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Sökning: WFRF:(Reinehr Thomas)

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1.
  • Speliotes, Elizabeth K., et al. (författare)
  • Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
  • 2010
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 937-948
  • Tidskriftsartikel (refereegranskat)abstract
    • Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ~2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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2.
  • Dimitri, P., et al. (författare)
  • An eHealth Framework for Managing Pediatric Growth Disorders and Growth Hormone Therapy
  • 2021
  • Ingår i: Journal of Medical Internet Research. - : JMIR Publications Inc.. - 1438-8871. ; 23:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The use of technology to support health and health care has grown rapidly in the last decade across all ages and medical specialties. Newly developed eHealth tools are being implemented in long-term management of growth failure in children, a low prevalence pediatric endocrine disorder. Objective: Our objective was to create a framework that can guide future implementation and research on the use of eHealth tools to support patients with growth disorders who require growth hormone therapy. Methods: A total of 12 pediatric endocrinologists with experience in eHealth, from a wide geographical distribution, participated in a series of online discussions. We summarized the discussions of 3 workshops, conducted during 2020, on the use of eHealth in the management of growth disorders, which were structured to provide insights on existing challenges, opportunities, and solutions for the implementation of eHealth tools across the patient journey, from referral to the end of pediatric therapy. Results: A total of 815 responses were collected from 2 questionnaire-based activities covering referral and diagnosis of growth disorders, and subsequent growth hormone therapy stages of the patient pathway, relating to physicians, nurses, and patients, parents, or caregivers. We mapped the feedback from those discussions into a framework that we developed as a guide to integration of eHealth tools across the patient journey. Responses focused on improved clinical management, such as growth monitoring and automation of referral for early detection of growth disorders, which could trigger rapid evaluation and diagnosis. Patient support included the use of eHealth for enhanced patient and caregiver communication, better access to educational opportunities, and enhanced medical and psychological support during growth hormone therapy management. Given the potential availability of patient data from connected devices, artificial intelligence can be used to predict adherence and personalize patient support. Providing evidence to demonstrate the value and utility of eHealth tools will ensure that these tools are widely accepted, trusted, and used in clinical practice, but implementation issues (eg, adaptation to specific clinical settings) must be addressed. Conclusions: The use of eHealth in growth hormone therapy has major potential to improve the management of growth disorders along the patient journey. Combining objective clinical information and patient adherence data is vital in supporting decision-making and the development of new eHealth tools. Involvement of clinicians and patients in the process of integrating such technologies into clinical practice is essential for implementation and developing evidence that eHealth tools can provide value across the patient pathway.
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3.
  • Reinehr, Thomas, et al. (författare)
  • Is growth hormone treatment in children associated with weight gain? : Longitudinal analysis of KIGS data
  • 2014
  • Ingår i: Clinical Endocrinology. - : Wiley. - 0300-0664 .- 1365-2265. ; 81:5, s. 721-726
  • Tidskriftsartikel (refereegranskat)abstract
    • ObjectiveGrowth hormone (GH) increases lean body mass and reduces fat mass. However, the long-term changes in weight status during growth hormone treatment, according to age and weight status at onset of treatment, have not previously been reported in large data sets. MethodsChanges in BMI-SDS between starting GH treatment and attaining near adult height (NAH) were analysed in 2643 children with idiopathic GH deficiency (IGHD), 281 children small for gestational age (SGA), 1661 girls with Turner syndrome (TS), and 142 children with Prader-Willi syndrome (PWS) in the KIGS database. ResultsBMI-SDS increased significantly between onset of GH treatment and NAH (IGHD:+029, SGA:+069, TS:+048) except in PWS (-002). These increases were greater in children with younger age at onset of GH treatment (significant in all indications) and with lower doses of GH treatment (significant in IGHD & TS) in multiple linear regression analyses also including gender, duration of GH treatment, BMI-SDS and height-SDS at onset of treatment, and birth weight-SDS. Obese children at onset of GH treatment decreased their BMI-SDS, while underweight and normal weight children at onset of GH treatment increased their BMI-SDS independently of GH treatment indication. ConclusionsLong-term GH treatment was associated with changes in weight status, which were beneficial for underweight and obese children independent of the indication for GH. However, the increase in BMI-SDS in normal weight children treated with GH needs to be investigated in future prospective longitudinal studies to analyse whether this represents an increase of fat mass, lean body mass or both.
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