Review of eating disorders and oxytocin receptor polymorphisms.

BACKGROUND AND AIMS: Oxytocin, a nine amino acid peptide synthesised in the hypothalamus, has been widely recognised for its role in anxiolysis, bonding, sociality, and appetite. It binds to the oxytocin receptor (OXTR)-a G-protein coupled receptor-that is stimulated by the actions of oestrogen both peripherally and centrally. Studies have implicated OXTR genotypes in conferring either a risk or protective effect in autism, schizophrenia, and eating disorders (ED). There are numerous DNA variations of this receptor, with the most common DNA variation being in the form of the single nucleotide polymorphisms (SNPs). Two OXTR SNPs have been most studied in relation to ED: rs53576 and rs2254298. Each SNP has the same allelic variant that produces genotypes AA, AG, and GG. In this critical review we will evaluate the putative role of rs53576 and rs2254298 SNPs in ED. Additionally, this narrative review will consider the role of gene-environment interactions in the development of ED pathology. FINDINGS: The OXTR SNPs rs53576 and rs2254298 show independent associations between the A allele and restrictive eating behaviours. Conversely, the G allele of the OXTR rs53576 SNP is associated with binging behaviours, findings that were also evident in neuroanatomy. One study found the A allele of both OXTR SNPs to confer risk for more severe ED symptomatology while the G allele conferred some protective effect. An interaction between poor maternal care and rs2254298 AG/AA genotype conferred increased risk for binge eating and purging in women. CONCLUSIONS: Individual OXTR SNP are unlikely in themselves to explain complex eating disorders but may affect the expression of and/or effectiveness of the OXTR. A growing body of G x E work is indicating that rs53576G homozygosity becomes disadvantageous for later mental health under early adverse conditions but further research to extend these findings to eating pathology is needed. The GWAS approach would benefit this area of knowledge

GLI equations improve interpretation of FEV1 decline among patients with cystic fibrosis

No abstract for this research letter

The Assessment of Breeding Value of First Farrowed Sows by the Method of Selection Indices

The goal of this research paper was to assess the breeding value of first farrowed Swedish Landrace sows by the means of selection indices method. The traits on the basis of which the breeding value of animals was assessed are following: daily liveweight gain, average thickness of collected back fat measured at five sites and number of liveborn piglets in the first litter. The liveweight gain and carcass quality traits determined at the end of performance test were corrected for the body mass of 100kg by the method of basic indexes and following mean values were determined: for corrected daily liveweight gain (KZDP) 499.92g/day and for corrected average collected backfat thickness (KSL) 20.01mm. The first farrowed sows on average produced 8.09 liveborn piglets in the litter. Studying the effect of the gilts` birth year and season on KZDP and KSL it was determined that the gilts` birth year and season had no statistically significant influence (P>0.05) on KZDP variation but they had a statistically significant effect on KSL (P0.05) on BZPL, while the KZDP class and the age at first farrowing had a statistically significant effect on the variability of these trait (P<0.05; P<0.01). All studied traits varied statistically significantly (P<0.01) under the impact of the gilts` sire or dam. Heritability coefficients were: h2= 0.402 for KZDP, h2= 0.261 for KSL and h2= 0.177 for BZPL. The relation between KZDP and KSL was of a medium strength both at phenotype and genetic levels (rph=0.491; rg=0.411), while the relation of these traits with BZPL did not exist, except for the genetic relationship between KSL and KZDP which was of a medium strength (rg=0.252). Three equations for the selection indexes were constructed among which as the most optimal was chosen the one which includes all three traits (KZDP, KSL and BZPL) and whose correlation coefficent of selection index and aggregate genotype was rIAG = 0.5473

Spirometry reference equations for central European populations from school age to old age.

Spirometry reference values are important for the interpretation of spirometry results. Reference values should be updated regularly, derived from a population as similar to the population for which they are to be used and span across all ages. Such spirometry reference equations are currently lacking for central European populations. To develop spirometry reference equations for central European populations between 8 and 90 years of age. We used data collected between January 1993 and December 2010 from a central European population. The data was modelled using "Generalized Additive Models for Location, Scale and Shape" (GAMLSS). The spirometry reference equations were derived from 118'891 individuals consisting of 60'624 (51%) females and 58'267 (49%) males. Altogether, there were 18'211 (15.3%) children under the age of 18 years. We developed spirometry reference equations for a central European population between 8 and 90 years of age that can be implemented in a wide range of clinical settings

Exploring flexible polynomial regression as a method to align routine clinical outcomes with daily data capture through remote technologies

Data Availability: The data that support the findings of this study are available from Great Ormond Street Hospital, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Great Ormond Street Hospital.Copyright © The Author(s) 2023. Background: Clinical outcomes are normally captured less frequently than data from remote technologies, leaving a disparity in volumes of data from these different sources. To align these data, flexible polynomial regression was investigated to estimate personalised trends for a continuous outcome over time. Methods: Using electronic health records, flexible polynomial regression models inclusive of a 1st up to a 4th order were calculated to predict forced expiratory volume in 1 s (FEV1) over time in children with cystic fibrosis. The model with the lowest AIC for each individual was selected as the best fit. The optimal parameters for using flexible polynomials were investigated by comparing the measured FEV1 values to the values given by the individualised polynomial. Results: There were 8,549 FEV1 measurements from 267 individuals. For individuals with > 15 measurements (n = 178), the polynomial predictions worked well; however, with < 15 measurements (n = 89), the polynomial models were conditional on the number of measurements and time between measurements. The method was validated using BMI in the same population of children. Conclusion: Flexible polynomials can be used to extrapolate clinical outcome measures at frequent time intervals to align with daily data captured through remote technologies.UCL, GOSH and Toronto SickKids studentship. GD is supported by a Future Leaders Fellowship from UK Research & Innovation (UKRI), Grant reference: MR/T041285. All research at Great Ormond Street Hospital NHS Foundation Trust and UCL Great Ormond Street Institute of Child Health is made possible by the NIHR Great Ormond Street Hospital Biomedical Research Centre

The Terneuzen Birth Cohort: BMI Changes between 2 and 6 Years Correlate Strongest with Adult Overweight

Background: Complications of overweight amplify with age, and irreversible damage already exists in young persons. Identifying the most sensitive age interval(s) for adult overweight is relevant for primary prevention. The aim of the study was to assess the relative contribution of body mass index (BMI) changes between 0 and 18 years to adult overweight, and to identify the earliest critical growth period. Methods and Findings: Data from 762 subjects in the Terneuzen Birth Cohort with an average of 21 growth measurements per subject from birth until 18 years were used. The main outcome measure was the BMI standard deviation score (SDS) at young adulthood. For each subject BMI SDS was fitted by a piecewise linear model at eight different ages and correlated to adult BMI SDS. The age intervals in between are considered critical according to three criteria, tested by respectively Students' t-tests, multiple linear regression analyses and Pearson's correlation tests. In the age intervals 4 months(m) -1 year(y), 2-6 y, 6-10 y and 10-18 y the BMI SDS change differs between adults with and without overweight (P≤0.001). The age intervals 2-6 y and 10-18 y also meet the second criterion, implying that the BMI change during this period has a predictive value for adult BMI SDS in addition to BMI SDS at the end of the period. The largest rise in correlation between estimated BMI SDS and measured adult BMI SDS occurs during the period 2-6 y (from 0.36 to 0.63), which results in a high sensitivity (0.6) and specificity (0.8) by the age of 6 y. Conclusions/Significance: The age interval from 2 y to 6 y is the earliest and most critical growth period for adult overweight. Therefore, primary prevention of adult overweight seems most likely to be successful if targeted at this specific age interval. By identifying those with an upwards centile crossing between 2 and 6 years, the development towards adult overweight might be reversed. © 2010 De Kroon et al