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

Ethical, legal, and social implications (ELSI) and challenges in the design of a randomized controlled trial to test the online return of cancer genetic research results to U.S. Black women

BACKGROUND

A central challenge to precision medicine research efforts is the return of genetic research results in a manner that is effective, ethical, and efficient. Formal tests of alternate modalities are needed, particularly for racially marginalized populations that have historically been underserved in this context.

METHODS

We are conducting a randomized controlled trial (RCT) to test scalable modalities for results return and to examine the clinical utility of returning genetic research results to a research cohort of Black women. The primary aim is to compare the efficacy of two communication modalities for results return: 1) a conventional modality that entails telephone disclosure by a Board-certified genetic counselor, and 2) an online self-guided modality that entails results return directly to participants, with optional genetic counselor follow-up via telephone. The trial is being conducted among participants in the Black Women's Health Study (BWHS), where targeted sequencing of 4000 participants was previously completed.

RESULTS

Several ethical, legal, and social implications (ELSI) and challenges presented, which necessitated substantial revision of the original study protocol. Challenges included chain of custody, re-testing of research results in a CLIA lab, exclusion of VUS results, and digital literacy. Bioethical principles of autonomy, justice, non-maleficence, and beneficence were considered in the design of the study protocol.

CONCLUSION

This study is uniquely situated to provide critical evidence on the effectiveness of alternative models for genetic results return and provide further insight into the factors influencing access and uptake of genetic information among U.S. Black women.

CLINICALTRIALS

gov: NCT04407611.

Individuals with CYP2C8 and CYP2C9 reduced metabolism haplotypes self-adjusted ibuprofen dose in the Coriell Personalized Medicine Collaborative

OBJECTIVES

The objectives of this study were to determine whether differences in CYP2C8 and CYP2C9 haplotype influence the dose of ibuprofen self-administered by individuals, and to examine the potential relationship between CYP2C8 and CYP2C9 reduced metabolism haplotypes and adverse events.

PARTICIPANTS AND METHODS

We investigated relationships between genetic variations in CYP2C8 and CYP2C9 and ibuprofen use, dose, and side effects (reported by questionnaire) in 445 participants from the Coriell Personalized Medicine Collaborative.

RESULTS

Carriers of reduced metabolism haplotypes for CYP2C8 (*2, *3, *4) and CYP2C9 (*2, *3) were significantly (P=0.0171) more likely than those lacking these variants to take less than the recommended dose of ibuprofen, after controlling for sex, age, race, and cohort. In contrast to ibuprofen dose, there were no differences in ibuprofen use frequency or reported side effects based on haplotype. However, there are often no early signs of acute kidney injury, the most serious side effect of elevated ibuprofen exposure.

CONCLUSION

These results suggest a subset of individuals with genetic variation in CYP2C8 and CYP2C9 recognize that they obtain adequate drug efficacy with lower ibuprofen doses, or take lower doses due to prior side effects. However, most (82.6%) individuals with reduced metabolism haplotypes nonetheless took recommended or higher doses, potentially putting them at increased risk for side effects.

rs11670527 Upstream of ZNF264 Associated with Body Mass Index in the Coriell Personalized Medicine Collaborative

INTRODUCTION

the effects of obesity on health are a concern for the military as they affect the fitness to serve of active service members, increase costs to the Military Health System, and reduce quality of life for veterans and beneficiaries. Although obesity can be influenced by behavioral and environmental factors, it has also been shown to be associated with genetic risk factors that are not fully understood.

MATERIALS AND METHODS

we performed a genome-wide association study of 5,251 participants in the Coriell Personalized Medicine Collaborative, which includes 2,111 Air Force participants. We applied a generalized linear model, using principal component analysis to account for population structure, and analyzed single-variant associations with body mass index (BMI) as a continuous variable, using a Bonferroni-corrected P-value threshold to account for multiplicity.

RESULTS

we identified one genome-wide significant locus, rs11670527, upstream of the ZNF264 gene on chromosome 19, associated with BMI.

CONCLUSIONS

the finding of an association between rs11670527 and BMI adds to the growing body of literature characterizing the complex genetics of obesity. These efforts may eventually inform personalized interventions aimed at achieving and maintaining healthy weight.

Proactive Assessment of Obesity Risk during Infancy (ProAsk): a qualitative study of parents' and professionals' perspectives on an mHealth intervention

Background

Prevention of childhood obesity is a public health priority. Interventions that establish healthy growth trajectories early in life promise lifelong benefits to health and wellbeing. Proactive Assessment of Obesity Risk during Infancy (ProAsk) is a novel mHealth intervention designed to enable health professionals to assess an infant’s risk of future overweight and motivate parental behaviour change to prevent childhood overweight and obesity. The aim of this study was to explore parents’ and health professionals’ experiences of the overweight risk communication and behaviour change aspects of this mHealth intervention.

Methods

The study was conducted in four economically deprived localities in the UK. Parents (N = 66) were recruited to the ProAsk feasibility study when their infant was 6–8 weeks old. Twenty two health visitors (HVs) used a hand-held tablet device to deliver ProAsk to parents when their infants were 3 months old. Parents (N = 12) and HVs (N = 15) were interviewed when infants in the study were 6 months old. Interview data were transcribed and analysed thematically using an inductive, interpretative approach.

Results

Four key themes were identified across both parent and health visitor data: Engaging and empowering with digital technology; Unfamiliar technology presents challenges and opportunity; Trust in the risk score; Resistance to targeting. Most participants found the interactivity and visual presentation of information on ProAsk engaging. Health visitors who were unfamiliar with mobile technology drew support from parents who were more confident using tablet devices. There was evidence of resistance to targeting infants at greatest risk of future overweight and obesity, and both parents and health visitors drew on a number of reasons why a higher than average overweight risk score might not apply to a particular infant.

Conclusions

An mHealth intervention actively engaged parents, enabling them to take ownership of the process of seeking strategies to reduce infant risk of overweight. However, cognitive and motivational biases that prevent effective overweight risk communication are barriers to targeting an intervention at those infants most at risk.

Trial registration

NCT02314494. Date registered 11th December 2014.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6616-5) contains supplementary material, which is available to authorized users.

Learning one's genetic risk changes physiology independent of actual genetic risk

Millions of people now access personal genetic risk estimates for diseases such as Alzheimer's, cancer and obesity¹. While this information can be informative^2-4, research on placebo and nocebo effects^5-8 suggests that learning of one's genetic risk may evoke physiological changes consistent with the expected risk profile. Here we tested whether merely learning of one's genetic risk for disease alters one's actual risk by making people more likely to exhibit the expected changes in gene-related physiology, behaviour and subjective experience. Individuals were genotyped for actual genetic risk and then randomly assigned to receive either a 'high-risk' or 'protected' genetic test result for obesity via cardiorespiratory exercise capacity (experiment 1, N = 116) or physiological satiety (experiment 2, N = 107) before engaging in a task in which genetic risk was salient. Merely receiving genetic risk information changed individuals' cardiorespiratory physiology, perceived exertion and running endurance during exercise, and changed satiety physiology and perceived fullness after food consumption in a self-fulfilling manner. Effects of perceived genetic risk on outcomes were sometimes greater than the effects associated with actual genetic risk. If simply conveying genetic risk information can alter actual risk, clinicians and ethicists should wrestle with appropriate thresholds for when revealing genetic risk is warranted.

Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine?

Obesity is a heritable trait that contributes to substantial global morbidity and mortality. Here, we summarize findings from the past decade of genetic and epigenetic research focused on unravelling the underpinnings of adiposity. More than 140 genetic regions now are known to influence adiposity traits. The genetics of general adiposity, as measured by body mass index, and that of abdominal obesity, as measured by waist-to-hip ratio, have distinct biological backgrounds. Gene expression associated with general adiposity is enriched in the nervous system. In contrast, genes associated with abdominal adiposity function in adipose tissue. Recent population-based epigenetic analyses have highlighted additional distinct loci. We discuss how associated genetic variants can lead to understanding causal mechanisms, and to disentangling reverse causation in epigenetic analyses. Discoveries emerging from population genomics are identifying new disease markers and potential novel drug targets to better define and combat obesity and related diseases.