Genetic risk clustering increases children's body weight at 2 years of age - the STEPS Study

İlköğretim Çağındaki Çocuklarda Obezite Üzerinde Etkili Olan Bazı Faktörlerin İncelenmesi: İstanbul Örneği

Amaç: Çocukluk çağında obezite tüm dünyada artmaktadır. Bu çalışma ilköğretim çağındaki çocuklarda obezite üzerinde etkili olan bazı faktörlerin araştırılması amacıyla yapılmıştır.Yöntem: Çalışma İstanbul'da iki farklı okulda 621 ilköğretim öğrencisi üzerinde gerçekleştirilmiştir. Çocuklar 7-15 yaş grubunda olup rastgele örneklem yöntemi ile seçilmiştir. Çocuklara demografik özellikler, beslenme ve fiziksel aktivite ile ilgili sorulardan oluşan bir anket uygulanmış olup, bazı antropometrik ölçümleri alınmıştır. Çocukların Beden Kütle Indeksi (BKİ) değerleri Türk çocuklarının persentillerine göre sınıflandırılmıştır. Veriler SPSS 13.0 programı ile değerlendirilmiştir.Bulgular: Öğrencilerin %47,5’i kız, %52,5’i erkektir. BKİ sınıflandırmasında öğrencilerin %11,8'i obez bulunmuştur. Özel okuldaki öğrencilerde obezite prevalansı %17,3 devlet okulundaki öğrencilerde %6,6’dır (p<0,05). Üniversite mezunu anne ve babaların çocuklarında, aile birey sayısı üç kişi olanlarda obezite oranı daha fazladır (p<0,05). Beslenme alışkanlıklarına göre düzenli akşam yemeği tüketmeyenlerde ve sevinçli/mutlu olduğunda iştah değişimi olmayanlarda daha fazla obezite oranı görülmüştür (p<0,05). Ayrıca, okula özel araba ile giden öğrencilerin obezite oranı en fazladır (%18,2; p< 0,05).Sonuç: Çalışma sonucunda çocuklarda obezite oranı yüksek eğitim düzeyine sahip anne ve babaların çocuklarında, özel okula giden çocuklarda ve üç kişilik ailelerde yaşayanlarda daha yüksek bulunmuştur. Çocuklarda obezite gelişimini önlemek için okullarda düzenli olarak antropometrik ölçümlerin alınması, öğrencilere ve ebeveynlere sağlıklı beslenmeye yönelik eğitimlerin verilmesi faydalı olabilir.

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques

The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potential risk factors: genetics, dietary and physical activity habits, socio-economic environment, lifestyle, etc. In addition, all these factors are expected to exert their influence through a specific and especially convoluted way during childhood, given the fast growth along this period. Machine Learning methods are the appropriate tools to model this complexity, given their ability to cope with high-dimensional, non-linear data. Here, we have analyzed by Machine Learning a sample of 221 children (6–9 years) from Madrid, Spain. Both Random Forest and Gradient Boosting Machine models have been derived to predict the body mass index from a wide set of 190 multidomain variables (including age, sex, genetic polymorphisms, lifestyle, socio-economic, diet, exercise, and gestation ones). A consensus relative importance of the predictors has been estimated through variable importance measures, implemented robustly through an iterative process that included permutation and multiple imputation. We expect this analysis will help to shed light on the most important variables associated to childhood obesity, in order to choose better treatments for its prevention.

Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty

Polygenetic risk scores (pGRSs) consisting of adult body mass index (BMI) genetic variants have been widely associated with obesity in children populations. The implication of such obesity pGRSs in the development of cardio-metabolic alterations during childhood as well as their utility for the clinical prediction of pubertal obesity outcomes has been barely investigated otherwise. In the present study, we evaluated the utility of an adult BMI predisposing pGRS for the prediction and pharmacological management of obesity in Spanish children, further investigating its implication in the appearance of cardio-metabolic alterations. For that purpose, we counted on genetics data from three well-characterized children populations (composed of 574, 96 and 124 individuals), following both cross-sectional and longitudinal designs, expanding childhood and puberty. As a result, we demonstrated that the pGRS is strongly associated with childhood BMI Z-Score (B = 1.56, SE = 0.27 and p-value = 1.90 × 10⁻⁸), and that could be used as a good predictor of obesity longitudinal trajectories during puberty. On the other hand, we showed that the pGRS is not associated with cardio-metabolic comorbidities in children and that certain environmental factors interact with the genetic predisposition to the disease. Finally, according to the results derived from a weight-reduction metformin intervention in children with obesity, we discarded the utility of the pGRS as a pharmacogenetics marker of metformin response.

Genetic risk score predicts risk for overweight and obesity in Finnish preadolescents

Common genetic variants predispose to obesity with varying contribution by age. We incorporated known genetic variants into genetic risk scores (GRSs) and investigated their associations with overweight/obesity and central obesity in preadolescents. Furthermore, we compared GRSs with lifestyle factors, and tested if they predict the change in body size and shape in a 4-year follow-up. We utilized 1142 subjects from the Finnish Health in Teens (Fin-HIT) cohort. Overweight and obesity were defined with age- and gender-specific body mass index (BMI) z-score (BMIz), while central obesity by the waist-to-height ratio (WHtR). Background data on parental language, eating habits, leisure-time physical activity (LTPA) and sleep duration were included. Genotyping was performed with the Metabochip platform. Weighted, standardized GRSs were derived. Of the11-year-old children, 25.5% were at least overweight and 90.8% had Finnish speaking background. BMI-GRS was associated with higher risk for overweight with odds ratio (95% confidence interval) of 1.39 (1.20; 1.60) and obesity 1.41 (1.08; 1.83), but not with central obesity. BMI-GRS was weakly and inversely associated with the changes in BMIz and WHtR in the 4-year follow-up. Waist-to-hip ratio-GRS was not related to any obesity measures at baseline nor in the follow-up. The effect of BMI-GRS is similar to that of low LTPA on overweight. An interaction between parental language and BMI-GRS was noted (P = .019): BMI-GRS associated more strongly with overweight in Swedish than in Finnish speakers. We further identified two suggestive genetic variants near LOC101926977 and LOC105369677 associated with BMIz in preadolescents which were replicated in the adult population. In preadolescents, known genetic predisposing factors induce a risk for overweight comparable to low LTPA. However, the GRS was poor in predicting short-term changes in BMI or WHtR.

Genetic risk scores demonstrate the cumulative association of single nucleotide polymorphisms in gut microbiome-related genes with obesity phenotypes in preschool age children

BACKGROUND

Childhood obesity is a nutrition-related disease with multiple underlying aetiologies. While genetic factors contribute to obesity, the gut microbiome is also implicated through fermentation of nondigestible polysaccharides to short-chain fatty acids (SCFA), which provide some energy to the host and are postulated to act as signalling molecules to affect expression of gut hormones.

OBJECTIVE

To study the cumulative association of causal, regulatory, and tagged single nucleotide polymorphisms (SNPs) within genes involved in SCFA recognition and metabolism with obesity.

DESIGN

Study participants were non-Hispanic White (NHW, n = 270) and non-Hispanic Black (NHB, n = 113) children (2-5 years) from the Synergistic Theory and Research on Obesity and Nutrition Group (STRONG) Kids 1 Study. SNP variables were assigned values according to the additive, dominant, or recessive inheritance models. Weighted genetic risk scores (GRS) were constructed by multiplying the reassigned values by independently generated β-coefficients or by summing the β-coefficients. Ethnicity-specific SNPs were selected for inclusion in GRS by cohort.

RESULTS

GRS were directly associated with body mass index (BMI) z-score. The models explained 3.75%, 12.9%, and 26.7% of the variance for NHW/NHB, NHW, and NHB (β = 0.89 [CI: 0.43-1.35], P = 0.0002; β = 0.78 [CI: 0.54-1.03], P < 0.0001; β = 0.74 [CI: 0.51-0.97], P < 0.0001).

CONCLUSION

This analysis supports the cumulative association of several candidate genetic variants selected for their role in SCFA signalling, transport, and metabolism with early-onset obesity. These data strengthen the concept that microbiome influences obesity development through host genes interacting with SCFA.

Association between UCP1, UCP2, and UCP3 gene polymorphisms with markers of adiposity in European adolescents: The HELENA study

AIMS

To examine the association between UCP1, UCP2, and UCP3 gene polymorphisms with adiposity markers in European adolescents and to test if there were gene interactions with objectively measured physical activity and adiposity.

METHODS

A cross-sectional study that involves 1.057 European adolescents (12-18 years old) from the Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study. A total of 18 polymorphisms in UCP1, UCP2, and UCP3 genes were genotyped. We measured weight, height, waist, and hip circumferences and triceps and subscapular skinfold thickness. Physical activity was objectively measured by accelerometry during 7 days.

RESULTS

The C allele of the UCP1 rs6536991 polymorphism was associated with a lower risk of overweight (odds ratio [OR]: T/C + C/C vs T/T) = 0.72; 95% confidence interval [CI]: 0.53-0.98; P = 0.034; false discovery rate [FDR] = 0.048). There was a significant interaction between UCP1 rs2071415 polymorphism and physical activity with waist-to-hip ratio (P = 0.006; FDR = 0.026). Adolescents who did not meet the physical activity recommendations (less than 60 min/day of moderate to vigorous physical activity) and carrying the C/C genotype had higher waist-to-hip ratio (+ 0.067; 95% CI, 0.028-0.106; P = 0.003), while no differences across genotypes were observed in adolescents meeting the recommendations.

CONCLUSIONS

Two UCP1 polymorphisms were associated with adiposity in European adolescents. Meeting the daily physical activity recommendations may overcome the effect of the UCP1 rs2071415 polymorphism on obesity-related traits.

Genetic determinants of BMI from early childhood to adolescence: the Santiago Longitudinal Study

BACKGROUND

While the genetic contribution to obesity is well established, few studies have examined how genetic variants influence standardized body mass index Z-score (BMIz) in Hispanics/Latinos, especially across childhood and adolescence.

OBJECTIVES

We estimated the effect of established BMIz loci in Chilean children of the Santiago Longitudinal Study (SLS).

METHODS

We examined associations with BMIz at age 10 for 15 loci previously identified in European children. For significant loci, we performed association analyses at ages 5 and 16 years, for which we have smaller sample sizes. We tested associations of unweighted genetic risk scores (GRSs) for previously identified tag variants (GRS_EUR) and from the most significant variants in SLS at each locus (GRS_SLS).

RESULTS

We generalized five variants at age 10 (P < 0.05 and directionally consistent), including rs543874 that reached Bonferroni-corrected significance. The effect on BMIz was greatest at age 10 for all significant loci, except FTO, which exhibited an increase in effect from ages 5 to 16. Both GRSs were associated with BMIz (P < 0.0001), but GRS_SLS explained a much greater proportion of the variation (13.63%).

CONCLUSION

Our results underscore the importance of conducting genetic investigations across life stages and selecting ancestry appropriate tag variants in future studies for disease prediction and clinical evaluation.

Parental and child genetic contributions to obesity traits in early life based on 83 loci validated in adults: the FAMILY study

BACKGROUND

The genetic influence on child obesity has not been fully elucidated.

OBJECTIVE

This study investigated the parental and child contributions of 83 adult body mass index (BMI)-associated single-nucleotide polymorphisms (SNPs) to obesity-related traits in children from birth to 5 years old.

METHODS

A total of 1402 individuals were genotyped for 83 SNPs. An unweighted genetic risk score (GRS) was generated by the sum of BMI-increasing alleles. Repeated weight and length/height were measured at birth, 1, 2, 3 and 5 years of age, and age-specific and sex-specific weight and BMI Z-scores were computed.

RESULTS

The GRS was significantly associated with birthweight Z-score (P = 0.03). It was also associated with weight/BMI Z-score gain between birth and 5 years old (P = 0.02 and 6.77 × 10^-3 , respectively). In longitudinal analyses, the GRS was associated with weight and BMI Z-score from birth to 5 years (P = 5.91 × 10^-3 and 5.08 × 10^-3 , respectively). The maternal effects of rs3736485 in DMXL2 on weight and BMI variation from birth to 5 years were significantly greater compared with the paternal effects by Z test (P = 1.53 × 10^-6 and 3.75 × 10^-5 , respectively).

CONCLUSIONS

SNPs contributing to adult BMI exert their effect at birth and in early childhood. Parent-of-origin effects may occur in a limited subset of obesity predisposing SNPs.