Do we know enough? A scientific and ethical analysis of the basis for genetic-based personalized nutrition

This article discusses the prospects and limitations of the scientific basis for offering personalized nutrition advice based upon individual genetic information. Two divergent scientific positions are presented, with an ethical comment. The crucial question is whether the current knowledge base is sufficiently strong for taking an ethically responsible decision to offer personalized nutrition advice based upon gene–diet–health interaction. According to the first position, the evidence base for translating the outcomes of nutrigenomics research into personalized nutritional advice is as yet immature. There is also limited evidence that genotype-based dietary advice will motivate appropriate behavior changes. Filling the gaps in our knowledge will require larger and better randomized controlled trials. According to the second position, personalized nutrition must be evaluated in relation to generally accepted standard dietary advice—partly derived from epidemiological observations and usually not proven by clinical trials. With personalized nutrition, we cannot demand stronger evidence. In several specific cases of gene–diet interaction, it may be more beneficial for individuals with specific genotypes to follow personalized advice rather than general dietary recommendations. The ethical comment, finally, considers the ethical aspects of deciding how to proceed in the face of such uncertainty. Two approaches for an ethically responsible way forward are proposed. Arguing from a precautionary approach, it is suggested that personalized dietary advice should be offered only when there is strong scientific evidence for health effects, followed by stepwise evaluation of unforeseen behavioral and psychological effects. Arguing from theoretical and applied ethics as well as psychology, it is also suggested that personalized advice should avoid paternalism and instead focus on supporting the autonomous choice of each person.     

Values at stake: autonomy, responsibility, and trustworthiness in relation to genetic testing and personalized nutrition advice

Personalized nutrition has the potential to enhance individual health control. It could be seen as a means to strengthen people’s autonomy as they learn more about their personal health risks, and receive dietary advice accordingly. We examine in what sense personalized nutrition strengthens or weakens individual autonomy. The impact of personalized nutrition on autonomy is analyzed in relation to responsibility and trustworthiness. On a societal level, individualization of health promotion may be accompanied by the attribution of extended individual responsibility for one’s health. This constitutes a dilemma of individualization, caused by a conflict between the right to individual freedom and societal interests. The extent to which personalized nutrition strengthens autonomy is consequently influenced by how responsibility for health is allocated to individuals. Ethically adequate allocation of responsibility should focus on prospective responsibility and be differentiated with regard to individual differences concerning the capacity of adults to take responsibility. The impact of personalized nutrition on autonomy also depends on its methodological design. Owing to the complexity of information received, personalized nutrition through genetic testing (PNTGT) is open to misinterpretation and may not facilitate informed choices and autonomy. As new technologies, personalized nutrition and PNTGT are subject to issues of trust. To strengthen autonomy, trust should be approached in terms of trustworthiness. Trustworthiness implies that an organization that develops or introduces personalized nutrition can show that it is competent to deal with both the technical and moral dimensions at stake and that its decisions are motivated by the interests and expectations of the truster.     

Ethical, legal and social issues in nutrigenomics: the challenges of regulating service delivery and building health professional capacity

Nutrigenomics, the conjunction of molecular nutrition with human genomics, is among the first publicly available applications of the human genome project. Nutrigenomics raises ethical, legal and social issues particularly with respect to how the public may access nutrigenetic tests and associated nutritional and lifestyle advice. Current regulatory controversy focuses on potential harms associated with direct-to-consumer (DTC) marketing of nutrigenetic tests and especially the need to protect consumers from unreliable tests, false claims and unproven dietary supplements. Nutrigenomics does, however, offer the potential of important health benefits for some individuals. The regulation of nutrigenomic services is slowly evolving, but there is little indication of increased professional capacity to support service delivery. Primary care physicians have minimal training in nutrition and genetics, and medical geneticists are in high demand and short supply. Dietetic practitioners are experts in nutrition science and interest in nutrigenomics is growing among members of this professional group. However, as with physicians, dietetics practitioners would require considerable training to bring nutrigenomics into their practice capacity. A downside of regulatory restrictions on direct consumer access to nutrigenomics companies is that responsible businesses may be hindered in meeting emergent public demand while health care professional groups have not yet developed capacity to provide nutrigenomics services.     

稳定同位素质量平衡混合模型的性能评估

稳定同位素技术可以用于消费者营养溯源,以确定多种营养来源对消费者营养的贡献比重。因此,稳定同位素质量平衡混合模型已经是消费者营养溯源分析的必要方法之一。通常使用贝叶斯混合模型来估计不同营养来源的贡献;此类模型提供了每个营养来源对消费者的贡献比例的概率分布特征。然而,混合模型拟合结果的好坏,及其与实际生态学理论的匹配水平,是模型性能的重要评价内容。例如,模型在不能很好地解析营养来源贡献时,仍将返回默认先验结果,给模型解释带来困难。为直接避免同位素构建消费者营养溯源分析中的诸多技术问题,文章将综述在拟合和评估贝叶斯混合模型时遵循的最佳实践。因此,文章基于实测的同位素数据集(蒙古鲌Culter mongolicus mongolicus同位素数据集),通过识别消费者营养功能类群特征、改变营养来源先验信息特征,构建系列贝叶斯模型;通过比较模型总体性能、实测值与预测值差异,及先验信息和后验信息差异等多种模型性能评价方法,来描述模型性能评价的方法和过程。通过这些方法的综合运用,将进一步提高消费者营养溯源准确性,为更深刻地认识食物网规律提供科学支撑。     

Editorial

This special section of Genes and Nutrition presents a baseline analysis of ethical and legal issues undertaken within the EU FP7 research project Food4Me, which investigates the feasibility today of the vision for delivering personalized nutrition. Four major topics are addressed: Do we know enough for offering personalized nutritional advice? How can personal, cultural, and scientific perspectives on food and health be integrated? How does personalized nutrition affect individual autonomy? Which urgent ethical and legal matters stand out when personalized nutrition is commercialized?     

Nutrigenomics-based personalised nutritional advice: in search of a business model?

Nutritional advice has mainly focused on population-level recommendations. Recent developments in nutrition, communication, and marketing sciences have enabled potential deviations from this dominant business model in the direction of personalisation of nutrition advice. Such personalisation efforts can take on many forms, but these have in common that they can only be effective if they are supported by a viable business model. The present paper takes an inventory of approaches to personalised nutrition currently available in the market place as its starting point to arrive at an identification of their underlying business models. This analysis is presented as a unifying framework against which the potential of nutrigenomics-based personalised advice can be assessed. It has uncovered nine archetypical approaches to personalised nutrition advice in terms of their dominant underlying business models. Differentiating features among such business models are the type of information that is used as a basis for personalisation, the definition of the target group, the communication channels that are being adopted, and the partnerships that are built as a part of the business model. Future research should explore the consumer responses to the diversity of “archetypical” business models for personalised nutrition advice as a source of market information on which the delivery of nutrigenomics-based personalised nutrition advice may further build.     

Foodomics for human health: current status and perspectives

Introduction: In the post-genomic era, the opportunity to combine and integrate cutting-edge analytical platforms and data processing systems allowed the birth of foodomics, ‘a discipline that studies the Food and Nutrition domains through the application of advanced omics technologies to improve consumer’s well-being, health, and confidence’. Since then, this discipline has rapidly evolved and researchers are now facing the daunting tasks to meet consumers’ needs in terms of food traceability, sustainability, quality, safety and integrity. Most importantly, today it is imperative to provide solid evidence of the mechanisms through which food can promote human health and well-being.

Areas covered: In this review, the complex relationships connecting food, nutrition and human health will be discussed, with emphasis on the relapses for the development of functional foods and nutraceuticals, personalized nutrition approaches, and the study of the interplay among gut microbiota, diet and health/diseases.

Expert commentary: Evidence has been provided supporting the role of various omic platforms in studying the health-promoting effects of food and customized dietary interventions. However, although associated to major analytical challenges, only the proper integration of multi-omics studies and the implementation of bioinformatics tools and databases will help translate findings from clinical practice into effective personalized treatment strategies.     

Integrate personalized medicine into clinical practice to improve patient safety

Medical practice is based on the experience of practitioners and on learned medical knowledge. This knowledge is based on studies of patient's population. Modern medicine is facing a variety of clinical forms and also variable patients’ responses to treatment. Pharmacogenomics has brought insights to this variability and has led to the development of personalized medicine. The adoption of personalized medicine is slowed down by a number of technical and methodology barriers. The concept of personalized medicine should not be only limited to genetics but must reuse all patient information to get the most suitable patient profile. In this paper we present a methodology for the integration of personalized medicine into clinical practice.     

How Can the Operating Environment for Nutrition Research Be Improved in Sub-Saharan Africa? The Views of African Researchers

Optimal nutrition is critical for human development and economic growth. Sub-Saharan Africa is facing high levels of food insecurity and only few sub-Saharan African countries are on track to eradicate extreme poverty and hunger by 2015. Effective research capacity is crucial for addressing emerging challenges and designing appropriate mitigation strategies in sub-Saharan Africa. A clear understanding of the operating environment for nutrition research in sub-Saharan Africa is a much needed prerequisite. We collected data on the barriers and requirements for conducting nutrition research in sub-Saharan Africa through semi-structured interviews with 144 participants involved in nutrition research in 35 countries in sub-Saharan Africa. A total of 133 interviews were retained for coding. The main barriers identified for effective nutrition research were the lack of funding due to poor recognition by policymakers of the importance of nutrition research and under-utilisation of research findings for developing policy, as well as an absence of research priority setting from within Africa. Current research topics were perceived to be mainly determined by funding bodies from outside Africa. Nutrition researchers argued for more commitment from policymakers at national level. The low capacity for nutrition research was mainly seen as a consequence of insufficient numbers of nutrition researchers, limited skills and a poor research infrastructure. In conclusion, African nutrition researchers argued how research priorities need to be identified by African stakeholders, accompanied by consensus building to enable creating a problem-driven national research agenda. In addition, it was considered necessary to promote interactions among researchers, and between researchers and policymakers. Multidisciplinary research and international and cross-African collaboration were seen as crucial to build capacity in sub-Saharan nutrition research.     

Does point-of-sale nutrition information improve the nutritional quality of food choices?

Point-of-sale nutrition information has been adopted by numerous grocery stores to respond to the demand for easy-to-understand nutrition labeling by consumers. Although there is conflicting evidence regarding the effectiveness of providing nutrition information, previous research indicates simplified shelf nutrition labels may lead to healthier choices. However, these studies have not examined how different consumer segments respond to these labels, nor the differential impacts across foods. Using household purchase data from a store that voluntarily adopted the (now defunct) NuVal shelf nutrition labels (a 1-100 numeric score derived from a nutrition-profiling algorithm), we assess NuVal impacts across different consumers and foods. NuVal scores potentially influence not only purchase quantity but also likelihood of buying. Thus, the effect of NuVal was measured by estimating a two-part model and predicting consumers’ unconditional purchase responses. We found evidence of heterogeneous impacts of NuVal across consumers and foods. High-income households and households with children shifted their yogurt and frozen dinner purchases to more healthful items. In contrast, households with children and households headed by heads with college education slightly shifted their canned soup purchases to less healthful options. Our findings suggest that specific foods and consumer segments are influenced by simplified shelf nutrition information and further research is necessary to better understand its effect on consumer dietary quality.     

Early initiation of breastfeeding: a systematic literature review of factors and barriers in South Asia

Background

Early or timely initiation of breastfeeding is crucial in preventing newborn deaths and influences childhood nutrition however remains low in South Asia and the factors and barriers warrant greater consideration for improved action. This review synthesises the evidence on factors and barriers to initiation of breastfeeding within 1 h of birth in South Asia encompassing Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka.

Methods

Studies published between 1990 and 2013 were systematically reviewed through identification in Academic Search Complete, CINAHL, Global Health, MEDLINE and Scopus databases. Twenty-five studies meeting inclusion criteria were included for review. Structured thematic analysis based on leading frameworks was undertaken to understand factors and barriers.

Results

Factors at geographical, socioeconomic, individual, and health-specific levels, such as residence, education, occupation, income, mother’s age and newborn’s gender, and ill health of mother and newborn at delivery, affect early or timely breastfeeding initiation in South Asia. Reported barriers impact through influence on acceptability by traditional feeding practices, priests’ advice, prelacteal feeding and discarding colostrum, mother-in-law’s opinion; availability and accessibility through lack of information, low access to media and health services, and misperception, support and milk insufficiency, involvement of mothers in decision making.

Conclusions

Whilst some barriers manifest similarly across the region some factors are context-specific thus tailored interventions are imperative. Initiatives halting factors and directed towards contextual barriers are required for greater impact on newborn survival and improved nutrition in the South Asia region.

     

Controlling futures? Online Genetic Testing and Neurodegenerative Disease

Online personalized genetic testing services offer accessible and convenient options for satisfying personal curiosity about health and obtaining answers about one’s genetic provenance. They are especially attractive to healthy people who wish to learn about their future risk of disease, as Paul Mason’s (2017) case study of “Jordan” illustrates. In this response, we consider how online genetic testing services are used by people diagnosed with a common neurodegenerative disease, Parkinson’s disease, to gain a sense of certainty regarding the future.     

The Mining Minds digital health and wellness framework

Background

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people’s conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems.

Methods

This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people’s lifestyles and provide a variety of smart coaching and support services.

Results

This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework.

Conclusions

Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

     

EFFECT OF QUESTION ORDER ON SENSORY PERCEPTION AND PREFERENCE IN CENTRAL LOCATION TRIALS

In the running of consumer studies aimed at obtaining information about products and services, it has become increasingly popular to include some sensory type questions about the characteristics of the test product as well as the standard question about overall preference. The implications of this for the resultant data are complex, and as Sudman and Schwarz (1989) point out question order effects have been implicated as one of the major causes of unreplicated or unexpected findings in survey research. This study aims to establish the effect of question order on overall preference scores and sensory scores in consumer studies. Results indicate that there is a significant effect of asking sensory questions on overall preference ratings and the position of the preference questions (relative to the sensory questions) also has implications for overall ratings of preference.     

Incorporating service and user information and latent features to predict QoS for selecting and recommending cloud service compositions

The rapid growth of published cloud services in the Internet makes the service selection and recommendation a challenging task for both users and service providers. In cloud environments, software re services collaborate with other complementary services to provide complete solutions to end users. The service selection is performed based on QoS requirements submitted by end users. Software providers alone cannot guarantee users’ QoS requirements. These requirements must be end-to-end, representing all collaborating services in a cloud solution. In this paper, we propose a prediction model to compute end-to-end QoS values for vertically composed services which are composed of three types of cloud services: software (SaaS), infrastructure (IaaS) and data (DaaS) services. These values can be used during the service selection and recommendation process. Our model exploits historical QoS values and cloud service and user information to predict unknown end-to-end QoS values of composite services. The experiments demonstrate that our proposed model outperforms other prediction models in terms of the prediction accuracy. We also study the impact of different parameters on the prediction results. In the experiments, we used real cloud services’ QoS data collected using our developed QoS monitoring and collecting system.     

Automation of in-silico data analysis processes through workflow management systems

Data integration is needed in order to cope with the huge amounts of biological information now available and to perform data mining effectively. Current data integration systems have strict limitations, mainly due to the number of resources, their size and frequency of updates, their heterogeneity and distribution on the Internet. Integration must therefore be achieved by accessing network services through flexible and extensible data integration and analysis network tools. EXtensible Markup Language (XML), Web Services and Workflow Management Systems (WMS) can support the creation and deployment of such systems. Many XML languages and Web Services for bioinformatics have already been designed and implemented and some WMS have been proposed. In this article, we review a methodology for data integration in biomedical research that is based on these technologies. We also briefly describe some of the available WMS and discuss the current limitations of this methodology and the ways in which they can be overcome.     

Does searching online for vaccination information affect vaccination coverage? Evidence from Sub-Saharan African countries

The Internet is reshaping the way people access health information. Over the past decades, an increasing number of people have been using the Internet to access vaccine-related information. Many studies suggest that the Internet can help improve people’s understanding of health issues but at the same time facilitate the rapid spread of misinformation. This study explores the impact that searching the Internet for immunization information has on vaccination coverage. Using Google trends data, we found that access to online vaccination information has impacted vaccine uptake from 2004 to 2017, in Sub-Saharan African countries. The results indicate an overall positive impact on vaccine uptake. We also found that the effects are heterogeneous among vaccines. The effect is statistically significant for the vaccine related to high-risk disease, but not significant for the controversial vaccine and the vaccine related to low-risk disease.     

The clinical characterization of the adult patient with depression aimed at personalization of management

Depression is widely acknowledged to be a heterogeneous entity, and the need to further characterize the individual patient who has received this diagnosis in order to personalize the management plan has been repeatedly emphasized. However, the research evidence that should guide this personalization is at present fragmentary, and the selection of treatment is usually based on the clinician's and/or the patient's preference and on safety issues, in a trial‐and‐error fashion, paying little attention to the particular features of the specific case. This may be one of the reasons why the majority of patients with a diagnosis of depression do not achieve remission with the first treatment they receive. The predominant pessimism about the actual feasibility of the personalization of treatment of depression in routine clinical practice has recently been tempered by some secondary analyses of databases from clinical trials, using approaches such as individual patient data meta‐analysis and machine learning, which indicate that some variables may indeed contribute to the identification of patients who are likely to respond differently to various antidepressant drugs or to antidepressant medication vs. specific psychotherapies. The need to develop decision support tools guiding the personalization of treatment of depression has been recently reaffirmed, and the point made that these tools should be developed through large observational studies using a comprehensive battery of self‐report and clinical measures. The present paper aims to describe systematically the salient domains that should be considered in this effort to personalize depression treatment. For each domain, the available research evidence is summarized, and the relevant assessment instruments are reviewed, with special attention to their suitability for use in routine clinical practice, also in view of their possible inclusion in the above‐mentioned comprehensive battery of measures. The main unmet needs that research should address in this area are emphasized. Where the available evidence allows providing the clinician with specific advice that can already be used today to make the management of depression more personalized, this advice is highlighted. Indeed, some sections of the paper, such as those on neurocognition and on physical comorbidities, indicate that the modern management of depression is becoming increasingly complex, with several components other than simply the choice of an antidepressant and/or a psychotherapy, some of which can already be reliably personalized.     

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.     

深圳城市生态大数据智慧管理和服务平台技术集成与应用研究

生态环境是人类赖以生存和发展的基础,城市生态大数据智慧管理和服务平台建设是生态城市和美丽城市建设的需要。以深圳市为例,借助物联网、移动互联网、计算机、数据库和网络地理信息系统技术,以及时空地理大数据整合和共享、大数据挖掘分析和云端一体化业务协同等关键技术,结合城市生态系统评估分析决策模型/方法/对策库,在实现深圳市“空-地-网-统计-众源”等多源异构生态大数据有效集成的基础上,搭建了 “数据采集-信息提取-知识发现-决策生成-快速服务”全流程、一体化的深圳市生态大数据智慧管理和服务平台,构建了面向业务部门和科研人员等专业用户的生态野外数据调查采集系统和城市生态监测与评估管理决策分析系统,以及面向社会大众的深圳生态大调查APP。平台首次揭示了深圳市1979年以来不同生态系统的格局、构成、过程、服务和健康状况的变化,提升了深圳市生态环境综合决策科学化、生态环境监管精准化、生态环境公共服务便民化水平。平台有效降低了用户数据收集与处理和操作专业模型的难度,突破了原始数据应用的瓶颈和难点,提高了专业模型在业务部门中的使用率。未来,依靠“生态大数据+生态专业模型”的技术方案实现从数据到知识的挖掘,是实现城市生态大数据智慧化和专业化管理的关键,也是全面提高城市生态环境保护信息化服务水平的重要途径。