Growth charts for Marfan syndrome in the Netherlands and analysis of genotype-phenotype relationships.

To optimize care for children with Marfan syndrome (MFS) in the Netherlands, Dutch MFS growth charts were constructed. Additionally, we aimed to investigate the effect of FBN1 variant type (haploinsufficiency [HI]/dominant negative [DN]) on growth, and compare MFS-related height increase across populations. Height and weight data of individuals with MFS aged 0-21 years were retrospectively collected. Generalized Additive Models for Location, Scale and Shape (GAMLSS) was used for growth chart modeling. To investigate genotype-phenotype relationships, FBN1 variant type was included as an independent variable in height-for-age and BMI-for-age models. MFS-related height increase was compared with that of previous MFS growth studies from the United States, Korea, and France. Height and weight data of 389 individuals with MFS were included (210 males). Height-for-age, BMI-for-age, and weight-for-height charts reflected the tall and slender MFS habitus throughout childhood. Mean increase in height of individuals with MFS compared with the general Dutch population was significantly lower than in the other three MFS populations compared to their reference populations. FBN1-HI variants were associated with taller height in both sexes, and decreased BMI in females (p-values <0.05). This Dutch MFS growth study broadens the notion that genetic background and MFS variant type (HI/DN) influence tall and slender stature in MFS.

Longitudinal body composition assessment in healthy term-born infants until 2 years of age using ADP and DXA with vacuum cushion.

OBJECTIVES: Accelerated gain in fat mass (FM) in early life increases the risk for adult diseases. Longitudinal data on infant body composition are crucial for clinical and research use, but very difficult to obtain due to limited measurement tools and unsuccessful measurements between age 6-24 months. We compared FM% by dual-energy X-ray absorptiometry (DXA), with cushion to reduce movement artifacts, with FM% by air-displacement plethysmography (ADP) and evaluated the reliability of this cushion during DXA by comparing FM% with and without cushion. Subsequently, we constructed sex-specific longitudinal body composition charts from 1-24 months. METHODS: In 692 healthy, term-born infants (Sophia Pluto Cohort), FM% was measured by ADP from 1-6 months and DXA with cushion from 6-24 months. At 6 months, FM% was measured in triplicate by ADP and DXA with and without cushion(n = 278), later on in smaller numbers. RESULTS: At 6 months, mean FM% by DXA with cushion was 24.1 and by ADP 25.0, mean difference of 0.9% (Bland-Altman p = 0.321, no proportional bias). Mean FM% by DXA without cushion was 12.5% higher compared to ADP (Bland-Altman p < 0.001). DXA without cushion showed higher mean FM% compared to DXA with cushion (+11.6%, p < 0.001) at 6 months. Longitudinally, FM% increased between 1-6 months and decreased from 6-24 months(both p < 0.001). CONCLUSIONS: In infants, DXA scan with cushion limits movement artifacts and shows reliable FM%, comparable to ADP. This allowed us to construct longitudinal body composition charts until 24 months. Our study shows that FM% increases from 1-6 months and gradually declines until 24 months.

Instability of hierarchical cluster analysis due to input order of the data: the PermuCLUSTER solution.

Hierarchical agglomerative cluster analysis (HACA) may yield different solutions under permutations of the input order of the data. This instability is caused by ties, either in the initial proximity matrix or arising during agglomeration. The authors recommend to repeat the analysis on a large number of random permutations of the rows and columns of the proximity matrix and select a solution with the highest goodness-of-fit. This approach was implemented in an SPSS add-in, PermuCLUSTER, which can perform all HACA methods of SPSS. Analyses of 2 data sets show that (a) results are affected by input order, (b) instability in one method co-occurs with instability in other methods, and (c) some instability effects are more dramatic because they occur at higher agglomeration levels.