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We evaluated possible mediators underlying lifestyle intervention effects on neonatal adiposity, assessed with sum of skinfolds and cord blood leptin. This is a secondary analysis of the DALI study, a randomised controlled trial in nine European countries. Pregnant women with a pre-pregnancy body mass index of ≥29 kg/m2 were randomly assigned to counselling for healthy eating (HE), physical activity (PA), HE&PA combined, or to usual care. We considered five maternal metabolic factors at 24–28 and 35–37 weeks of gestation, and four cord blood factors as possible mediators of the effect of combined HE&PA counselling on neonatal adiposity. From all potential mediators, the intervention only affected cord blood non-esterified fatty acids (NEFA), which was higher in the HE&PA group compared to UC (0.068 (mmol/L), 95% CI: 0.004 to 0.133). Cord blood NEFA did not mediate the HE&PA intervention effects on neonatal sum of skinfolds or cord blood leptin, based on an indirect effect on skinfolds of 0.018 (mm), 95% CI: −0.217 to 0.253 and an indirect effect on leptin of −0.143 (μg/l), 95% CI: −0.560 to 0.273. The Dali study observed reductions in neonatal adiposity in pregnant women with obesity, but we were not able to identify the underlying metabolic pathway.

Additional file 1.

Die Hyperglykämie ist wesentlich an der Entstehung der Spätkomplikationen bei an Diabetes mellitus Typ 2 erkrankten Patienten/Patientinnen beteiligt. Während Lebensstilmaßnahmen die Eckpfeiler jeder Diabetestherapie bleiben, benötigen im Verlauf die meisten Patienten/Patientinnen mit Typ 2 Diabetes eine medikamentöse Therapie. Bei der Definition individueller Behandlungsziele stellen die Therapiesicherheit, die Effektivität sowie substanzspezifische, kardiovaskuläre Effekte der Therapie die wichtigsten Faktoren dar. In dieser Leitlinie haben wir die rezenten evidenzbasierten Daten für die klinische Praxis zusammengestellt. Hyperglycemia significantly contributes to complications in patients with diabetes mellitus. While lifestyle interventions remain cornerstones of disease prevention and treatment, most patients with type 2 diabetes will eventually require pharmacotherapy for glycemic control. The definition of individual targets regarding optimal therapeutic efficacy and safety as well as cardiovascular effects is of great importance. In this guideline we present the most current evidence-based best clinical practice data for healthcare professionals. Version of record

Der Body-Mass-Index (BMI) ist individuell betrachtet ein sehr grobes Maß für den Anteil des Körperfetts am Körpergewicht. Sogar Normalgewichtige können bei Muskelmangel zu viel Körperfett aufweisen (Sarkopenie), weswegen zusätzlich Messungen der Körperzusammensetzung (z. B. Bioimpedanzanalyse [BIA]) empfohlen werden. Lebensstilmanagement mit Ernährungsumstellung und Bewegung ist eine der wichtigsten Maßnahmen in der Diabetesprävention und -therapie. In der Therapie des Typ-2-Diabetes hat das Gewicht als sekundärer Zielparameter zunehmende Bedeutung erlangt. Auch die Wahl der antidiabetischen Therapie, aber auch der Begleittherapien nimmt immer mehr darauf Rücksicht. Die modernen GLP‑1 Analoga als auch der kombinierte GLP-1–GIP-Agonist Tirzepatid nehmen einen wichtigen Stellenwert in der gemeinsamen Behandlung von Adipositas und Diabetes mellitus Typ 2 ein. Die bariatrische Chirurgie ist derzeit bei an Diabetes mellitus Typ 2 erkrankten Menschen mit BMI > 35 kg/m2 indiziert und kann zumindest teilweise zur Diabetesremission beitragen, sie muss aber in ein entsprechendes lebenslanges Betreuungskonzept eingebunden sein. The body mass index (BMI) is a very crude measure of body fatness in individuals. Even normal weight persons can have too much body fat in cases of a lack of muscle mass (sarcopenia), which is why additional measurements of waist circumference and body fatness, e.g. bioimpedance analysis (BIA), are recommended. Lifestyle management including nutrition modification and increase in physical activity are important measures for the prevention and treatment of diabetes. Regarding the treatment of type 2 diabetes, body weight is increasingly used as a secondary target parameter. The choice of anti-diabetic treatment and additional concomitant therapies is increasingly influenced by body weight. The importance of modern GLP‑1 agonists and dual GLP‑1 GIP agonists increases since these drugs target obesity and type 2 diabetes. Bariatric surgery is at present indicated with a BMI > 35 kg/m2 with concomitant risk factors, such as diabetes and can lead at least to partial diabetes remission but has to be incorporated into an appropriate lifelong care concept. Version of record

Shared etiological pathways are suggested in ASD and ADHD given high rates of comorbidity, phenotypic overlap and shared genetic susceptibility. Given the peak of cortical gyrification expansion and emergence of ASD and ADHD symptomology in early development, we investigated gyrification morphology in 539 children and adolescents (6–17 years of age) with ASD (n=197) and ADHD (n=96) compared to typically developing controls (n=246) using the local Gyrification Index (lGI) to provide insight into contributing etiopathological factors in these two disorders. We also examined IQ effects and functional implications of gyrification by exploring the relation between lGI and ASD and ADHD symptomatology beyond diagnosis. General Linear Models yielded no group differences in lGI, and across groups, we identified an age-related decrease of lGI and greater lGI in females compared to males. No diagnosis-by-age interactions were found. Accounting for IQ variability in the model (n=484) yielded similar results. No significant associations were found between lGI and social communication deficits, repetitive and restricted behaviours, inattention or adaptive functioning. By examining both disorders and controls using shared methodology, we found no evidence of atypicality in gyrification as measured by the lGI in these conditions.

Social communication differences are seen in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive–compulsive disorder (OCD), but the brain mechanisms contributing to these differences remain largely unknown. To address this gap, we used a data-driven and diagnosis-agnostic approach to discover brain correlates of social communication differences in ASD, ADHD, and OCD, and subgroups of individuals who share similar patterns of brain-behavior associations. A machine learning pipeline (regression clustering) was used to discover the pattern of association between structural brain measures (volume, surface area, and cortical thickness) and social communication abilities. Participants (n = 416) included children with a diagnosis of ASD (n = 192, age = 12.0[5.6], 19% female), ADHD (n = 109, age = 11.1[4.1], 18% female), or OCD (n = 50, age = 12.3[4.2], 42% female), and typically developing controls (n = 65, age = 11.6[7.1], 48% female). The analyses revealed (1) associations with social communication abilities in distributed cortical and subcortical networks implicated in social behaviors, language, attention, memory, and executive functions, and (2) three data-driven, diagnosis-agnostic subgroups based on the patterns of association in the above networks. Our results suggest that different brain networks may contribute to social communication differences in subgroups that are not diagnosis-specific.

The authors regret that a few lines in Tables 1 and 2 were formatted incorrectly in the published version of the article with numbers all appearing in one line instead of being in separate lines. The correctly formatted tables are shown below. The authors would like to apologise for any inconvenience caused.