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

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study

BACKGROUND

Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective blood glucose control and most dietary advice emphasizes carbohydrate and calorie reduction. Emerging global evidence demonstrates marked interindividual differences in postprandial glucose response (PPGR) although no such data exists in India and previous studies have primarily evaluated PPGR variation in individuals without diabetes.

OBJECTIVE

This prospective cohort study seeks to characterize the PPGR variability among individuals with diabetes living in India and to identify factors associated with these differences.

METHODS

Adults with T2D and a hemoglobin A1c of ≥7 are being enrolled from 14 sites around India. Participants wear a continuous glucose monitor, eat a series of standardized meals, and record all free-living foods, activities, and medication use for a 14-day period. The study's primary outcome is PPGR, calculated as the incremental area under the curve 2 hours after each logged meal.

RESULTS

Data collection commenced in May 2022, and the results will be ready for publication by September 2025. Results from our study will generate data to facilitate the creation of machine learning models to predict individual PPGR responses and to facilitate the prescription of personalized diets for individuals with T2D.

CONCLUSIONS

This study will provide the first large scale examination variability in blood glucose responses to food in India and will be among the first to estimate PPGR variability for individuals with T2D in any jurisdiction.

TRIAL REGISTRATION

Clinical Trials Registry-India CTRI/2022/02/040619; https://tinyurl.com/mrywf6bf.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59308.

N-of-1 trials in epilepsy: A systematic review and lessons paving the way forward

OBJECTIVE

Defined as prospective single-patient crossover studies with repeated paired cycles of active and control intervention, N-of-1 trials have gained attention as an option to obtain high-quality evidence of efficacy, particularly for patients with rare epilepsies in whom conduction of well-powered randomized controlled trials can be challenging. The objective of this systematic review is to provide an appraisal of the literature on N-of-1 trials in individuals with epilepsy.

METHODS

We searched PubMed and Embase on January 12, 2024, for studies meeting the following criteria: prospectively planned, within-patient, multiple-crossover design in individuals with epilepsy and outcomes related to comorbidities. Information on design, outcome measurements, intervention, and analyses was retrieved. Risk of bias assessment was performed using the Risk of Bias in N-of-1 Trials (RoBiNT) scale. We highlighted methodological aspects of the N-of-1 trials identified and discuss future recommendations.

RESULTS

Five studies met our inclusion criteria. An additional multiple-crossover trial that evaluated treatment effects exclusively at group level was also included because of its relevance to N-of-1 study methodology. The studies enrolled individuals with focal seizures, absences or cognitive impairement and electrographic discharges. Treatments included established or investigational antiseizure medications, off-label medications, neurostimulation or lifestyle intervention. Three of the five N-of-1 trials reported on individual cases. The studies' strengths were the use of individualized treatment dosages and symptom-specific patient-reported outcomes. Limitations were related to minimal reporting of baseline characteristics and seizure burden.

SIGNIFICANCE

The trials identified by our search exemplify how the N-of-1 design can be applied to assess interventions in individuals with epilepsy-related disorders. Future N-of-1 trials of antiseizure interventions should take into account baseline seizure frequency, should apply statistical models suited to capture seizure frequency changes reliably and make predefined interim assessments. Non-seizure outcome measures evaluable over short periods should be considered. Tailored N-of-1 methodology could pave the way to evidence-based, treatment selection for patients with rare epilepsies.

Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments

Since dietary intake is challenging to directly measure in large-scale cohort studies, we often rely on self-reported instruments (e.g., food frequency questionnaires, 24-hour recalls, and diet records) developed in nutritional epidemiology. Those self-reported instruments are prone to measurement errors, which can lead to inaccuracies in the calculation of nutrient profiles. Currently, few computational methods exist to address this problem. In the present study, we introduce a deep-learning approach-Microbiome-based nutrient profile corrector (METRIC), which leverages gut microbial compositions to correct random errors in self-reported dietary assessments using 24-hour recalls or diet records. We demonstrate the excellent performance of METRIC in minimizing the simulated random errors, particularly for nutrients metabolized by gut bacteria in both synthetic and three real-world datasets. Additionally, we find that METRIC can still correct the random errors well even without including gut microbial compositions. Further research is warranted to examine the utility of METRIC to correct actual measurement errors in self-reported dietary assessment instruments.

Nutraceuticals in osteoporosis prevention

Nutraceuticals are gaining popularity as they can contribute to bone health by delaying the onset or slowing down the progression of pathological bone loss. Osteoporosis's bone loss is a concern for older adults and a crucial aspect of aging. Maintaining healthy bones is the key to living a full and active life. Our review explores the current knowledge on the role of nutraceuticals in preventing osteoporosis by focusing on three main aspects. First, we provide an overview of osteoporosis. Second, we discuss the latest findings on natural nutraceuticals and their efficacy in reducing bone loss, emphasizing clinical trials. Third, we conduct a structured analysis to evaluate nutraceuticals' pros and cons and identify translational gaps. In conclusion, we must address several challenges to consolidate our knowledge, better support clinicians in their prescriptions, and provide people with more reliable nutritional recommendations to help them lead healthier lives.

Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments

Since dietary intake is challenging to directly measure in large-scale cohort studies, we often rely on self-reported instruments (e.g., food frequency questionnaires, 24-hour recalls, and diet records) developed in nutritional epidemiology. Those self-reported instruments are prone to measurement errors, which can lead to inaccuracies in the calculation of nutrient profiles. Currently, few computational methods exist to address this problem. In the present study, we introduce a deep-learning approach --- Microbiome-based nutrient profile corrector (METRIC), which leverages gut microbial compositions to correct random errors in self-reported dietary assessments using 24-hour recalls or diet records. We demonstrate the excellent performance of METRIC in minimizing the simulated random errors, particularly for nutrients metabolized by gut bacteria in both synthetic and three real-world datasets. Further research is warranted to examine the utility of METRIC to correct actual measurement errors in self-reported dietary assessment instruments.

Effects of different types of meals on postprandial glycaemia in healthy subjects

Nowadays, continuous glycaemic monitoring systems are used primarily for diabetic patients. The most popular continuous glycaemic monitoring (CGMs) measure the glucose concentration in the interstitial fluid every 1 or 5 minutes, providing the patient with 288 or 1,440 measurements in a day. CGM is also useful for observing sudden changes in glycaemia after the introduction of dietary interventions and those related to physical activity. Peri-prandial glycaemia is defined as the change in blood glucose levels depending on the carbohydrate-containing meal consumed. A state of peri-prandial hyperglycaemia begins when blood glucose levels rise above the level of 140 mg/dl (7.8 mmol/l) within 1-2 hours after food intake in healthy people without diabetes. The influence of the peri-prandial glycaemic response is briefly related to the amount and type of food consumed. Optimising the glycaemic profile is important for our health. The purpose of this article is to summarise the current knowledge of the effects of various meals on peri-prandial glycaemia in healthy individuals.

Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health

Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.

Role of metabolomics in the delivery of precision nutrition

Precision nutrition aims to deliver personalised dietary advice to individuals based on their personal genetics, metabolism and dietary/environmental exposures. Recent advances have demonstrated promise for the use of omic technologies for furthering the field of precision nutrition. Metabolomics in particular is highly attractive as measurement of metabolites can capture information on food intake, levels of bioactive compounds and the impact of diets on endogenous metabolism. These aspects contain useful information for precision nutrition. Furthermore using metabolomic profiles to identify subgroups or metabotypes is attractive for the delivery of personalised dietary advice. Combining metabolomic derived metabolites with other parameters in prediction models is also an exciting avenue for understanding and predicting response to dietary interventions. Examples include but not limited to role of one carbon metabolism and associated co-factors in blood pressure response. Overall, while evidence exists for potential in this field there are also many unanswered questions. Addressing these and clearly demonstrating that precision nutrition approaches enable adherence to healthier diets and improvements in health will be key in the near future.

The Short-Term Variation of Human Gut Mycobiome in Response to Dietary Intervention of Different Macronutrient Distributions

While the human gut is home to a complex and diverse community of microbes, including bacteria and fungi, research on the gut microbiome has largely focused on bacteria, with relatively little attention given to the gut mycobiome. This study aims to investigate how diets with different dietary macronutrient distributions impact the gut mycobiome. We investigated gut mycobiome response to high-carbohydrate, low-fat (HC) and low-carbohydrate high-fat (LC) diet interventions based on a series of 72-day feeding-based n-of-1 clinical trials. A total of 30 participants were enrolled and underwent three sets of HC and LC dietary interventions in a randomized sequence. Each set lasted for 24 days with a 6-day washout period between dietary interventions. We collected and analyzed the fungal composition of 317 stool samples before and after each intervention period. To account for intra-individual variation across the three sets, we averaged the mycobiome data from the repeated sets for analysis. Of the 30 participants, 28 (aged 22-34 years) completed the entire intervention. Our results revealed a significant increase in gut fungal alpha diversity (p < 0.05) and significant changes in fungal composition (beta diversity, p < 0.05) after the HC dietary intervention. Specifically, we observed the enrichment of five fungal genera (Pleurotus, Kazachstania, Auricularia, Paraphaeosphaeria, Ustilaginaceae sp.; FDR < 0.052) and depletion of one fungal genus (Blumeria; FDR = 0.03) after the HC intervention. After the LC dietary intervention, one fungal genus was enriched (Ustilaginaceae sp.; FDR = 0.003), and five fungal genera were depleted (Blumeria, Agaricomycetes spp., Malassezia, Rhizopus, and Penicillium; FDR < 0.1). This study provides novel evidence on how the gut mycobiome structure and composition change in response to the HC and LC dietary interventions and reveals diet-specific changes in the fungal genera.

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.

Breaking new frontiers: Assessment and re-evaluation of clinical trial design for nutraceuticals

Despite sophisticated study designs and measurement tools, we have yet to create an innovative space for diet and dietary supplements in the health care system. The path is challenging due to current hierarchies of scientific evidence and regulatory affairs. The role of the randomized, double-blind, placebo-controlled clinical trial (RCT) as a research approach functions well to characterize the benefits and risks of drugs but lacks the sensitivity to capture the efficacy and safety of nutraceuticals. While some facets of RCTs can be relevant and useful when applied to nutraceuticals, other aspects are limiting and potentially misleading when taken in their entirety. A differentiation between guidelines for evidence-based medicine and the evidence required for nutrition spotlight the need to reconceptualize constituents of the RCT and their applicability with relevance to health promotion. This perspective identifies the limitations of the traditional RCT to capture the complexities of nutraceuticals and proposes the N-of-1 as Level 1 evidence better suited for the proof of efficacy of nutraceuticals.

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.

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.

The Relationship between Macronutrient Distribution and Type 2 Diabetes in Asian Indians

Asian Indians (AIs) are at increased risk for type 2 diabetes mellitus than other ethnic groups. AIs also have lower body mass index (BMI) values than other populations, so can benefit from strategies other than weight reduction. Macronutrient distributions are associated with improved glycemic control; however, no specific distribution is generally recommended. This study looks at whether a macronutrient distribution of 50:30:20 (percent of total calories from carbohydrates, fats, and protein) is related to diabetes status in AIs. Diet and Hemoglobin A1c (HbA1c) were assessed from convenience sample of AI adults in Maryland. A ratio of actual to needed calories using the 50:30:20 macronutrient distribution was then tested against diabetes status to identify associations. All groups except non-diabetic females, were in negative energy balance. The non-diabetic group consumed larger actual to needed ratios of protein than pre-diabetics and diabetics. However, all groups consumed protein at the lower end of the Acceptable Macronutrient Distribution Range (AMDR), and the quality of all macronutrients consumed was low. Therefore, weight loss may not be the recommendation for diabetes management for AIs. Increasing protein and insoluble fiber consumption, could play a critical role.