Obesity: Genetic, molecular, and environmental aspects

Abstract

Obesity has emerged as one of the most serious public health concerns in the 21st century. Obese children tend to become obese adults. The dramatic rise in pediatric obesity closely parallels the rapid increase in the prevalence of adult obesity. As overweight children become adults they face the multitude of health problems associated with obesity at younger ages. The morbidity and mortality associated with obesity continue to increase. Obesity is one of the leading causes of preventable death. Complications of obesity include cardiovascular risks, hypertension, dyslipidemia, endothelial dysfunction, type 2 diabetes mellitus and impaired glucose tolerance, acanthosis nigricans, hepatic steatosis, premature puberty, hypogonadism and polycystic ovary syndrome, obstructive sleep disorder, orthopedic complications, cholelithiasis and pseudotumor cerebri. Genetic and molecular and environmental factors play an important role in the assessment and management of obesity.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

“…Body size, shape, and composition are anthropometric measures correlated with obesity and patterns of fat deposition and are associated with important metabolic health outcomes. [1][2][3] Large-scale genome-wide association studies (GWASs) for body mass index (BMI), waist to hip ratio, and height have to date focused on the role of common-frequency variants and have unveiled numerous associations that explain a modest proportion of trait variance; 4-6 the role of low-frequency variants has not been systematically explored across the entire genome.…”

“…We followed up Low-quality samples were identified by comparing the samples to their GWAS genotypes using $20,000 sites on chromosome 20. Comparing the raw genotype calls to existing GWAS data, a total of 112 samples were removed for one or more of the following causes: (1) high overall discordance to SNP array data, (2) heterozygosity rate > 3 standard deviations (SD) from population mean, (3) no SNP array data available for that sample, or (4) sample below 43 mean coverage. Overall, 3,798 samples were brought forward to the genotype refinement step.…”

“…Additional sample-level QC steps were carried out on refined genotypes, leading to the exclusion of additional 17 samples for one or more of the following causes: (1) non-reference discordance with GWAS SNP data > 5%, (2) contamination identified by multiple relations (>25 to other samples with IBS > 0.125), or (3) failed sex check. A final set of 3,781 samples (1,854 TwinsUK and 1,927 ALSPAC) in VCF files were submitted to the European Genomephenome Archive (EGA).…”

Syndrome de Bardet-Biedl : cils et obésité

“…Lorsque surviennent des anomalies d'origine génétique induisant un défaut au niveau de cet organite, celles-ci causent des pathologies, souvent syndromiques, que l'on nomme les ciliopathies [9,10] Longtemps considéré comme un organite vestigial [1], le cil primaire connaît depuis une quinzaine d'années un regain d'intérêt scientifique considérable par les découvertes d'une part, de sa présence à la surface de la plupart des cellules et, d'autre part, de son rôle comme centre intégrateur impliqué dans la détection, l'interprétation et la transmission de nombreux signaux intra-et extracellulaires [2,3]. L'importance du cil primaire a été confortée par de nombreux travaux démon-trant son rôle dans le cycle cellulaire, le développement embryonnaire, et par la mise en évidence qu'un dysfonctionnement du cil primaire serait impliqué dans des [36,37], car, tel l'apport d'oxygène, l'apport d'én ergie étant vital à la survie, les organismes ont développé, au cours de l'évolution, toute une batterie de régulateurs, activateurs et inhibiteurs d'appétit et de dépense énergétique. Cette multitude de signaux, ainsi que leurs interactions, rend extrêmement difficile la compréhension fine des causes de l'obésité et l'élaboration de stratégies de lutte efficace.…”

Inferring User Goals Using Customer Feedback andAnalyzing Customer Behavior

“…For these questions other customers can also propose their answers or responses. [16] and [19] demonstrated the behavioural outcome of customers. These responses can be analyzed to predict the customer behaviour ( Figure. 2).…”