Lasten ja nuorten ylipaino yleistyy asuinalueen maaseutumaisuuden lisääntyessä

Lasten ja nuorten yleistynyt ylipaino ja lihavuus sekä niihin yhteydessä olevat fyysiset ja psykososiaaliset terveysvaikutukset ovat merkittävä globaali kansanterveydellinen ongelma. Suomessa asuvista 2 16-vuotiaista pojista 29 prosentilla ja tytöistä 19 prosentilla oli ylipainoa (ml. lihavuus) vuonna 2021. Tässä tutkimuksessa tarkasteltiin millaisia eroja lasten ja nuorten ylipainon yleisyydessä oli kaupunkimaisten ja maaseutumaisten alueiden välillä vuonna 2019. Ylipainon ja lihavuuden yleisyyden analyyseissa aineistona oli 2 16-vuotiaiden lasten ja nuorten pituus- ja painotiedot, jotka perustuvat lastenneuvoloiden ja kouluterveydenhuollon terveystarkastuksissa vuoden 2019 aikana tehtyihin mittauksiin. Ylipainon ja lihavuu-den yleisyyttä tarkasteltiin lasten ja nuorten sukupuolen, ikäryhmän (2 6-vuotiaat, 7 12-vuotiaat ja 13 16-vuotiaat) ja seitsemänluokkaisen Suomen ympäristökeskuksen (SYKE) maaseutu-kaupunki-alueluokituksen mukaan

Mutations in the U11/U12-65K protein associated with isolated growth hormone deficiency lead to structural destabilization and impaired binding of U12 snRNA

Mutations in the components of the minor spliceosome underlie several human diseases. A subset of patients with isolated growth hormone deficiency (IGHD) harbors mutations in the RNPC3 gene, which encodes the minor spliceosome-specific U11/U12-65K protein. Although a previous study showed that IGHD patient cells have defects in U12-type intron recognition, the biochemical effects of these mutations on the 65K protein have not been characterized. Here, we show that a proline-to-threonine missense mutation (P474T) and a nonsense mutation (R502X) in the C-terminal RNA recognition motif (C-RRM) of the 65K protein impair the binding of 65K to U12 and U6atac snRNAs. We further show that the nonsense allele is targeted to the nonsense-mediated decay (NMD) pathway, but in an isoform-specific manner, with the nuclear-retained 65K long-3'UTR isoform escaping the NMD pathway. In contrast, the missense P474T mutation leads, in addition to the RNA-binding defect, to a partial defect in the folding of the C-RRM and reduced stability of the full-length protein, thus reducing the formation of U11/U12 di-snRNP complexes. We propose that both the C-RRM folding defect and NMD-mediated decrease in the levels of the U11/U12-65K protein reduce formation of the U12-type intron recognition complex and missplicing of a subset of minor introns leading to pituitary hypoplasia and a subsequent defect in growth hormone secretion.Peer reviewe

Valtava-hanke : Diabetesrekisterin pääraportti

Tässä raportissa kuvataan STM:n Toivo-ohjelman Valtava-hankkeen projektin "Diabetesrekisterin tietoallaspilotti" toteutusta ja tuloksia. Projekti toteutettiin vuosina 2020-2021 yhteistyössä Valtava-hankkeen Kelan projektin "Potilastiedon arkisto tietoaltaaseen (PTA)" sekä THL:n laaturekisterien kehittämisen projektin kanssa

Pituuden, painon ja BMIn kehityskulut lapsuudessa: Bayesilainen hierarkkinen mallinnus pitkittäisaineistolla

Children’s height and weight development remains a subject of interest especially due to increasing prevalence of overweight and obesity in the children. With statistical modeling, height and weight development can be examined as separate or connected outcomes, aiding with understanding of the phenomenon of growth. As biological connection between height and weight development can be assumed, their joint modeling is expected to be beneficial. One more advantage of joint modeling is its convenience of the Body Mass Index (BMI) prediction. In the thesis, we modeled longitudinal data of children’s heights and weights of the dataset obtained from Finlapset register of the Institute of Health and Welfare (THL). The research aims were to predict the modeled quantities together with the BMI, interpret the obtained parameters with relation to the phenomenon of growth, as well as to investigate the impact of municipalities on to the growth of children. The dataset’s irregular, register-based nature together with positively skewed, heteroschedastic weight distributions and within- and between-subject variability suggested Hierarchical Linear Models (HLMs) as the modeling method of choice. We used HLMs in Bayesian setting with the benefits of incorporating existing knowledge, and obtaining full posterior predictive distribution for the outcome variables. HLMs were compared with the less suitable classical linear regression model, and bivariate and univariate HLMs with or without area as a covariate were compared in terms of their posterior predictive precision and accuracy. One of the main research questions was the model’s ability to predict the BMI of the child, which we assessed with various posterior predictive checks (PPC). The most suitable model was used to estimate growth parameters of 2-6 year old males and females in Vihti, Kirkkonummi and Tuusula. With the parameter estimates, we could compare growth of males and females, assess the differences of within-subject and between-subject variability on growth and examine correlation between height and weight development. Based on the work, we could conclude that the bivariate HLM constructed provided the most accurate and precise predictions especially for the BMI. The area covariates did not provide additional advantage to the models. Overall, Bayesian HLMs are a suitable tool for the register-based dataset of the work, and together with log-transformation of height and weight they can be used to model skewed and heteroschedastic longitudinal data. However, the modeling would ideally require more observations per individual than we had, and proper out-of-sample predictive evaluation would ensure that current models are not over-fitted with regards to the data. Nevertheless, the built models can already provide insight into contemporary Finnish childhood growth and to simulate and create predictions for the future BMI population distributions