Genetic Predisposition to Weight Loss and Regain With Lifestyle Intervention: Analyses From the Diabetes Prevention Program and the Look AHEAD Randomized Controlled Trials

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control

Background

Type 2 Diabetes (T2D) is a complex condition marked by insulin resistance and beta-cell dysfunction. Traditional dietary interventions, such as low-calorie or low-carbohydrate diets, typically overlook individual variability in postprandial glycemic responses (PPGRs), which can lead to suboptimal management of the disease. Recent advancements suggest that personalized nutrition, tailored to individual metabolic profiles, may enhance the effectiveness of T2D management.

Objective

This study aims to present the development and application of a Digital Twin (DT) technology-a machine learning (ML)-powered platform designed to predict and modulate PPGRs in T2D patients. By integrating continuous glucose monitoring (CGM), dietary data, and other physiological inputs, the DT provides individualized dietary recommendations to improve insulin sensitivity, reduce hyperinsulinemia, and support the remission of T2D.

Methods

We developed a sophisticated DT platform that synthesizes real-time data from CGM, dietary logs, and other biometric inputs to create personalized metabolic models for T2D patients. The intervention is delivered via a mobile application, which dynamically adjusts dietary recommendations based on predicted PPGRs. This methodology is validated through a randomized controlled trial (RCT) assessing its impact on various metabolic markers, including HbA1c, metabolic-associated fatty liver disease (MAFLD), blood pressure, body weight, ASCVD risk, albuminuria, and diabetic retinopathy.

Results

Preliminary data from the ongoing RCT and real-world study demonstrate the DT's capacity to generate significant improvements in glycemic control and metabolic health. The DT-driven personalized nutrition plan has been associated with reductions in HbA1c, enhanced beta-cell function, and normalization of hyperinsulinemia, supporting sustained T2D remission. Additionally, the DT's predictions have contributed to improvements in MAFLD markers, blood pressure, and cardiovascular risk factors, highlighting its potential as a comprehensive management tool.

Conclusion

The DT technology represents a novel and scalable approach to personalized nutrition in T2D management. By addressing individual variability in PPGRs, this method offers a promising alternative to conventional dietary interventions, with the potential to improve long-term outcomes and reduce the global burden of T2D.

Evaluating physical activities in clinical diabetes: lifestyle scores hypothesis

BACKGROUND

The concept of lifestyle-based risk scores is known but not evaluated in most rural communities of low- to mid-income countries. This study investigated the correlation of lifestyle scores with health indices.

METHODS

This was a descriptive cross-sectional investigation. A total of 203 participants (141 females and 62 males), 18-90 years, had anthropometric assessments and lifestyle scores determined from a 12-item framework. Data analysis included average age in different health conditions, lifestyle scores in age groups, and correlations with age.

RESULTS

Average age of healthy subpopulation was 39 years while diabetes, hypertension, and obesity subpopulations were 58, 64, and 56 years, respectively. The percentage of participants whose activities of daily living (ADL) were unaffected by ill-health decreased with age (P < 0.0001), and lifestyle scores also decreased with age (P < 0.01) and negatively correlated with physical activities.

CONCLUSION

This report contributes to diabetes cardiovascular complications management. Sedentary ADL factors need integration in healthy lifestyle education especially among the elderly.

Impact of baseline adipose tissue characteristics on change in adipose tissue volume during a low calorie diet in people with obesity-results from the LION study

BACKGROUND/OBJECTIVES

Weight loss outcomes vary individually. Magnetic resonance imaging (MRI)-based evaluation of adipose tissue (AT) might help to identify AT characteristics that predict AT loss. This study aimed to assess the impact of an 8-week low-calorie diet (LCD) on different AT depots and to identify predictors of short-term AT loss using MRI in adults with obesity.

METHODS

Eighty-one adults with obesity (mean BMI 34.08 ± 2.75 kg/m², mean age 46.3 ± 10.97 years, 49 females) prospectively underwent baseline MRI (liver dome to femoral head) and anthropometric measurements (BMI, waist-to-hip-ratio, body fat), followed by a post-LCD-examination. Visceral and subcutaneous AT (VAT and SAT) volumes and AT fat fraction were extracted from the MRI data. Apparent lipid volumes based on MRI were calculated as approximation for the lipid contained in the AT. SAT and VAT volumes were subdivided into equidistant thirds along the craniocaudal axis and normalized by length of the segmentation. T-tests compared baseline and follow-up measurements and sex differences. Effect sizes on subdivided AT volumes were compared. Spearman Rank correlation explored associations between baseline parameters and AT loss. Multiple regression analysis identified baseline predictors for AT loss.

RESULTS

Following the LCD, participants exhibited significant weight loss (11.61 ± 3.07 kg, p < 0.01) and reductions in all MRI-based AT parameters (p < 0.01). Absolute SAT loss exceeded VAT loss, while relative apparent lipid loss was higher in VAT (both p < 0.01). The lower abdominopelvic third showed the most significant SAT and VAT reduction. The predictor of most AT and apparent lipid losses was the normalized baseline SAT volume in the lower abdominopelvic third, with smaller volumes favoring greater AT loss (p < 0.01 for SAT and VAT loss and SAT apparent lipid volume loss).

CONCLUSIONS

The LCD primarily reduces lower abdominopelvic SAT and VAT. Furthermore, lower abdominopelvic SAT volume was detected as a potential predictor for short-term AT loss in persons with obesity.

The metabolic consequences of 'yo-yo' dieting are markedly influenced by genetic diversity

BACKGROUND

Weight loss can improve the metabolic complications of obesity. However, it is unclear whether insulin resistance persists despite weight loss and whether any protective benefits are preserved following weight regain (weight cycling). The impact of genetic background on weight cycling is undocumented. We aimed to investigate the effects of weight loss and weight cycling on metabolic outcomes and sought to clarify the role of genetics in this relationship.

METHOD

Both C57BL/6 J and genetically heterogeneous Diversity Outbred Australia (DOz) mice were alternately fed high fat Western-style diet (WD) and a chow diet at 8-week intervals. Metabolic measures including body composition, glucose tolerance, pancreatic beta cell activity, liver lipid levels and adipose tissue insulin sensitivity were determined.

RESULTS

After diet switch from WD (8-week) to chow (8-week), C57BL/6 J mice displayed a rapid normalisation of body weight, adiposity, hyperinsulinemia, liver lipid levels and glucose uptake into adipose tissue comparable to chow-fed controls. In response to the same dietary intervention, genetically diverse DOz mice conversely maintained significantly higher fat mass and insulin levels compared to chow-fed controls and exhibited much more profound interindividual variability than C57BL/6 J mice. Weight cycled (WC) animals were re-exposed to WD (8-week) and compared to age-matched controls fed 8-week WD for the first time (LOb). In C57BL/6 J but not DOz mice, WC animals had significantly higher blood insulin levels than LOb controls. All WC animals exhibited significantly greater beta cell activity than LOb controls despite similar fat mass, glucose tolerance, liver lipid levels and insulin-stimulated glucose uptake in adipose tissue.

CONCLUSION

Following weight loss, metabolic outcomes return to baseline in C57BL/6 J mice with obesity. However, genetic diversity significantly impacts this response. A period of weight loss does not provide lasting benefits after weight regain, and weight cycling is detrimental and associated with hyperinsulinemia and elevated basal insulin secretion.

Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

Impact of polygenic score for BMI on weight loss effectiveness and genome-wide association analysis

BACKGROUND

While environmental factors play an important role in weight loss effectiveness, genetics may also influence its success. We examined whether a genome-wide polygenic score for BMI was associated with weight loss effectiveness and aimed to identify common genetic variants associated with weight loss.

METHODS

Participants in the ONTIME study (n = 1210) followed a uniform, multimodal behavioral weight-loss intervention. We first tested associations between a genome-wide polygenic score for higher BMI and weight loss effectiveness (total weight loss, rate of weight loss, and attrition). We then conducted a genome-wide association study (GWAS) for weight loss in the ONTIME study and performed the largest weight loss meta-analysis with earlier studies (n = 3056). Lastly, we ran exploratory GWAS in the ONTIME study for other weight loss outcomes and related factors.

RESULTS

We found that each standard deviation increment in the polygenic score was associated with a decrease in the rate of weight loss (Beta (95% CI) = -0.04 kg per week (-0.06, -0.01); P = 3.7 × 10-03) and with higher attrition after adjusting by treatment duration. No associations reached genome-wide significance in meta-analysis with previous GWAS studies for weight loss. However, associations in the ONTIME study showed effects consistent with published studies for rs545936 (MIR486/NKX6.3/ANK1), a previously noted weight loss locus. In the meta-analysis, each copy of the minor A allele was associated with 0.12 (0.03) kg/m2 higher BMI at week five of treatment (P = 3.9 × 10-06). In the ONTIME study, we also identified two genome-wide significant (P < 5×10-08) loci for the rate of weight loss near genes implicated in lipolysis, body weight, and metabolic regulation: rs146905606 near NFIP1/SPRY4/FGF1; and rs151313458 near LSAMP.

CONCLUSION

Our findings are expected to help in developing personalized weight loss approaches based on genetics.

CLINICAL TRIAL REGISTRATION

Obesity, Nutrigenetics, Timing, and Mediterranean (ONTIME; clinicaltrials.gov: NCT02829619) study.

Genetics, Nutrition, and Health: A New Frontier in Disease Prevention

The field of nutrition research has traditionally focused on the effects of macronutrients and micronutrients on the body. However, it has become evident that individuals have unique genetic makeups that influence their response to food. Nutritional genomics, which includes nutrigenetics and nutrigenomics, explores the interaction between an individual's genetic makeup, diet, and health outcomes. Nutrigenetics studies the impact of genetic variation on an individual's response to dietary nutrients, while nutrigenomics investigates how dietary components affect gene regulation and expression. These disciplines seek to understand the impact of diet on the genome, transcriptome, proteome, and metabolome. It provides insights into the mechanisms underlying the effect of diet on gene expression. Nutrients can cause the modification of genetic expression through epigenetic changes, such as DNA methylation and histone modifications. The aim of nutrigenomics is to create personalized diets based on the unique metabolic profile of an individual, gut microbiome, and genetic makeup to prevent diseases and promote health. Nutrigenomics has the potential to revolutionize the field of nutrition by combining the practicality of personalized nutrition with knowledge of genetic factors underlying health and disease. Thus, nutrigenomics offers a promising approach to improving health outcomes (in terms of disease prevention) through personalized nutrition strategies based on an individual's genetic and metabolic characteristics.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

C-Reactive Protein Levels Correlate with Measures of Dysglycemia and Gut Microbiome Profiles

C-reactive protein (CRP) is a commonly used marker of low-grade inflammation as well as a marker of acute infection. CRP levels are elevated in those with diabetes and increased CRP concentrations are a risk factor for developing type 2 diabetes. Gut microbiome effects on metabolism and immune responses can impact chronic inflammation, including affecting CRP levels, that in turn can lead to the development and maintenance of dysglycemia. Using a high-sensitivity C-reactive protein (hsCRP) assay capable of detecting subtle changes in C-reactive protein, we show that higher hsCRP levels specifically correlate with worsening glycemia, reduced microbial richness and evenness, and with a reduction in the Firmicutes/Bacteroidota ratio. These data demonstrate a pivotal role for CRP not only in the context of worsening glycemia and changes to the gut microbiota, but also highlight CRP as a potential target for mitigating type 2 diabetes progression or as a therapeutic target that could be manipulated through the microbiome. Understanding these processes will provide insights into the etiology of type 2 diabetes in addition to opening doors leading to possible novel diagnostic strategies and therapeutics.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

The Influence of Single Nucleotide Polymorphisms On Body Weight Trajectory After Bariatric Surgery: A Systematic Review

PURPOSE OF REVIEW

To conduct a systematic review to summarize the results of studies on this subject and to identify whether single nucleotide polymorphisms (SNPs) are good prognostic markers for body weight trajectory after bariatric surgery.

RECENT FINDINGS

A considerable number of events can influence the body weight trajectory after bariatric surgery, and in the post-genomic era, genetic factors have been explored. This study is registered with PROSPERO (CRD42021240903). SNPs positively associated with poor weight loss after bariatric surgery were rs17702901, rs9939609, rs1360780, rs1126535, rs1137101, rs17782313, rs490683, and rs659366. Alternatively, SNPs rs2229616, rs5282087, rs490683, rs9819506, rs4771122, rs9939609, rs4846567, rs9930506, rs3813929, rs738409, rs696217, rs660339, rs659366, rs6265, rs1801260, and rs2419621 predicted a higher weight loss after bariatric surgery. Six studies performed with a genetic risk score (GRS) model presented significant associations between GRS and outcomes following bariatric surgery. This systematic review shows that, different SNPs and genetic models could be good predictors for body weight trajectory after bariatric surgery. Based on the results of the selected studies for this Systematic Review is possible to select SNPs and metabolic pathways of interest for the GRS construction to predict the outcome of bariatric surgery to be applied in future studies.

Differential mechanisms affecting weight loss and weight loss maintenance

In most lifestyle, pharmacological and surgical interventions, weight loss occurs over an approximately 6- to 9-month period and is followed by a weight plateau and then weight regain. Overall, only about 15% of individuals can sustain a 10% or greater non-surgical, non-pharmacological, weight loss. A key question is the degree to which the genotypes, phenotypes and environmental correlates of success in weight loss and weight loss maintenance are continuous or dichotomous. This Perspective is a comparison of the interactions of weight loss and maintenance with genetic, behavioural, physiological and environmental homeostatic systems and a discussion of the implications of these findings for research in, and treatment of, obesity. Data suggest that weight loss and weight loss maintenance are physiologically and psychologically different in many ways. Consequently, individuals may require different interventions designed for temporarily sustaining a negative energy balance during weight loss versus permanently maintaining energy balance after weight loss.

Engineered allele substitution at PPARGC1A rs8192678 alters human white adipocyte differentiation, lipogenesis, and PGC-1α content and turnover

AIMS/HYPOTHESIS

PPARGC1A encodes peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α), a central regulator of energy metabolism and mitochondrial function. A common polymorphism in PPARGC1A (rs8192678, C/T, Gly482Ser) has been associated with obesity and related metabolic disorders, but no published functional studies have investigated direct allele-specific effects in adipocyte biology. We examined whether rs8192678 is a causal variant and reveal its biological function in human white adipose cells.

METHODS

We used CRISPR-Cas9 genome editing to perform an allelic switch (C-to-T or T-to-C) at rs8192678 in an isogenic human pre-adipocyte white adipose tissue (hWAs) cell line. Allele-edited single-cell clones were expanded and screened to obtain homozygous T/T (Ser482Ser), C/C (Gly482Gly) and heterozygous C/T (Gly482Ser) isogenic cell populations, followed by functional studies of the allele-dependent effects on white adipocyte differentiation and mitochondrial function.

RESULTS

After differentiation, the C/C adipocytes were visibly less BODIPY-positive than T/T and C/T adipocytes, and had significantly lower triacylglycerol content. The C allele presented a dose-dependent lowering effect on lipogenesis, as well as lower expression of genes critical for adipogenesis, lipid catabolism, lipogenesis and lipolysis. Moreover, C/C adipocytes had decreased oxygen consumption rate (OCR) at basal and maximal respiration, and lower ATP-linked OCR. We determined that these effects were a consequence of a C-allele-driven dysregulation of PGC-1α protein content, turnover rate and transcriptional coactivator activity.

CONCLUSIONS/INTERPRETATION

Our data show allele-specific causal effects of the rs8192678 variant on adipogenic differentiation. The C allele confers lower levels of PPARGC1A mRNA and PGC-1α protein, as well as disrupted dynamics of PGC-1α turnover and activity, with downstream effects on cellular differentiation and mitochondrial function. Our study provides the first experimentally deduced insights on the effects of rs8192678 on adipocyte phenotype.

Identification of a weight loss-associated causal eQTL in MTIF3 and the effects of MTIF3 deficiency on human adipocyte function

Genetic variation at the MTIF3 (Mitochondrial Translational Initiation Factor 3) locus has been robustly associated with obesity in humans, but the functional basis behind this association is not known. Here, we applied luciferase reporter assay to map potential functional variants in the haplotype block tagged by rs1885988 and used CRISPR-Cas9 to edit the potential functional variants to confirm the regulatory effects on MTIF3 expression. We further conducted functional studies on MTIF3-deficient differentiated human white adipocyte cell line (hWAs-iCas9), generated through inducible expression of CRISPR-Cas9 combined with delivery of synthetic MTIF3-targeting guide RNA. We demonstrate that rs67785913-centered DNA fragment (in LD with rs1885988, r² > 0.8) enhances transcription in a luciferase reporter assay, and CRISPR-Cas9-edited rs67785913 CTCT cells show significantly higher MTIF3 expression than rs67785913 CT cells. Perturbed MTIF3 expression led to reduced mitochondrial respiration and endogenous fatty acid oxidation, as well as altered expression of mitochondrial DNA-encoded genes and proteins, and disturbed mitochondrial OXPHOS complex assembly. Furthermore, after glucose restriction, the MTIF3 knockout cells retained more triglycerides than control cells. This study demonstrates an adipocyte function-specific role of MTIF3, which originates in the maintenance of mitochondrial function, providing potential explanations for why MTIF3 genetic variation at rs67785913 is associated with body corpulence and response to weight loss interventions.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The genetic architecture of changes in adiposity during adulthood

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 1.5 million primary-care health records in over 177,000 individuals in UK Biobank to study the genetic architecture of weight-change. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (a missense variant in APOE). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI, and higher in women than in men. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology driving quantitative trait values in adulthood.

MicroRNAs Associated with Incident Diabetes in the Diabetes Prevention Program

OBJECTIVE

MicroRNAs (miRs) are short (i.e., 18-26 nucleotide) regulatory elements of messenger RNA translation to amino acids. The purpose of this study was to assess whether miRs are predictive of incident T2D in the Diabetes Prevention Program (DPP) trial.

RESEARCH DESIGN AND METHODS

This was a secondary analysis (n = 1,000) of a subset of the DPP cohort that leveraged banked biospecimens to measure miRs. We used random survival forest and Lasso to identify the optimal miR predictors and cox proportional hazards to model time to T2D overall and within intervention arms.

RESULTS

We identified five miRs (miR-144, miR-186, miR-203a, miR-205, miR-206) that constituted the optimal predictors of incident T2D after adjustment for covariates (hazards ratio 2.81 (95% confidence interval (CI) 2.05, 3.87); p < 0.001). Predictive risk scores following cross-validation showed the HR for the highest quartile risk group compared to the lowest quartile risk group was 5.91 (95% CI (2.02, 17.3); p < 0.001). There was significant interaction between the intensive lifestyle (HR 3.60, 95% CI (2.50, 5.18); p < 0.001) and the metformin (HR 2.72; 95% CI (1.47, 5.00); p = 0.001) groups compared to placebo. Of the five miRs identified, one targets a gene with prior known associations with risk for T2D.

DISCUSSION

We identified five miRs that are optimal predictors of incident T2D in the DPP cohort. Future directions include validation of this finding in an independent sample in order to determine whether this risk score may have potential clinical utility for risk stratification of individuals with prediabetes, and functional analysis of the potential genes and pathways targeted by the miRs that were included in the risk score.

Physiology of the Weight-Reduced State and Its Impact on Weight Regain

Obesity is a chronic disease characterized by long duration, slow progression, and periods of remission and relapses. Despite the development of effective medical and surgical interventions and millions of people conducting tremendous personal efforts to manage their weight every year, recidivism remains a significant barrier to attaining long-term weight maintenance. This review aimed to explain the underlying physiology of the weight-reduced state including changes in energy balance, adipose tissue, genetic, environmental, and behavioral factors that may predispose individuals to weight regain following weight loss.

Understanding weight regain after a nutritional weight loss intervention: Systematic review and meta-analysis

BACKGROUND & AIMS

The purpose of this systematic review was to analyze the effects of lifestyle interventions on long-term weight maintenance of weight loss. In addition, we seek to address which period is most susceptible to weight regain; and what is the time required for following-up weight maintenance after the intervention.

METHODS

Articles published up to August 2020 were identified using the Medline (PubMed), Embase, Web of Science, CENTRAL and Scopus.

RESULTS

After the selection process, 27 clinical trials involving 7236 individuals were included. The results showed that around 36 weeks after the end of the intervention, weight variation reduces, and a sign of continuous weight gain begin to occur with some patients (n = 208,209) presenting even a completely regain of the lost weight before one year (∼40-48 weeks). However, some strategies used during the weight loss intervention and maintenance period may impact the amount and when the weight regain happens, like intervention type;, intervention duration;, presence of dietitian on the care team;, and maintenance period with counseling by a health professional at least once a month.

CONCLUSION

This systematic review and meta-analysis showed that lifestyle interventions remained effective in maintaining the mean weight (5% lower than baseline weight) after weight loss interventions were over. However, weight regain started 36 weeks after intervention conclusion. And, it turns out, some strategies used during the weight loss intervention and maintenance period may impact the amount and when the weight regain happens. Obesity complexity and chronicity should be considered, therefore constant and lifelong monitoring and support are important.

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.

Epidemiology of Antibiotic Use and Drivers of Cross-Border Procurement in a Mexican American Border Community

Background

The U.S.-Mexico Border is an area of opportunity for improved health care access; however, gaps remain as to how and where U.S. border residents, particularly those who are underinsured, obtain care. Antibiotics are one of the most common reported drivers of cross-border healthcare access and a medication of particular concern since indiscriminate or inappropriate use is associated with antimicrobial resistance. In addition, many studies assessing preferences for Mexican pharmaceuticals and healthcare in U.S. border residents were done prior to 2010 when many prescription medications, including antibiotics, were available over the counter in Mexico.

Methods

Data used in this study were collected during the baseline examination of an ongoing longitudinal cohort study in Starr Country, Texas, one of 14 counties on the Texas-Mexico border. Participants self-reported the name, date of use, and the source country of each antibiotic used in the past 12 months. Logistic regression was used to determine social, cultural, and clinical features associated with cross-border procurement of antibiotics.

Results

Over 10% of the study cohort reported using antibiotics in the past 30 days with over 60% of all rounds used in the past 12 months sourced from Mexico. A lack of health insurance and generation score, a measure of acculturation, were the strongest predictors of cross-border procurement of antibiotics.

Conclusions

Factors previously associated with cross-border acquisition of antibiotics are still present despite changes in 2010 to prescription drug regulations in Mexico. These results may be used to inform future public health initiatives to provide culturally sensitive education about responsible antibiotic stewardship and to address barriers to U.S. healthcare and pharmaceutical access in medically underserved, impoverished U.S.-Mexico border communities.

Low-frequency Coding Variants Associated With Body Mass Index Affect the Success of Bariatric Surgery

CONTEXT

A recent study identified 14 low-frequency coding variants associated with body mass index (BMI) in 718 734 individuals predominantly of European ancestry.

OBJECTIVE

We investigated the association of 2 genetic scores (GS) with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery.

METHODS

The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective GS based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study.

RESULTS

While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they affect BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery.

CONCLUSION

Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also affect the outcomes of bariatric surgery in patients with severe/morbid obesity.

Different Effects of Lifestyle Intervention in High- and Low-Risk Prediabetes: Results of the Randomized Controlled Prediabetes Lifestyle Intervention Study (PLIS)

Lifestyle intervention (LI) can prevent type 2 diabetes, but response to LI varies depending on risk subphenotypes. We tested whether individuals with prediabetes with low risk (LR) benefit from conventional LI and individuals with high risk (HR) benefit from an intensification of LI in a multicenter randomized controlled intervention over 12 months with 2 years' follow-up. A total of 1,105 individuals with prediabetes based on American Diabetes Association glucose criteria were stratified into an HR or LR phenotype based on previously described thresholds of insulin secretion, insulin sensitivity, and liver fat content. LR individuals were randomly assigned to conventional LI according to the Diabetes Prevention Program (DPP) protocol or control (1:1) and HR individuals to conventional or intensified LI with doubling of required exercise (1:1). A total of 908 (82%) participants completed the study. In HR individuals, the difference between conventional and intensified LI in postchallenge glucose change was -0.29 mmol/L [95% CI -0.54; -0.04], P = 0.025. Liver fat (-1.34 percentage points [95% CI -2.17; -0.50], P = 0.002) and cardiovascular risk (-1.82 percentage points [95% CI -3.13; -0.50], P = 0.007) underwent larger reductions with intensified than with conventional LI. During a follow-up of 3 years, intensified compared with conventional LI had a higher probability of normalizing glucose tolerance (P = 0.008). In conclusion, it is possible in HR individuals with prediabetes to improve glycemic and cardiometabolic outcomes by intensification of LI. Individualized, risk phenotype-based LI may be beneficial for the prevention of diabetes.

Lifestyle Genetics-Based Reports in the Treatment of Obesity

Obesity becomes a chronic disease due to the increasing number of mortality and morbidity cases around the world. In most regions, chronic illnesses, such as obesity, are important sources of morbidity and mortality. Due to a lack of effective strategies for prevention and management, the adverse effects of obesity and related diseases on health continue to be a serious problem. Relevant information was searched from Google Scholar, Scopus, and PubMed using such different terms as "Obesity", "Obesity Management", "Obesity AND Physical activity", "Obesity AND Genetics", "Obesity AND Diet", and "Obesity AND Nutrigenomics". Obesity is characterized by a complex interaction of hereditary and lifestyle factors, which includes food. Diet is an environmental element that plays an important and considerable role in the management of health and reduces the risk of obesity and its comorbidities. Changes in lifestyle patterns not only help burn extra calories but also prevent the development of obesity via its modulating effect on genetic factors. Different people respond differently to an obesogenic environment. The notion of nutrigenetics emerged as a result of various genetic variations that may explain this heterogeneity. Nutritional genomics, also known as nutrigenetics, is the study that investigates and analyses gene variations linked to varied responses to certain foods; moreover, it links this variation to diseases, such as obesity. As a result, tailored nutrition advice based on a person's genetic profile may improve the outcomes of a specific dietary strategy and offer a novel dietary strategy to improve life quality and preventing obesity. This study concluded that physical activity and dietary interventions play an effective role in the management of obesity. Moreover, understanding of the function of the most prominent obesity-related genes, as well as the interaction between nutrition and gene expression, will help researchers design personalized treatment strategies for humans.

Genetic risk for obesity and the effectiveness of the ChooseWell 365 workplace intervention to prevent weight gain and improve dietary choices

BACKGROUND

It is unknown whether behavioral interventions to improve diet are effective in people with a genetic predisposition to obesity.

OBJECTIVES

To examine associations between BMI genetic risk and changes in weight and workplace purchases by employees participating in a randomized controlled trial of an automated behavioral workplace intervention to promote healthy food choices.

METHODS

Participants were hospital employees enrolled in a 12-mo intervention followed by a 12-mo follow-up. Hospital cafeterias utilized a traffic-light labeling system (e.g., green = healthy, red = unhealthy) that was used to calculate a validated Healthy Purchasing Score (HPS; higher = healthier). A weighted genome-wide BMI genetic score was generated by summing BMI-increasing alleles.

RESULTS

The study included 397 adults of European ancestry (mean age, 44.9 y; 80.9% female). Participants in the highest genetic quartile (Q4) had a lower HPS and higher purchases of red-labeled items relative to participants in the lowest quartile (Q1) at baseline [Q4-Q1 Beta HPS, -4.66 (95% CI, -8.01 to -1.32); red-labeled items, 4.26% (95% CI, 1.45%-7.07%)] and at the 12-mo [HPS, -3.96 (95% CI, -7.5 to -0.41); red-labeled items, 3.20% (95% CI, 0.31%-6.09%)] and 24-mo [HPS, -3.70 (95% CI, -7.40 to 0.00); red-labeled items, 3.48% (95% CI, 0.54%-6.41%)] follow-up periods. In the intervention group, increases in HPS were similar in Q4 and Q1 at 12 mo (Q4-Q1 Beta, 1.04; 95% CI, -2.42 to 4.50). At the 24-mo follow-up, the change in BMI from baseline was similar between Q4 and Q1 (0.17 kg/m2; 95% CI, -0.55 to 0.89 kg/m2) in the intervention group, but higher in Q4 than Q1 (1.20 kg/m2; 95% CI, 0.26-2.13 kg/m2) in the control group. No interaction was evident between the treatment arm and genetic score for BMI or HPS.

CONCLUSIONS

Having a high BMI genetic risk was associated with greater increases in BMI and lower quality purchases over 2 y. The 12-mo behavioral intervention improved employees' food choices, regardless of the genetic burden, and may have attenuated weight gain conferred by having the genetic risk.

Genetics of Obesity: What We Have Learned Over Decades of Research

There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.

Strategies to Understand the Weight-Reduced State: Genetics and Brain Imaging

Most individuals with obesity or overweight have difficulty maintaining weight loss. The weight-reduced state induces changes in many physiological processes that appear to drive weight regain. Here, we review the use of cell biology, genetics, and imaging techniques that are being used to begin understanding why weight regain is the normal response to dieting. As with obesity itself, weight regain has both genetic and environmental drivers. Genetic drivers for "thinness" and "obesity" largely overlap, but there is evidence for specific genetic loci that are different for each of these weight states. There is only limited information regarding the genetics of weight regain. Currently, most genetic loci related to weight point to the central nervous system as the organ responsible for determining the weight set point. Neuroimaging tools have proved useful in studying the contribution of the central nervous system to the weight-reduced state in humans. Neuroimaging technologies fall into three broad categories: functional, connectivity, and structural neuroimaging. Connectivity and structural imaging techniques offer unique opportunities for testing mechanistic hypotheses about changes in brain function or tissue structure in the weight-reduced state.

Describing the Weight-Reduced State: Physiology, Behavior, and Interventions

Although many persons with obesity can lose weight by lifestyle (diet and physical activity) therapy, successful long-term weight loss is difficult to achieve, and most people who lose weight regain their lost weight over time. The neurohormonal, physiological, and behavioral factors that promote weight recidivism are unclear and complex. The National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop in June 2019, titled "The Physiology of the Weight-Reduced State," to explore the mechanisms and integrative physiology of adaptations in appetite, energy expenditure, and thermogenesis that occur in the weight-reduced state and that may oppose weight-loss maintenance. The proceedings from the first session of this workshop are presented here. Drs. Michael Rosenbaum, Kevin Hall, and Rudolph Leibel discussed the physiological factors that contribute to weight regain; Dr. Michael Lowe discussed the biobehavioral issues involved in weight-loss maintenance; Dr. John Jakicic discussed the influence of physical activity on long-term weight-loss maintenance; and Dr. Louis Aronne discussed the ability of drug therapy to maintain weight loss.

Physiology of the Weight-Reduced State: A Report from a National Institute of Diabetes and Digestive and Kidney Diseases Workshop

Preventing regain of lost weight is the most difficult challenge in the treatment of obesity. The National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop, "The Physiology of the Weight-Reduced State," on June 3 to 4, 2019, in order to explore the physiologic mechanisms of appetitive and metabolic adaptation that take place in the weight-reduced state and counter an individual's efforts to maintain reduced weight following weight loss.

Examining the effect of obesity-associated gene variants on breast cancer survivors in a randomized weight loss intervention

PURPOSE

Our study examined whether common variants of obesity-associated genes FTO, MC4R, BDNF, and CREB1 moderated the effects of a lifestyle intervention on weight change among breast cancer survivors.

METHODS

151 breast cancer survivors with a body mass index ≥ 25 kg/m² were randomly assigned to a 6-month weight loss intervention or usual care group. Genotyping of FTO rs9939609, MC4R rs6567160, BDNF rs11030104, CREB1 rs17203016 was performed. Linear mixed models were used including the main effects of genotype (assuming a dominant genetic model), treatment arm on weight and percent body fat changes, and genotype by treatment interaction variable. All statistical tests were evaluated against a Bonferroni-corrected alpha of 0.0125.

RESULTS

Women in the intervention group achieved significantly greater weight loss than the usual care group (5.9% vs 0.4%, p < 0.001), regardless of genotype. Changes in weight and percent body fat did not differ significantly between carriers of the FTO rs9939609, MC4R rs6567160, BDNF rs11030104, and CREB1 rs17203016 risk alleles compared to non-carriers (p-interaction > 0.0125 for each single-nucleotide polymorphisms).

CONCLUSIONS

Women who are genetically predisposed to obesity and recently diagnosed with breast cancer may achieve significant and clinically meaningful weight loss through healthy eating and exercise.

CLINICAL TRIAL REGISTRATION

NCT02863887 (Date of Registration: August 11, 2016); NCT02110641 (Date of Registration: April 10, 2014).

Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions-A Pooled Analysis

Knowledge of the association between single nucleotide polymorphisms (SNPs) and weight loss is limited. The aim was to analyse whether selected obesity-associated SNPs within the fat mass and obesity-associated (FTO), transmembrane protein 18 (TMEM18), melanocortin-4 receptor (MC4R), SEC16 homolog B (SEC16B), and brain-derived neurotrophic factor (BDNF) gene are associated with anthropometric changes during behavioural intervention for weight loss. genetic and anthropometric data from 576 individuals with overweight and obesity from four lifestyle interventions were obtained. A genetic predisposition score (GPS) was calculated. Our results show that study participants had a mean age of 48.2 ± 12.6 years and a mean baseline body mass index of 33.9 ± 6.4 kg/m². Mean weight reduction after 12 months was −7.7 ± 10.9 kg. After 12 months of intervention, the MC4R SNPs rs571312 and rs17782313 were significantly associated with a greater decrease in body weight and BMI (p = 0.012, p = 0.011, respectively). The investigated SNPs within the other four genetic loci showed no statistically significant association with changes in anthropometric parameters. The GPS showed no statistically significant association with weight reduction. In conclusion there was no consistent evidence for statistically significant associations of SNPs with anthropometric changes during a behavioural intervention. It seems that other factors play a more significant in weight management than the investigated SNPs.

Factors affecting weight loss variability in obesity

Current obesity treatment strategies include diet, exercise, bariatric surgery, and a limited but growing repertoire of medications. Individual weight loss in response to each of these strategies is highly variable. Here we review research into factors potentially contributing to inter-individual variability in response to treatments for obesity, with a focus on studies in humans. Well-recognized factors associated with weight loss capacity include diet adherence, physical activity, sex, age, and specific medications. However, following control for each of these, differences in weight loss appear to persist in response to behavioral, pharmacological and surgical interventions. Adaptation to energy deficit involves complex feedback mechanisms, and inter-individual differences likely to arise from a host of poorly defined genetic factors, as well as differential responses in neurohormonal mechanisms (including gastrointestinal peptides), metabolic efficiency and capacity of tissues, non-exercise activity thermogenesis, thermogenic response to food, and in gut microbiome. A better understanding of the factors involved in inter-individual variability in response to therapies will guide more personalized approaches to the treatment of obesity.

Long-Term Changes in Weight in Patients With Severe and Complicated Obesity After Completion of a Milk-Based Meal Replacement Programme

Introduction: Even with very significant short term weight loss with intensive dietary restriction, subsequent weight regain remains a challenge for most patients. We sought to assess long-term weight change in patients with obesity following completion of a 24-week milk-based meal replacement programme. Methods: We conducted a retrospective cohort study of bariatric patients who completed our milk-based meal replacement programme. This programme started with an 8-week weight loss phase, followed by weight stabilization (8 weeks) and weight maintenance (8 weeks) phases, after which patients were followed up in the bariatric outpatient clinics. A paired sample t-test was used to compare mean differences in weight at the start and the end of the programme and at follow-up. Linear regression was used to identify predictors of weight regain. Results: In total, 78 patients had long term follow-up data at a mean of 34.4 ± 19.8 months after the start of the milk diet and were included in this analysis. Mean body mass index at baseline was 50.5 ± 7.6 kg m^-2, 41 (52.6%) were female and the mean age was 51.6 ± 12.0 (range 18.0-71.5) years. Weight decreased from144 ± 26 kg at the start of the milk diet to 121.2 ± 24 kg at completion (P < 0.001), with a non-significant trend upwards in the 1st and 2nd years of follow-up to 129.0 ± 27.7 (P = 0.07 compared to nadir) and 123.4 ± 29.0kg (P = 0.17), respectively. Although regains in the 3rd and 4th follow-up years were substantial to 131.0 ± 22.3 (P < 0.001), and 139.8 ± 35.4 kg (P < 0.001), there was still a moderate net weight loss of 4.7 [9.5, 0.21] and 7.0 [13.9, 0.26] kg (both P = 0.04) between the start and the 3rd and 4th follow-up years, respectively. The amount of weight regain was inversely associated with weight loss at completion of the programme, age, and directly associated with the duration of follow up in months (β = 1.2 [0.46, 1.9] P = 0.002). Conclusion: In patients with severe obesity who completed a milk-based meal replacement programme and lost a large amount of weight, over 4 years of follow-up there was very substantial weight regain. Greater initial weight loss and older age were associated with less subsequent weight regain.

The impact of genetic polymorphisms on weight regain after successful weight loss

Obesity is associated with an increased risk of various diseases and mortality. Although nearly 50 % of adults have been reported trying to lose weight, the prevalence of obesity has increased. One factor that hinders weight loss-induced decrease in obesity prevalence is weight regain. Although behavioural, psychological and physiological factors associated with weight regain have been reviewed, the information regarding the relationship between weight regain and genetics has not been previously summarised. In this paper, we comprehensively review the association between genetic polymorphisms and weight regain in adults and children with obesity after weight loss. Based on this information, identification of genetic polymorphism in patients who undergo weight loss intervention might be used to estimate their risks of weight regain. Additionally, the genetic-based risk estimation may be used as a guide for physicians and dietitians to provide each of their patients with the most appropriate strategies for weight loss and weight maintenance.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Human postprandial responses to food and potential for precision nutrition

Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866.

Unexpected clues emerge about why diets fail

The physiology of weight regain still baffles scientists, but surprising insights have emerged.

Translation initiation in mammalian mitochondria- a prokaryotic perspective

ATP is generated in mitochondria of eukaryotic cells by oxidative phosphorylation (OXPHOS). The OXPHOS complex, which is crucial for cellular metabolism, comprises of both nuclear and mitochondrially encoded subunits. Also, the occurrence of several pathologies because of mutations in the mitochondrial translation apparatus indicates the importance of mitochondrial translation and its regulation. The mitochondrial translation apparatus is similar to its prokaryotic counterpart due to a common origin of evolution. However, mitochondrial translation has diverged from prokaryotic translation in many ways by reductive evolution. In this review, we focus on mammalian mitochondrial translation initiation, a highly regulated step of translation, and present a comparison with prokaryotic translation.

Precision behavioral medicine: Implications of genetic and genomic discoveries for behavioral weight loss treatment

This article reviews the concept of precision behavioral medicine and the progress toward applying genetics and genomics as tools to optimize weight management intervention. We discuss genetic, epigenetic, and genomic markers, as well as interactions between genetics and the environment as they relate to obesity and behavioral weight loss to date. Recommendations for the conditions under which genetics and genomics could be incorporated to support clinical decision-making in behavioral weight loss are outlined and illustrative scenarios of how this approach could improve clinical outcomes are provided. It is concluded that there is not yet sufficient evidence to leverage genetics or genomics to aid the treatment of obesity but the foundations are being laid. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Primary Prevention of ASCVD and T2DM in Patients at Metabolic Risk: An Endocrine Society* Clinical Practice Guideline

OBJECTIVE

To develop clinical practice guidelines for the primary prevention of atherosclerotic cardiovascular disease (ASCVD) and type 2 diabetes mellitus (T2DM) in individuals at metabolic risk for developing these conditions.

CONCLUSIONS

Health care providers should incorporate regular screening and identification of individuals at metabolic risk (at higher risk for ASCVD and T2DM) with measurement of blood pressure, waist circumference, fasting lipid profile, and blood glucose. Individuals identified at metabolic risk should undergo 10-year global risk assessment for ASCVD or coronary heart disease to determine targets of therapy for reduction of apolipoprotein B-containing lipoproteins. Hypertension should be treated to targets outlined in this guideline. Individuals with prediabetes should be tested at least annually for progression to diabetes and referred to intensive diet and physical activity behavioral counseling programs. For the primary prevention of ASCVD and T2DM, the Writing Committee recommends lifestyle management be the first priority. Behavioral programs should include a heart-healthy dietary pattern and sodium restriction, as well as an active lifestyle with daily walking, limited sedentary time, and a structured program of physical activity, if appropriate. Individuals with excess weight should aim for loss of ≥5% of initial body weight in the first year. Behavior changes should be supported by a comprehensive program led by trained interventionists and reinforced by primary care providers. Pharmacological and medical therapy can be used in addition to lifestyle modification when recommended goals are not achieved.

Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis

OBJECTIVE

To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.

DESIGN

Individual participant data meta-analysis.

DATA SOURCES

Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.

REVIEW METHODS

Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.

RESULTS

Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I²=7.1%, τ²=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I²=18.0%, τ²=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I²=58.8%, τ²=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I²=25.9%, τ²=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.

CONCLUSIONS

These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.

Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 × 10-8) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.

A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management

Various studies showed that a "one size fits all" dietary recommendation for weight management is questionable. For this reason, the focus increasingly falls on personalised nutrition. Although there is no precise and uniform definition of personalised nutrition, the inclusion of genetic variants for personalised dietary recommendations is more and more favoured, whereas scientific evidence for gene-based dietary recommendations is rather limited. The purpose of this article is to provide a science-based viewpoint on gene-based personalised nutrition and weight management. Most of the studies showed no clinical evidence for gene-based personalised nutrition. The Food4Me study, e.g., investigated four different groups of personalised dietary recommendations based on dietary guidelines, and physiological, clinical, or genetic parameters, and resulted in no difference in weight loss between the levels of personalisation. Furthermore, genetic direct-to-consumer (DTC) tests are widely spread by companies. Scientific organisations clearly point out that, to date, genetic DTC tests are without scientific evidence. To date, gene-based personalised nutrition is not yet applicable for the treatment of obesity. Nevertheless, personalised dietary recommendations on the genetic landscape of a person are an innovative and promising approach for the prevention and treatment of obesity. In the future, human intervention studies are necessary to prove the clinical evidence of gene-based dietary recommendations.

Genome-wide gene-based analyses of weight loss interventions identify a potential role for NKX6.3 in metabolism

Hundreds of genetic variants have been associated with Body Mass Index (BMI) through genome-wide association studies (GWAS) using observational cohorts. However, the genetic contribution to efficient weight loss in response to dietary intervention remains unknown. We perform a GWAS in two large low-caloric diet intervention cohorts of obese participants. Two loci close to NKX6.3/MIR486 and RBSG4 are identified in the Canadian discovery cohort (n = 1166) and replicated in the DiOGenes cohort (n = 789). Modulation of HGTX (NKX6.3 ortholog) levels in Drosophila melanogaster leads to significantly altered triglyceride levels. Additional tissue-specific experiments demonstrate an action through the oenocytes, fly hepatocyte-like cells that regulate lipid metabolism. Our results identify genetic variants associated with the efficacy of weight loss in obese subjects and identify a role for NKX6.3 in lipid metabolism, and thereby possibly weight control.

Individuals show large variability in their capacity to lose weight and maintain this weight. Here, the authors perform GWAS in two weight loss intervention cohorts and identify two genetic loci associated with weight loss that are taken forward for Bayesian fine-mapping and functional assessment in flies.