Low grade mosaic for a complex supernumerary ring chromosome 18 in an adult patient with multiple congenital anomalies

Background. Several cases have been reported of patients with a ring chromosome 18 replacing one of the normal chromosomes 18. Less common are patients with a supernumerary ring chromosomes 18. High resolution whole genome examination in patients with multiple congenital abnormalities might reveal cytogenetic abnormalities of an unexpected complexity. Results. We report a 24 years old male patient with lower spinal anomalies, hypospadia, bifid scrotum, cryptorchism, anal atresia, kidney stones, urethra anomalies, radial dysplasia, and a hypoplastic thumb. Some of the anomalies overlap with the VACTERL association. Chromosome analysis of cultured peripheral blood lymphocytes revealed an additional ring chromosome in 13% of the metaphases. Both parents had a normal karyotype, demonstrating the de novo origin of this ring chromosome. FISH analysis using whole chromosome paints showed that the additional chromosomal material was derived from chromosome 18. Chromosome analysis of cultured fibroblasts revealed only one cell with the supernumerary ring chromosome in the 400 analyzed. To characterize the ring chromosome in more detail peripheral blood derived DNA was analyzed using SNP-arrays. The array results indicated a 5 Mb gain of the pericentromeric region of chromosome 18q10-q11.2. FISH analysis using BAC-probes located in the region indicated the presence of 6 signals on the r(18) chromosome. In addition, microsatellite analysis demonstrated that the unique supernumerary ring chromosome was paternally derived and both normal copies showed biparental disomy. Conclusions. We report on an adult patient with multiple congenital abnormalities who had in 13% of his cells a unique supernumerary ring chromosome 18 that was composed of 6 copies of the 5 Mb gene rich region of 18q11

EuropeaN Energy balance Research to prevent excessive weight Gain among Youth (ENERGY) project: Design and methodology of the ENERGY cross-sectional survey

Background: Obesity treatment is by large ineffective long term, and more emphasis on the prevention of excessive weight gain in childhood and adolescence is warranted. To inform energy balance related behaviour (EBRB) change interventions, insight in the potential personal, family and school environmental correlates of these behaviours is needed. Studies on such multilevel correlates of EBRB among schoolchildren in Europe are lacking. The ENERGY survey aims to (1) provide up-to-date prevalence rates of measured overweight, obesity, self-reported engagement in EBRBs, and objective accelerometer-based assessment of physical activity and sedentary behaviour and blood-sample biomarkers of metabolic function in countries in different regions of Europe, (2) to identify personal, family and school environmental correlates of these EBRBs. This paper describes the design, methodology and protocol of the survey. Method/Design: A school-based cross-sectional survey was carried out in 2010 in seven different European countries; Belgium, Greece, Hungary, the Netherlands, Norway, Slovenia, and Spain. The survey included measurements of anthropometrics, child, parent and school-staff questionnaires, and school observations to measure and assess outcomes (i.e. height, weight, and waist circumference), EBRBs and potential personal, family and school environmental correlates of these behaviours including the social-cultural, physical, political, and economic environmental factors. In addition, a selection of countries conducted accelerometer measurements to objectively assess physical activity and sedentary behaviour, and collected blood samples to assess several biomarkers of metabolic function. Discussion: The ENERGY survey is a comprehensive cross-sectional study measuring anthropometrics and biomarkers as well as assessing a range of EBRBs and their potential correlates at the personal, family and school level, among 10-12 year old children in seven European countries. This study will result in a unique dataset, enabling cross country comparisons in overweight, obesity, risk behaviours for these conditions as well as the correlates of engagement in these risk behaviours

Sedentary Time and Physical Activity Surveillance Through Accelerometer Pooling in Four European Countries.

OBJECTIVE: The objective of this study was to pool, harmonise and re-analyse national accelerometer data from adults in four European countries in order to describe population levels of sedentary time and physical inactivity. METHODS: Five cross-sectional studies were included from England, Portugal, Norway and Sweden. ActiGraph accelerometer count data were centrally processed using the same algorithms. Multivariable logistic regression analyses were conducted to study the associations of sedentary time and physical inactivity with sex, age, weight status and educational level, in both the pooled sample and the separate study samples. RESULTS: Data from 9509 participants were used. On average, participants were sedentary for 530 min/day, and accumulated 36 min/day of moderate to vigorous intensity physical activity. Twenty-three percent accumulated more than 10 h of sedentary time/day, and 72% did not meet the physical activity recommendations. Nine percent of all participants were classified as high sedentary and low active. Participants from Norway showed the highest levels of sedentary time, while participants from England were the least physically active. Age and weight status were positively associated with sedentary time and not meeting the physical activity recommendations. Men and higher-educated people were more likely to be highly sedentary, while women and lower-educated people were more likely to be inactive. CONCLUSIONS: We found high levels of sedentary time and physical inactivity in four European countries. Older people and obese people were most likely to display these behaviours and thus deserve special attention in interventions and policy planning. In order to monitor these behaviours, accelerometer-based cross-European surveillance is recommended.The original studies were funded by the Norwegian Directorate of Health and the Norwegian School of Sport Sciences; the Portuguese Institute of Sport; a grant from the Stockholm County Council; and grants from the Swedish Council for Working Life and Social Research, and The Swedish Research Council for Environment, Agricultural Sciences, and Spatial Planning. AL, JL, JB and HvdP were supported by the Netherlands Organisation for Health Research and Development (Grant no. 200.600.001). KS was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health (award no. R01HL116381). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. KW was supported by the British Heart Foundation (Grant FS/12/58/29709). KW and SB were supported by the UK Medical Research Council (Grant MC_UU_12015/3)

¹⁸F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma

PURPOSE: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. METHODS: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. RESULTS: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUV(peak) and the maximal distance between the largest lesion and any other lesion (Dmax(bulk), AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUV(peak) and Dmax(bulk)) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). CONCLUSION: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance. TRIAL REGISTRATION NUMBER AND DATE: EudraCT: 2006–005,174-42, 01–08-2008. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-021-05480-3