An obesity genetic risk score predicts risk of insulin resistance among Chinese children

Distinct causal effects of body fat distribution on cardiometabolic traits among children: Findings from the BCAMS study

BACKGROUND AND AIMS

Observational studies reveal that different body fat measures are associated with cardiometabolic disease with different effects. However, causality is not reflected by such observations. To explore and compare the causal relationships of general obesity (measured by body mass index (BMI)), adipose obesity (measured by fat mass percentage (FMP)) and central obesity (measured by waist-to-height ratio (WHtR)) with cardiometabolic traits among children.

METHODS AND RESULTS

We conducted one sample Mendelian randomization (MR) analysis in 3266 children from Beijing Children and Adolescents Metabolic Syndrome Study. Genetic instruments based on 28 SNPs were performed to explore and compare the causal associations of genetically BMI, FMP and WHtR with cardiometabolic traits. The genetic instruments were robustly correlated with observed BMI, FMP and WHtR. Each genetically 1-SD increment in BMI, FMP and WHtR were causally associated with increment in systolic blood pressure (SBP), diastolic blood pressure (DBP), log-transformed fasting plasma glucose (FPG), log-transformed HOMA-β, and decrease in log-transformed high-density lipoprotein cholesterol (HDL), respectively (all P < 0.05 after Bonferroni correction). The receiver operating characteristic curve indicated that BMI and FMP showed stronger effects on SBP, DBP, HOMA-β and HDL than WHtR (all P < 0.05). We also observed causal associations of BMI and FMP with log-transformed fasting insulin and HOMA-IR.

CONCLUSIONS

The MR analysis based on population-based cohort indicated a causal relationship of adiposity and body fat distribution with cardiometabolic traits. When compared with central obesity, general obesity and adipose obesity might own stronger effects on blood pressure and blood lipids among children.

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.

No clinical utility of common polymorphisms in IGF1, IRS1, GCKR, PPARG, GCK1 and KCTD1 genes previously associated with insulin resistance in overweight children from Romania and Moldova

Background Previous genome-wide association studies (GWAS) identified IGF1, IRS1, GCKR, PPARG, GCK1 and KCTD1 as candidate genes for insulin resistance and type 2 diabetes (T2D). We investigated the associations of these previously reported common variants in these genes with insulin resistance in overweight children from Romania and Moldova. Methods Six single nucleotide polymorphisms (SNPs), IGF1 (rs35767), IRS1 (rs2943634), GCKR (rs780094), PPARG (rs1801282), GCK1 (rs1799884) and KCTD15 (rs29941), were genotyped in 100 overweight children along with clinical and metabolic parameters. Homeostatic model assessment of insulin resistance (HOMA-IR) above 3.4 (defining insulin resistance) was used as the outcome. Results Children differed in insulin resistance status despite having similar body mass index (BMI) standard deviation scores (SDS) (World Health Organization, [WHO] reference). The identified predictors for altered insulin metabolism were higher cholesterol levels, higher diastolic blood pressure and higher waist-to-hip-ratio (as a marker for increased abdominal fat). None of the SNPs showed significant association with increase in the risk for insulin resistance in children (p range=0.478-0.724; odds ratio [OR] range=1.924-4.842); however, the risk allele in GCKR (rs780094, p=0.06, OR=6.871) demonstrated near statistical significance. Conclusions The interrogated risk alleles did not show any significant association with insulin resistance in children in our cohort; however, the GCKR (rs780094) might be a viable candidate in larger cohorts. The lack of replication of the proposed association may point to differences in linkage disequilibrium or effect modifiers across studies.

The combined effects of cardiovascular disease related SNPs on ischemic stroke

PURPOSE

Previous studies have revealed multiple common variants associated with known risk factors for cardiovascular disease (CVD). Ischemic stroke (IS) and CVD share several risk factors with each having substantial heritability. We aimed to generate a multi-locus genetic risk score (GRS) for IS based on CVD related SNPs to evaluate their combined effects on IS.

METHODS

A total of 851 patients and 977 controls were selected from Beijing, Tianjin, Shandong, Shanxi, Shaanxi and Heilongjiang communities. The candidate genes were genotyped by PCR-hybridization. Information about demographic factors, history of disease (such as hypertension), and lifestyle was obtained using structured questionnaires. A GRS model weighted by the absolute value of regression coefficient β was established to comprehensively assess the association between candidate SNPs and IS. Using the area under the receiver operating characteristic curve (AUC) to evaluate the value of GRS on predicting IS.

RESULTS

The GRS of cases was 2.87 ± 0.28, which was significantly higher than controls' GRS (2.78 ± 0.30) (P < 0.000). With the increase of the GRS, the risk of IS became higher (P_trend < 0.000). Subjects in the top quartile of the GRS had about 1.9-fold increased risk of IS compared with subjects in the lowest quartile (OR _adjusted = 1.880, 95%CI = 1.442-2.452, P < 0.000). The AUC = 0.580, P < 0.000.

CONCLUSION

13 CVD related SNPs had combined effects on IS. The GRS of cases was significantly higher than controls' GRS. As the GRS increased, the risk of IS increased. The GRS model has some value for the prediction of IS.

Identification of novel alleles associated with insulin resistance in childhood obesity using pooled-DNA genome-wide association study approach

Background:

Recently, we witnessed great progress in the discovery of genetic variants associated with obesity and type 2 diabetes (T2D), especially in adults. Much less is known regarding genetic variants associated with insulin resistance (IR). We hypothesized that novel IR genes could be efficiently detected in a population of obese children and adolescents who may not exhibit comorbidities and other confounding factors.

Objectives:

This study aimed to determine whether a genome-wide association study (GWAS), using a DNA-pooling approach, could identify novel genes associated with IR.

Subjects:

The pooled-DNA GWAS analysis included Slovenian obese children and adolescents with and without IR matched for body mass index, gender and age. A replication study was conducted in another independent cohort with or without IR.

Methods:

For the pooled-DNA GWAS, we used HumanOmni5-Quad SNP array (Illumina). Allele frequency distributions were compared with modified t-tests and χ²-tests and ranked using PLINK. Top single nucleotide polymorphisms (SNPs) were validated using individual genotyping by high-resolution melting analysis and TaqMan assay.

Results:

We identified five top-ranking SNPs from the pooled-DNA GWAS analysis within the ECE1, IL1R2, GNPDA1, HLA-J and PYGB loci. All except SNP rs9261108 (HLA-J locus) were confirmed in the validation phase using individual genotyping. The SNP rs2258617 within PYGB remained statistically significant for both recessive and additive models in both cohorts and in a merged analysis of both cohorts and present the strongest novel candidate gene for IR.

Conclusion:

We report for the first time a pooled-DNA GWAS approach to identify five novel SNPs or genes for IR in a paediatric population. The four loci confirmed in the second validation phase study warrant further studies, especially the strongest SNP rs2258617 within PYGB, and provide targets for further basic research of IR mechanisms and for the development of potential new IR and T2D therapies.

Independent relationship between body mass index and LH peak value of GnRH stimulation test in ICPP girls: A cross-sectional study

The effect of obesity on idiopathic central precocious puberty (ICPP) girls is still under discussion. The relationship between body mass index (BMI) and sexual hormone levels of gonadotropin-releasing hormone (GnRH) stimulation test in ICPP girls is controversial and the underlying mechanism is unclear. This study aims to further explore the independent effect of excess adiposity on peak luteinizing hormone (LH) level of stimulation test in ICPP girls and the role of other related factors. A retrospective cross-sectional study was performed on 618 girls diagnosed as having ICPP, including 355 cases of normal weight, 99 cases of overweight and 164 cases of obese. The results showed that obese group had more progressed Tanner stage and no significant difference (P=0.28) in LH peak was found as basal LH value was used as a covariate. The obese group had higher total testosterone (TT), adrenocorticotrophic hormone (ACTH), 17-α hydroxyprogesterone (17-αOHP) and androstendione (AN), with significantly increased fasting insulin (FIN) and homeostasis model of assessment for insulin resistance index (HOMA-IR). Stratified analysis showed inconsistency of the relationship between BMI-standard deviation score (BMI-SDS) and LH peak in different Tanner stages (P for interaction=0.017). Further smoothing plot showed linear and non-linear relationship between BMI-SDS and LH peak in three Tanner stages. Then linear regression model was used to analyze the relationship between BMI-SDS and LH peak in different Tanner stages, with and without different confounding factors being adjusted. In B2 stage, BMI-SDS was negatively associated with LH peak. In B3 stage, when BMI-SDS <1.5, as BMI-SDS increased, the level of LH peak decreased (model I: β=-1.8, 95% CI=-4.7 to 1.1, P=0.214). When BMI-SDS ≥1.5, BMI-SDS was significantly positively associated with LH peak (model I: β=4.5, 95% CI=1.7 to 7.4, P=0.002). In B4 stage, when BMI-SDS <1.5, BMI-SDS was negatively associated with LH peak (model I: β=-11.6, 95% CI=-22.7 to-0.5, P=0.049). When BMI-SDS ≥1.5, BMI-SDS was positively associated with LH peak (model I: β=-4.2, 95% CI=-3.3 to 11.7, P=0.28). It is concluded that there is an independent correlation between BMI-SDS and LH peak of stimulation test in ICPP girls, their relationships are different in different Tanner stages, and the effect of BMI-SDS can be affected by adrenal androgens, estradiol and glucose metabolism parameters.

Identification, expression and variation of the GNPDA2 gene, and its association with body weight and fatness traits in chicken

Background. The GNPDA2 (glucosamine-6-phosphate deaminase 2) gene is a member of Glucosamine-6-phosphate (GlcN6P) deaminase subfamily, which encoded an allosteric enzyme of GlcN6P. Genome-wide association studies (GWAS) have shown that variations of human GNPDA2 are associated with body mass index and obesity risk, but its function and metabolic implications remain to be elucidated.The object of this study was to characterize the gene structure, expression, and biological functions of GNPDA2 in chickens.

Methods. Variant transcripts of chicken GNPDA2 and their expression were investigated using rapid amplification of cDNA ends (RACE) system and real-time quantitative PCR technology. We detected the GNPDA2 expression in hypothalamic, adipose, and liver tissue of Xinghua chickens with fasting and high-glucose-fat diet treatments, and performed association analysis of variations of GNPDA2 with productive traits in chicken. The function of GNPDA2 was further studied by overexpression and small interfering RNA (siRNA) methods in chicken preadipocytes.

Results.Four chicken GNPDA2 transcripts (cGNPDA2-a∼cGNPDA2-d) were identified in this study. The complete transcript GNPDA2-a was predominantly expressed in adipose tissue (subcutaneous fat and abdominal fat), hypothalamus, and duodenum. In fasting chickens, the mRNA level of GNPDA2 was decreased by 58.8% (P < 0.05) in hypothalamus, and returned to normal level after refeeding. Chicken fed a high-glucose-fat diet increased GNPDA2 gene expression about 2-fold higher in adipose tissue (P < 0.05) than that in the control (fed a basal diet), but decreased its expression in hypothalamus. Two single-nucleotide polymorphisms of the GNPDA2 gene were significantly associated with body weight and a number of fatness traits in chicken (P < 0.05).

Conclusion. Our findings indicated that the GNPDA2 gene has a potential role in the regulation of body weight, fat and energy metabolism in chickens.

Characterisation of betatrophin concentrations in childhood and adolescent obesity and insulin resistance

BACKGROUND AND OBJECTIVE

Betatrophin, a novel hormone, is correlated with insulin resistance and promotes pancreatic β-cell growth in mice. The aim of this study was to determine circulating betatrophin levels in overweight or obese children and adolescents.

METHODS

The following pairs of subjects were included: (i) normal-weight healthy (n = 27) and overweight or obese (n = 28); (ii) non-insulin-resistant overweight or obese (n = 25) and insulin-resistant obese (n = 15); (iii) normal-weight males (n = 18) and females (n = 20); (4) 5 to 8 yr olds (n = 20) and 8 to 14 yr olds (n = 18). Circulating betatrophin levels were measured using enzyme-linked immunosorbent assay (ELISA). In addition, clinical data were recorded and anthropometrical measurements were performed.

RESULTS

Circulating betatrophin levels were increased significantly in obese children and adolescents with insulin resistance (365.77 ± 30.86 pg/mL) compared with overweight or obese subjects without insulin resistance (274.25 ± 26.52 pg/mL; p < 0.05). However, no differences in betatrophin levels were seen between lean and overweight or obese children (323.18 ± 25.91 vs. 348.27 ± 18.91 pg/mL, respectively; p > 0.05). In the normal-weight cohort, males had higher serum betatrophin level than did females, and subjects <8 yr old had lower serum betatrophin levels compared with those >8 yr. Surprisingly, betatrophin concentrations were correlated negatively with body mass index (BMI), but not with the BMI Z-score, in non-insulin-resistant children and adolescents.

CONCLUSIONS

These results demonstrated that circulating betatrophin levels were increased in insulin-resistant obese children or adolescents and might act as a potential biomarker of insulin resistance in these populations. Furthermore, serum betatrophin concentrations might vary during the development of children and adolescents, as well as between genders.

The importance of prediction model validation and assessment in obesity and nutrition research

Deriving statistical models to predict one variable from one or more other variables, or predictive modeling, is an important activity in obesity and nutrition research. To determine the quality of the model, it is necessary to quantify and report the predictive validity of the derived models. Conducting validation of the predictive measures provides essential information to the research community about the model. Unfortunately, many articles fail to account for the nearly inevitable reduction in predictive ability that occurs when a model derived on one data set is applied to a new data set. Under some circumstances, the predictive validity can be reduced to nearly zero. In this overview, we explain why reductions in predictive validity occur, define the metrics commonly used to estimate the predictive validity of a model (for example, coefficient of determination (R(2)), mean squared error, sensitivity, specificity, receiver operating characteristic and concordance index) and describe methods to estimate the predictive validity (for example, cross-validation, bootstrap, and adjusted and shrunken R(2)). We emphasize that methods for estimating the expected reduction in predictive ability of a model in new samples are available and this expected reduction should always be reported when new predictive models are introduced.

Obesity susceptibility loci in Qataris, a highly consanguineous Arabian population

OBJECTIVES

In Qataris, a population characterized by a small size and a high rate of consanguinity, between two-thirds to three-quarters of adults are overweight or obese. We investigated the relevance of 23 obesity-related loci in the Qatari population.

METHODS

Eight-hundred-four individuals assessed to be third generation Qataris were included in the study and assigned to 3 groups according to their body mass index (BMI): 190 lean (BMI < 25 kg/m(2)); 131 overweight (25 kg/m(2) ≤ BMI < 30 kg/m(2)) and 483 obese (BMI ≥ 30 kg/m(2)). Genomic DNA was isolated from peripheral blood and genotyped by TaqMan.

RESULTS

Two loci significantly associated with obesity in Qataris: the TFAP2B variation (rs987237) (A allele versus G allele: chi-square = 10.3; P = 0.0013) and GNPDA2 variation (rs10938397) (A allele versus G allele: chi-square = 6.15; P = 0.013). The TFAP2B GG genotype negatively associated with obesity (OR = 0.21; P = 0.0031). Conversely, the GNDPA2 GG homozygous genotype associated with higher risk of obesity in subjects of age < 32 years (P = 0.0358).

CONCLUSION

We showed a different genetic profile associated with obesity in the Qatari population compared to Western populations. Studying the genetic background of Qataris is of primary importance as the etiology of a given disease might be population-specific.

Eating habits of preschool children and the risk of obesity, insulin resistance and metabolic syndrome in adults

Background & Objective : Nutrient excess and nutrient deficiency in the diets of preschool children can lead to permanent modification of metabolic pathways and increased risk of diet-dependent diseases in adults. Children are most susceptible to the adverse consequences of bad eating habits.The objective of this study was to evaluate the eating habits and the diets of preschool children as risk factors for excessive weight, obesity, insulin resistance and the metabolic syndrome. Methods : The study was conducted on 350 randomly selected preschool children attending kindergartens in south-eastern Poland. Three-day dietary recalls were processed and evaluated in the Dieta 5 application. Results : The analyzed diets were characterized by low diversity and a high share of processed foods, such as pate, sausages, ketchup, mayonnaise, fried meat, French fries and fast-food. The dietary content of vegetables, raw fruit, dairy products and whole grain products was alarmingly low. Conclusions : Diets characterized by excessive energy value and nutritional deficiency can lead to health problems. In most cases, excessive weight gain in children can be blamed on parents and caretakers who are not aware of the health consequences of high-calorie foods rich in fats and sugar.

Expression of variant transcripts of the potassium channel tetramerization domain-containing 15 (KCTD15) gene and their association with fatness traits in chickens

The aim of this study was to characterize the structure, expression, and biological functions of potassium channel tetramerization domain containing 15 (KCTD15) in chickens. We compared the KCTD15 expression level in samples of hypothalamic, adipose, and liver tissue of Xinghua chickens that were maintained on different dietary status. An association analysis of KCTD15 gene variant transcripts with fatness traits in a F2 resource population of chickens was performed. Three KCTD15 transcripts were identified in which the complete transcript was predominantly expressed in adipose tissue and the hypothalamus. The chicken KCTD15 gene was regulated by both feeding and fasting and consumption of a high-fat diet. The expression level of KCTD15 gene was markedly decreased in hypothalamus and liver of fasted and refed chickens (P < 0.05) and significantly downregulated in adipose tissue by the high-fat diet (P < 0.05). Three single-nucleotide polymorphisms of the KCTD15 gene were significantly associated with a number of fatness traits in chicken (P < 0.05). These results suggest that KCTD15 have a potential role regulation of obesity and fat metabolism in chickens.