Differential lipid metabolism outcomes associated with ADRB2 gene polymorphisms in response to two dietary interventions in overweight/obese subjects

Role of beta-2 adrenergic receptor polymorphism (rs1042714) on body weight and glucose metabolism response to a meal-replacement hypocaloric diet

OBJECTIVES

The beta-2 adrenergic receptor (ADRB2) is involved in energy balance regulation. The objective of our study was to evaluate the role of the rs1042714 genetic variant of ADRB2 gene on weight loss, body composition, and metabolic changes secondary to partial meal replacement (pMR) hypocaloric diet in women with obesity.

METHODS

We conducted an interventional study in 95 premenopausal women with body mass index ≥ 35 kg/m2. The subjects received two intakes per day of a normocaloric hyperproteic formula during 12 wk of a pMR diet. Body weight, body mass index, fat mass, waist circumference, lipid profile, fasting insulin levels, and homeostasis model assessment for insulin resistance were determined. All patients were genotyped rs1042714 and evaluated in a dominant model (CC versus CG + GG).

RESULTS

Genotype frequencies were 31 (37.3%), 38 (45.8%), and 14 (16.9%) for the CC, CG, and GG genotypes, respectively. We found significant interaction effects between ADRB2 variant and pMR-induced changes (CC versus CG + GG) on body weight (-7.1 ± 0.3 versus -13.5 ± 0.5 kg; P = 0.03), body mass index (-0.9 ± 0.1 versus -1.2 ± 0.2 kg/m2; P = 0.03), fat mass (-4.9 ± 0.5 versus -10.2 ±1.2 kg; P = 0.01), waist circumference (-5.1 ± 0.2 versus -10.1 ± 1.9 cm; P = 0.03), glucose (-5.1 ± 1.3 versus -12.5 ± 2.5 mg/dL; P = 0.03), total cholesterol (-18.1 ± 9.3 versus -33.5 ± 4.5 mg/dL; P = 0.03), low-density lipoprotein cholesterol (-9.1 ± 5.3 versus -24.5 ± 4.1 mg/dL; P = 0.04), triacylglycerol levels (-6.1 ± 5.3 versus -31.5 ± 9.5 mg/dL; P = 0.04), fasting insulin levels (-1.8 ± 0.3 versus -6.3 ± 0.5 IU/L; P = 0.03), and homeostasis model assessment for insulin resistance (-0.6 ± 0.3 versus -1.9 ± 0.5 U; P = 0.03). The odds ratio to improve alteration in glucose metabolism adjusted by age and weight loss throughout the study was 0.26 (95% CI, 0.07-0.95; P = 0.02) in G allele carriers.

CONCLUSIONS

The G allele of rs1042714 predicts the magnitude of weight loss resulting from a pMR diet. These adiposity improvements produce a better improvement of insulin resistance and percentage of impaired glucose metabolism in G allele carriers.

Network Pharmacology and Molecular Docking Analysis on Targets and Mechanisms of Berberine in Atypical Antipsychotic-Induced Metabolic Syndrome

Berberine (BBR), an isoquinoline alkaloid, possesses multiply pharmacological effects as a potential therapeutic drug for antipsychotic-induced metabolic syndrome (MetS). However, the underlying therapeutic mechanisms have not been fully elucidated. In this study, we aim to investigate the possible mechanisms by identifying the key targets and biological pathways through network pharmacology and molecular docking analysis. A total of 23 overlapping targets in the intersection set among BBR, atypical antipsychotic drugs (AADs), and MetS were determined. PPI network analysis showed that 22 out of the 23 overlapping targets closely interacted with the others. The following pathway enrichment analysis and molecular docking indicated a central role of peroxisome proliferator-activated receptor-γ (PPARG) as the key target of BBR against AAD-induced MetS by acting on the PPAR signaling pathway, lipid and atherosclerosis, and AMP activated protein kinase (AMPK) signaling pathway. In addition, cytochrome P-450 2D6 (CYP2D6) could be considered as another target of BBR in ameliorating antipsychotic-induced metabolic side effects. Collectively, this study investigated the central targets and biological pathways of BBR against AAD-induced MetS from a systematic perspective, and thus brings novel insights into further understanding of the protective effects of BBR.

Low-carbohydrate versus balanced-carbohydrate diets for reducing weight and cardiovascular risk

BACKGROUND

Debates on effective and safe diets for managing obesity in adults are ongoing. Low-carbohydrate weight-reducing diets (also known as 'low-carb diets') continue to be widely promoted, marketed and commercialised as being more effective for weight loss, and healthier, than 'balanced'-carbohydrate weight-reducing diets.

OBJECTIVES

To compare the effects of low-carbohydrate weight-reducing diets to weight-reducing diets with balanced ranges of carbohydrates, in relation to changes in weight and cardiovascular risk, in overweight and obese adults without and with type 2 diabetes mellitus (T2DM).

SEARCH METHODS

We searched MEDLINE (PubMed), Embase (Ovid), the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science Core Collection (Clarivate Analytics), ClinicalTrials.gov and WHO International Clinical Trials Registry Platform (ICTRP) up to 25 June 2021, and screened reference lists of included trials and relevant systematic reviews. Language or publication restrictions were not applied.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in adults (18 years+) who were overweight or living with obesity, without or with T2DM, and without or with cardiovascular conditions or risk factors. Trials had to compare low-carbohydrate weight-reducing diets to balanced-carbohydrate (45% to 65% of total energy (TE)) weight-reducing diets, have a weight-reducing phase of 2 weeks or longer and be explicitly implemented for the primary purpose of reducing weight, with or without advice to restrict energy intake.  DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and full-text articles to determine eligibility; and independently extracted data, assessed risk of bias using RoB 2 and assessed the certainty of the evidence using GRADE. We stratified analyses by participants without and with T2DM, and by diets with weight-reducing phases only and those with weight-reducing phases followed by weight-maintenance phases. Primary outcomes were change in body weight (kg) and the number of participants per group with weight loss of at least 5%, assessed at short- (three months to < 12 months) and long-term (≥ 12 months) follow-up.

MAIN RESULTS

We included 61 parallel-arm RCTs that randomised 6925 participants to either low-carbohydrate or balanced-carbohydrate weight-reducing diets. All trials were conducted in high-income countries except for one in China. Most participants (n = 5118 randomised) did not have T2DM. Mean baseline weight across trials was 95 kg (range 66 to 132 kg). Participants with T2DM were older (mean 57 years, range 50 to 65) than those without T2DM (mean 45 years, range 22 to 62). Most trials included men and women (42/61; 3/19 men only; 16/19 women only), and people without baseline cardiovascular conditions, risk factors or events (36/61). Mean baseline diastolic blood pressure (DBP) and low-density lipoprotein (LDL) cholesterol across trials were within normal ranges. The longest weight-reducing phase of diets was two years in participants without and with T2DM. Evidence from studies with weight-reducing phases followed by weight-maintenance phases was limited. Most trials investigated low-carbohydrate diets (> 50 g to 150 g per day or < 45% of TE; n = 42), followed by very low (≤ 50 g per day or < 10% of TE; n = 14), and then incremental increases from very low to low (n = 5). The most common diets compared were low-carbohydrate, balanced-fat (20 to 35% of TE) and high-protein (> 20% of TE) treatment diets versus control diets balanced for the three macronutrients (24/61). In most trials (45/61) the energy prescription or approach used to restrict energy intake was similar in both groups. We assessed the overall risk of bias of outcomes across trials as predominantly high, mostly from bias due to missing outcome data. Using GRADE, we assessed the certainty of evidence as moderate to very low across outcomes.  Participants without and with T2DM lost weight when following weight-reducing phases of both diets at the short (range: 12.2 to 0.33 kg) and long term (range: 13.1 to 1.7 kg).  In overweight and obese participants without T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to 8.5 months (mean difference (MD) -1.07 kg, (95% confidence interval (CI) -1.55 to -0.59, I2 = 51%, 3286 participants, 37 RCTs, moderate-certainty evidence) and over one to two years (MD -0.93 kg, 95% CI -1.81 to -0.04, I2 = 40%, 1805 participants, 14 RCTs, moderate-certainty evidence); as well as change in DBP and LDL cholesterol over one to two years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one year (risk ratio (RR) 1.11, 95% CI 0.94 to 1.31, I2 = 17%, 137 participants, 2 RCTs, very low-certainty evidence).  In overweight and obese participants with T2DM: low-carbohydrate weight-reducing diets compared to balanced-carbohydrate weight-reducing diets (weight-reducing phases only) probably result in little to no difference in change in body weight over three to six months (MD -1.26 kg, 95% CI -2.44 to -0.09, I2 = 47%, 1114 participants, 14 RCTs, moderate-certainty evidence) and over one to two years (MD -0.33 kg, 95% CI -2.13 to 1.46, I2 = 10%, 813 participants, 7 RCTs, moderate-certainty evidence); as well in change in DBP, HbA1c and LDL cholesterol over 1 to 2 years. The evidence is very uncertain about whether there is a difference in the number of participants per group with weight loss of at least 5% at one to two years (RR 0.90, 95% CI 0.68 to 1.20, I2 = 0%, 106 participants, 2 RCTs, very low-certainty evidence).  Evidence on participant-reported adverse effects was limited, and we could not draw any conclusions about these.  AUTHORS' CONCLUSIONS: There is probably little to no difference in weight reduction and changes in cardiovascular risk factors up to two years' follow-up, when overweight and obese participants without and with T2DM are randomised to either low-carbohydrate or balanced-carbohydrate weight-reducing diets.

A predictive regression model of the obesity-related inflammatory status based on gut microbiota composition

BACKGROUND AND AIM

Fecal microbiome disturbances are linked to different human diseases. In the case of obesity, gut microbiota seems to play a role in the development of low-grade inflammation. The purpose of the present study was to identify specific bacterial families and genera associated with an increased obesity-related inflammatory status, which would allow to build a regression model for the prediction of the inflammatory status of obese and overweight subjects based on fecal microorganisms.

METHODS

A total of 361 volunteers from the Obekit trial (65 normal-weight, 110 overweight, and 186 obese) were classified according to four variables: waist/hip ratio (≥0.86 for women and ≥1.00 for men), leptin/adiponectin ratio (LAR, ≥3.0 for women and ≥1.4 for men), and plasma C-reactive protein (≥2 mg/L) and TNF levels (≥0.85 pg/mL). An inflammation score was designed to classify individuals in low (those subjects who did exceed the threshold value in 0 or 1 variable) or high inflammatory index (those subjects who did exceed the threshold value in 2 or more variables). Fecal 16 S rRNA sequencing was performed for all participants, and differential abundance analyses for family and genera were performed using the MicrobiomeAnalyst web-based platform.

RESULTS

Methanobacteriaceae, Christensenellaceae, Coriobacteriaceae, Bifidobacteriaceae, Catabacteriaceae, and Dehalobacteriaceae families, and Methanobrevibacter, Eggerthella, Gemmiger, Anaerostipes, and Collinsella genera were significantly overrepresented in subjects with low inflammatory index. Conversely, Carnobacteriaceae, Veillonellaceae, Pasteurellaceae, Prevotellaceae and Enterobacteriaceae families, and Granulicatella, Veillonella, Haemophilus, Dialister Parabacteroides, Prevotella, Shigella, and Allisonella genera were more abundant in subjects with a high inflammatory index. A regression model adjusted by BMI, sex, and age and including the families Coriobacteriaceae and Prevotellaceae and the genus Veillonella was developed.

CONCLUSION

A microbiota-based regression model was able to predict the obesity-related inflammatory status (area under the ROC curve = 0.8570 ± 0.0092 Harrell's optimism-correction) and could be useful in the precision management of inflammobesity.

Gut Microbiota Differences According to Ultra-Processed Food Consumption in a Spanish Population

Ultra-processed foods (UPFs) consumption could affect gut microbiota diversity and profile. We aimed to evaluate the effects of UPFs on microbiota, considering the role of sex. The consumption of UPFs (using NOVA criteria) was assessed with a validated 137-item food-frequency questionnaire. Participants (n = 359) were classified into less than three servings per day (n = 96) of UPFs and more than five (n = 90). Women and men were subclassified following the same criteria. 16S rRNA sequencing was performed from DNA fecal samples, and differences in microbiota were analyzed using EdgeR. The relationship between UPFs and bacteria was assessed by Spearman correlation and comparison of tertiles of consumption. Women who consumed more than five servings/day of UPFs presented an increase in Acidaminococcus, Butyrivibrio, Gemmiger, Shigella, Anaerofilum, Parabacteroides, Bifidobacterium, Enterobacteriales, Bifidobacteriales and Actinobacteria and a decrease in Melainabacter and Lachnospira. Bifidobacterium, Bifidobacteriales and Actinobacteria was positively associated with pizza and Actinobacteria with industrially processed dairy in women. Men who consumed more than five servings/day presented an increase of Granulicatella, Blautia, Carnobacteriaceae, Bacteroidaceae, Peptostreptococcaceae, Bacteroidia and Bacteroidetes and a decrease of Anaerostipes and Clostridiaceae. Bacteroidia and Bacteroidetes correlated positively with industrially processed meat. This study suggests that UPFs may affect microbiota composition differently in women and men.

Gut Microbiota Bacterial Species Associated with Mediterranean Diet-Related Food Groups in a Northern Spanish Population

The MD (Mediterranean diet) is recognized as one of the healthiest diets worldwide and is associated with the prevention of cardiovascular and metabolic diseases. Dietary habits are considered one of the strongest modulators of gut microbiota, which seem to play a significant role in health status of the host. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and habitual dietary intake in 360 Spanish adults from the Obekit cohort (normal weight, overweight, and obese participants). Dietary intake and adherence to the MD tests were administered and fecal samples were collected from each participant. Fecal 16S rRNA (ribosomal Ribonucleic Acid) gene sequencing was performed and checked against the dietary habits. MetagenomeSeq was the statistical tool applied to analyze data at the species taxonomic level. Results from this study identified several beneficial bacteria that were more abundant in the individuals with higher adherence to the MD. Bifidobacterium animalis was the species with the strongest association with the MD. Some SCFA (Short Chain Fatty Acids) -producing bacteria were also associated with MD. In conclusion, this study showed that MD, fiber, legumes, vegetable, fruit, and nut intake are associated with an increase in butyrate-producing taxa such as Roseburia faecis, Ruminococcus bromii, and Oscillospira (Flavonifractor) plautii.

Diet- and sex-related changes of gut microbiota composition and functional profiles after 4 months of weight loss intervention

PURPOSE

Obesity has been related to intestinal dysbiosis and the modification of gut microbiota composition by dietary strategies becomes a promising strategy to help manage obesity. The aim of the current study was to evaluate the effect of two weight-loss diets on the composition and functional profile of gut microbiota.

METHODS

55 men and 124 women with BMI > 25 kg/m² were randomly assigned to moderately high-protein (MHP) or low-fat (LF) diet. Differences in fecal bacteria abundance (based on 16 s rRNA sequencing) between before and after 4 months of calorie restriction was analyzed using EdgeR tool in MicrobiomeAnalyst platform. Bacterial functional profile was predicted using Tax4Fun and metagenomeSeq analysis. Significant KEGG Orthology (KO) terms were selected for the metabolomic study using chromatography.

RESULTS

After the intervention, MHP-men showed a significant decrease in Negativicutes, Selenomonadales, Dielma and Dielma fastidiosa. LF-men showed a significant increase in Bacilli, Lactobacillales, Christensenellaceae, Peptococcaceae, and Streptococcaceae, Peptococcus, Streptococcus and Christensenella, Duncaniella dubosii_CP039396_93.49%, Roseburia sp_AB744234_98.96% and Alistipes inops_KJ572413_99.57%. MHP-women increased Pasteurellales, Phascolarctobacterium succinatutens, Ruthenibacterium lactatiformans_LR215981_99.55% and decreased in Phascolarctobacterium succinatutens_NR112902_99.56%. Finally, LF-women presented a significant decrease in Bacteroides clarus and Erysipelothrix inopinata_CP060715_84.4%. Surprisingly, no matching bacterial changes were found between these four groups. A total of 42 KO, 10 metabolic pathways and 107 related metabolites related were found implicated in these bacterial changes. Seven metabolites were confirmed in plasma.

CONCLUSION

Weight-loss-related-changes in gut microbiome composition and the functional profile occur in a sex- and diet-related manner, showing that women and men could differentially benefit from the consumption of MHP and LF diets.

TRIAL REGISTRATION

NCT02737267, 10th March 2016 retrospectively registered.

Differential response to a 6-month energy-restricted treatment depending on SH2B1 rs7359397 variant in NAFLD subjects: Fatty Liver in Obesity (FLiO) Study

PURPOSE

Non-alcoholic fatty liver disease (NAFLD) is worldwide recognized as the most common cause of chronic liver disease. Current NAFLD clinical management relies on lifestyle change, nevertheless, the importance of the genetic make-up on liver damage and the possible interactions with diet are still poorly understood. The aim of the study was to evaluate the influence of the SH2B1 rs7359397 genetic variant on changes in body composition, metabolic status and liver health after 6-month energy-restricted treatment in overweight/obese subjects with NAFLD. In addition, gene-treatment interactions over the course of the intervention were examined.

METHODS

The SH2B1 genetic variant was genotyped in 86 overweight/obese subjects with NAFLD from the FLiO study (Fatty Liver in Obesity study). Subjects were metabolically evaluated at baseline and at 6-months. Liver assessment included ultrasonography, Magnetic Resonance Imaging, elastography, a lipidomic test (OWL^®-test) and specific blood liver biomarkers. Additionally, body composition, general biochemical markers and dietary intake were determined.

RESULTS

Both genotypes significantly improved their body composition, general metabolic status and liver health after following an energy-restricted strategy. Liver imaging techniques showed a greater decrease in liver fat content (- 44.3%, p < 0.001) and in serum ferritin levels (p < 0.001) in the carriers of the T allele after the intervention. Moreover, lipidomic analysis, revealed a higher improvement in liver status when comparing risk vs. no-risk genotype (p = 0.006 vs. p = 0.926, respectively). Gene-treatment interactions showed an increase in fiber intake and omega-3 fatty acid in risk genotype (p interaction = 0.056 and p interaction = 0.053, respectively), while a significant increase in MedDiet score was observed in both genotype groups (p = 0.020). Moreover, no-risk genotype presented a relevant decrease in hepatic iron as well as in MUFA intake (p = 0.047 and p = 0.034, respectively).

CONCLUSION

Subjects carrying the T allele of the rs7359397 polymorphism may benefit more in terms of hepatic health and liver status when prescribed an energy-restricted treatment, where a Mediterranean dietary pattern rich in fiber and other components such as omega-3 fatty acids might boost the benefits.

TRIAL REGISTRATION

The Fatty Liver in Obesity was approved by the Research Ethics Committee of the University of Navarra and retrospectively registered (NCT03183193; www.clinicaltrials.gov ); June 2017.

Associations between Genotype-Diet Interactions and Weight Loss-A Systematic Review

Studies on the interactions between single nucleotide polymorphisms (SNPs) and macronutrient consumption on weight loss are rare and heterogeneous. This review aimed to conduct a systematic literature search to investigate genotype-diet interactions on weight loss. Four databases were searched with keywords on genetics, nutrition, and weight loss (PROSPERO: CRD42019139571). Articles in languages other than English and trials investigating special groups (e.g., pregnant women, people with severe diseases) were excluded. In total, 20,542 articles were identified, and, after removal of duplicates and further screening steps, 27 articles were included. Eligible articles were based on eight trials with 91 SNPs in 63 genetic loci. All articles examined the interaction between genotype and macronutrients (carbohydrates, fat, protein) on the extent of weight loss. However, in most cases, the interaction results were not significant and represented single findings that lack replication. The publications most frequently analyzed genotype-fat intake interaction on weight loss. Since the majority of interactions were not significant and not replicated, a final evaluation of the genotype-diet interactions on weight loss was not possible. In conclusion, no evidence was found that genotype-diet interaction is a main determinant of obesity treatment success, but this needs to be addressed in future studies.

Sex-Specific Associations between Gut Prevotellaceae and Host Genetics on Adiposity

The gut microbiome has been recognized as a tool for understanding adiposity accumulation and for providing personalized nutrition advice for the management of obesity and accompanying metabolic complications. The genetic background is also involved in human energy homeostasis. In order to increase the value of nutrigenetic dietary advice, the interplay between genetics and microbiota must be investigated. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and 95 obesity-related single nucleotide polymorphisms (SNPs) searched in the literature. Oral mucosa and fecal samples from 360 normal weight, overweight and obese subjects were collected. Next generation genotyping of these 95 SNPs and fecal 16S rRNA sequencing were performed. A genetic risk score (GRS) was constructed with 10 SNPs statistically or marginally associated with body mass index (BMI). Several microbiome statistical analyses at family taxonomic level were applied (LEfSe, Canonical Correspondence Analysis, MetagenomeSeq and Random Forest), and Prevotellaceae family was found in all of them as one of the most important bacterial families associated with BMI and GRS. Thus, in this family it was further analyzed the interactive association between BMI and GRS with linear regression models. Interestingly, women with higher abundance of Prevotellaceae and higher GRS were more obese, compared to women with higher GRS and lower abundance of Prevotellaceae. These findings suggest relevant interrelationships between Prevotellaceae and the genetic background that may determine interindividual BMI differences in women, which opens the way to new precision nutrition-based treatments for obesity.

Association of the SH2B1 rs7359397 Gene Polymorphism with Steatosis Severity in Subjects with Obesity and Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is a major cause of liver disease worldwide. Some genetic variants might be involved in the progression of this disease. The study hypothesized that individuals with the rs7359397 T allele have a higher risk of developing severe stages of NAFLD compared with non-carriers where dietary intake according to genotypes could have a key role on the pathogenesis of the disease. SH2B1 genetic variant was genotyped in 110 overweight/obese subjects with NAFLD. Imaging techniques, lipidomic analysis and blood liver biomarkers were performed. Body composition, general biochemical and dietary variables were also determined. The SH2B1 risk genotype was associated with higher HOMA-IR p = 0.001; and Fatty Liver Index (FLI) p = 0.032. Higher protein consumption (p = 0.028), less mono-unsaturated fatty acid and fiber intake (p = 0.045 and p = 0.049, respectively), was also referred to in risk allele genotype. Lipidomic analysis showed that T allele carriers presented a higher frequency of non-alcoholic steatohepatitis (NASH) (69.1% vs. 44.4%; p = 0.006). In the genotype risk group, adjusted logistic regression models indicated a higher risk of developing an advanced stage of NAFLD measured by FLI (OR 2.91) and ultrasonography (OR 4.15). Multinomial logistic regression models showed that risk allele carriers had higher liver fat accumulation risk (RRR 3.93) and an increased risk of NASH (RRR 7.88). Consequently, subjects carrying the T allele were associated with a higher risk of developing a severe stage of NAFLD. These results support the importance of considering genetic predisposition in combination with a healthy dietary pattern in the personalized evaluation and management of NAFLD.

Modeling of an integrative prototype based on genetic, phenotypic, and environmental information for personalized prescription of energy-restricted diets in overweight/obese subjects

BACKGROUND

Interindividual variability in weight loss and metabolic responses depends upon interactions between genetic, phenotypic, and environmental factors.

OBJECTIVE

We aimed to model an integrative (nutri) prototype based on genetic, phenotypic, and environmental information for the personalized prescription of energy-restricted diets with different macronutrient distribution.

METHODS

A 4-mo nutritional intervention was conducted in 305 overweight/obese volunteers involving 2 energy-restricted diets (30% restriction) with different macronutrient distribution: a moderately high-protein (MHP) diet (30% proteins, 30% lipids, and 40% carbohydrates) and a low-fat (LF) diet (22% lipids, 18% proteins, and 60% carbohydrates). A total of 201 subjects with good dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) related to energy homeostasis. Genotyping was performed by targeted next-generation sequencing. Two weighted genetic risk scores for the MHP (wGRS1) and LF (wGRS2) diets were computed using statistically relevant SNPs. Multiple linear regression models were performed to estimate percentage BMI decrease depending on the dietary macronutrient composition.

RESULTS

After energy restriction, both the MHP and LF diets induced similar significant decreases in adiposity, body composition, and blood pressure, and improved the lipid profile. Furthermore, statistically relevant differences in anthropometric and biochemical markers depending on sex and age were found. BMI decrease in the MHP diet was best predicted at ∼28% (optimism-corrected adjusted R2 = 0.279) by wGRS1 and age, whereas wGRS2 and baseline energy intake explained ∼29% (optimism-corrected adjusted R2 = 0.287) of BMI decrease variability in the LF diet. The incorporation of these predictive models into a decision algorithm allowed the personalized prescription of the MHP and LF diets.

CONCLUSIONS

Different genetic, phenotypic, and exogenous factors predict BMI decreases depending on the administration of a hypocaloric MHP diet or an LF diet. This holistic approach may help to personalize dietary advice for the management of excessive body weight using precision nutrition variables.This trial was registered at clinicaltrials.gov as NCT02737267.

Long-Term Effectiveness of Liraglutide for Weight Management and Glycemic Control in Type 2 Diabetes

Background: Liraglutide is the first glucagon-like peptide-1 receptor agonist (GLP-1 RA) based on the human GLP-1 sequence, with potential weight loss benefits, approved for the treatment of type 2 diabetes (T2D) mellitus. Herein, we aimed to assess the 5-year effectiveness of Liraglutide in the management of weight and glycometabolic control in a Southern Italian cohort of overweight/obese T2D patients, who were naïve to GLP-1 RAs. Patients and Methods: Forty overweight or obese patients treated with Liraglutide at doses up to 1.8 mg/day, in combination with one or more oral antidiabetic agents, were retrospectively assessed at baseline, during, and after 60 months of continuous therapy. Results: After 5 years of Liraglutide treatment, body weight decreased from 92.1 ± 20.5 kg to 87.3 ± 20.0 Kg (p < 0.001), with a mean reduction of 5.0 ± 7.0 Kg and a body mass index (BMI) decrement of −2.0 ± 3.1 Kg/m². On Spearman’s univariate analysis, change in body weight was correlated with female gender and baseline BMI. Hemoglobin A1c (HbA1c) decreased from 7.9 ± 0.9% at baseline to 7.0 ± 0.7% at the end of the study period (p < 0.001), followed by a significant reduction in fasting plasma glucose. No significant differences emerged in other biochemical parameters, despite a trend toward improvement in lipid profile. Notwithstanding encouraging effects on several markers of cardiovascular disease (CVD), increments in the 5- and 10-year risk for the first atherosclerotic cardiovascular event were documented, as four incident cases of myocardial infarction. Conclusions: Prolonging treatment with Liraglutide can lead to durable benefits in relation to weight and glycemic control, with a greater impact on women. These results extend and corroborate previous observations, suggesting that gender per se may modulate the response to Liraglutide. Despite favorable effects on some established CVD risks factors, the long-term role of Liraglutide in primary prevention of CVD in patients with T2D remains controversial.

Interplay of an Obesity-Based Genetic Risk Score with Dietary and Endocrine Factors on Insulin Resistance

This study aimed to nutrigenetically screen gene-diet and gene-metabolic interactions influencing insulin resistance (IR) phenotypes. A total of 232 obese or overweight adults were categorized by IR status: non-IR (HOMA-IR (homeostatic model assessment - insulin resistance) index ≤ 2.5) and IR (HOMA-IR index > 2.5). A weighted genetic risk score (wGRS) was constructed using 95 single nucleotide polymorphisms related to energy homeostasis, which were genotyped by a next generation sequencing system. Body composition, the metabolic profile and lifestyle variables were evaluated, where individuals with IR showed worse metabolic outcomes. Overall, 16 obesity-predisposing genetic variants were associated with IR (p < 0.10 in the multivariate model). The wGRS strongly associated with the HOMA-IR index (adj. R squared = 0.2705, p < 0.0001). Moreover, the wGRS positively interacted with dietary intake of cholesterol (P int. = 0.002), and with serum concentrations of C-reactive protein (P int. = 0.008) regarding IR status, whereas a negative interaction was found regarding adiponectin blood levels (P int. = 0.006). In conclusion, this study suggests that interactions between an adiposity-based wGRS with nutritional and metabolic/endocrine features influence IR phenotypes, which could facilitate the prescription of personalized nutrition recommendations for precision prevention and management of IR and diabetes.

Serum lipid profile as a biomarker of intra-pancreatic fat deposition: A nested cross-sectional study

BACKGROUND AND AIMS

The relationship between intra-pancreatic fat deposition (IPFD) and lipid profile has been investigated in individuals with obesity and/or type 2 diabetes, but not in healthy non-obese individuals and those after acute pancreatitis. The aim of the study was to investigate the association between serum lipid profile and IPFD in the latter individuals and to determine the effect of abdominal fat distribution and other covariates.

METHODS AND RESULTS

A total of 90 individuals with a history of acute pancreatitis as well as 23 healthy non-obese individuals participated in the study. Magnetic resonance imaging was used to quantify IPFD and visceral-to-subcutaneous fat volume ratio, followed by fasting state measurement of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), TC/HDL-C ratio, and triglycerides. In healthy non-obese individuals, IPFD was not significantly associated with any of the studied markers. In individuals after acute pancreatitis, IPFD was significantly associated with triglycerides in both unadjusted (β = 0.360; 95% CI, 0.090-0.629; p = 0.009) and adjusted models, with a β-coefficient of 0.280 [(95% CI, 0.016-0.545); p = 0.038] in the most adjusted model. Also, IPFD was significantly associated with TC/HDL-C ratio in both unadjusted (β = 0.336; 95% CI, 0.045-0.626; p = 0.024) and adjusted models, with a β-coefficient of 0.375 [(95% CI, 0.090-0.660); p = 0.010] in the most adjusted model. Multiple regression yielded triglycerides, but not TC/HDL-C ratio, as a significant marker of IPFD in individuals after acute pancreatitis.

CONCLUSIONS

Serum lipid profile is not associated with IPFD in healthy non-obese. Triglycerides, but not other components of lipid profile, is a promising biomarker for IPFD in individuals following acute pancreatitis.

Methylome-Wide Association Study in Peripheral White Blood Cells Focusing on Central Obesity and Inflammation

Epigenetic signatures such as DNA methylation may be associated with specific obesity traits in different tissues. The onset and development of some obesity-related complications are often linked to visceral fat accumulation. The aim of this study was to explore DNA methylation levels in peripheral white blood cells to identify epigenetic methylation marks associated with waist circumference (WC). DNA methylation levels were assessed using Infinium Human Methylation 450K and MethylationEPIC beadchip (Illumina) to search for putative associations with WC values of 473 participants from the Methyl Epigenome Network Association (MENA) project. Statistical analysis and Ingenuity Pathway Analysis (IPA) were employed for assessing the relationship between methylation and WC. A total of 669 CpGs were statistically associated with WC (FDR < 0.05, slope ≥ |0.1|). From these CpGs, 375 CpGs evidenced a differential methylation pattern between females with WC ≤ 88 and > 88 cm, and 95 CpGs between males with WC ≤ 102 and > 102 cm. These differentially methylated CpGs are located in genes related to inflammation and obesity according to IPA. Receiver operating characteristic (ROC) curves of the top four significant differentially methylated CpGs separated by sex discriminated individuals with presence or absence of abdominal fat. ROC curves of all the CpGs from females and one CpG from males were validated in an independent sample (n = 161). These methylation results add further insights about the relationships between obesity, adiposity-associated comorbidities, and DNA methylation where inflammation processes may be involved.

Association of FTO and ADRB2 gene variation with energy restriction induced adaptations in resting energy expenditure and physical activity

Background

Energy restriction induces adaptations in resting energy expenditure (REE) and physical activity; inter-individual variability could be ascribed to genetic predisposition.The aim was to examine if changes in REE and physical activity as a result of weight loss were affected by candidate single nucleotide polymorphisms (SNPs).

Methods

148 subjects (39 men, 109 women), mean ± SD age: 41 ± 9 year; body mass index (BMI): 31.9 ± 3.0 kg/m², followed a very low energy diet for 8 weeks. SNPs were selected from six candidate genes: ADRB2, FTO, MC4R, PPARG2, PPARD and PPARGC1A. REE (ventilated hood) and physical activity (tri-axial accelerometer) were assessed before and after the diet. General linear modelling included gender, age and additional relevant covariates for all parameters.

Results

The heterozygotic genotype of FTO was associated with a higher amount of physical activity (1.71 Mcounts/d; CI 1.62-1.81) compared to the homozygotic major genotype (1.50 Mcounts/d; CI 1.40-1.59) (P < 0.001) while the homozygotic risk allele genotype was not different (1.56 Mcounts/d; CI 1.39-1.74) at baseline; moreover, a similar pattern was observed after energy restriction. Carrying the homozygotic minor genotype of ADRB2 was associated with a larger decrease in REE (P < 0.05) and greater adaptive thermogenesis (P < 0.05) after weight loss.

Conclusion

Carrying the minor ADRB2 allele homozygous was associated with a larger diet induced metabolic adaptation in energy expenditure and suggest a central role for reduced lipid mobilization. Carrying the risk allele of FTO homozygous was not associated with lower physical activity at baseline or after weight loss. Heterozygous carriers of one FTO risk allele showed greater physical activity before and after weight loss which might protect them in part from the higher obesity risk associated with FTO.

Epigenome-wide association study in peripheral white blood cells involving insulin resistance

Insulin resistance (IR) is a hallmark of type 2 diabetes, metabolic syndrome and cardiometabolic risk. An epigenetic phenomena such as DNA methylation might be involved in the onset and development of systemic IR. The aim of this study was to explore the genetic DNA methylation levels in peripheral white blood cells with the objective of identifying epigenetic signatures associated with IR measured by the Homeostatic Model Assessment of IR (HOMA-IR) following an epigenome-wide association study approach. DNA methylation levels were assessed using Infinium Methylation Assay (Illumina), and were associated with HOMA-IR values of participants from the Methyl Epigenome Network Association (MENA) project, finding statistical associations for at least 798 CpGs. A stringent statistical analysis revealed that 478 of them showed a differential methylation pattern between individuals with HOMA-IR ≤ 3 and > 3. ROC curves of top four CpGs out of 478 allowed differentiating individuals between both groups (AUC≈0.88). This study demonstrated the association between DNA methylation in some specific CpGs and HOMA-IR values that will help to the understanding and in the development of new strategies for personalized approaches to predict and prevent IR-associated diseases.

Genetic and nongenetic factors explaining metabolically healthy and unhealthy phenotypes in participants with excessive adiposity: relevance for personalized nutrition

BACKGROUND

Different genetic and environmental factors can explain the heterogeneity of obesity-induced metabolic alterations between individuals. In this study, we aimed to screen factors that predict metabolically healthy (MHP) and unhealthy (MUP) phenotypes using genetic and lifestyle data in overweight/obese participants.

METHODS

In this cross-sectional study we enrolled 298 overweight/obese Spanish adults. The Adult Treatment Panel III criteria for metabolic syndrome were used to categorize MHP (at most, one trait) and MUP (more than one feature). Blood lipid and inflammatory profiles were measured by standardized methods. Body composition was determined by dual-energy X-ray absorptiometry. A total of 95 obesity-predisposing single-nucleotide polymorphisms (SNPs) were genotyped by a predesigned next-generation sequencing system. SNPs associated with a MUP were used to compute a weighted genetic-risk score (wGRS). Information concerning lifestyle (dietary intake and physical activity level) was collected using validated questionnaires.

RESULTS

The prevalence of MHP and MUP was 44.3% and 55.7%, respectively, in this sample. Overall, 12 obesity-related genetic variants were associated with the MUP. Multiple logistic regression analyses revealed that wGRS (OR = 4.133, p < 0.001), total dietary fat [odds ratio (OR) = 1.105, p = 0.002], age (OR = 1.064, p = 0.001), and BMI (OR = 1.408, p < 0.001) positively explained the MUP, whereas female sex (OR = 0.330, p = 0.009) produced a protective effect. The area under the receiver operating characteristic curve using the multivariable model was high (0.8820). Interestingly, the wGRS was the greatest contributor to the MUP (squared partial correlation = 0.3816, p < 0.001).

CONCLUSIONS

The genetic background is an important factor explaining MHP and MUP related to obesity, in addition to lifestyle variables. This information could be useful to metabolically categorize individuals, as well as for the design/implementation of personalized nutrition interventions aimed at promoting metabolic health and nutritional wellbeing.

Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight

Background and Aim

Individual lipid phenotypes including circulating total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG) determinations are influenced by gene-environment interactions. The aim of this study was to predict blood lipid level (TC, LDL-c, HDL-c, and TG) variability using genetic and lifestyle data in subjects with excessive body weight-for-height.

Methods

This cross-sectional study enrolled 304 unrelated overweight/obese adults of self-reported European ancestry. A total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Relevant genotypes of each SNP were coded as 0 (nonrisk) and 1 (risk). Four genetic risk scores (GRS) for each lipid phenotype were calculated by adding the risk genotypes. Information concerning lifestyle (diet, physical activity, alcohol drinking, and smoking) was obtained using validated questionnaires. Total body fat (TFAT) and visceral fat (VFAT) were determined by dual-energy X-ray absorptiometry.

Results

Overall, 45 obesity-related genetic variants were associated with some of the studied blood lipids. In addition to conventional factors (age, sex, dietary intakes, and alcohol consumption), the calculated GRS significantly contributed to explain their corresponding plasma lipid trait. Thus, HDL-c, TG, TC, and LDL-c serum concentrations were predicted by approximately 28% (optimism-corrected adj. R² = 0.28), 25% (optimism-corrected adj. R² = 0.25), 24% (optimism-corrected adj. R² = 0.24), and 21% (optimism-corrected adj. R²=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC²) = 0.18) and LDL-c (PC² = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC² = 0.09 and PC² = 0.06, respectively) and TG levels (PC² = 0.20 and PC² = 0.07, respectively) than the rest of variables.

Conclusions

Besides known lifestyle influences, some obesity-related genetic variants could help to predict blood lipid phenotypes.

Dopamine gene methylation patterns are associated with obesity markers and carbohydrate intake

INTRODUCTION

Dopamine (DA) is a neurotransmitter that regulates the rewarding and motivational processes underlying food intake and eating behaviors. This study hypothesized associations of DNA methylation signatures at genes modulating DA signaling with obesity features, metabolic profiles, and dietary intake.

METHODS

An adult population within the Methyl Epigenome Network Association project was included (n = 473). DNA methylation levels in white blood cells were measured by microarray (450K). Differentially methylated genes were mapped within the dopaminergic synapse pathway using the KEGG reference database (map04728). Subsequently, network enrichment analyses were run in the pathDIP portal. Associations of methylation patterns with anthropometric markers of general (BMI) and abdominal obesity (waist circumference), the blood metabolic profile, and daily dietary intakes were screened.

RESULTS

After applying a correction for multiple comparisons, 12 CpG sites were strongly associated (p < 0.0001) with BMI: cg03489495 (ITPR3), cg22851378 (PPP2R2D), cg04021127 (PPP2R2D), cg22441882 (SLC18A1), cg03045635 (DRD5), cg23341970 (ITPR2), cg13051970 (DDC), cg08943004 (SLC6A3), cg20557710 (CACNA1C), cg24085522 (GNAL), cg16846691 (ITPR2), and cg09691393 (SLC6A3). Moreover, average methylation levels of these genes differed according to the presence or absence of abdominal obesity. Pathway analyses revealed a statistically significant contribution of the aforementioned genes to dopaminergic synapse transmission (p = 4.78E-08). Furthermore, SLC18A1 and SLC6A3 gene methylation signatures correlated with total energy (p < 0.001) and carbohydrate (p < 0.001) intakes.

CONCLUSIONS

The results of this investigation reveal that methylation status on DA signaling genes may underlie epigenetic mechanisms contributing to carbohydrate and calorie consumption and fat deposition.