Single-Subject Studies in Translational Nutrition Research

Levels of evidence for human system risk evaluation

NASA uses a continuous risk management process to seek out new knowledge of spaceflight-induced risk to human health and performance. The evidence base that informs the risk assessments in this domain is constantly changing as more information is gleaned from a continuous human presence in space and from ongoing research. However, the limitations of this evidence are difficult to characterize because fewer than 700 humans have ever flown in space, and information comes from a variety of sources that span disciplines, including engineering, medicine, food and nutrition, and many other life sciences. The Human System Risk Board (HSRB) at NASA is responsible for assessing risk to astronauts and communicating this risk to agency decision-makers. A critical part of that communication is conveying the uncertainty regarding the understanding of the changes that spaceflight induces in human processes and the complex interactions between humans and the spacecraft. Although the strength of evidence grades is common in the academic literature, these scores are often not useful for the problems of human spaceflight. The HSRB continues to update the processes used to report the levels of evidence. This paper describes recent updates to the methods used to assign the level of evidence scores to the official risk postures and to the causal diagrams used by the HSRB.

Emerging therapeutic drug monitoring technologies: considerations and opportunities in precision medicine

In recent years, the development of sensor and wearable technologies have led to their increased adoption in clinical and health monitoring settings. One area that is in early, but promising, stages of development is the use of biosensors for therapeutic drug monitoring (TDM). Traditionally, TDM could only be performed in certified laboratories and was used in specific scenarios to optimize drug dosage based on measurement of plasma/blood drug concentrations. Although TDM has been typically pursued in settings involving medications that are challenging to manage, the basic approach is useful for characterizing drug activity. TDM is based on the idea that there is likely a clear relationship between plasma/blood drug concentration (or concentration in other matrices) and clinical efficacy. However, these relationships may vary across individuals and may be affected by genetic factors, comorbidities, lifestyle, and diet. TDM technologies will be valuable for enabling precision medicine strategies to determine the clinical efficacy of drugs in individuals, as well as optimizing personalized dosing, especially since therapeutic windows may vary inter-individually. In this mini-review, we discuss emerging TDM technologies and their applications, and factors that influence TDM including drug interactions, polypharmacy, and supplement use. We also discuss how using TDM within single subject (N-of-1) and aggregated N-of-1 clinical trial designs provides opportunities to better capture drug response and activity at the individual level. Individualized TDM solutions have the potential to help optimize treatment selection and dosing regimens so that the right drug and right dose may be matched to the right person and in the right context.

Human Nutrition Research in the Data Era: Results of 11 Reports on the Effects of a Multiple-Micronutrient-Intervention Study

Large datasets have been used in molecular and genetic research for decades, but only a few studies have included nutrition and lifestyle factors. Our team conducted an n-of-1 intervention with 12 vitamins and five minerals in 9- to 13-year-old Brazilian children and teens with poor healthy-eating indices. A unique feature of the experimental design was the inclusion of a replication arm. Twenty-six types of data were acquired including clinical measures, whole-genome mapping, whole-exome sequencing, and proteomic and a variety of metabolomic measurements over two years. A goal of this study was to use these diverse data sets to discover previously undetected physiological effects associated with a poor diet that include a more complete micronutrient composition. We summarize the key findings of 11 reports from this study that (i) found that LDL and total cholesterol and fasting glucose decreased in the population after the intervention but with inter-individual variation; (ii) associated a polygenic risk score that predicted baseline vitamin B12 levels; (iii) identified metabotypes linking diet intake, genetic makeup, and metabolic physiology; (iv) found multiple biomarkers for nutrient and food groups; and (v) discovered metabolites and proteins that are associated with DNA damage. This summary also highlights the limitations and lessons in analyzing diverse omic data.

Veganism and body weight: An N of 1 self-experiment

The causal effect that veganism has on body weight has not been scientifically examined. An N of 1 self-experiment was conducted in which blinded body weight and additional behavioural and psychological measures were assessed during two phases of vegan vs. non-vegan lifestyle adherence. In study phase 1, body weight change was -0.8 kg over 1 month of veganism (vs. +0.5 kg non-vegan month). In study phase 2, weight change was -1.2 kg over two veganism months (vs. +1.6 kg non-vegan months). Behavioural and psychological measures were similar during vegan vs. non-vegan periods. Veganism appeared to reduce body weight in this N of 1 self-experiment.

Nutrition-Related N-of-1 Studies Warrant Further Research to Provide Evidence for Dietitians to Practice Personalized (Precision) Medical Nutrition Therapy: A Systematic Review

N-of-1 trials provide a higher level of evidence than randomized controlled trials for determining which treatment works best for an individual, and the design readily accommodates testing of personalized nutrition. The aim of this systematic review was to synthesize nutrition-related studies using an N-of-1 design. The inclusion criterion was adult participants; the intervention/exposure was any nutrient, food, beverage, or dietary pattern; the comparators were baseline values, a control condition untreated or placebo, or an alternate treatment, alongside any outcomes such as changes in diet, body weight, biochemical outcomes, symptoms, quality of life, or a disease outcome resulting from differences in nutritional conditions. The information sources used were Medline, Embase, Scopus, Cochrane Central, and PsychInfo. The quality of study reporting was assessed using the Consort Extension for N-of-1 trials (CENT) statement or the STrengthening Reporting of OBservational Studies in Epidemiology (STROBE) guidelines, as appropriate. From 211 articles screened, a total of 7 studies were included and were conducted in 5 countries with a total of 83 participants. The conditions studied included prediabetes, diabetes, irritable bowel syndrome, weight management, and investigation of the effect of diet in healthy people. The quality of reporting was mostly adequate, and dietary assessment quality varied from poor to good. The evidence base is small, but served to illustrate the main characteristics of N-of-1 study designs and considerations for moving research forward in the era of personalized medical nutrition therapy.

Exploring human biology with N-of-1 clinical trials

Studies on humans that exploit contemporary data-intensive, high-throughput 'omic' assay technologies, such as genomics, transcriptomics, proteomics and metabolomics, have unequivocally revealed that humans differ greatly at the molecular level. These differences, which are compounded by each individual's distinct behavioral and environmental exposures, impact individual responses to health interventions such as diet and drugs. Questions about the best way to tailor health interventions to individuals based on their nuanced genomic, physiologic, behavioral, etc. profiles have motivated the current emphasis on 'precision' medicine. This review's purpose is to describe how the design and execution of N-of-1 (or personalized) multivariate clinical trials can advance the field. Such trials focus on individual responses to health interventions from a whole-person perspective, leverage emerging health monitoring technologies, and can be used to address the most relevant questions in the precision medicine era. This includes how to validate biomarkers that may indicate appropriate activity of an intervention as well as how to identify likely beneficial interventions for an individual. We also argue that multivariate N-of-1 and aggregated N-of-1 trials are ideal vehicles for advancing biomedical and translational science in the precision medicine era since the insights gained from them can not only shed light on how to treat or prevent diseases generally, but also provide insight into how to provide real-time care to the very individuals who are seeking attention for their health concerns in the first place.

Assessing brain and biological aging trajectories associated with Alzheimer's disease

The development of effective treatments to prevent and slow Alzheimer's disease (AD) pathogenesis is needed in order to tackle the steady increase in the global prevalence of AD. This challenge is complicated by the need to identify key health shifts that precede the onset of AD and cognitive decline as these represent windows of opportunity for intervening and preventing disease. Such shifts may be captured through the measurement of biomarkers that reflect the health of the individual, in particular those that reflect brain age and biological age. Brain age biomarkers provide a composite view of the health of the brain based on neuroanatomical analyses, while biological age biomarkers, which encompass the epigenetic clock, provide a measurement of the overall health state of an individual based on DNA methylation analysis. Acceleration of brain and biological ages is associated with changes in cognitive function, as well as neuropathological markers of AD. In this mini-review, we discuss brain age and biological age research in the context of cognitive decline and AD. While more research is needed, studies show that brain and biological aging trajectories are variable across individuals and that such trajectories are non-linear at older ages. Longitudinal monitoring of these biomarkers may be valuable for enabling earlier identification of divergent pathological trajectories toward AD and providing insight into points for intervention.

Variation of volatile organic compound levels within ambient room air and its impact upon the standardisation of breath sampling

The interest around analysis of volatile organic compounds (VOCs) within breath has increased in the last two decades. Uncertainty remains around standardisation of sampling and whether VOCs within room air can influence breath VOC profiles. To assess the abundance of VOCs within room air in common breath sampling locations within a hospital setting and whether this influences the composition of breath. A secondary objective is to investigate diurnal variation in room air VOCs. Room air was collected using a sampling pump and thermal desorption (TD) tubes in the morning and afternoon from five locations. Breath samples were collected in the morning only. TD tubes were analysed using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF-MS). A total of 113 VOCs were identified from the collected samples. Multivariate analysis demonstrated clear separation between breath and room air. Room air composition changed throughout the day and different locations were characterized by specific VOCs, which were not influencing breath profiles. Breath did not demonstrate separation based on location, suggesting that sampling can be performed across different locations without affecting results.

Exceptional Speech Recognition Outcomes After Cochlear Implantation: Lessons From Two Case Studies

PURPOSE

Individual differences and variability in outcomes following cochlear implantation (CI) in patients with hearing loss remain significant unresolved clinical problems. Case reports of specific individuals allow for detailed examination of the information processing mechanisms underlying variability in outcomes. Two adults who displayed exceptionally good postoperative CI outcomes shortly after activation were administered a novel battery of auditory, speech recognition, and neurocognitive processing tests.

METHOD

A case study of two adult CI recipients with postlingually acquired hearing loss who displayed excellent postoperative speech recognition scores within 3 months of initial activation. Preoperative City University of New York sentence testing and a postoperative battery of sensitive speech recognition tests were combined with auditory and visual neurocognitive information processing tests to uncover their strengths, weaknesses, and milestones.

RESULTS

Preactivation CUNY auditory-only (A) scores were < 5% correct while the auditory + visual (A + V) scores were > 74%. Acoustically with their CIs, both participants' scores on speech recognition, environmental sound identification and speech in noise tests exceeded average CI users scores by 1-2 standard deviations. On nonacoustic visual measures of language and neurocognitive functioning, both participants achieved above average scores compared with normal hearing adults in vocabulary knowledge, rapid phonological coding of visually presented words and nonwords, verbal working memory, and executive functioning.

CONCLUSIONS

Measures of multisensory (A + V) speech recognition and visual neurocognitive functioning were associated with excellent speech recognition outcomes in two postlingual adult CI recipients. These neurocognitive information processing domains may underlie the exceptional speech recognition performance of these two patients and offer new directions for research explaining variability in postimplant outcomes. Results further suggest that current clinical outcome measures should be expanded beyond the conventional speech recognition measures to include more sensitive robust tests of speech recognition as well as neurocognitive measures of working memory, vocabulary, lexical access, and executive functioning.

Valuing the Diversity of Research Methods to Advance Nutrition Science

The ASN Board of Directors appointed the Nutrition Research Task Force to develop a report on scientific methods used in nutrition science to advance discovery, interpretation, and application of knowledge in the field. The genesis of this report was growing concern about the tone of discourse among nutrition professionals and the implications of acrimony on the productive study and translation of nutrition science. Too often, honest differences of opinion are cast as conflicts instead of areas of needed collaboration. Recognition of the value (and limitations) of contributions from well-executed nutrition science derived from the various approaches used in the discipline, as well as appreciation of how their layering will yield the strongest evidence base, will provide a basis for greater productivity and impact. Greater collaborative efforts within the field of nutrition science will require an understanding that each method or approach has a place and function that should be valued and used together to create the nutrition evidence base. Precision nutrition was identified as an important emerging nutrition topic by the preponderance of task force members, and this theme was adopted for the report because it lent itself to integration of many approaches in nutrition science. Although the primary audience for this report is nutrition researchers and other nutrition professionals, a secondary aim is to develop a document useful for the various audiences that translate nutrition research, including journalists, clinicians, and policymakers. The intent is to promote accurate, transparent, verifiable evidence-based communication about nutrition science. This will facilitate reasoned interpretation and application of emerging findings and, thereby, improve understanding and trust in nutrition science and appropriate characterization, development, and adoption of recommendations.

The Niche of n-of-1 Trials in Precision Medicine for Weight Loss and Obesity Treatment: Back to the Future

PURPOSE OF REVIEW

The n-of-1 clinical trials are considered the epitome of individualized health care. They are employed to address differences in treatment response and adverse events between patients, in a comparative effectiveness manner, extending beyond the delivery of horizontal recommendations for all.

RECENT FINDINGS

The n-of-1 design has been applied to deliver precision exercise interventions, through eHealth and mHealth technologies. Regarding personalized and precision medical nutrition therapy, few trials have implemented dietary manipulations and one series of n-of-1 trials has applied comprehensive genetic data to improve body weight. With regard to anti-obesity medication, pharmacogenetic data could be applied using the n-of-1 trial design, although none have been implemented yet. The n-of-1 clinical trials consist of the only tool for the delivery of evidence-based, personalized obesity treatment (lifestyle and pharmacotherapy), reducing non-responders, while tailoring the best intervention to each patient, through "trial and error". Their application is expected to improve obesity treatment and mitigate the epidemic.

Does Modulation of an Epigenetic Clock Define a Geroprotector?

There is growing interest in the development of interventions (e.g., drugs, diets, dietary supplements, behavioral therapies, etc.) that can enhance health during the aging process, prevent or delay multiple age-related diseases, and ultimately extend lifespan. However, proving that such 'geroprotectors' do what they are hypothesized to do in relevant clinical trials is not trivial. We briefly discuss some of the more salient issues surrounding the design and interpretation of clinical trials of geroprotectors, including, importantly, how one defines a geroprotector. We also discuss whether emerging surrogate endpoints, such as epigenetic clocks, should be treated as primary or secondary endpoints in such trials. Simply put, geroprotectors should provide overt health and disease prevention benefits but the time-dependent relationships between epigenetic clocks and health-related phenomena are complex and in need of further scrutiny. Therefore, studies that enable understanding of the relationships between epigenetic clocks and disease processes while simultaneously testing the efficacy of a candidate geroprotector are crucial to move the field forward.

Genetically-Guided Medical Nutrition Therapy in Type 2 Diabetes Mellitus and Pre-diabetes: A Series of n-of-1 Superiority Trials

Type 2 diabetes mellitus (T2DM) is a heterogeneous metabolic disorder of multifactorial etiology that includes genetic and dietary influences. By addressing the latter, medical nutrition therapy (MNT) contributes to the management of T2DM or pre-diabetes toward achieving glycaemic control and improved insulin sensitivity. However, the clinical outcomes of MNT vary and may further benefit from personalized nutritional plans that take into consideration genetic variations associated with individual responses to macronutrients. The aim of the present series of n-of-1 trials was to assess the effects of genetically-guided vs. conventional MNT on patients with pre-diabetes or T2DM. A quasi-experimental, cross-over design was adopted in three Caucasian adult men with either diagnosis. Complete diet, bioclinical and anthropometric assessment was performed and a conventional MNT, based on the clinical practice guidelines was applied for 8 weeks. After a week of “wash-out,” a precision MNT was prescribed for an additional 8-week period, based on the genetic characteristics of each patient. Outcomes of interest included changes in body weight (BW), fasting plasma glucose (FPG), and blood pressure (BP). Collectively, the trials indicated improvements in BW, FPG, BP, and glycosylated hemoglobin (HbA1c) following the genetically-guided precision MNT intervention. Moreover, both patients with pre-diabetes experienced remission of the condition. We conclude that improved BW loss and glycemic control can be achieved in patients with pre-diabetes/T2DM, by coupling MNT to their genetic makeup, guiding optimal diet, macronutrient composition, exercise and oral nutrient supplementation in a personalized manner.

Individual Postprandial Glycemic Responses to Diet in n-of-1 Trials: Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR)

BACKGROUND

The role of different types and quantities of macronutrients on human health has been controversial, and the individual response to dietary macronutrient intake needs more investigation.

OBJECTIVES

We aimed to use an 'n-of-1' study design to investigate the individual variability in postprandial glycemic response when eating diets with different macronutrient distributions among apparently healthy adults.

METHODS

Thirty apparently healthy young Chinese adults (women, 68%) aged between 22 and 34 y, with BMI between 17.2 and 31.9 kg/m2, were provided with high-fat, low-carbohydrate (HF-LC, 60-70% fat, 15-25% carbohydrate, 15% protein, of total energy) and low-fat, high-carbohydrate (LF-HC, 10-20% fat, 65-75% carbohydrate, 15% protein) diets, for 6 d wearing continuous glucose monitoring systems, respectively, in a randomized sequence, interspersed by a 6-d wash-out period. Three cycles were conducted. The primary outcomes were the differences of maximum postprandial glucose (MPG), mean amplitude of glycemic excursions (MAGE), and AUC24 between intervention periods of LF-HC and HF-LC diets. A Bayesian model was used to predict responders with the posterior probability of any 1 of the 3 outcomes reaching a clinically meaningful difference.

RESULTS

Twenty-eight participants were included in the analysis. Posterior probability of reaching a clinically meaningful difference of MPG (0.167 mmol/L), MAGE (0.072 mmol/L), and AUC24 (13.889 mmol/L·h) between LF-HC and HF-LC diets varied among participants, and those with posterior probability >80% were identified as high-carbohydrate responders (n = 9) or high-fat responders (n = 6). Analyses of the Bayesian-aggregated n-of-1 trials among all participants showed a relatively low posterior probability of reaching a clinically meaningful difference of the 3 outcomes between LF-HC and HF-LC diets.

CONCLUSIONS

N-of-1 trials are feasible to characterize personal response to dietary intervention in young Chinese adults.

Efficacy of Bilberry and Grape Seed Extract Supplement Interventions to Improve Glucose and Cholesterol Metabolism and Blood Pressure in Different Populations-A Systematic Review of the Literature

Intervention with fruit extracts may lower glucose and lipid levels, as well as blood pressure. We reviewed the efficacy of bilberry and grape seed extracts to affect these outcomes across populations with varying health status, age and ethnicity, across intervention doses and durations, in 24 intervention studies with bilberry and blackcurrant (n = 4) and grape seed extract (n = 20). Bilberry and blackcurrant extract lowered average levels of glycated hemoglobin (HbA1c), at least in Chinese subjects, especially in those who were older, who were diagnosed with Type 2 Diabetes Mellitus (T2DM) and who were participating in longer-term studies. We also found good evidence that across studies and in subjects with hypercholesterolemia, T2DM or metabolic syndrome, intervention with bilberry and blackcurrant extract, and to some extent grape seed extract, significantly lowered total and low density lipoprotein (LDL) cholesterol levels after four weeks. Intervention with grape seed extract may reduce systolic and diastolic blood pressure in subjects with hypertension or metabolic syndrome. Differential responsiveness in cholesterol and blood pressure outcomes between stratified populations could not be explained by age, dose or study duration. In conclusion, bilberry and blackcurrant extract appears effective in lowering HbA1c and total and LDL cholesterol, whereas grape seed extract may lower total and LDL cholesterol, and blood pressure, in specific population groups.

Prebiotic and probiotic supplementation and the tryptophan-kynurenine pathway: A systematic review and meta analysis

This systematic review aimed to synthesise the results from studies investigating the effects of prebiotics and probiotics on kynurenine pathway metabolism. Thirteen studies were identified for inclusion, comprising 12 probiotic and two prebiotic arms. Participants included healthy individuals and individuals with various clinical conditions. Twelve metabolites were examined across the studies, using a range of biological samples. Across all interventions, 11 reported an effect on ≤ metabolite. Although limited by clinical and methodological heterogeneity, pooled analysis (n = 253) found probiotics to significantly affect serum kynurenine (g = 0.315, CI = 0.070 to 0.560, p = 0.012, 4 studies, I² = 0%) and the kynurenine:tryptophan ratio (g = 0.442, CI = 0.074 to 0.810, p = 0.018, 4 studies, I² = 42 %). Risk of bias across the studies was generally low. The results provide preliminary evidence that probiotics can modulate kynurenine pathway metabolism, with less evidence available regarding prebiotics. Future studies which further consider methodological confounds and sample characteristics are required, to establish intervention efficacy. PROSPERO registration #CRD42019154677.

Perspective: Application of N-of-1 Methods in Personalized Nutrition Research

Personalized and precision nutrition aim to examine and improve health on an individual level, and this requires reconsideration of traditional dietary interventions or behavioral study designs. The limited frequency of measurements in group-level human nutrition trials cannot be used to infer individual responses to interventions, while in behavioral studies, retrospective data collection does not provide an accurate measure of how everyday behaviors affect individual health. This review introduces the concept of N-of-1 study designs, which involve the repeated measurement of a health outcome or behavior on an individual level. Observational designs can be used to monitor a participant's usual health or behavior in a naturalistic setting, with repeated measurements conducted in real time using an Ecological Momentary Assessment. Interventional designs can introduce a dietary or behavioral intervention with predictors and outcomes of interest measured repeatedly either during or after 1 or more intervention and control periods. Due to their flexibility, N-of-1 designs can be applied to both short-term physiological studies and longer-term studies of eating behaviors. As a growing number of disease markers can be measured outside of the clinic, with self-reported data delivered via electronic devices, it is now easier than ever to generate large amounts of data on an individual level. Statistical techniques can be utilized to analyze changes in an individual or to aggregate data from sets of N-of-1 trials, enabling hypotheses to be tested on a small number of heterogeneous individuals. Although their designs necessitate extra methodological and statistical considerations, N-of-1 studies could be used to investigate complex research questions and to study underrepresented groups. This may help to reveal novel associations between participant characteristics and health outcomes, with repeated measures providing power and precision to accurately determine an individual's health status.

More Nutrition Precision, Better Decisions for the Health of Our Nation

Nutritional science is evolving to an enhanced emphasis on recent scientific and technological advancements supporting a transition to precision nutrition as a strategy for disease prevention and management across populations. The complexity of chronic disease, which afflicts 6 in 10 adult Americans, is highlighted in the diet-disease relation where it is apparent that there is no "one size fits all" approach to disease management. Precision nutrition is the study of how individuals respond differently to food and nutrients, and it leads to personalized or classified, evidence-based guidelines that represent the best approach for fighting chronic disease. Enhanced resources are imperative as we transition to a precision nutrition approach that will transform agriculture and nutritional science to support positive health outcomes. Both the USDA and the NIH recognize the need to prioritize research and funding on precision nutrition. Increased federal investment in this realm is critical as we look ahead; it will help lower health care costs, while supporting individual health and quality of life.

Single-case experimental designs: Characteristics, changes, and challenges

Tactics of Scientific Research (Sidman, 1960) provides a visionary treatise on single-case designs, their scientific underpinnings, and their critical role in understanding behavior. Since the foundational base was provided, single-case designs have proliferated especially in areas of application where they have been used to evaluate interventions with an extraordinary range of clients, settings, and target foci. This article highlights core features of single-case experimental designs, how key and ancillary features of the designs have evolved, the special strengths of the designs, and challenges that have impeded their integration in many areas where their contributions are sorely needed. The article ends by placing the methodological approach in the context of other research traditions. In this way, the discussion moves from the specific designs toward foundations and philosophy of science issues in keeping with the strengths of the person and book we are honoring.

Precision medicine for pancreatic diseases

PURPOSE OF REVIEW

We describe and contrast the strengths of precision medicine with Western medicine, and complex trait genetics with Mendelian genetics. Classic genetics focuses on highly penetrant pathogenic variants in a single gene believed to cause or confer a high risk for well-defined phenotypes. However, a minority of disorders have a single gene cause. Further, even individuals with identical Mendelian disease-associated genotypes may exhibit substantial phenotypic variability indicative of genetic and environmental modifiers. Still, most diseases are considered complex traits (or complex diseases).

RECENT FINDINGS

New insights into the genetic underpinnings of complex traits provide opportunities for advances in diagnosis and management. Precision medicine provides the framework for integrating complex trait knowledge into clinical care through a sophisticated analysis pipeline. Multidimensional modeling of acquired diseases includes multiple genetic risks scattered over many genes and gene regulators that must be interpreted on the basis of functional evidence (e.g., genomics, transcriptomics) with structured models and expert systems; strengthened with machine learning and artificial intelligence. The choice of genotyping approaches (shotgun sequencing, single nucleotide polymorphism chips, targeted panels) is discussed.

SUMMARY

The result of a good precision medicine tool is clinical-decision support and guidance to tackle complex disorders such as pancreatitis, diabetes, and pancreatic cancer oncogenesis.

Application of n-of-1 Clinical Trials in Personalized Nutrition Research: A Trial Protocol for Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR)

Personalized dietary recommendations can help with more effective disease prevention. This study aims to investigate the individual postprandial glucose response to diets with diverse macronutrient proportions at both the individual level and population level, and explore the potential of the novel single-patient (n-of-1) trial for personalization of diet. Secondary outcomes include individual phenotypic responses and the effects of dietary ingredients on the composition of gut microbiota. Westlake N-of-1 Trials for Macronutrient Intake is a multiple crossover feeding trial consisting of 3 successive 12-d dietary intervention pairs including a 6-d washout period before each 6-d isocaloric dietary intervention: a 6-d high-fat, low-carbohydrate diet, and a 6-d low-fat, high-carbohydrate diet. The results will help provide personalized dietary recommendations for macronutrients in terms of postprandial blood glucose responses. The proposed n-of-1 trial methods could help in optimizing individual health and advancing health care. This trial was registered with clinicaltrials.gov (NCT04125602).

Targeting the delivery of dietary plant bioactives to those who would benefit most: from science to practical applications

Background

A healthy diet and optimal lifestyle choices are amongst the most important actions for the prevention of cardiometabolic diseases. Despite this, it appears difficult to convince consumers to select more nutritious foods. Furthermore, the development and production of healthier foods do not always lead to economic profits for the agro-food sector. Most dietary recommendations for the general population represent a “one-size-fits-all approach” which does not necessarily ensure that everyone has adequate exposure to health-promoting constituents of foods. Indeed, we now know that individuals show a high variability in responses when exposed to specific nutrients, foods, or diets.

Purpose

This review aims to highlight our current understanding of inter-individual variability in response to dietary bioactives, based on the integration of findings of the COST Action POSITIVe. We also evaluate opportunities for translation of scientific knowledge on inter-individual variability in response to dietary bioactives, once it becomes available, into practical applications for stakeholders, such as the agro-food industry. The potential impact from such applications will form an important impetus for the food industry to develop and market new high quality and healthy foods for specific groups of consumers in the future. This may contribute to a decrease in the burden of diet-related chronic diseases.

Individual differences in ADME (Absorption, Digestion, Metabolism and Excretion) is believed to underpin much of the inter-individual variation in responses.

Recent developments in the area of food metabolome databases and fast improvements in innovative metabotyping technologies hold great promise for improved profiling of dietary intake, exposure to individual ingredients, foods and dietary patterns, as well as our ability to identify individual responsiveness.

The food industry needs well-defined population clusters or targets in order to be able to design “personalized products”.

There are indeed excellent industrial opportunities for foods that modulate gut microbiota, and thereby enable the delivery of food bioactive metabolites.

It is currently not clear whether knowledge on individual nutrient needs, based on genetic or metagenomic data, would affect long-term dietary and health behaviours.

Data to support the development of dietary recommendations may need to be generated by new n-of-1-based study designs in the future.

N-of-1 Clinical Trials in Nutritional Interventions Directed at Improving Cognitive Function

Longer life expectancy has led to an increase in the prevalence of age-related cognitive decline and dementia worldwide. Due to the current lack of effective treatment for these conditions, preventive strategies represent a research priority. A large body of evidence suggests that nutrition is involved in the pathogenesis of age-related cognitive decline, but also that it may play a critical role in slowing down its progression. At a population level, healthy dietary patterns interventions, such as the Mediterranean and the MIND diets, have been associated with improved cognitive performance and a decreased risk of neurodegenerative disease development. In the era of evidence-based medicine and patient-centered healthcare, personalized nutritional recommendations would offer a considerable opportunity in preventing cognitive decline progression. N-of-1 clinical trials have emerged as a fundamental design in evidence-based medicine. They consider each individual as the only unit of observation and intervention. The aggregation of series of N-of-1 clinical trials also enables population-level conclusions. This review provides a general view of the current scientific evidence regarding nutrition and cognitive decline, and critically states its limitations when translating results into the clinical practice. Furthermore, we suggest methodological strategies to develop N-of-1 clinical trials focused on nutrition and cognition in an older population. Finally, we evaluate the potential challenges that researchers may face when performing studies in precision nutrition and cognition.

Paving the way to better population health through personalised nutrition

As each individual person differs from the next in multiple ways, it is a beguiling idea that our individual nutritional needs also differ. In support of this idea, findings from nutritional intervention studies provide ample evidence of considerable interindividual variation in response to the same dietary exposure. We have a limited understanding of the mechanisms responsible for this variation but, following sequencing of the human genome, the role of genes in explaining interindividual differences has been centre stage. In addition, evidence of diet–gene interactions that influence phenotype, including health, emphasises the importance of both nature and nurture. Eating patterns are major determinants of health, so public health advice to reduce the risk of common complex diseases focuses on diet. However, most dietary interventions are relatively ineffective and personalised approaches that tailor the intervention to the individual may be more acceptable and more effective. That idea was tested in the Food4Me study in which adults from seven European countries were randomised to one of four treatment groups in an internet‐delivered dietary intervention. Compared with the Control (standardised healthy eating advice), those people randomised to a personalised nutrition intervention had bigger, sustained changes, in eating behaviour after 6 months. However, including more complex phenotypic and/or genotypic information in developing the personalised nutrition advice had no added benefit. Research in personalised nutrition is broadening its scope to consider effects mediated by the gut microbiome as well as multiple aspects of genotype and phenotype. Such research has the potential to explain interindividual differences in the response to specific dietary factors and may provide a scientific basis for more refined approaches to personalised nutrition. However, if this research is to make a significant contribution to improving public health, it will need to address the psychological, social, economic and cultural factors that influence eating patterns to ensure that advice is converted into action and that improved dietary habits are sustained in perpetuity.

Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods

“N-of-1,” or single subject, clinical trials seek to determine if an intervention strategy is more efficacious for an individual than an alternative based on an objective, empirical, and controlled study. The design of such trials is typically rooted in a simple crossover strategy with multiple intervention response evaluation periods. The effect of serial correlation between measurements, the number of evaluation periods, the use of washout periods, heteroscedasticity (i.e., unequal variances among responses to the interventions) and intervention-associated carry-over phenomena on the power of such studies is crucially important for putting the yield and feasibility of N-of-1 trial designs into context. We evaluated the effect of these phenomena on the power of different designs for N-of-1 trials using analytical theory based on standard likelihood principles assuming an autoregressive lag 1, i.e., AR(1), serial correlation structure among the measurements as well as simulation studies. By evaluating the power to detect effects in many different settings, we show that the influence of serial correlation and heteroscedasticity on power can be substantial, but can also be mitigated to some degree through the use of appropriate multiple evaluation periods. We also show that the detection of certain types of carry-over effects can be heavily influenced by design considerations as well.

Primer on Precision Medicine for Complex Chronic Disorders

Precision medicine promises patients with complex disorders the right treatment for the right patient at the right dose at the right time with expectation of better health at a lower cost. The demand for precision medicine highlights the limitations of modern Western medicine. Modern Western medicine is a population-based, top-down approach that uses pathology to define disease. Precision medicine is a bottom-up approach that identifies predisease disorders using genetics, biomarkers, and modeling to prevent disease. This primer demonstrates the contrasting strengths and limitations of each paradigm and why precision medicine will eventually deliver on the promises.

What is Evidence-Based Functional Medicine in the 21st Century?

The 21st century has already demonstrated itself to be an era of change for medicine and science. There is a new openness-to ideas, to a shift in perspectives, to a redefinition of evidence and the many ways it can be gathered. New interest in real-world data, patient-experience information has also become an increasingly important contributor to the evaluation of treatment effectiveness. It is a fertile time on many fronts, including an expanded reach for a systems biology formalism and the Functional Medicine movement.

Accelerating the Drug Delivery Pipeline for Acute and Chronic Pancreatitis: Summary of the Working Group on Drug Development and Trials in Recurrent Acute Pancreatitis at the National Institute of Diabetes and Digestive and Kidney Diseases Workshop

Recurrent acute pancreatitis (RAP) is a complex clinical syndrome with significant morbidity, unpredictable outcomes, and limited treatment options. The National Institute of Diabetes and Digestive and Kidney Disease sponsored a workshop on July 25, 2018, in Pittsburgh, Pennsylvania, to address research gaps impeding development of effective therapies for pancreatitis. The RAP working group identified challenges to clinical progress using existing definitions, risk assessment, diagnostic and severity criteria, disease trajectories, outcomes, and research methods. Recurrent acute pancreatitis includes all the risk of acute pancreatitis and often progresses to chronic pancreatitis with variable complications of chronic pain, exocrine insufficiency, diabetes, and pancreatic cancer. However, the great variability among individuals with RAP requires better precision in defining the risks, individual episodes, as well as their frequency, pathogenic pathways, and specific outcome measures for each of the systems affected by pancreatic inflammation. Because of disease complexity, few patients are similar enough for traditional studies and methods to conduct clinical trials with small sample sizes are required. The need for genetic testing, biomarker development, and better imaging methods was highlighted. Adaptive and N-of-one study designs, better endpoints, and outcome measures including patient-reported outcomes should considered early in developing future therapeutic trial design and include all stakeholders.

A Genetic Score of Predisposition to Low-Grade Inflammation Associated with Obesity May Contribute to Discern Population at Risk for Metabolic Syndrome

Omega-3 rich diets have been shown to improve inflammatory status. However, in an ex vivo system of human blood cells, the efficacy of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) modulating lipid metabolism and cytokine response is attenuated in overweight subjects and shows high inter-individual variability. This suggests that obesity may be exerting a synergistic effect with genetic background disturbing the anti-inflammatory potential of omega-3 long-chain polyunsaturated fatty acids (PUFA). In the present work, a genetic score aiming to explore the risk associated to low grade inflammation and obesity (LGI-Ob) has been elaborated and assessed as a tool to contribute to discern population at risk for metabolic syndrome. Pro-inflammatory gene expression and cytokine production as a response to omega-3 were associated with LGI-Ob score; and lower anti-inflammatory effect of PUFA was observed in subjects with a high genetic score. Furthermore, overweight/obese individuals showed positive correlation of both plasma C-Reactive Protein and triglyceride/HDLc-index with LGI-Ob; and high LGI-Ob score was associated with greater hypertension (p = 0.047), Type 2 diabetes (p = 0.026), and metabolic risk (p = 0.021). The study shows that genetic variation can influence inflammation and omega-3 response, and that the LGI-Ob score could be a useful tool to classify subjects at inflammatory risk and more prone to suffer metabolic syndrome and associated metabolic disturbances.

Personalized medicine: motivation, challenges, and progress

There is a great deal of hype surrounding the concept of personalized medicine. Personalized medicine is rooted in the belief that since individuals possess nuanced and unique characteristics at the molecular, physiological, environmental exposure, and behavioral levels, they may need to have interventions provided to them for diseases they possess that are tailored to these nuanced and unique characteristics. This belief has been verified to some degree through the application of emerging technologies such as DNA sequencing, proteomics, imaging protocols, and wireless health monitoring devices, which have revealed great inter-individual variation in disease processes. In this review, we consider the motivation for personalized medicine, its historical precedents, the emerging technologies that are enabling it, some recent experiences including successes and setbacks, ways of vetting and deploying personalized medicines, and future directions, including potential ways of treating individuals with fertility and sterility issues. We also consider current limitations of personalized medicine. We ultimately argue that since aspects of personalized medicine are rooted in biological realities, personalized medicine practices in certain contexts are likely to be inevitable, especially as relevant assays and deployment strategies become more efficient and cost-effective.

Artificial Intelligence and Personalized Medicine

The development of high-throughput, data-intensive biomedical research assays and technologies has created a need for researchers to develop strategies for analyzing, integrating, and interpreting the massive amounts of data they generate. Although a wide variety of statistical methods have been designed to accommodate 'big data,'  experiences with the use of artificial intelligence (AI) techniques suggest that they might be particularly appropriate. In addition,  the results of the application of these assays reveal a great heterogeneity in the pathophysiologic factors and processes that contribute to disease, suggesting that there is a need to tailor, or 'personalize,' medicines to the nuanced and often unique features possessed by individual patients. Given how important data-intensive assays are to revealing appropriate intervention targets and strategies for  treating an individual with a disease, AI can play an important role in the development of personalized medicines. We describe many areas where AI can play such a role and argue that AI's ability to advance personalized medicine will depend critically on not only the refinement of relevant assays, but also on ways of storing, aggregating, accessing, and ultimately integrating, the data they produce. We also point out the limitations of many AI techniques in developing personalized medicines as well as consider areas for further research.

Variable Glycemic Responses to Intact and Hydrolyzed Milk Proteins in Overweight and Obese Adults Reveal the Need for Precision Nutrition

Background

Dietary modifications can contribute to improved pancreatic β cell function and enhance glycemic control.

Objectives

The objectives of this study were as follows: 1) to investigate the potential of milk protein hydrolysates to modulate postprandial glucose response; 2) to assess individual responses; and 3) to explore the inter- and intraindividual reproducibility of the response.

Methods

A 14-d randomized crossover study investigated interstitial glucose levels of participants in response to 12% w/v milk protein drinks (intact caseinate and casein hydrolysate A and B) consumed in random order with a 2-d washout between treatments. Milk protein drinks were consumed immediately prior to study breakfast and evening meals. Twenty participants (11 men, 9 women) aged 50 ± 8 y with a body mass index (in kg/m2) of 30.2 ± 3.1 were recruited. Primary outcome was glucose levels assessed at 15-min intervals with the use of glucose monitors.

Results

Repeated-measures ANOVA revealed that for breakfast there was a significant difference across the 3 treatment groups (P = 0.037). The ability to reduce postprandial glucose was specific to casein hydrolysate B in comparison with intact caseinate (P = 0.039). However, despite this significant difference, further examination revealed that only 3 out of 18 individuals were classified as responders (P < 0.05). High intraclass correlation coefficients were obtained for glucose response to study meals (intraclass correlation coefficient: 0.892 for breakfast with intact caseinate). The interindividual CVs were higher than the intraindividual CVs. Mean inter- and intraindividual CVs were 19.4% and 5.7%, respectively, for breakfast with intact caseinate.

Conclusion

Ingestion of a specific casein hydrolysate successfully reduced the postprandial glucose response; however, at an individual level only 3 participants were classified as responders, highlighting the need for precision nutrition. Exploration of high interindividual responses to nutrition interventions is needed, in combination with the development of precision nutrition, potentially through an n-of-1 approach. This clinical trial was registered as ISRCTN61079365 (https://www.isrctn.com/).

Barriers and Research Priorities for Implementing Precision Medicine

Effective management of complex pancreatic diseases demands precision medicine. While this new approach is technically feasible, many barriers to implementation impede realization of its promised benefits. Barriers exist in the acquisition and utilization of high quality, accurate, specific and quantitative information from both the clinical records and basic sciences. Barriers exist in integrating various domains of knowledge. Barriers exist in translating new insights from the bench to the bedside. Logistical barriers prevent seamless connection and interpretation of the necessary data elements. Barriers also exist with acceptance and application of precision medicine by major institutions and payers. Overcome these barriers will require high-level planning, clarity of vision into short and long term steps, and the commitment of innovative leaders, representing all stakeholders, to work together to reach a common goal.

The Effect of Food Unit Sizes and Meal Serving Occasions on Eating Behaviour Characteristics: Within Person Randomised Crossover Studies on Healthy Women

Manipulating food properties and serving environment during a meal can significantly change food intake at group level. However, the evaluation of the usefulness of such manipulations requires an understanding of individual behavioural changes. Three studies were conducted to explore the effect of unit size and meal occasion on eating behaviour characteristics (food intake, meal duration, number of bites and chews). All studies used a randomised crossover design, with a one-week wash-out period, starting with a familiarisation meal, with the participation of healthy, normal weight females between the ages of 18–35 years. In Study 1 (n = 19) three cube sizes (0.5, 1.0 and 1.5 cm³) of vegetable hash and chicken were compared. In Study 2 (n = 18) mashed potatoes and mincemeat were compared to whole potatoes and meatballs. In Study 3 (n = 29) meals served at lunch time (11:00–13:00) were compared to identical meals served at dinner time (17:00–19:00). The largest food unit size lead to significantly increased meal duration in Study 2 (mean difference 0.9 min, 95% confidence interval (CI) 0.0–1.8), but not in Study 1 (mean difference 1 min, 95% CI 0.1–2.0). There was a significant increase in number of chews in the large unit size condition of both Study 1 (mean difference 88, 95% CI 12–158) and Study 2 (mean difference 95, 95% CI 12–179). Different serving occasions did not significantly change any of the eating behaviours measured. Except for number of bites in Study 2 (R² = 0.60), most individuals maintained their eating behaviour relative to the group across unit sizes and serving occasions conditions (R² > 0.75), which suggests single meal testing can provide information about the behavioural characteristics of individual eating styles under different conditions.

Personalised nutrition and health

Jose Ordovas and colleagues consider that nutrition interventions tailored to individual characteristics and behaviours have promise but more work is needed before they can deliver

Clinical and Vitamin Response to a Short-Term Multi-Micronutrient Intervention in Brazilian Children and Teens: From Population Data to Interindividual Responses

SCOPE

Micronutrients are in small amounts in foods, act in concert, and require variable amounts of time to see changes in health and risk for disease. These first principles are incorporated into an intervention study designed to develop new experimental strategies for setting target recommendations for food bioactives for populations and individuals.

METHODS AND RESULTS

A 6-week multivitamin/mineral intervention is conducted in 9-13 year olds. Participants (136) are (i) their own control (n-of-1); (ii) monitored for compliance; (iii) measured for 36 circulating vitamin forms, 30 clinical, anthropometric, and food intake parameters at baseline, post intervention, and following a 6-week washout; and (iv) had their ancestry accounted for as modifier of vitamin baseline or response. The same intervention is repeated the following year (135 participants). Most vitamins respond positively and many clinical parameters change in directions consistent with improved metabolic health to the intervention. Baseline levels of any metabolite predict its own response to the intervention. Elastic net penalized regression models are identified, and significantly predict response to intervention on the basis of multiple vitamin/clinical baseline measures.

CONCLUSIONS

The study design, computational methods, and results are a step toward developing recommendations for optimizing vitamin levels and health parameters for individuals.

Personalised Interventions-A Precision Approach for the Next Generation of Dietary Intervention Studies

Diet is a key modifiable risk factor for non-communicable diseases. However, we currently are not benefitting from the full potential of its protective effects. This is due to a number of reasons, including high individual variability in response to certain diets. It is now well acknowledged that in order to gain the full benefit of dietary regimes it is essential to take into account individual responses. With this in mind, the present review examines the concept of precision nutrition and the performance of n-of-1 studies, and discusses the development of certain approaches that will be critical for development of the concepts.