314 research outputs found
Genetics of Childhood Obesity
Obesity is a major health problem and an immense economic burden on the health care systems both in the United States and the rest of the world. The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Besides environmental factors, genetic factors are known to play an important role in the pathogenesis of obesity. Genome-wide association studies (GWAS) have revealed strongly associated genomic variants associated with most common disorders; indeed there is general consensus on these findings from generally positive replication outcomes by independent groups. To date, there have been only a few GWAS-related reports for childhood obesity specifically, with studies primarily uncovering loci in the adult setting instead. It is clear that a number of loci previously reported from GWAS analyses of adult BMI and/or obesity also play a role in childhood obesity
Genetic Susceptibility to Type 2 Diabetes and Obesity: Follow-Up of Findings from Genome-Wide Association Studies
Canonical Notch signaling is required for bone morphogenetic proteinâmediated human osteoblast differentiation
Osteoblast differentiation of bone marrowâderived human mesenchymal stem cells (hMSC) can be induced by stimulation with canonical Notch ligand, Jagged1, or bone morphogenetic proteins (BMPs). However, it remains elusive how these two pathways lead to the same phenotypic outcome. Since Runx2 is regarded as a master regulator of osteoblastic differentiation, we targeted Runx2 with siRNA in hMSC. This abrogated both Jagged1 and BMP2 mediated osteoblastic differentiation, confirming the fundamental role for Runx2. However, while BMP stimulation increased Runx2 and downstream Osterix protein expression, Jagged1 treatment failed to upregulate either, suggesting that canonical Notch signals require basal Runx2 expression. To fully understand the transcriptomic profile of differentiating osteoblasts, RNA sequencing was performed in cells stimulated with BMP2 or Jagged1. There was common upregulation of ALPL and extracellular matrix genes, such as ACAN, HAS3, MCAM, and OLFML2B. Intriguingly, genes encoding components of Notch signaling (JAG1, HEY2, and HES4) were among the top 10 genes upregulated by both stimuli. Indeed, ALPL expression occurred concurrently with Notch activation and inhibiting Notch activity for up to 24âhours after BMP administration with DAPT (a gamma secretase inhibitor) completely abrogated hMSC osteoblastogenesis. Concordantly, RBPJ (recombination signal binding protein for immunoglobulin kappa J region, a critical downstream modulator of Notch signals) binding could be demonstrated within the ALPL and SP7 promoters. As such, siRNAâmediated ablation of RBPJ decreased BMPâmediated osteoblastogenesis. Finally, systemic Notch inhibition using diabenzazepine (DBZ) reduced BMP2âinduced calvarial bone healing in mice supporting the critical regulatory role of Notch signaling in BMPâinduced osteoblastogenesis.Bone morphogenetic protein (BMP) stimulation of boneâmarrowâderived human mesenchymal progenitor cells (hMSCs) increases Notch proteins via increased Notch ligand Jagged1 expression. Canonical Notch signaling is required for BMPâinduced ALPL expression and osteoblastic commitment of hMSCs. Both BMPâinduced osteoblastogenesis and Notchâinduced osteoblastogenesis require Runx2.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162778/2/stem3245_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162778/1/stem3245.pd
Infant BMI or Weight-for-Length and Obesity Risk in Early Childhood
Weight-for-length (WFL) is currently used to assess adiposity under 2 years. We assessed WFL- versus BMI-based estimates of adiposity in healthy infants in determining risk for early obesity
Relation of alleles of the collagen type Ialpha1 gene to bone density and the risk of osteoporotic fractures in postmenopausal women
BACKGROUND: Osteoporosis is a common disorder with a strong genetic
component. One way in which the genetic component could be expressed is
through polymorphism of COLIA1, the gene for collagen type Ialpha1, a
bone-matrix protein. METHODS: We determined the COLIA1 genotypes SS, Ss,
and ss in a population-based sample of 177
Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies
BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5â40âyears. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2âyears in females and 13.9âyears in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8
Modeling genetic inheritance of copy number variations
Copy number variations (CNVs) are being used as genetic markers or functional candidates in gene-mapping studies. However, unlike single nucleotide polymorphism or microsatellite genotyping techniques, most CNV detection methods are limited to detecting total copy numbers, rather than copy number in each of the two homologous chromosomes. To address this issue, we developed a statistical framework for intensity-based CNV detection platforms using family data. Our algorithm identifies CNVs for a family simultaneously, thus avoiding the generation of calls with Mendelian inconsistency while maintaining the ability to detect de novo CNVs. Applications to simulated data and real data indicate that our method significantly improves both call rates and accuracy of boundary inference, compared to existing approaches. We further illustrate the use of Mendelian inheritance to infer SNP allele compositions in each of the two homologous chromosomes in CNV regions using real data. Finally, we applied our method to a set of families genotyped using both the Illumina HumanHap550 and Affymetrix genome-wide 5.0 arrays to demonstrate its performance on both inherited and de novo CNVs. In conclusion, our method produces accurate CNV calls, gives probabilistic estimates of CNV transmission and builds a solid foundation for the development of linkage and association tests utilizing CNVs
BMD loci contribute to ethnic and developmental differences in skeletal fragility across populations: Assessment of evolutionary selection pressures
Bone mineral density (BMD) is a highly heritable trait used both for the diagnosis of osteoporosis in adults and to assess bone health in children. Ethnic differences in BMD have been documented, with markedly higher levels in individuals of African descent, which partially explain disparity in osteoporosis risk across populations. To date, 63 independent genetic variants have been associated with BMD in adults of Northern-European ancestry. Here, we demonstrate that at least 61 of these variants are predictive of BMD early in life by studying their compound effect within two multiethnic pediatric cohorts. Furthermore, we show that within these cohorts and across populations worldwide the frequency of those alleles associated with increased BMD is systematically elevated in individuals of Sub-Saharan African ancestry. The amount of differentiation in the BMD genetic scores among Sub-Saharan and non-Sub-Saharan populations together with neutrality tests, suggest that these allelic differences are compatible with the hypothesis of selective pressures acting on the genetic determinants of BMD. These findings constitute an explorative contribution to the role of selection on ethnic BMD differences and likely a new example of polygenic adaptation acting on a human trait
Genetic Discrimination Between LADA and Childhood-Onset Type 1 Diabetes Within the MHC
OBJECTIVE The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region. RESEARCH DESIGN AND METHODS Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects). RESULTS The strongest associations in the MHC class II region (rs3957146, beta [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (beta [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, beta [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA. CONCLUSIONS In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.Peer reviewe
Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution
To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldWe recently described an association between risk of type 2diabetes and variants in the transcription factor 7-like 2 gene (TCF7L2; formerly TCF4), with a population attributable risk (PAR) of 17%-28% in three populations of European ancestry. Here, we refine the definition of the TCF7L2 type 2diabetes risk variant, HapB(T2D), to the ancestral T allele of a SNP, rs7903146, through replication in West African and Danish type 2 diabetes case-control studies and an expanded Icelandic study. We also identify another variant of the same gene, HapA, that shows evidence of positive selection in East Asian, European and West African populations. Notably, HapA shows a suggestive association with body mass index and altered concentrations of the hunger-satiety hormones ghrelin and leptin in males, indicating that the selective advantage of HapA may have been mediated through effects on energy metabolism
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