Identifying risk profiles for childhood obesity using recursive partitioning based on individual, familial, and neighborhood environment factors.

International audienceFew studies consider how risk factors within multiple levels of influence operate synergistically to determine childhood obesity. We used recursive partitioning analysis to identify unique combinations of individual, familial, and neighborhood factors that best predict obesity in children, and tested whether these predict 2-year changes in body mass index (BMI). Data were collected in 2005-2008 and in 2008-2011 for 512 Quebec youth (8-10 years at baseline) with a history of parental obesity (QUALITY study). CDC age- and sex-specific BMI percentiles were computed and children were considered obese if their BMI was ≥95th percentile. Individual (physical activity and sugar-sweetened beverage intake), familial (household socioeconomic status and measures of parental obesity including both BMI and waist circumference), and neighborhood (disadvantage, prestige, and presence of parks, convenience stores, and fast food restaurants) factors were examined. Recursive partitioning, a method that generates a classification tree predicting obesity based on combined exposure to a series of variables, was used. Associations between resulting varying risk group membership and BMI percentile at baseline and 2-year follow up were examined using linear regression. Recursive partitioning yielded 7 subgroups with a prevalence of obesity equal to 8%, 11%, 26%, 28%, 41%, 60%, and 63%, respectively. The 2 highest risk subgroups comprised i) children not meeting physical activity guidelines, with at least one BMI-defined obese parent and 2 abdominally obese parents, living in disadvantaged neighborhoods without parks and, ii) children with these characteristics, except with access to ≥1 park and with access to ≥1 convenience store. Group membership was strongly associated with BMI at baseline, but did not systematically predict change in BMI. Findings support the notion that obesity is predicted by multiple factors in different settings and provide some indications of potentially obesogenic environments. Alternate group definitions as well as longer duration of follow up should be investigated to predict change in obesity

Innovation through Wearable Sensors to Collect Real-Life Data among Pediatric Patients with Cardiometabolic Risk Factors

Background. While increasing evidence links environments to health behavior, clinicians lack information about patients’ physical activity levels and lifestyle environments. We present mobile health tools to collect and use spatio-behavioural lifestyle data for personalized physical activity plans in clinical settings. Methods. The Dyn@mo lifestyle intervention was developed at the Sainte-Justine University Hospital Center to promote physical activity and reduce sedentary time among children with cardiometabolic risk factors. Mobility, physical activity, and heart rate were measured in free-living environments during seven days. Algorithms processed data to generate spatio-behavioural indicators that fed a web-based interactive mapping application for personalised counseling. Proof of concept and tools are presented using data collected among the first 37 participants recruited in 2011. Results. Valid accelerometer data was available for 5.6 (SD=1.62) days in average, heart rate data for 6.5 days, and GPS data was available for 6.1 (2.1) days. Spatio-behavioural indicators were shared between patients, parents, and practitioners to support counseling. Conclusion. Use of wearable sensors along with data treatment algorithms and visualisation tools allow to better measure and describe real-life environments, mobility, physical activity, and physiological responses. Increased specificity in lifestyle interventions opens new avenues for remote patient monitoring and intervention

Natural history and determinants of dysglycemia in Canadian children with parental obesity from ages 8–10 to 15–17 years : the QUALITY cohort

In children, the mechanisms implicated in deterioration of glucose homeostasis versus reversion to normal glucose tolerance (NGT) remain uncertain. We aimed to describe the natural history of dysglycemia from childhood to late adolescence and to identify its early determinants. We used baseline (8–10 years, n = 630), 1st follow-up (10–12 years, n = 564) and 2nd follow-up (15–17 years, n = 377) data from the QUALITY cohort of White Canadian children with parental obesity. Children underwent a 2-h oral glucose tolerance test at each cycle with plasma glucose and insulin measured at 0/30/60/90/120 min. American Diabetes Association criteria defined dysglycemia (impaired fasting glucose, impaired glucose tolerance or type 2 diabetes). Longitudinal patterns of insulin sensitivity and beta-cell function were estimated using generalized additive mixed models. Model averaging identified biological, sociodemographic and lifestyle-related determinants of dysglycemia. Of the children NGT at baseline, 66 (21%) developed dysglycemia without reverting to NGT. Among children with dysglycemia at baseline, 24 (73%) reverted to NGT. In children with dysglycemia at 1st follow-up, 18 (53%) later reverted to NGT. Among biological, sociodemographic and lifestyle determinants at 8–10 years, only fasting and 2-h glucose were associated with developing dysglycemia (odds ratio [95% CI] per 1 mmol/L increase: 4.50 [1.06; 19.02] and 1.74 [1.11; 2.73], respectively). Beta-cell function decreased by 40% in children with overweight or obesity. In conclusion, up to 75% of children with dysglycemia reverted to NGT during puberty. Children with higher fasting and 2-h glucose were at higher risk for progression to dysglycemia, while no demographic/lifestyle determinants were identified

Ablation of the Sam68 RNA Binding Protein Protects Mice from Age-Related Bone Loss

The Src substrate associated in mitosis of 68 kDa (Sam68) is a KH-type RNA binding protein that has been shown to regulate several aspects of RNA metabolism; however, its physiologic role has remained elusive. Herein we report the generation of Sam68-null mice by homologous recombination. Aged Sam68(−/−) mice preserved their bone mass, in sharp contrast with 12-month-old wild-type littermates in which bone mass was decreased up to approximately 75%. In fact, the bone volume of the 12-month-old Sam68(−/−) mice was virtually indistinguishable from that of 4-month-old wild-type or Sam68(−/−) mice. Sam68(−/−) bone marrow stromal cells had a differentiation advantage for the osteogenic pathway. Moreover, the knockdown of Sam68 using short hairpin RNA in the embryonic mesenchymal multipotential progenitor C3H10T1/2 cells resulted in more pronounced expression of the mature osteoblast marker osteocalcin when differentiation was induced with bone morphogenetic protein-2. Cultures of mouse embryo fibroblasts generated from Sam68(+/+) and Sam68(−/−) littermates were induced to differentiate into adipocytes with culture medium containing pioglitazone and the Sam68(−/−) mouse embryo fibroblasts shown to have impaired adipocyte differentiation. Furthermore, in vivo it was shown that sections of bone from 12-month-old Sam68(−/−) mice had few marrow adipocytes compared with their age-matched wild-type littermate controls, which exhibited fatty bone marrow. Our findings identify endogenous Sam68 as a positive regulator of adipocyte differentiation and a negative regulator of osteoblast differentiation, which is consistent with Sam68 being a modulator of bone marrow mesenchymal cell differentiation, and hence bone metabolism, in aged mice

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Widespread genomic influences on phenotype in Dravet syndrome, a ‘monogenic’ condition

Dravet syndrome is an archetypal rare severe epilepsy, considered “monogenic”, typically caused by loss-of-function SCN1A variants. Despite a recognisable core phenotype, its marked phenotypic heterogeneity is incompletely explained by differences in the causal SCN1A variant or clinical factors. In 34 adults with SCN1A-related Dravet syndrome, we show additional genomic variation beyond SCN1A contributes to phenotype and its diversity, with an excess of rare variants in epilepsy-related genes as a set and examples of blended phenotypes, including one individual with an ultra-rare DEPDC5 variant and focal cortical dysplasia. Polygenic risk scores for intelligence are lower, and for longevity, higher, in Dravet syndrome than in epilepsy controls. The causal, major-effect, SCN1A variant may need to act against a broadly compromised genomic background to generate the full Dravet syndrome phenotype, whilst genomic resilience may help to ameliorate the risk of premature mortality in adult Dravet syndrome survivors

Use of whole genome sequencing to determine genetic basis of suspected mitochondrial disorders: cohort study

Funder: University of Cambridge; FundRef: http://dx.doi.org/10.13039/501100000735Funder: Alzheimer's Society; FundRef: http://dx.doi.org/10.13039/501100000320Funder: Leverhulme Trust; FundRef: http://dx.doi.org/10.13039/501100000275Funder: National Institute for Health Research; FundRef: http://dx.doi.org/10.13039/501100000272Funder: Department of Health; FundRef: http://dx.doi.org/10.13039/501100000276Funder: Evelyn Trust; FundRef: http://dx.doi.org/10.13039/501100004282Funder: Wellcome Trust; FundRef: http://dx.doi.org/10.13039/100004440Funder: Medical Research Council; FundRef: http://dx.doi.org/10.13039/501100000265Abstract: Objective: To determine whether whole genome sequencing can be used to define the molecular basis of suspected mitochondrial disease. Design: Cohort study. Setting: National Health Service, England, including secondary and tertiary care. Participants: 345 patients with suspected mitochondrial disorders recruited to the 100 000 Genomes Project in England between 2015 and 2018. Intervention: Short read whole genome sequencing was performed. Nuclear variants were prioritised on the basis of gene panels chosen according to phenotypes, ClinVar pathogenic/likely pathogenic variants, and the top 10 prioritised variants from Exomiser. Mitochondrial DNA variants were called using an in-house pipeline and compared with a list of pathogenic variants. Copy number variants and short tandem repeats for 13 neurological disorders were also analysed. American College of Medical Genetics guidelines were followed for classification of variants. Main outcome measure: Definite or probable genetic diagnosis. Results: A definite or probable genetic diagnosis was identified in 98/319 (31%) families, with an additional 6 (2%) possible diagnoses. Fourteen of the diagnoses (4% of the 319 families) explained only part of the clinical features. A total of 95 different genes were implicated. Of 104 families given a diagnosis, 39 (38%) had a mitochondrial diagnosis and 65 (63%) had a non-mitochondrial diagnosis. Conclusion: Whole genome sequencing is a useful diagnostic test in patients with suspected mitochondrial disorders, yielding a diagnosis in a further 31% after exclusion of common causes. Most diagnoses were non-mitochondrial disorders and included developmental disorders with intellectual disability, epileptic encephalopathies, other metabolic disorders, cardiomyopathies, and leukodystrophies. These would have been missed if a targeted approach was taken, and some have specific treatments

Spectrum of mutational signatures in T-cell lymphoma reveals a key role for UV radiation in cutaneous T-cell lymphoma

Funder: Galderma; doi: http://dx.doi.org/10.13039/501100009754Funder: NIHR-BRC Cambridge core grantFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272Funder: NHS EnglandAbstract: T-cell non-Hodgkin’s lymphomas develop following transformation of tissue resident T-cells. We performed a meta-analysis of whole exome sequencing data from 403 patients with eight subtypes of T-cell non-Hodgkin’s lymphoma to identify mutational signatures and associated recurrent gene mutations. Signature 1, indicative of age-related deamination, was prevalent across all T-cell lymphomas, reflecting the derivation of these malignancies from memory T-cells. Adult T-cell leukemia-lymphoma was specifically associated with signature 17, which was found to correlate with the IRF4 K59R mutation that is exclusive to Adult T-cell leukemia-lymphoma. Signature 7, implicating UV exposure was uniquely identified in cutaneous T-cell lymphoma (CTCL), contributing 52% of the mutational burden in mycosis fungoides and 23% in Sezary syndrome. Importantly this UV signature was observed in CD4 + T-cells isolated from the blood of Sezary syndrome patients suggesting extensive re-circulation of these T-cells through skin and blood. Analysis of non-Hodgkin’s T-cell lymphoma cases submitted to the national 100,000 WGS project confirmed that signature 7 was only identified in CTCL strongly implicating UV radiation in the pathogenesis of cutaneous T-cell lymphoma