The group defined what a PMFD program should encompass, what the benefits and drawbacks of such a PMFD program would be, and how to overcome barriers. The group reached six conclusions related to the power of PMFD to improve care of type 2 diabetes by resulting in (1) better prediction, (2) better prophylactic interventions, (3) better treatments, and (4) decreased cardiovascular disease burden. Additional research is needed to demonstrate the benefits of this approach. The US Air Force is well positioned to conduct research and develop clinical programs in PMFD.