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Additional file 1: S1 STROBE Checklist. S2 TRIPOD Statement. Text S1. Statistical analysis plan. Text S2. Statistical methods. Text S3. Quantification of individual risk. Figure S1. Influence of maternal obesity on offspring BMI growth outcomes. Shown are ORs and 95% CIs of the influence of maternal pre-conception obesity on BMI growth outcomes up to age 5 years in all offspring belonging to upper BMI growth clusters from the PEACHES cohort study. Values were derived from univariate logistic regression. aThe term “multiple occasions” was defined as having BMI z-scores >1 SD [51] at least 5 out of 6 times at the well-child visits at age 6 months, 1 year, 2 years, 3 years, 4 years, and 5 years. BMI, body mass index; CI, confidence interval; OR, odds ratio; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening. Figure S2. Proportion of offspring in upper and lower BMI growth clusters according to birth weight category. Shown are percentages in offspring of mothers with obesity (panel A) and without (panel B) enrolled in the PEACHES cohort study, according to their birth weight category for gestational age and sex. AGA, average-for-gestational-age; BMI, body mass index; LGA, large-for-gestational-age; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening; SGA, small-for-gestational-age. Figure S3. Mean BMI growth clusters by birth weight category in offspring of mothers with and without obesity. Shown are mean BMI z-score growth clusters from birth to age 6 months (panel A, C) and birth to age 5 years (panel B, D) by birth weight category for gestational age and sex in offspring of mothers with and without obesity enrolled in the PEACHES cohort study. AGA, average-for-gestational-age; BMI, body mass index; LGA, large-for-gestational-age; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening; SGA, small-for-gestational-age. Figure S4. Effects of prenatal and postnatal factors on BMI growth outcomes in offspring of mothers without obesity. Shown are ORs and 95% CI of the influence of prenatal and postnatal factors on the development of an upper cluster of BMI growth (birth to age 5 years, panel A) and a “higher-than-normal BMI growth pattern,” defined as BMI z-score >1 SD [51] at least twice, during early phase (6 months to 2 years, panel B) and late phase (3 years to 5 years, panel C) in offspring of mothers without obesity enrolled in the PEACHES cohort study. Values were derived from multivariable logistic regression with stepwise backward selection. Only final models based on the lowest Akaike information criterion are presented. Included variables in all initial models were maternal pre-conception BMI group, total GWG, GDM, parity, smoking during pregnancy, sex, birth weight category for gestational age and sex, SES, breastfeeding status at 1 month. Additionally, for associations shown in panel C, “higher-than-normal BMI growth pattern” in the early phase was also included as an explanatory variable in the initial model. BMI, body mass index; CI, confidence interval; GDM, gestational diabetes; GWG, gestational weight gain; LGA, large-for-gestational-age; OR, odds ratio; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening; SES, socioeconomic status; SGA, small-for-gestational-age. Figure S5. Calibration plots of prediction models for identifying a “higher-than-normal BMI growth pattern” in the validation cohort. Shown are calibration curves (blue lines) and calibration slopes and intercepts for offspring of mothers with obesity (panel A, B) and without obesity (panel C, D) by the prediction models at age 1 year and 2 years. The diagonal gray lines represent the optimal prediction; the closer the model curve is to the diagonal line, the more accurate is the prediction. At the top of each graph, dots indicate presence of the outcome “higher-than-normal BMI growth pattern,” defined as BMI z-score >1 SD [51] at least twice, in the late phase (3 years to 5 years). At the bottom of each graph, dots indicate absence of the outcome “higher-than-normal BMI growth pattern” in the late phase. Calibration of models at age 3 months for “higher-than-normal BMI growth pattern” in the early phase (6 months to 2 years) could not be performed due to the lack of follow-up data at age 3 months in the validation cohort PEPO. BMI, body mass index; PEPO, PErinatal Prevention of Obesity. Table S1. Offspring follow-up rates in the study populations. Values are n (%). aMissing data in the PEACHES cohort were due to loss to follow-up. Missing data in the PEPO cohort were due to lack of availability of data in the records of the regular well-child visits at the time of school entry health examination. bA total of 13 and 297 children enrolled in the PEACHES cohort were too young for the follow-up visit at age 4 and 5 years, respectively, and therefore were not included in the “total” category. Missing data were considered missing completely at random. NA, not available; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening; PEPO, PErinatal Prevention of Obesity. Table S2. Mean BMI z-scores by BMI growth cluster in offspring of mothers with and without obesity. Values are mean and 95% CI in offspring of mothers with and without obesity enrolled in the PEACHES cohort study. aOf a total of 887 children included for cluster analysis, 875 children could be categorized into longitudinal BMI growth clusters based on an adequate number of data points. bOf a total of 670 children included for cluster analysis, 655 children could be categorized into clusters based on an adequate number of data points. cA total of 276 and 549 children enrolled in the PEACHES cohort were not included in the cluster analysis at age 4 and 5 years, respectively, because of follow-up not yet due (age 4 years: n=13, age 5 years: n=297) or missing data due to loss to follow-up (age 4 years: n=263, age 5 years: n=252). Missing data were considered missing completely at random. BMI, body mass index; CI, confidence interval; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening. Table S3. Offspring BMI growth dynamics in consecutive life phases after birth following exposure to gestational obesity. Values are n (%) in offspring enrolled in the PEACHES cohort study. Only children with complete data on BMI z-scores in both the early and late phase are presented. aIncludes values for categories “normal range” (≥-2 to ≤1 SD) and a minor proportion of children with 1 SD defined as occurring once. Includes values for categories “at risk of overweight” (>1 to ≤2 SD), overweight (>2 to ≤3 SD), and obesity (>3 SD) [51]. c“Higher-than-normal BMI growth pattern” defined as BMI z-score >1 SD [51] at least twice. BMI, body mass index; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening. Table S4. Predictive performance of a sequential algorithm to identify higher-than-normal BMI growth in offspring of mothers without obesity. We used the PEACHES cohort study as the discovery cohort and the PEPO cohort study as the external validation cohort for calculation of the individual child’s risk of a “higher-than-normal BMI growth pattern” (BMI z-score >1 SD [51] at least twice). Values are predictive parameters and their 95% CI. aPotential predictors included: maternal pre-conception BMI group, total GWG, GDM, parity, smoking during pregnancy, sex, birth weight category for gestational age and sex, SES, breastfeeding status at 1 month, breastfeeding status at 3 months, and BMI z-score >1 SD at age 3 months. External validation of models at age 3 months could not be performed due to the lack of follow-up data at age 3 months in the validation cohort PEPO. bPotential predictors included: maternal pre-conception BMI group, total GWG, GDM, parity, smoking during pregnancy, sex, birth weight category for gestational age and sex, SES, breastfeeding status at 1 month, breastfeeding status at 3 months, breastfeeding status at 6 months, and BMI z-score >1 SD at age 1 year. External validation of models at age 1 year was performed in the validation cohort PEPO. cPotential predictors included: maternal pre-conception BMI group, total GWG, GDM, parity, smoking during pregnancy, sex, birth weight category for gestational age and sex, SES, breastfeeding status at 1 month, breastfeeding status at 3 months, breastfeeding status at 6 months, and BMI z-score >1 SD at age 2 years. External validation of models at age 2 years was performed in the validation cohort PEPO. dOffspring with a risk score above or equal to the respective cut-off score value are considered to be at risk of developing a “higher-than-normal BMI growth pattern.” The cut-off value of the score was optimized to avoid false-negative findings (sensitivity), which resulted in negative cut-off score values. AUROC, area under the receiver operating characteristic; BMI, body mass index; CI, confidence interval; GDM, gestational diabetes; GWG, gestational weight gain; NA, not applicable; PEACHES, Programming of Enhanced Adiposity Risk in CHildhood–Early Screening; PEPO, PErinatal Prevention of Obesity; SES, socioeconomic status. Table S5. Scoring system for quantification of risk of higher-than-normal BMI growth in young offspring. aThe equations can be used for sequential individual risk quantification of a “higher-than-normal BMI growth pattern” (BMI z-score >1 SD [51] at least twice) in offspring of mothers with or without pre-conception obesity separately. The prenatal and postnatal variables in the risk quantification equations should be replaced by pre-defined values (0 or 1) depending on whether the condition stated is fulfilled (1) or not (0). The calculated risk score should be compared to the respective cut-off score value (Table 2, Additional file 1: Table S4) . Offspring with a risk score above or equal to the respective cut-off are considered to be at risk of developing a “higher-than-normal BMI growth pattern.” Details on calculating individual risk probabilities and use of individual risk score calculations along with clinical case scenarios are provided in the Text S3 (Additional file 1). BMI, body mass index; BF, breastfeeding; GDM, gestational diabetes; GWG, gestational weight gain; m, month(s); LGA, large-for-gestational-age; SES, socioeconomic status; SGA, small-for-gestational-age; y, year(s).

Although the value of newborn screening (NBS) for early detection and treatment opportunity in SMA patients is generally accepted, there is still an ongoing discussion about the best strategy in children with 4 and more copies of the SMN2 gene. This gene is known to be the most important but not the only disease modifier. In our SMA-NBS pilot project in Germany comprising 278,970 infants screened between January 2018 and November 2019 were 38 positive cases with a homozygous SMN1 deletion. 40% of them had 4 or more SMN2 copies. The incidence for homozygous SMN1 deletion was 1 : 7350, which is within the known range of SMA incidence in Germany. Of the 15 SMA children with 4 SMN2 copies, one child developed physical signs of SMA by the age of 8 months. Reanalysis of the SMN2 copy number by a different test method revealed 3 copies. Two children had affected siblings with SMA Type III, who were diagnosed only after detection of the index patient in the NBS. One had a positive family history with an affected aunt (onset of disease at the age of 3 years). Three families were lost to medical follow up; two because of socioeconomic reasons and one to avoid the psychological stress associated with the appointments. Decisions on how to handle patients with 4 SMN2 copies are discussed in the light of the experience gathered from our NBS pilot SMA program.

Additional file 1. Table S1: Age at first consultation at the treatment center or at collection of thesecond blood sample, discrepancy in SMN2 estimation, early-onset symptoms, and initial resultsfrom electrophysiology and CHOP INTEND. Y = years, mo = months, d = days, neg = negative,pos = positive.

Additional file 1.

Newborn screening (NBS) is an important part of public healthcare systems in many countries. The provision of information to parents about NBS is now recognised as an integral part of the screening process. Informing parents on all aspects of screening helps to achieve the benefits, promote trust and foster support for NBS. Therefore, policies and guidelines should exist to govern how the information about NBS is provided to parents, taking into account evidence-based best practices. The purpose of our survey was to explore whether any legally binding provisions, guidelines or recommendations existed pertaining to the provision of information about NBS to parents across Europe. Questions were designed to determine the regulatory process of when, by whom and how parents should be informed about screening. Twenty-seven countries participated in the survey. The results indicated that most countries had some sort of legal framework or guidelines for the provision of information to parents. However, only 37% indicated that the provision of information was required prenatally. The majority of countries were verbally informing parents with the aid of written materials postnatally, just prior to sample collection. Information was provided by a neonatologist, midwife or nurse. A website dedicated to NBS was available for 67% of countries and 89% had written materials about NBS for parents. The survey showed that there is a lack of harmonisation among European countries in the provision of information about NBS and emphasised the need for more comprehensive guidelines at the European level. Institutional support was provided by projects LM2018132 from the Large Infrastructure Projects of the Czech Ministry of Education, PROGRES Q26 from Charles University and RVO VFN 64165 from the Ministry of Health, Czech Republic. Several authors of this publication are members of the European Reference Network for Rare Hereditary Metabolic Disorders (MetabERN)—Project ID No. 739543. info:eu-repo/semantics/publishedVersion

Additional file 2. Table S2: Patient’s family history, ethnical background, and outcome details. = years, mo = months, d = days, neg = negative, pos = positive.