Genetic predisposition, dietary restraint and disinhibition in relation to short and long-term weight loss

BACKGROUND: Interindividual differences in response to weight loss and maintenance thereafter are ascribed to genetic predisposition and behavioral changes. OBJECTIVE: To examine whether body weight and short and long-term body weight loss were affected by candidate single nucleotide polymorphisms (SNPs) and changes in eating behavior or by an interaction between these genetic and behavioral factors. METHODS: 150 healthy subjects (39 males, 111 females) aged 20-50y with a BMI of 27-38kg/m2 followed a very low energy diet for 8-weeks, followed by a 3-month weight maintenance period. SNPs were selected from six candidate genes: ADRB2, FTO, MC4R, PPARG, PPARD, and PPARGC1A. Changes in eating behavior were determined with the Three Factor Eating Questionnaire. RESULTS: A high genetic predisposition score was associated with a high body weight at baseline and more short-term weight loss. From the six selected obesity-related SNPs, FTO was associated with increased body weight at baseline, and the effect allele of PPARGC1A was positively associated with short-term weight loss, when assessed for each SNP separately. Long-term weight loss was associated with a larger increase in dietary restraint and larger decrease in disinhibition. CONCLUSION: During long-term weight loss, genetic effects are dominated by changes in eating behavior

Heritability and genetic etiology of habitual physical activity: a twin study with objective measures

Twin studies with objective measurements suggest habitual physical activity (HPA) are modestly to highly heritable, depending on age. We aimed to confirm or refute this finding and identify relevant genetic variants using a candidate gene approach. HPA was measured for 14 days with a validated triaxial accelerometer (Tracmor) in two populations: (1) 28 monozygotic and 24 dizygotic same-sex twin pairs (aged 22 ± 5 years, BMI 21.8 ± 3.4 kg/m(2), 21 male, 31 female pairs); (2) 52 and 65 unrelated men and women (aged 21 ± 2 years, BMI 22.0 ± 2.5 kg/m(2)). Single nucleotide polymorphisms (SNPs) in PPARD, PPARGC1A, NRF1 and MTOR were considered candidates. Association analyses were performed for both groups separately followed by meta-analysis. Structural equation modeling shows significant familiality for HPA, consistent with a role for additive genetic factors (heritability 57 %, 95 % CI 32–74 %, AE model) or common environmental factors (47 %, 95 % CI 23–65 %, CE model). A moderate heritability was observed for the time spent on low- and high-intensity physical activity (P ≤ 0.05), but could not be confirmed for the time spent on moderate-intensity physical activity. For PPARD, each additional effect allele was inversely associated with HPA (P ≤ 0.01; rs2076168 allele C) or tended to be associated with HPA (P ≤ 0.05; rs2267668 allele G). Linkage disequilibrium existed between those two SNPs (alleles A/G and A/C, respectively) and meta-analysis showed that carriers of the AAGC haplotype were less physically active than carriers of the AAAA and AA AC haplotypes combined (P = 0.017). For PPARGC1A, carriers of AA in rs8192678 spent more time on high-intensity physical activity than GG carriers (P = 0.001). No associations were observed with SNPs in NRF1 and MTOR. In conclusion, HPA may be modestly heritable, which is confirmed by an association with variants in PPARD

Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index

Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI) diet improved weight maintenance. OBJECTIVE: To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study. DESIGN: Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured. RESULTS: Angiotensin I converting enzyme (ACE) was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%. CONCLUSIONS: A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss

Adipose tissue transcriptome reflects variations between subjects with continued weight loss and subjects regaining weight 6 mo after caloric restriction independent of energy intake

BACKGROUND: The mechanisms underlying body weight evolution after diet-induced weight loss are poorly understood. OBJECTIVE: We aimed to identify and characterize differences in the subcutaneous adipose tissue (SAT) transcriptome of subjects with different weight changes after energy restriction-induced weight loss during 6 mo on 4 different diets. DESIGN: After an 8-wk low-calorie diet (800 kcal/d), we randomly assigned weight-reduced obese subjects from 8 European countries to receive 4 diets that differed in protein and glycemic index content. In addition to anthropometric and plasma markers, SAT biopsies were taken at the beginning [clinical investigation day (CID) 2] and end (CID3) of the weight follow-up period. Microarray analysis was used to define SAT gene expression profiles at CID2 and CID3 in 22 women with continued weight loss (successful group) and in 22 women with weight regain (unsuccessful group) across the 4 dietary arms. RESULTS: Differences in SAT gene expression patterns between successful and unsuccessful groups were mainly due to weight variations rather than to differences in dietary macronutrient content. An analysis of covariance with total energy intake as a covariate identified 1338 differentially expressed genes. Cellular growth and proliferation, cell death, cellular function, and maintenance were the main biological processes represented in SAT from subjects who regained weight. Mitochondrial oxidative phosphorylation was the major pattern associated with continued weight loss. CONCLUSIONS: The ability to control body weight loss independent of energy intake or diet composition is reflected in the SAT transcriptome. Although cell proliferation may be detrimental, a greater mitochondrial energy gene expression is suggested as being beneficial for weight control

Future Nutrigenetics: In Search of the Missing Genetic Variation

Despite considerable effort, genetic analysis of complex disorders and traits, including those related to nutrition, has revealed only a very small part of the expected genetic variation. Missing variation may occur as conditional variation depending on the presence of defined lifestyle factors, as epigenetic variation or as low-moderate effect size variation not detected by mutation screening and genome-wide association studies. Experience with genetic analysis of patients with neural tube defects provides evidence of the existence of the latter type of variation and demonstrates that candidate gene analysis is an efficient approach to discover part of this missing variation. By reviewing the genes with rare and common variation associated with obesity or related parameters, guidelines are proposed for the proper selection of candidate genes. This selection fits into an analytic strategy to deal with the complex and massive data sets expected to arise from the application of routine whole genome sequencing

Insulin resistance in an energy-centered perspective

Insulin resistance, of which the incidence is dramatically increasing in Western societies, is usually regarded as a pathological condition. However, arguments can be provided that insulin resistance may be a normal physiological mechanism to let cells and organs deal with the competition for various sources of energy, especially under circumstances of energy stress. Here we review four different hypotheses dealing with insulin resistance: the glucose-fatty acid cycle, the ER and oxidative stress response, the selfish brain, and the thrifty/not-so-thrifty genotype. Each hypothesis has a specific view on insulin resistance, but they also can complement each other. Combining the four hypotheses supports the view that physiological insulin resistance is indeed one of the adaptive regulation mechanisms, which has benefit for survival of the organism by restoring and maintaining the energy balance at the cellular and organism level. In principle insulin resistance seems to be a reversible physiological trait implying that there may be a specific mechanism to down-regulate insulin resistance once the energy balance is regained. The combined model also describes several ways, by which insulin resistance is promoted during prolonged increased energy supply. A better understanding of the complex background of physiological insulin resistance and of the nature of its regulatory mechanisms will be valuable for the treatment of pathological insulin resistance and type 2 diabetes. The present review may be helpful for this

Generally detected proteins in comparative proteomics--a matter of cellular stress response?

The specificity of proteins identified by proteomics as biomarkers for defined conditions or as components of biological processes and pathways is crucial. We critically reviewed differentially expressed proteins from comparative proteomic studies identified by 2-DE followed by MS, especially with MALDI technique. Based on 66 of those studies, a list of 44 proteins is presented as generally detected proteins regardless of species, in vivo or in vitro conditions, tissues and organs, and experimental objective. Similarly, a list of 28 generally detected protein families is presented. The enriched functions linked to these generally detected proteins reveal that there are some common biological features beyond the technical limitations. Cellular stress response can be the universal reason as to why these proteins are generally expressed differentially. Using those proteins as biomarkers for cellular processes other than stress response should be done with caution. In future proteomic studies more profound approaches should be applied to look beyond these proteins to find specific biomarkers. Our results are discussed in relation to a recent viewpoint publication by Petrak et al. [Proteomics 2008, 8, 1744-1749]