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The black solid circle indicates the mean, the left and right borders of the box mark the first and third quartiles, the black vertical line indicates the median, the error bars indicate the 5th and 95th percentiles, and the hollow circles indicate the individuals whose values were outside the 5th or 95th percentiles.

The No. Statistical analyses include data from all individuals randomized described in the Statistical Analysis section. A, Three-way interaction term among diet, genotype, and the month time point was not statistically ificant beta coefficient, 1. As described in Stanton et al, 10 of all the possible combinations of variance in 3 single-nucleotide polymorphism multilocus genotype patterns, some were considered consistent with the low-fat genotype pattern, some with the low-carbohydrate genotype pattern, and some with neither of these 2 genotype patterns.

By de, as described in the initial National Institutes of Health grant application, those individuals with neither of the main 2 genotype patterns were not included in the main analyses. There were 39 participants who had compromised or missing DNA. Insulin is the blood concentration of insulin 30 minutes after consuming 75 g of glucose as part of a standard oral glucose tolerance test.

Insulin was treated as a continuous variable in the statistical model. Tertiles were used in this Figure for ease of presentation. The mean for the lowest tertile was Additional rationale for the 3-SNP multilocus genotype as written at the time of 13 the original grant submission, in Anthropometric and metabolic variables at all four time points. Baseline characteristics of the 6 subgroups of Diet X Genotype pattern.

Mean weight for 6 Diet X Genotype subgroups at four time points: Baseline, 3- 6- 32 and months. Mean weight for 6 Diet X Ins Tertile subgroups at four time points: Baseline, 3- 35 6- and months. Question What is the effect of a healthy low-fat HLF diet vs a healthy low-carbohydrate HLC diet on weight change at 12 months and are these effects related to genotype pattern or insulin secretion? Meaning There was no ificant difference in month weight loss between the HLF and HLC diets, and neither genotype pattern nor baseline insulin secretion was associated with the dietary effects on weight loss.

Importance Dietary modification remains key to successful weight loss. Yet, no one dietary strategy is consistently Adult singles dating in Atkins to others for the general population. research suggests genotype or insulin-glucose dynamics may modify the effects of diets. Objective To determine the effect of a healthy low-fat HLF diet vs a healthy low-carbohydrate HLC diet on weight change and if genotype pattern or insulin secretion are related to the dietary effects on weight loss.

The trial enrollment was from January 29,through April 14, ; the date of final follow-up was May 16, The study also tested whether 3 single-nucleotide polymorphism multilocus genotype responsiveness patterns or insulin secretion INS; blood concentration of insulin 30 minutes after a glucose challenge were associated with weight loss. The sessions focused on ways to achieve the lowest fat or carbohydrate intake that could be maintained long-term and emphasized diet quality. Main Outcomes and Measures Primary outcome was month weight change and determination of whether there were ificant interactions among diet type and genotype pattern, diet and insulin secretion, and diet and weight loss.

There were 18 adverse events or serious adverse events that were evenly distributed across the 2 diet groups. Conclusions and Relevance In this month weight loss diet study, there was no ificant difference in weight change between Adult singles dating in Atkins healthy low-fat diet vs a healthy low-carbohydrate diet, and neither genotype pattern nor baseline insulin secretion was associated with the dietary effects on weight loss.

In the context of these 2 common weight loss diet approaches, neither of the 2 hypothesized predisposing factors was helpful in identifying which diet was better for whom. Trial Registration clinicaltrials. Quiz Ref ID Obesity is a 21st-century major public health challenge.

The substantial variability of weight loss response suggests some strategies may work better for some individuals than others, and that no one diet should be recommended universally. Some studies have reported that genotype variation could predispose individuals to differential weight loss that varies by diet type.

In a preliminary retrospective study, a 3-fold difference was observed in month weight loss for initially overweight women who were determined to have been appropriately matched mean weight loss of 6 kg vs mismatched mean weight loss of 2 kg to a low-fat or low-carbohydrate diet based on multilocus genotype patterns with single-nucleotide polymorphisms SNPs from 3 genes PPARGADRB2and FABP2 relevant to fat and carbohydrate metabolism a putative low-fat—responsive genotype and a low-carbohydrate—responsive genotype.

The participants with the low-fat—responsive genotype were observed to lose more weight when ased to a low-fat diet than those ased to a low-carbohydrate diet, and vice versa for those with the low-carbohydrate—responsive genotype.

Quiz Ref ID Similarly, several studies 11 - 14 have reported that baseline insulin dynamics may explain differential weight loss success obtained via a low-fat diet vs a low-carbohydrate diet. For example, individuals with greater insulin resistance may have better success with low-carbohydrate diets due to the decreased demand on insulin to clear a lower amount of dietary carbohydrate delivered to the circulation. However, these studies were limited by relatively small sample sizes or post hoc analyses of the. The primary objective of the Diet Intervention Examining The Factors Interacting with Treatment Success DIETFITS study was to test whether 1 a set of 3 SNP genotype patterns or 2 baseline differences in insulin secretion the blood insulin concentration at 30 minutes after a glucose challenge; INS1213 or both, predisposed individuals to differential success in month weight change while on a low-fat diet vs a low-carbohydrate diet.

The Stanford University human subjects committee approved the study. All study participants provided written informed consent. This single-site, parallel-group, weight loss diet trial randomized individuals to a healthy low-fat diet or a healthy low-carbohydrate diet for 12 months. Participant enrollment began on January 29,and continued through April 14, The date of final follow-up was May 16, Interventions consisted primarily of class-based instruction.

Five waves of recruitment cohorts had staggered start dates between March and March The primary outcome was month weight change. Secondary outcomes included anthropometric measures, plasma lipid levels, insulin and glucose levels, and blood pressure levels. The protocol update and statistical analysis plan are included in Supplement 1 and the full study protocol was published ly 10 the protocol included details regarding blood sampling, storage, and specific laboratory assays.

We aimed to recruit adults from the Stanford and San Francisco Bay areas of California using media advertisements and lists from recruitment for nutrition studies conducted by our laboratory group. We considered men and premenopausal women aged 18 to 50 years with a body mass index calculated as weight in kilograms divided by height in meters squared of 28 to The major criteria for exclusion were having uncontrolled hypertension or metabolic disease; diabetes; cancer; heart, renal, or liver disease; and being pregnant or lactating.

Individuals were excluded if taking hypoglycemic, lipid-lowering, antihypertensive, psychiatric, or other medications known to affect body weight or energy expenditure. Any medication type not noted was allowed if the individual had been stable while taking such medication for at least 3 months prior to Adult singles dating in Atkins data collection.

Randomization to a healthy low-fat diet or a healthy low-carbohydrate diet was performed using an allocation sequence determined by computerized random- generation Blockrand in R version 3. Participants did not learn of their diet group asment until they completed all baseline measures and attended their first intervention class Figure 1. To test for both primary hypotheses, the study was changed to a simple parallel group de with testing for 2 interactions described in further detail in eAppendix 1 in Supplement 2.

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The protocol included a 1-month run-in period during which participants were instructed to maintain their habitual diet, physical activity level, and body weight. The intervention involved 22 instructional sessions held over 12 months in diet-specific groups of approximately 17 participants per class. Sessions were held weekly for 8 weeks, then every 2 weeks for 2 months, then every 3 weeks until the sixth month, and monthly thereafter. Classes were led by 5 registered dietitian health educators who each taught 1 healthy low-fat class and 1 healthy low-carbohydrate class per cohort.

Dietitians were blinded to all laboratory measures and genotype. The dietary interventions were described ly. Higher priorities for reduction were given to specific foods and food groups that derived their energy content primarily from fats or carbohydrates. For example, the reduction of edible oils, fatty meats, whole-fat dairy, and nuts was prioritized for the healthy low-fat group, whereas the reduction of cereals, grains, rice, starchy vegetables, and legumes was prioritized for the healthy low-carbohydrate group.

No explicit instructions for energy kilocalories restriction were given. Both diet groups were instructed to 1 maximize vegetable intake; 2 minimize intake of added sugars, refined flours, and trans fats; and 3 focus on whole foods that were minimally processed, nutrient dense, and prepared at home whenever possible.

Other components of the emphasis on high-quality food for both diet groups are described elsewhere. Participants were encouraged to follow current physical activity recommendations.

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Behavioral modification strategies included empirically supported principles of self-regulatory behavior change eg, goal setting, self-efficacy building, supportive environments, and relapse prevention based on social cognitive theory and the transtheoretical model. All data were collected at baseline and at months 3, 6, and 12 for all cohorts unless noted otherwise.

Staff who measured outcomes were blinded to diet asment, genotype pattern, INS, and diet asment. Dietary intake at each time point was assessed using 3 unannounced hour multiple-pass recall interviews 2 on weekdays and 1 on a weekend day. Weight was measured by digital scale at the Stanford Clinical Translational Research Unit and month weight change was the primary outcome. Genotype pattern and insulin secretion were assessed for interaction testing. Additional details appear in eAppendix 2 in Supplement 2.

The 3 SNP multilocus genotype patterns have been explored ly. The multilocus genotypes were grouped into those predicted to be more sensitive to fat low-fat genotype; patternsmore sensitive to carbohydrates low-carbohydrate genotype; patternsor sensitive to neither genotype pattern Additional details are available in eAppendix 3 in Supplement 2.

Before randomization and at months 6 and 12, each participant completed an oral glucose tolerance test of 75 g. This included measurement of insulin concentration 30 minutes after glucose consumption ie, INS, which is a proxy measure of insulin secretion. After the study was initiated, reports were published 12132324 indicating INS was a successful predictor of weight loss in the context of low-carbohydrate diets or similar diets. Adult singles dating in Atkins to examining any data, we modified the primary hypothesis of our study and tested baseline INS rather than a measure of insulin sensitivity as the putative effect modifier.

No other glucose or insulin variables were tested for effect modification.

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A set of related secondary outcomes was assessed. Concentrations of plasma lipids, glucose, and insulin were measured in fasting samples, waist circumference was assessed by measuring tape, blood pressure was measured via automated device, and all of these were assessed using standard assessment techniques. Body composition was assessed by dual-energy x-ray absorptiometry and both respiratory exchange ratio bounded by 0.

Adequate funding became available for dual-energy x-ray absorptiometry, respiratory exchange ratio, and resting energy expenditure only after cohort 1 was enrolled. This calculation was based on simulations, and assumed a 2-sided Wald test conducted at the. These power calculations were performed a priori for the originally planned sample size of As described in greater detail in eAppendix 1 in Supplement 2after initially being funded by the National Institutes of Health and the National Institute of Diabetes and Digestive and Kidney Diseases inadditional funding was received to augment the trial, which involved, among other modifications, increasing the sample size from toand adding INS as a second variable for interaction testing.

The main hypotheses addressed month weight change by diet, diet and genotype, and diet and baseline INS All hypotheses were addressed using generalized, linear mixed-effects models. This means that all participants who were randomized and had baseline information were included in the analysis and analyzed according to original treatment asment, regardless of adherence or loss to follow-up Figure 1.

For the hypothesis about the effect of diet group on month weight change, a linear mixed-effects model for weight that ed for missing data under flexible assumptions regarding missingness was used with fixed effects for diet, time baseline, 3, 6, and 12 monthsand their interaction, along with a random effect for participant. For the hypotheses involving diet and genotype or diet and baseline INSan additional fixed effect was added for Adult singles dating in Atkins or baseline INSalong with all 2- and 3-way interactions model appears in eAppendix 4 in Supplement 2.

The validity of such an analysis relies on the assumption that the missing outcome data measured at follow-up are unrelated to unobserved values of weight conditional on observed variables such as treatment asment and baseline and intermittent values of weight. The hypothesis about diet was tested using a Wald test for the 2-way interaction between the month time point and diet. The hypothesis about genotype or baseline INS was tested using a Wald test for the 3-way interaction between the month time point, diet, and genotype or baseline INS Genotype was defined as matched for those participants with a 3-SNP combination suggesting success on a low-carbohydrate diet who were randomized to the low-carbohydrate diet, or for those participants with a 3-SNP combination suggesting success on a low-fat diet who were randomized to the low-fat diet.

Genotype was otherwise defined as mismatched and is described in eAppendices 2 and 3 in Supplement 2. There were individuals who were not classified as having either the low-fat genotype pattern or a low-carbohydrate genotype Adult singles dating in Atkins individuals with other 3-SNP patterns and 39 with missing or compromised genotyping data who were excluded from the genotype analysis for the first hypothesis as originally planned. The INS variable was analyzed as a continuous variable, but is presented as tertiles for ease of presentation in parallel to the presentation of genotype pattern data.

The cutoffs for the tertiles were determined using the baseline insulin concentrations of all participants. A Satterthwaite approximation for denominator degrees of freedom was used in all Wald tests.

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Formal hypothesis testing was performed only for the 2 primary hypotheses. All other P values that were generated were purely descriptive in nature and correspond to secondary and exploratory analyses. Statistical analyses were performed using R version 3. Specifically, the lme4 30 package was used for mixed-effects models and the lmerTest 29 package was used for hypothesis tests in the mixed-effects models. The flow of the participants through the trial appears in Figure 1.

Baseline characteristics by diet group appear in Table 1. Among participants in the healthy low-fat diet group, Of 22 ased intervention instruction sessions for the full study sample, the mean of sessions attended was Participant ratings for health educator enthusiasm and knowledge of material was high and similar between diet groups. The mean ratings were 4. At baseline, there were no ificant between-group differences for any nutrients examined.

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The test for the interaction among diet, genotype pattern, and the month time point was not statistically ificant. The interpretation of the beta coefficient for the 3-way interaction beta coefficient, 1.

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This indicates that there was no ificant difference in weight change among participants matched vs mismatched to their diet asment based on their 3-SNP genotype pattern. In analyses restricted to participants of European descent only, no ificant interaction was observed by genotype pattern the 3-way interaction for the main diet, genotype, and time yielded a beta coefficient of 2.

Similarly, the test for interaction among diet, baseline insulin secretion INSand the month time point was not statistically ificant. The interpretation of the beta coefficient for the 3-way interaction beta coefficient, 0.

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