Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans.

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals' stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

Primary outcomes from Partner2Lose: A randomized controlled trial to evaluate partner involvement on long-term weight loss.

Background: Partner support is associated with better weight loss outcomes in observational studies, but randomized trials show mixed results for including partners. Unclear is whether teaching communication skills to couples will improve weight loss in index participants. Purpose: To compare the efficacy of a partner-assisted intervention versus participant-only weight management program on long-term weight loss. Methods: This community-based study took place in Madison, WI. Index participants were eligible if they met obesity guideline criteria to receive weight loss counseling, were aged 74 years or younger, lived with a partner, and had no medical contraindications to weight loss; partners were aged 74 years or younger and not underweight. Couples were randomized 1:1 to a partner-assisted or participant-only intervention. Index participants in both arms received an evidence-based weight management program. In the partner-assisted arm, partners attended half of the intervention sessions, and couples were trained in communication skills. The primary outcome was index participant weight at 24 months, assessed by masked personnel; secondary outcomes were 24-month self-reported caloric intake and average daily steps assessed by an activity tracker. General linear mixed models were used to compare group differences in these outcomes following intent-to-treat principles. Results: Among couples assigned to partner-assisted (n=115) or participant-only intervention (n=116), most index participants identified as female (67%) and non-Hispanic White (87%). Average baseline age was 47.27 years (SD 11.51 years) and weight was 106.55 kg (SD 19.41 kg). The estimated mean 24-month weight loss was similar in the partner-assisted (2.66 kg) and participant-only arms (2.89 kg) (estimated mean difference, 0.23 kg [95% CI, -1.58, 2.04 kg]). There were no differences in 24-month average daily caloric intake (50 cal [95% CI: -233, 132 cal]) or steps (806 steps [95% CI: -1675, 64 steps]). The percentage of participants reporting an adverse event with at least possible attribution to the intervention did not differ by arm (partner-assisted: 9%, participant-only, 3%, p=0.11). Conclusions: Partner-assisted and individual weight management interventions led to similar outcomes in index participants. Trial registration: Clinicaltrials.gov NCT03801174.

Expert consensus on nutrition and lower-carbohydrate diets: An evidence- and equity-based approach to dietary guidance.

There is a substantial body of clinical evidence supporting the beneficial effects of lower-carbohydrate dietary patterns on multiple established risk factors associated with insulin resistance and cardiovascular diseases in adult populations. Nutrition and health researchers, clinical practitioners, and stakeholders gathered for, "The Scientific Forum on Nutrition, Wellness, and Lower-Carbohydrate Diets: An Evidence- and Equity-Based Approach to Dietary Guidance" to discuss the evidence base around lower-carbohydrate diets, health outcomes, and dietary guidance. Consensus statements were agreed upon to identify current areas of scientific agreement and spotlight gaps in research, education, and practice to help define and prioritize future pathways. Given the evidence base and considering that most American adults are living with at least one nutrition-related chronic disease, there was consensus that including a lower-carbohydrate dietary pattern as one part of the Dietary Guidelines for Americans could help promote health equity among the general population.

Does Medically Supervised Weight Loss Prior to Total Knee Arthroplasty Improve Patient-Reported Pain and Physical Function?

BACKGROUND: Weight loss is commonly recommended before total knee arthroplasty (TKA) despite inconsistent evidence for better outcomes. This study sought to examine the impacts of preoperative weight loss on patient-reported and adverse outcomes among TKA patients supervised by a medical weight management clinic. METHODS: This study retrospectively analyzed patients who underwent medical weight management supervision within 18 months before TKA comparing patients who did and did not have clinically relevant weight loss. Preoperative body mass indices, demographics, Patient-Reported Outcomes Measurement Information System physical function and pain interference scores, pain intensity scores, and adverse outcomes were extracted. Multivariable linear regressions were performed to determine if preoperative weight loss correlated with patient-reported outcomes after controlling for confounders. RESULTS: There were 90 patients, 75.6% women, who had a mean age of 65 years (range, 42-82) and were analyzed. There were 51 (56.7%) patients who underwent clinically relevant weight loss with a mean weight loss of 10.4% and experienced no difference in adverse outcomes. Preoperative weight loss predicted significantly improved 3-month postoperative physical function (ß = 15.2 [13.0-17.3], P < .001), but not pain interference (ß = -18.9 [-57.1-19.4], P = .215) or pain intensity (ß = -1.8 [-4.9-1.2], P = .222) scores. CONCLUSION: We found that medically supervised preoperative weight loss predicted improvement in physical function 3 months after TKA. This weight loss caused no major adverse effects. Further research is needed to understand the causal relationships between preoperative weight loss, medical supervision, and outcome after TKA and to elucidate potential longer-term benefits in a larger sample.

Quantifying and correcting bias due to outcome dependent self-reported weights in longitudinal study of weight loss interventions.

In response to the escalating global obesity crisis and its associated health and financial burdens, this paper presents a novel methodology for analyzing longitudinal weight loss data and assessing the effectiveness of financial incentives. Drawing from the Keep It Off trial-a three-arm randomized controlled study with 189 participants-we examined the potential impact of financial incentives on weight loss maintenance. Given that some participants choose not to weigh themselves because of small weight change or weight gains, which is a common phenomenon in many weight-loss studies, traditional methods, for example, the Generalized Estimating Equations (GEE) method tends to overestimate the effect size due to the assumption that data are missing completely at random. To address this challenge, we proposed a framework which can identify evidence of missing not at random and conduct bias correction using the estimating equation derived from pairwise composite likelihood. By analyzing the Keep It Off data, we found that the data in this trial are most likely characterized by non-random missingness. Notably, we also found that the enrollment time (i.e., duration time) would be positively associated with the weight loss maintenance after adjusting for the baseline participant characteristics (e.g., age, sex). Moreover, the lottery-based intervention was found to be more effective in weight loss maintenance compared with the direct payment intervention, though the difference was non-statistically significant. This framework's significance extends beyond weight loss research, offering a semi-parametric approach to assess missing data mechanisms and robustly explore associations between exposures (e.g., financial incentives) and key outcomes (e.g., weight loss maintenance). In essence, the proposed methodology provides a powerful toolkit for analyzing real-world longitudinal data, particularly in scenarios with data missing not at random, enriching comprehension of intricate dataset dynamics.

Comparison of weight captured via electronic health record and cellular scales to the gold-standard clinical method.

Introduction: Obtaining body weights remotely could improve feasibility of pragmatic trials. This investigation examined whether weights collected via cellular scale or electronic health record (EHR) correspond to gold standard in-person study weights. Methods: The agreement of paired weight measurements from cellular scales were compared to study scales from a weight loss intervention and EHR-collected weights were compared to study scales from a weight loss maintenance intervention. Differential weight change estimates between intervention and control groups using both pragmatic methods were compared to study collected weight. In the Log2Lose feasibility weight loss trial, in-person weights were collected bi-weekly and compared to weights collected via cellular scales throughout the study period. In the MAINTAIN weight loss maintenance trial, in-person weights were collected at baseline, 14, 26, 42 and 56 weeks. All available weights from the EHR during the study period were obtained. Results: On average, in Log2Lose cellular scale weights were 0.6 kg (95% CI: -2.9, 2.2) lower than in-person weights; in MAINTAIN, EHR weights were 2.8 kg (SE: -0.5, 6.0) higher than in-person weights. Estimated weight change using pragmatic methods and study scales in both studies were in the same direction and of similar magnitude. Conclusion: Both methods can be used as cost-effective and real-world surrogates within a tolerable variability for the gold-standard. Trial registration: NCT02691260; NCT01357551.

Does Preoperative Weight Loss Within 6 Months or 1 Year Change the Risk of Adverse Outcomes in Total Knee Arthroplasty by Initial Body Mass Index Classification?

BACKGROUND: High body mass index (BMI) is associated with adverse outcomes after total knee arthroplasty (TKA). Thus, many patients are advised to lose weight before TKA. This study examined how weight loss before TKA is associated with adverse outcomes depending on patients' initial BMI. METHODS: This was a retrospective study of 2,110 primary TKAs at a single academic center. Data on preoperative BMIs, demographics, comorbidities, and incidences of revision or prosthetic joint infection (PJI) were obtained. Multivariable logistic regressions segmented by patients' initial (1-year preoperative) BMI classifications were performed to determine if a > 5% BMI decrease from 1 year or 6 months preoperatively predicted PJI and revision controlling for patient age, race, sex, and Elixhauser comorbidity index. RESULTS: Preoperative weight loss did not predict adverse outcomes for patients who had Obesity Class II or III. 6-month weight loss had greater odds of adverse outcomes than 1-year weight loss and most significantly predicted the occurrence of 1-year PJI (adjusted odds ratio: 6.55, P < .001) for patients who had Obesity Class 1 or lower. CONCLUSION: This study does not show a statistically significant effect to patients who had Obesity Class II and III losing weight preoperatively with respect to PJI or revision. For patients who have Obesity Class I or lower pursuing TKA, future research should consider potential risks associated with weight loss. Further study is needed to determine if weight loss can be implemented as a safe and effective risk reduction strategy for specific BMI classes of TKA patients.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income.

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

Applying a nutrition security lens to the Dietary Guidelines for Americans to address metabolic health.

Nutrition security - access to food that promotes well-being and prevents or treats disease, particularly among racial and ethnic minority populations, lower income populations, and rural and remote populations - is a national priority. Leading causes of death and disability in America, such as heart disease, stroke, cancer, and diabetes that disproportionately affect minorities are linked to preventable diet-related risk factors. Mounting evidence indicates that adherence to a lower-carbohydrate dietary pattern is associated with weight maintenance, improved blood glucose and insulin control, lower blood pressure, reduced markers of inflammation, and a more favorable lipid profile. Additionally, prior concerns regarding the higher fat and cholesterol content of this dietary pattern are less founded in modern research. The inclusion of a lower-carbohydrate option that meets all essential nutrient requirements aligns with the contemporary movement toward more flexibility and precision nutrition. Most important, a lower-carbohydrate option positions the Dietary Guidelines for Americans to more accurately reflect the current scientific evidence and more effectively address the metabolic health of the nation. Further, it has the potential to improve nutrition security by addressing metabolic diseases that disproportionately affect people from historically marginalized racial, ethnic, socioeconomic, and cultural backgrounds. Given that most American adults are living with at least one diet-related chronic metabolic disease, updating the Dietary Guidelines for Americans to recognize and reflect the poor health status of the general population is prudent and urgent.

A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial.

BACKGROUND: The use of digital technologies and software allows for new opportunities to communicate and engage with research participants over time. When software is coupled with automation, we can engage with research participants in a reliable and affordable manner. Research Electronic Data Capture (REDCap), a browser-based software, has the capability to send automated text messages. This feature can be used to automate delivery of tailored intervention content to research participants in interventions, offering the potential to reduce costs and improve accessibility and scalability. OBJECTIVE: This study aimed to describe the development and use of 2 REDCap databases to deliver automated intervention content and communication to index participants and their partners (dyads) in a 2-arm, 24-month weight management trial, Partner2Lose. METHODS: Partner2Lose randomized individuals with overweight or obesity and cohabitating with a partner to a weight management intervention alone or with their partner. Two databases were developed to correspond to 2 study phases: one for weight loss initiation and one for weight loss maintenance and reminders. The weight loss initiation database was programmed to send participants (in both arms) and their partners (partner-assisted arm) tailored text messages during months 1-6 of the intervention to reinforce class content and support goal achievement. The weight maintenance and reminder database was programmed to send maintenance-related text messages to each participant (both arms) and their partners (partner-assisted arm) during months 7-18. It was also programmed to send text messages to all participants and partners over the course of the 24-month trial to remind them of group classes, dietary recall and physical activity tracking for assessments, and measurement visits. All text messages were delivered via Twilio and were unidirectional. RESULTS: Five cohorts, comprising 231 couples, were consented and randomized in the Partner2Lose trial. The databases will send 53,518 automated, tailored text messages during the trial, significantly reducing the need for staff to send and manage intervention content over 24 months. The cost of text messaging will be approximately US $450. Thus far, there is a 0.004% known error rate in text message delivery. CONCLUSIONS: Our trial automated the delivery of tailored intervention content and communication using REDCap. The approach described provides a framework that can be used in future behavioral health interventions to create an accessible, reliable, and affordable method for intervention delivery and engagement that requires minimal trial-specific resources and personnel time. TRIAL REGISTRATION: ClinicalTrials.gov NCT03801174; https://clinicaltrials.gov/ct2/show/NCT03801174?term=NCT03801174.

Testing a very low-carbohydrate adaption of the Diabetes Prevention Program among adults with prediabetes: study protocol for the Lifestyle Education about prediabetes (LEAP) trial.

BACKGROUND: The Center for Disease Control and Prevention's National Diabetes Prevention Program (NDPP) aims to help individuals with prediabetes avoid progression to type 2 diabetes mellitus (T2DM) through weight loss. Specifically, the NDPP teaches individuals to follow a low-fat, calorie-restricted diet and to engage in regular physical activity to achieve ≥ 5% body weight loss. Most NDPP participants, however, do not achieve this weight loss goal, and glycemic control remains largely unchanged. One promising opportunity to augment the NDPP's weight loss and glycemic effectiveness may be to teach participants to follow a very low-carbohydrate diet (VLCD), which can directly reduce post-prandial glycemia and facilitate weight loss by reducing circulating insulin and enabling lipolysis. To date, there have been no high-quality, randomized controlled trials to test whether a VLCD can prevent progression to T2DM among individuals with prediabetes. The aim of this study is to test the effectiveness of a VLCD version the NDPP (VLC-NDPP) versus the standard NDPP. We hypothesize the VLC-NDPP will demonstrate greater improvements in weight loss and glycemic control. METHODS: We propose to conduct a 12-month, 1:1, randomized controlled trial that will assign 300 adults with overweight or obesity and prediabetes to either the NDPP or VLC-NDPP. The primary outcome will be glycemic control as measured by change in hemoglobin A1c (HbA1c) from baseline to 12 months. Secondary outcomes will include percent body weight change and changes in glycemic variability, inflammatory markers, lipids, and interim HbA1c. We will evaluate progression to T2DM and initiation of anti-hyperglycemic agents. We will conduct qualitative interviews among a purposive sample of participants to explore barriers to and facilitators of dietary adherence. The principal quantitative analysis will be intent-to-treat using hierarchical linear mixed effects models to assess differences over time. DISCUSSION: The NDPP is the dominant public health strategy for T2DM prevention. Changing the program's dietary advice to include a carbohydrate-restricted eating pattern as an alternative option may enhance the program's effectiveness. If the VLC-NDPP shows promise, this trial would be a precursor to a multi-site trial with incident T2DM as the primary outcome. TRIAL REGISTRATION: NCT05235425. Registered February 11, 2022.

Competing paradigms of obesity pathogenesis: energy balance versus carbohydrate-insulin models.

The obesity pandemic continues unabated despite a persistent public health campaign to decrease energy intake ("eat less") and increase energy expenditure ("move more"). One explanation for this failure is that the current approach, based on the notion of energy balance, has not been adequately embraced by the public. Another possibility is that this approach rests on an erroneous paradigm. A new formulation of the energy balance model (EBM), like prior versions, considers overeating (energy intake > expenditure) the primary cause of obesity, incorporating an emphasis on "complex endocrine, metabolic, and nervous system signals" that control food intake below conscious level. This model attributes rising obesity prevalence to inexpensive, convenient, energy-dense, "ultra-processed" foods high in fat and sugar. An alternative view, the carbohydrate-insulin model (CIM), proposes that hormonal responses to highly processed carbohydrates shift energy partitioning toward deposition in adipose tissue, leaving fewer calories available for the body's metabolic needs. Thus, increasing adiposity causes overeating to compensate for the sequestered calories. Here, we highlight robust contrasts in how the EBM and CIM view obesity pathophysiology and consider deficiencies in the EBM that impede paradigm testing and refinement. Rectifying these deficiencies should assume priority, as a constructive paradigm clash is needed to resolve long-standing scientific controversies and inform the design of new models to guide prevention and treatment. Nevertheless, public health action need not await resolution of this debate, as both models target processed carbohydrates as major drivers of obesity.

Adherence to Low-Carbohydrate Diets in Patients with Diabetes: A Narrative Review.

Evidence suggests that low carbohydrate (<130 g/day of carbohydrate) (LCD) and very low carbohydrate, ketogenic diets (typically <50 g/day of carbohydrate) (VLCKD) can be effective tools for managing diabetes given their beneficial effects on weight loss and glycemic control. VLCKD also result in favorable lipid profile changes. However, these beneficial effects can be limited by poor dietary adherence. Cultural, religious, and economic barriers pose unique challenges to achieving nutritional compliance with LCD and VLCKD. We review the various methods for assessing adherence in clinical studies and obstacles posed, as well as potential solutions to these challenges.

Factors associated with non-adherence to insulin and non-insulin medications in patients with poorly controlled diabetes.

OBJECTIVES: To evaluate differences in factors associated with self-reported medication non-adherence to insulin and non-insulin medications in patients with uncontrolled type 2 diabetes. METHODS: In this secondary analysis of a randomized trial in patients with obesity and uncontrolled type 2 diabetes, multivariable logistic regression was used to evaluate associations between several clinical factors (measured with survey questionnaires at study baseline) and self-reported non-adherence to insulin and non-insulin medications. RESULTS: Among 263 patients, reported non-adherence was 62% (52% for insulin, 55% for non-insulin medications). Reported non-adherence to non-insulin medications was less likely in white versus non-white patients (odds ratio (OR) = 0.42; 95%CI: 0.22,0.80) and with each additional medication taken (OR = 0.75; 95%CI: 0.61,0.93). Non-adherence to non-insulin medications was more likely with each point increase in a measure of diabetes medication intensity (OR = 1.43; 95%CI: 1.01,2.03), the Problem Areas in Diabetes (PAID) score (OR = 1.06; 95%CI: 1.02,1.12), and in men versus women (OR = 3.03; 95%CI: 1.06,8.65). For insulin, reporting non-adherence was more likely (OR = 1.02; 95%CI: 1.00,1.04) with each point increase in the PAID. DISCUSSION: Despite similar overall rates of reported non-adherence to insulin and non-insulin medications, factors associated with reported non-adherence to each medication type differed. These findings may help tailor approaches to supporting adherence in patients using different types of diabetes medications.

Alternative Dietary Patterns for Americans: Low-Carbohydrate Diets.

The decades-long dietary experiment embodied in the Dietary Guidelines for Americans (DGA) focused on limiting fat, especially saturated fat, and higher carbohydrate intake has coincided with rapidly escalating epidemics of obesity and type 2 diabetes (T2D) that are contributing to the progression of cardiovascular disease (CVD) and other diet-related chronic diseases. Moreover, the lack of flexibility in the DGA as it pertains to low carbohydrate approaches does not align with the contemporary trend toward precision nutrition. We argue that personalizing the level of dietary carbohydrate should be a high priority based on evidence that Americans have a wide spectrum of metabolic variability in their tolerance to high carbohydrate loads. Obesity, metabolic syndrome, and T2D are conditions strongly associated with insulin resistance, a condition exacerbated by increased dietary carbohydrate and improved by restricting carbohydrate. Low-carbohydrate diets are grounded across the time-span of human evolution, have well-established biochemical principles, and are now supported by multiple clinical trials in humans that demonstrate consistent improvements in multiple established risk factors associated with insulin resistance and cardiovascular disease. The American Diabetes Association (ADA) recently recognized a low carbohydrate eating pattern as an effective approach for patients with diabetes. Despite this evidence base, low-carbohydrate diets are not reflected in the DGA. As the DGA Dietary Patterns have not been demonstrated to be universally effective in addressing the needs of many Americans and recognizing the lack of widely available treatments for obesity, metabolic syndrome, and T2D that are safe, effective, and sustainable, the argument for an alternative, low-carbohydrate Dietary Pattern is all the more compelling.

The carbohydrate-insulin model: a physiological perspective on the obesity pandemic.

According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body-resulting from the hormonal responses to a high-glycemic-load diet-drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.

Heterogeneity of Treatment Effects Among Patients With Type 2 Diabetes and Elevated Body Mass Index in a Study Comparing Group Medical Visits Focused on Weight Management and Medication Intensification.

BACKGROUND: Illuminating heterogeneity of treatment effect (HTE) within trials is important for identifying target populations for implementation. OBJECTIVE: The aim of this study was to examine HTE in a trial of group medical visits (GMVs) for patients with type 2 diabetes and elevated body mass index. RESEARCH DESIGN AND MEASURES: Participants (n=263) were randomized to GMV-based medication management plus low carbohydrate diet-focused weight management (WM/GMV; n=127) or GMV-based medication management alone (GMV; n=136) for diabetes control. We used QUalitative INteraction Trees, a tree-based clustering method, to identify subgroups with greater improvement in hemoglobin A1c (HbA1c) and weight from either WM/GMV or GMV. Subgroup predictors included 32 baseline demographic, clinical, and psychosocial factors. Internal validation was conducted to estimate bias in the range of mean outcome differences between arms. RESULTS: QUalitative INteraction Trees analyses indicated that for patients who had not previously attempted weight loss, WM/GMV resulted in better glycemic control than GMV (mean difference in HbA1c improvement=1.48%). For patients who had previously attempted weight loss and had lower cholesterol and blood urea nitrogen, GMV was better than WM/GMV (mean difference in HbA1c improvement=1.51%). No treatment-subgroup effects were identified for weight. Internal validation resulted in moderate corrections in mean HbA1c differences between arms; however, differences remained in the clinically significant range. CONCLUSION: This work represents a novel step toward targeting care approaches for patients to maximize benefit based on individual patient characteristics.