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Summary: In clinical and biomedical research, multiple high-dimensional datasets are nowadays routinely collected from omics and imaging devices. Multivariate methods, such as Canonical Correlation Analysis (CCA), integrate two (or more) datasets to discover and understand underlying biological mechanisms. For an explorative method like CCA, interpretation is key. We present a sparse CCA method based on soft-thresholding that produces near-orthogonal components, allows for browsing over various sparsity levels, and permutation-based hypothesis testing. Our soft-thresholding approach avoids tuning of a penalty parameter. Such tuning is computationally burdensome and may render unintelligible results. In addition, unlike alternative approaches, our method is less dependent on the initialization. We examined the performance of our approach with simulations and illustrated its use on real cancer genomics data from drug sensitivity screens. Moreover, we compared its performance to Penalized Matrix Analysis (PMA), which is a popular alternative of sparse CCA with a focus on yielding interpretable results. Compared to PMA, our method offers improved interpretability of the results, while not compromising, or even improving, signal discovery., Availability and Implementation: The software and simulation framework are available at https://github.com/nuria-sv/toscca., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Statins are the primary therapy in patient with heterozygous familial hypercholesterolemia (HeFH). Non-adherence to statin therapy is associated with increased cardiovascular risk., Objective: We constructed a dynamic prediction model to predict statin adherence for an individual HeFH patient for each upcoming statin prescription., Methods: All patients with HeFH, identified by the Dutch Familial Hypercholesterolemia screening program between 1994 and 2014, were eligible. National pharmacy records dated between 1995 and 2015 were linked. We developed a dynamic prediction model that estimates the probability of statin adherence (defined as proportion of days covered >80%) for an upcoming prescription using a mixed effect logistic regression model. Static and dynamic patient-specific predictors, as well as data on a patient's adherence to past prescriptions were included. The model with the lowest AIC (Akaike Information Criterion) value was selected., Results: We included 1094 patients for whom 21,171 times a statin was prescribed. Based on the model with the lowest AIC, age at HeFH diagnosis, history of cardiovascular event, time since HeFH diagnosis and duration of the next statin prescription contributed to an increased adherence, while adherence decreased with higher untreated LDL-C levels and higher intensity of statin therapy. The dynamic prediction model showed an area under the curve of 0.63 at HeFH diagnosis, which increased to 0.85 after six years of treatment., Conclusion: This dynamic prediction model enables clinicians to identify HeFH patients at risk for non-adherence during statin treatment. These patients can be offered timely interventions to improve adherence and further reduce cardiovascular risk., Competing Interests: Declaration of conflicting interest A.J.C., M.H.H., L.Md.B., R.H. report no conflict of interests. E.S.G.S. has received fees paid to his institution from Amgen, Akcea, Athera, Sanofi-Regeneron, Esperion, Novo Nordisk, Lily, and Novartis. J.J.P.K. is the CSO of NewAmsterdam Pharma, the CMO of Staten Biotechnology is on the Board of North Sea Therapeutics and Oxitope, has received consulting fees from Akcea Therapeutics, AstraZeneca, CiVi Biopharma, Corvidia Therapeutics, CSL Behring, Daiichi Sankyo, Draupnir Bio, Esperion, Gemphire Therapeutics, Madrigal Pharmaceuticals, Matinas BioPharma, NorthSea Therapeutics, Novo Nordisk, Novartis, Regeneron Pharamaceuticals, REGENXBIO, Staten Biotechnology, and 89bio. GKH reports institutional research support from Aegerion, Amgen, AstraZeneca, Eli Lilly, Genzyme, Ionis, Kowa, Pfizer, Regeneron, Roche, Sanofi, and The Medicines Company; speaker's bureau and consulting fees from Amgen, Aegerion, Sanofi, and Regeneron (fees paid to the academic institution); and part-time employment at Novo Nordisk. BAH has received a research grant from Silence Therapeutics., (Copyright © 2022. Published by Elsevier Inc.)

Introduction: Patients participating in randomized controlled trials (RCTs) are susceptible to a wide range of different adverse events (AE) during the RCT. MedDRA ® is a hierarchical standardization terminology to structure the AEs reported in an RCT. The lowest level in the MedDRA hierarchy is a single medical event, and every higher level is the aggregation of the lower levels., Method: We propose a multi-stage Bayesian hierarchical Poisson model for estimating MedDRA-coded AE rate ratios (RRs). To deal with rare AEs, we introduce data aggregation at a higher level within the MedDRA structure and based on thresholds on incidence and MedDRA structure., Results: With simulations, we showed the effects of this data aggregation process and the method's performance. Furthermore, an application to a real example is provided and compared with other methods., Conclusion: We showed the benefit of using the full MedDRA structure and using aggregated data. The proposed model, as well as the pre-processing, is implemented in an R-package: BAHAMA., (© 2022. The Author(s).)

Background and Aims: Elevated lipoprotein(a) [Lp(a)] is an independent risk factor for cardiovascular disease. In clinical practice, Lp(a) is mostly measured only once assuming that it does not change with age nor vary within individuals. This is mainly based on adult data and data on Lp(a) levels during childhood is scarce. Therefore, we evaluated whether Lp(a) levels changed with age and determined the intra-individual variation of Lp(a) in a large cohort of children., Methods: We collected all Lp(a) measurements of children referred to the pediatric lipid clinic of the Amsterdam UMC between 1989 and 2017. The association between Lp(a) and age, as well as the intra-individual variation of Lp(a), was assessed using mixed models. We stratified for lipid-lowering medication use., Results: In total, we included 2740 children. From the age of 8 years onwards, mean Lp(a) increased with 22% in children that reached adulthood without lipid-lowering medication (n = 2254). In statin-users (n = 418) and children that used ezetimibe additionally (n = 65), Lp(a) increased with 43% and 9%, respectively. The intra-individual variation of Lp(a) was 70%., Conclusions: Lp(a) levels increase with age and exhibit considerable variation within children referred to a lipid clinic. Measuring Lp(a) only once during childhood might therefore lead to substantial over- or underestimation and possibly result in over- or under treatment in the future. Thus, to more accurately assess the Lp(a) level, we suggest measuring Lp(a) more than once during childhood and to repeat this in adulthood if a patient only has childhood assessment of Lp(a)., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Study Question: Do parental characteristics and treatment with ART affect perinatal outcomes in singleton pregnancies?, Summary Answer: Both parental and ART treatment characteristics affect perinatal outcomes in singleton pregnancies., What Is Known Already: Previous studies have shown that singleton pregnancies resulting from ART are at risk of preterm birth. ART children are lighter at birth after correction for duration of gestation and at increased risk of congenital abnormalities compared to naturally conceived children. This association is confounded by parental characteristics that are also known to affect perinatal outcomes. It is unclear to which extent parental and ART treatment characteristics independently affect perinatal outcomes., Study Design, Size, Duration: All IVF clinics in the Netherlands (n = 13) were requested to provide data on all ART treatment cycles (IVF, ICSI and frozen-thawed embryo transfers (FET)), performed between 1 January 2000, and 1 January 2011, which resulted in a pregnancy. Using probabilistic data-linkage, these data (n = 36 683) were linked to the Dutch Perinatal Registry (Perined), which includes all children born in the Netherlands in the same time period (n = 2 548 977)., Participants/materials, Setting, Methods: Analyses were limited to singleton pregnancies that resulted from IVF, ICSI or FET cycles. Multivariable models for linear and logistic regression were fitted including parental characteristics as well as ART treatment characteristics. Analyses were performed separately for fresh cycles and for fresh and FET cycles combined. We assessed the impact on the following perinatal outcomes: birth weight, preterm birth below 37 or 32 weeks of gestation, congenital malformations and perinatal mortality., Main Results and the Role of Chance: The perinatal outcomes of 31 184 out of the 36 683 ART treatment cycles leading to a pregnancy were retrieved through linkage with the Perined (85% linkage). Of those, 23 671 concerned singleton pregnancies resulting from IVF, ICSI or FET. Birth weight was independently associated with both parental and ART treatment characteristics. Characteristics associated with lower birth weight included maternal hypertensive disease, non-Dutch maternal ethnicity, nulliparity, increasing duration of subfertility, hCG for luteal phase support (compared to progesterone), shorter embryo culture duration, increasing number of oocytes retrieved and fresh embryo transfer. The parental characteristic with the greatest effect size on birth weight was maternal diabetes (adjusted difference 283 g, 95% CI 228-338). FET was the ART treatment characteristic with the greatest effect size on birth weight (adjusted difference 100 g, 95% CI 84-117) compared to fresh embryo transfer. Preterm birth was more common among mothers of South-Asian ethnicity. Preterm birth was less common among multiparous women and women with 'male factor' as treatment indication (compared to 'tubal factor')., Limitations, Reasons for Caution: Due to the retrospective nature of our study, we cannot prove causality. Further limitations of our study were the inability to adjust for mothers giving birth more than once in our dataset, missing values for several variables and limited information on parental lifestyle and general health., Wider Implications of the Findings: Multiple parental and ART treatment characteristics affect perinatal outcomes, with birth weight being influenced by the widest range of factors. This highlights the importance of assessing both parental and ART treatment characteristics in studies that focus on the health of ART-offspring, with the purpose of modifying these factors where possible. Our results further support the hypothesis that the embryo is sensitive to its early environment., Study Funding/competing Interest(s): This study was funded by Foreest Medical School, Alkmaar, the Netherlands (grants: FIO 1307 and FIO 1505). B.W.M. reports grants from NHMRC and consultancy for ObsEva, Merck KGaA, iGenomics and Guerbet. F.B. reports research support grants from Merck Serono and personal fees from Merck Serono. A.C. reports travel support from Ferring BV. and Theramex BV. and personal fees from UpToDate (Hyperthecosis), all outside the remit of the current work. The remaining authors report no conflict of interests., Trial Registration Number: N/A., (© The Author(s) 2021. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.)

Background: Milk feeding type (exclusive breastfeeding [EBF], formula feeding or mixed feeding) and timing of complementary feeding (CF) have been associated with infant growth. However, studies evaluating their combined role, and the role of ethnicity, are scarce. We examined associations of feeding patterns (milk feeding type combined with timing of CF) with infant body mass index (BMI) trajectories and potential ethnic-specific associations., Methods: Infant feeding and BMI data during the 1st year of life from 3524 children (Dutch n = 2880, Moroccan n = 404 and Turkish n = 240) from the Amsterdam Born Children and their Development (ABCD) cohort were used. Six feeding patterns were defined: EBF/earlyCF, EBF/lateCF (reference), formula/earlyCF, formula/lateCF, mixed/earlyCF and mixed/lateCF. A covariate adjusted latent class mixed model was applied to simultaneously model BMI trajectories and associations with feeding patterns. Potential ethnic differences in the associations were studied in a separate model where interactions between ethnicity and feeding patterns were included., Results: Four distinct BMI trajectories (low, mid-low, mid-high and high) were identified. Feeding pattern of formula/earlyCF was associated with lower odds for low (OR: 0.43; 95% CI: 0.25, 0.76) or mid-high (0.28; 0.16, 0.51) (ref: high) trajectory compared with EBF/lateCF pattern (ref). An ethnic-specific model revealed that among Dutch infants, formula/earlyCF pattern was associated with lower odds for low trajectory (0.46; 0.24, 0.87), whereas among Turkish/Moroccan infants almost all feeding patterns were associated with lower odds for the low trajectory (ref: high)., Conclusion: Infant feeding patterns are associated with early BMI trajectories with specific ethnic differences. Future studies should take the role of ethnicity into account in the associations between infant feeding and growth.

Background: Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data., Methods: We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN)., Results: Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score ., Conclusions: Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.

Background: Evidence on long-term dupilumab treatment for atopic dermatitis in daily practice is lacking., Objective: To investigate patient characteristics, treatment aspects, effectiveness, and safety of up to 84 weeks of dupilumab treatment., Methods: An observational prospective cohort study was conducted of patients with atopic dermatitis starting dupilumab in routine clinical care., Results: Of the 221 included patients, 103 used systemic therapy at baseline. At 84 weeks, we found a change of -15.2 (SE, 1.7) for the Eczema Area and Severity Index, -16.9 (SE, 1.4) for the Patient-Oriented Eczema Measure, and -17.2 (SE, 1.6) for the Dermatology Life Quality Index. We found a trend for improvement over time for the Investigator Global Assessment and Numerical Rating Scale for pruritus. Severe (n = 79) including serious (n = 11) adverse events were observed in 69 patients. Eye complaints were most frequently reported (n = 46). Twenty-one patients adjusted the regular dosing schedule, and 14 patients discontinued treatment, mainly due to ineffectiveness (n = 7)., Limitations: Only adverse events of severe and serious nature were registered for feasibility reasons., Conclusion: Daily practice dupilumab treatment of up to 84 weeks is generally well-tolerated, apart from the reporting of eye complaints. It can be considered a long-term effective treatment for atopic dermatitis in combination with topical and initial concomitant systemic treatment, showing a sustained improvement of signs, symptoms, and quality of life., (Copyright © 2020 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Introduction: People of South Asian origin are at high risk of type 2 diabetes (T2D), but the underpinning mechanisms are not fully understood. We determined ethnic differences in acylcarnitine, amino acid and sphingolipid concentrations and determined the associations with T2D., Research Design and Methods: Associations between these metabolites and incident T2D among Dutch and South-Asian Surinamese were determined in participants from the Healthy Life in an Urban Setting (HELIUS) study (Amsterdam, the Netherlands) using Prentice-weighted Cox regression. The HELIUS study includes 95 incident T2D cases and a representative subcohort of 700 people from a cohort of 5977 participants with a mean follow-up of 4 years., Results: Concentrations of acylcarnitines were comparable between both ethnic groups. Amino acid and lactosylceramide concentrations were higher among South-Asian Surinamese than Dutch (eg, isoleucine 65.7 (SD 16.3) vs 60.7 (SD 15.6) µmol/L). Ceramide concentrations were lower among South-Asian Surinamese than Dutch (eg, Cer d18:1 8.48 (SD 2.04) vs 9.08 (SD 2.29) µmol/L). Metabolic dysregulation preceded T2D without evidence for a multiplicative interaction by ethnicity. Most amino acids and (dihydro)ceramides were associated with increased risk (eg, Cer d18:1 HR 2.38, 95% CI 1.81 to 3.12) while acylcarnitines, glycine, glutamine and lactosylceramides were associated with decreased risk for T2D (eg, LacCer d18:2 HR 0.56, 95% CI 0.42 to 0.77)., Conclusions: Overall, these data suggest that the disturbances underlying amino acid and sphingolipid metabolism may be predictive of T2D risk in populations of both South Asian and European background. These observations may be used as starting point to unravel the underlying metabolic disturbances., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Background: Recent technological developments have enabled the measurement of a plethora of biomolecular data from various omics domains, and research is ongoing on statistical methods to leverage these omics data to better model and understand biological pathways and genetic architectures of complex phenotypes. Current reviews report that the simultaneous analysis of multiple (i.e. three or more) high dimensional omics data sources is still challenging and suitable statistical methods are unavailable. Often mentioned challenges are the lack of accounting for the hierarchical structure between omics domains and the difficulty of interpretation of genomewide results. This study is motivated to address these challenges. We propose multiset sparse Partial Least Squares path modeling (msPLS), a generalized penalized form of Partial Least Squares path modeling, for the simultaneous modeling of biological pathways across multiple omics domains. msPLS simultaneously models the effect of multiple molecular markers, from multiple omics domains, on the variation of multiple phenotypic variables, while accounting for the relationships between data sources, and provides sparse results. The sparsity in the model helps to provide interpretable results from analyses of hundreds of thousands of biomolecular variables., Results: With simulation studies, we quantified the ability of msPLS to discover associated variables among high dimensional data sources. Furthermore, we analysed high dimensional omics datasets to explore biological pathways associated with Marfan syndrome and with Chronic Lymphocytic Leukaemia. Additionally, we compared the results of msPLS to the results of Multi-Omics Factor Analysis (MOFA), which is an alternative method to analyse this type of data., Conclusions: msPLS is an multiset multivariate method for the integrative analysis of multiple high dimensional omics data sources. It accounts for the relationship between multiple high dimensional data sources while it provides interpretable results through its sparse solutions. The biomarkers found by msPLS in the omics datasets can be interpreted in terms of biological pathways associated with the pathophysiology of Marfan syndrome and of Chronic Lymphocytic Leukaemia. Additionally, msPLS outperforms MOFA in terms of variation explained in the chronic lymphocytic leukaemia dataset while it identifies the two most important clinical markers for Chronic Lymphocytic Leukaemia AVAILABILITY: http://uva.csala.me/mspls.https://github.com/acsala/2018_msPLS.

Background: Familial hypercholesterolemia is characterized by severely elevated low-density lipoprotein (LDL) cholesterol levels and premature cardiovascular disease. The short-term efficacy of statin therapy in children is well established, but longer follow-up studies evaluating changes in the risk of cardiovascular disease are scarce., Methods: We report a 20-year follow-up study of statin therapy in children. A total of 214 patients with familial hypercholesterolemia (genetically confirmed in 98% of the patients), who were previously participants in a placebo-controlled trial evaluating the 2-year efficacy and safety of pravastatin, were invited for follow-up, together with their 95 unaffected siblings. Participants completed a questionnaire, provided blood samples, and underwent measurements of carotid intima-media thickness. The incidence of cardiovascular disease among the patients with familial hypercholesterolemia was compared with that among their 156 affected parents., Results: Of the original cohort, 184 of 214 patients with familial hypercholesterolemia (86%) and 77 of 95 siblings (81%) were seen in follow-up; among the 214 patients, data on cardiovascular events and on death from cardiovascular causes were available for 203 (95%) and 214 (100%), respectively. The mean LDL cholesterol level in the patients had decreased from 237.3 to 160.7 mg per deciliter (from 6.13 to 4.16 mmol per liter) - a decrease of 32% from the baseline level; treatment goals (LDL cholesterol <100 mg per deciliter [2.59 mmol per liter]) were achieved in 37 patients (20%). Mean progression of carotid intima-media thickness over the entire follow-up period was 0.0056 mm per year in patients with familial hypercholesterolemia and 0.0057 mm per year in siblings (mean difference adjusted for sex, -0.0001 mm per year; 95% confidence interval, -0.0010 to 0.0008). The cumulative incidence of cardiovascular events and of death from cardiovascular causes at 39 years of age was lower among the patients with familial hypercholesterolemia than among their affected parents (1% vs. 26% and 0% vs. 7%, respectively)., Conclusions: In this study, initiation of statin therapy during childhood in patients with familial hypercholesterolemia slowed the progression of carotid intima-media thickness and reduced the risk of cardiovascular disease in adulthood. (Funded by the AMC Foundation.)., (Copyright © 2019 Massachusetts Medical Society.)

Background: Evidence of immunomodulatory therapies to guide clinical management of atopic eczema (AE) is scarce, despite frequent and often off-label use. Patient registries provide valuable evidence for the effects of treatments under real-world conditions that can inform treatment guidelines, give the opportunity for health economic evaluation and the evaluation of quality of care, as well as pharmacogenetic and dynamic research, which cannot be adequately addressed in clinical trials., Objectives: The TREatment of ATopic eczema (TREAT) Registry Taskforce aims to seek international consensus on a core set of domains and items ('what to measure') for AE research registries, using a Delphi approach., Methods: Participants from six stakeholder groups were included: doctors, nurses, nonclinical researchers, patients, industry and regulatory body representatives. The eDelphi comprised three sequential online rounds, requesting participants to rate the importance of each proposed domain item. Participants could add domain items to the proposed list in round 1. A final consensus meeting was held to ratify the core set., Results: Participants (n = 479) from 36 countries accessed the eDelphi platform, of whom 86%, 79% and 74% completed rounds 1, 2 and 3, respectively. At the face-to-face consensus meeting attended by 42 participants the final core set was established containing 19 domains with 69 domain items (49 baseline and 20 follow-up items)., Conclusions: This core set of domains and items to be captured by national AE systemic therapy registries will standardize data collection and thereby allow direct comparability across registries and facilitate data pooling between countries. Ultimately, it will provide greater insight into the effectiveness, safety and cost-effectiveness of photo- and systemic immunomodulatory therapies., (© 2018 The Authors. British Journal of Dermatology published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists.)

Redundancy Analysis (RDA) is a well-known method used to describe the directional relationship between related data sets. Recently, we proposed sparse Redundancy Analysis (sRDA) for high-dimensional genomic data analysis to find explanatory variables that explain the most variance of the response variables. As more and more biomolecular data become available from different biological levels, such as genotypic and phenotypic data from different omics domains, a natural research direction is to apply an integrated analysis approach in order to explore the underlying biological mechanism of certain phenotypes of the given organism. We show that the multiset sparse Redundancy Analysis (multi-sRDA) framework is a prominent candidate for high-dimensional omics data analysis since it accounts for the directional information transfer between omics sets, and, through its sparse solutions, the interpretability of the result is improved. In this paper, we also describe a software implementation for multi-sRDA, based on the Partial Least Squares Path Modeling algorithm. We test our method through simulation and real omics data analysis with data sets of 364,134 methylation markers, 18,424 gene expression markers, and 47 cytokine markers measured on 37 patients with Marfan syndrome., (© 2018 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Socioeconomically disadvantaged children often have psychosocial problems. This study examined the mediating role of maternal depressive symptoms during pregnancy, infancy and early childhood in the association between maternal education, as indicator of socioeconomic status (SES), and child's psychosocial problems., Methods: Included were 3410 children from the Amsterdam Born Children and their Development (ABCD) study. To assess the child's psychosocial problems at age 5-6 years, mothers and teachers completed the Strengths and Difficulties Questionnaire (SDQ). Maternal depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale and the Depressive Anxiety and Stress Scale 21. Mediation analysis was performed to calculate the direct effect of maternal education on SDQ score and indirect effects through maternal depressive symptoms., Results: The mean mother-reported SDQ total score was significantly higher (P < 0.001) for children of low-educated mothers (6.74 ± 4.41) compared with children of highly educated mothers (4.47 ± 3.73). Levels of maternal depressive symptoms were also higher in low-educated mothers during pregnancy, infancy and early childhood. Maternal depressive symptoms explained 27.5% of the association between maternal education and mother-reported SDQ scores and 22.9% for combined mother/teacher SDQ scores. Maternal depressive symptoms during pregnancy had the strongest indirect effect., Conclusion: Maternal depressive symptoms during pregnancy mediate the association between low maternal education and child's psychosocial problems. Early recognition and treatment of maternal depressive symptoms is important to prevent psychosocial problems in children, especially in those with low education.

Background: Atherosclerosis starts in childhood and its progression is influenced by lifelong low-density lipoprotein cholesterol (LDL-c) exposure, the so-called cholesterol burden. Early identification of children and adolescents with severely elevated LDL-c is thus of major clinical significance. This is especially true for children with familial hypercholesterolemia (FH), a frequent but undertreated genetic disorder. To identify children with possible FH, insight in the distribution of lipid levels in children is a prerequisite., Objective: To provide health care professionals with contemporary age- and gender-based pediatric reference values for lipid and lipoprotein levels to help the identification of children with dyslipidemia, especially FH., Methods: Lifelines is a large prospective population-based Dutch cohort study. Children from 8 till 18 years of age were included and fasting lipid levels were measured. Smoothed reference curves and percentiles (5 th , 10 th , 25 th , 50 th , 75 t h , 90 th , and 95 th ) were generated using the Generalized Additive Models for Location, Scale and Shape package in the statistical software R., Results: A total of 8071 children (3823 boys and 4248 girls) were included. In the total cohort we noted marked dynamic changes in lipid and lipoprotein levels over age, which were in part gender specific. Our data highlight a high and unexpected prevalence of severely elevated LDL-c (>190 mg/dL) in both boys and girls., Conclusion: Our cross-sectional data provide contemporary reference ranges for plasma lipids that can assist physicians in identifying children at increased risk of premature atherosclerosis, especially FH., (Copyright © 2018 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Motivation: Recent technological developments have enabled the possibility of genetic and genomic integrated data analysis approaches, where multiple omics datasets from various biological levels are combined and used to describe (disease) phenotypic variations. The main goal is to explain and ultimately predict phenotypic variations by understanding their genetic basis and the interaction of the associated genetic factors. Therefore, understanding the underlying genetic mechanisms of phenotypic variations is an ever increasing research interest in biomedical sciences. In many situations, we have a set of variables that can be considered to be the outcome variables and a set that can be considered to be explanatory variables. Redundancy analysis (RDA) is an analytic method to deal with this type of directionality. Unfortunately, current implementations of RDA cannot deal optimally with the high dimensionality of omics data (p≫n). The existing theoretical framework, based on Ridge penalization, is suboptimal, since it includes all variables in the analysis. As a solution, we propose to use Elastic Net penalization in an iterative RDA framework to obtain a sparse solution., Results: We proposed sparse redundancy analysis (sRDA) for high dimensional omics data analysis. We conducted simulation studies with our software implementation of sRDA to assess the reliability of sRDA. Both the analysis of simulated data, and the analysis of 485 512 methylation markers and 18,424 gene-expression values measured in a set of 55 patients with Marfan syndrome show that sRDA is able to deal with the usual high dimensionality of omics data., Availability and Implementation: http://uva.csala.me/rda., Contact: a.csala@amc.uva.nl., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Objective  We assessed, in women with a previous spontaneous preterm birth, the effect of interpregnancy interval on the subsequent preterm birth rate. Design  Retrospective cohort study. Setting  A nationwide longitudinal dataset of the the Netherlands Perinatal Registry. Population  Women with three sequential singleton pregnancies between 1999 and 2009 and a spontaneous preterm birth <37 weeks in the first pregnancy. Methods  We evaluated the impact of interpregnancy interval on the course of the next pregnancies. Antenatal death and/or congenital abnormalities were excluded. Conventional and conditional logistic regression analysis were applied. We adjusted for maternal age, ethnicity, socioeconomic status, artificial reproductive techniques, and year of birth. Main Outcome Measures  Outcomes studied were preterm birth <37 weeks, <32 weeks, low birth weight <2500 g, and small for gestational age <10th percentile. Results  Among 2,361 women with preterm birth in the first pregnancy, logistic regression analysis indicated a significant effect of a short interpregnancy interval (0-5 mo) on recurrent preterm birth <37 weeks (odds ratio [OR], 2.22; 95% confidence interval [CI], 1.62-3.05), <32 weeks (OR, 2.90; 95% CI, 1.43-5.87), and low birth weight (OR, 2.69; 95% CI, 1.79-4.03). In addition, a long interval (≥60 mo) had a significant effect on preterm birth <37 weeks (OR, 2.19; 95% CI, 1.29-3.74). Conditional logistic regression analysis confirmed the effect of a short interval on the recurrence of preterm birth rate <37 weeks and low birth weight. Conclusion  In women with a previous spontaneous preterm birth, a short interpregnancy interval has a strong impact on the risk of preterm birth before 37 weeks and low birth weight in the next pregnancy, irrespective of the type of analysis performed., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

Combining information from two data sources depends on finding records that belong to the same individual (matches). Sometimes, unique identifiers per individual are not available, and we have to rely on partially identifying variables that are registered in both data sources. A risk of relying on these variables is that some records from both datasets are wrongly linked to each other, which introduces bias in further regression analyses. In this paper, we propose a mixture model where we treat the indicator whether records belong to the same individual as missing. Each pair of records from both datasets contributes independently to a pairwise pseudo-likelihood, which we maximize with an expectation-maximization algorithm. Each part of the pseudo-likelihood is parameterized by the appropriate (parametric) density function. Moreover, some structures of the data allow for simplifying assumptions, which makes the pseudo-likelihood considerably easier to parameterize. Because the optimization requires a product over all combinations of records from both datasets, we suggest a procedure that summarizes information from highly unlikely matches. With simulations, we showed that the new approach produces accurate estimates in different linkage scenarios. Moreover, the estimator remained accurate in scenarios where previously proposed analysis approaches give biased results. We applied the method to estimation of the association between pregnancy duration of the first and second born children from the same mother from a register without mother identifier., (Copyright © 2014 John Wiley & Sons, Ltd.)

Objective: To investigate whether vaginal Group B Streptococcus (GBS) colonisation or other baseline characteristics of women with preterm premature rupture of membranes (PPROM) can help in identifying subgroups of women who would benefit from immediate delivery., Design: Secondary analysis of the PPROMEXIL trials., Setting: Sixty hospitals in the Netherlands., Population: Women with PPROM between 34 and 37 weeks of gestation., Methods: Random assignment of 723 women to immediate delivery or expectant management., Main Outcome Measures: Early onset neonatal sepsis., Results: Vaginal GBS colonisation status was the only marker which was significantly associated with the benefit of immediate delivery (P for interaction: 0.04). GBS colonisation was observed in 14% of women. The risk of early onset neonatal sepsis in GBS-positive women was high (15.2%) when they were managed expectantly but this risk was reduced to 1.8% with immediate delivery. The early onset neonatal sepsis risk was much lower in neonates of GBS-negative women: 2.6% after expectant management and 2.9% with immediate delivery. We estimated that by inducing labour only in GBS-positive women, there would be a 10.4% increase in term delivery rate, while keeping neonatal sepsis and caesarean delivery rates comparable to a strategy of labour induction for all., Conclusions: Our post hoc findings suggest that women with PROM between 34 and 37 weeks might benefit from immediate delivery if they have GBS vaginal colonisation, while in GBS-negative women labour induction could be delayed until 37 weeks., (© 2014 Royal College of Obstetricians and Gynaecologists.)

Background: In population-based observational studies, non-participation and delayed response to the invitation to participate are complications that often arise during the recruitment of a sample. When both are not properly dealt with, the composition of the sample can be different from the desired composition. Inviting too many individuals or too few individuals from a particular subgroup could lead to unnecessary costs or decreased precision. Another problem is that there is frequently no or only partial information available about the willingness to participate. In this situation, we cannot adjust the recruitment procedure for non-participation before the recruitment period starts., Methods: We have developed an adaptive list sequential sampling method that can deal with unknown participation probabilities and delayed responses to the invitation to participate in the study. In a sequential way, we evaluate whether we should invite a person from the population or not. During this evaluation, we correct for the fact that this person could decline to participate using an estimated participation probability. We use the information from all previously invited persons to estimate the participation probabilities for the non-evaluated individuals., Results: The simulations showed that the adaptive list sequential sampling method can be used to estimate the participation probability during the recruitment period, and that it can successfully recruit a sample with a specific composition., Conclusions: The adaptive list sequential sampling method can successfully recruit a sample with a specific desired composition when we have partial or no information about the willingness to participate before we start the recruitment period and when individuals may have a delayed response to the invitation.

Study Question: What is the time to conception in a cohort of women with unexplained recurrent miscarriage (RM)., Summary Answer: Median time to conception in women diagnosed with unexplained RM was 21 weeks (interquartile range (IQR) 8-55 weeks), with a cumulative incidence of conception of 74% after 12 months of trying to conceive., What Is Known Already: There is no effective treatment in couples with unexplained RM. Adequate counselling about their prognosis, for example time to conception and time to a live birth, is therefore very important. So far, there are no studies that give insight on these issues., Study Design, Size, Duration: A nested prospective cohort study was performed from February 2004 through July 2009 within a multicentre randomized placebo-controlled trial (ALIFE trial) on anticoagulant treatment in 364 women with unexplained RM., Participants/materials, Setting, Methods: A total of 251 women who were not pregnant at the time of diagnosis of unexplained RM were included in this study. Of these, 13% became pregnant with ART, and all other women conceived naturally. The primary outcome was time to conception in weeks, calculated from the moment of diagnosis until conception measured by a urinary HCG. Secondary outcome was time to a live birth in the subsequent pregnancy. The relative prognostic significance of female age, the number of preceding miscarriages, interventions within the trial and the presence or absence of a preceding late miscarriage, a previous live birth and factor V Leiden mutation, was evaluated by Cox regression for time to conception and by competing risk modelling for time to live birth, respectively., Main Results and the Role of Chance: The cumulative incidence of conception was 56% after 6 months, 74% after 12 months and 86% after 24 months of which 65% resulted in a live birth. The median time to conception was 21 weeks (IQR 8-55 weeks). Of potential prognostic factors, the presence of the factor V Leiden mutation resulted in a significantly shorter median time to conception of 11 weeks for carriers versus 23 weeks for non-carriers (hazard ratio (HR) 1.94, 95% confidence interval (CI) 1.03-3.65). The cumulative incidence of a live birth of the subsequent pregnancy was 0% after 6 months, 23% after 12 months and 50% after 24 months. The median time to a live birth of the subsequent pregnancy was 102 weeks (IQR 82-115 weeks). The number of previous miscarriages was the only prognostic factor (HR 0.83, 95% CI 0.74-0.94) significantly associated with time to a live birth of the subsequent pregnancy., Limitations, Reasons for Caution: In our study only the subsequent pregnancy after diagnosing unexplained RM was included. A future collection of cumulative follow-up data of all the women included in this cohort may provide outcomes of all pregnancies following the diagnosis of unexplained RM., Wider Implications of the Findings: Time to conception in women diagnosed with unexplained RM appears to be comparable with time to conception in healthy fertile women, as reported in the literature. The interesting finding that women with Factor V Leiden mutation have a significant shorter time to conception may suggest a favourable embryo implantation process. Future research is needed to confirm these findings and unravel the biology of early implantation., Study Funding/competing Interest(s): The RCT used for this nested cohort study was funded by a grant (945-27-003) from the Netherlands Organization for Health Research and Development and a grant from GlaxoSmithKline. Study drugs (aspirin and placebo) were packaged and donated by Meda Pharma. This analysis was supported by a VIDI innovative research grant from the Netherlands Organisation for Scientific Research (NWO) 016.126.364. There are no potential conflicts of interest to declare., Trial Registration Number: This cohort study was nested in the randomized controlled trial; ALIFE study (Current Controlled Trials number, ISRCTN 58496168).

Introduction: The development of overweight is often measured with the body mass index (BMI). During childhood the BMI curve has two characteristic points: the adiposity rebound at 6 years and the BMI peak at 9 months of age. In this study, the associations between the BMI peak and body composition measures and blood pressure at age 5-6 years were investigated., Methods: Measurements from the Amsterdam Born Children and their Development (ABCD) study were available for this study. Blood pressure (systolic and diastolic) and body composition measures (BMI, waist-to-height ratio, fat percentage) were gathered during a health check at about 6 years of age (n = 2822). All children had multiple BMI measurements between the 0-4 years of age. For boys and girls separately, child-specific BMI peaks were extracted from mixed effect models. Associations between the estimated BMI peak and the health check measurements were analysed with linear models. In addition, we investigated the potential use of the BMI at 9 months as a surrogate measure for the magnitude of the BMI peak., Results: After correction for the confounding effect of fetal growth, both timing and magnitude of the BMI peak were significantly and positively associated (p<0.001) with all body composition measures at the age of 5-6 years. The BMI peak showed no direct association with blood pressure at the age 5-6 year, but was mediated by the current BMI. The correlation between the magnitude of the BMI peak and BMI at 9 months was approximately 0.93 and similar associations with the measures at 5-6 years were found., Conclusion: The magnitude of the BMI peak was associated with body composition measures at 5-6 years of age. Moreover, the BMI at 9 months could be used as surrogate measure for the magnitude of the BMI peak.

Background: To investigate whether biomarkers consisting of baseline characteristics of advanced stage ovarian cancer patients can help in identifying subgroups of patients who would benefit more from primary surgery or neoadjuvant chemotherapy., Methods: We used data of the European Organisation for Research and Treatment of Cancer (EORTC) 55971 trial in which 670 patients were randomly assigned to primary surgery or neoadjuvant chemotherapy. The primary outcome was overall survival. Ten baseline clinical and pathological characteristics were selected as potential biomarkers. Using Subpopulation Treatment Effect Pattern Plots (STEPP), biomarkers with a statistically significant qualitative additive interaction with treatment were considered as potentially informative for treatment selection. We also combined selected biomarkers to form a multimarker treatment selection rule., Findings: The size of the largest metastatic tumour and clinical stage were significantly associated with the magnitude of the benefit from treatment, in terms of five-year survival (p for interaction: 0.008 and 0.016, respectively). Stage IIIC patients with metastatic tumours ⩽45 mm benefited more from primary surgery while stage IV patients with metastatic tumours >45 mm benefited more from neoadjuvant chemotherapy. In stage IIIC patients with larger metastatic tumours and in stage IV patients with less extensive metastatic tumours both treatments were equally effective. We estimated that by selecting treatments for patients based on largest metastatic tumour and clinical stage, the potential five-year survival rate in the population of treated patients would be 27.3% (95% confidence interval (CI) 21.9-33.0), 7.8% higher than if all were treated with primary surgery, and 5.6% higher if all were treated with neoadjuvant chemotherapy., Interpretation: Although survival was comparable after primary surgery and neoadjuvant chemotherapy in the overall group of patients with ovarian cancer in the EORTC 55971 trial, we found in this exploratory analysis that patients with stage IIIC and less extensive metastatic tumours had higher survival with primary surgery, while patients with stage IV disease and large metastatic tumours had higher survival with neoadjuvant chemotherapy. For patients who did not meet these criteria, both treatment options led to comparable survival rates., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In record linkage studies, unique identifiers are often not available, and therefore, the linkage procedure depends on combinations of partially identifying variables with low discriminating power. As a consequence, wrongly linked covariate and outcome pairs will be created and bias further analysis of the linked data. In this article, we investigated two estimators that correct for linkage error in regression analysis. We extended the estimators developed by Lahiri and Larsen and also suggested a weighted least squares approach to deal with linkage error. We considered both linear and logistic regression problems and evaluated the performance of both methods with simulations. Our results show that all wrong covariate and outcome pairs need to be removed from the analysis in order to calculate unbiased regression coefficients in both approaches. This removal requires strong assumptions on the structure of the data. In addition, the bias significantly increases when the assumptions do not hold and wrongly linked records influence the coefficient estimation. Our simulations showed that both methods had similar performance in linear regression problems. With logistic regression problems, the weighted least squares method showed less bias. Because the specific structure of the data in record linkage problems often leads to different assumptions, it is necessary that the analyst has prior knowledge on the nature of the data. These assumptions are more easily introduced in the weighted least squares approach than in the Lahiri and Larsen estimator., (Copyright © 2012 John Wiley & Sons, Ltd.)

Objective: To determine the risk of preterm birth in a subsequent twin pregnancy after previous singleton preterm birth., Design: Cohort study., Setting: Nationwide study in the Netherlands., Population: In all, 4071 nulliparous women who had a singleton delivery followed by a subsequent twin delivery between the years 1999 and 2007 were studied., Methods: Outcome of subsequent twin pregnancy of women with a history of preterm singleton delivery was compared with pregnancy outcome of women with a history of term singleton delivery. First deliveries were subdivided into iatrogenic and spontaneous preterm deliveries. Furthermore analyses were performed by subgroups for gestational age at the time of singleton delivery., Main Outcome Measure: Spontaneous preterm birth (<37 weeks of gestation) in subsequent twin pregnancy., Results: In the index singleton pregnancy, preterm birth occurred in 232 (5.7%) of 4071 women. The risk of subsequent twin preterm birth was significantly higher after previous singleton preterm delivery (56.9 versus 20.9%; odds ratio 5.0; 95% CI 3.8-6.6). Risk of subsequent twin preterm birth was dependent on the severity of previous singleton preterm birth and was highest after preceding spontaneous instead of iatrogenic singleton preterm delivery., Conclusion: Preterm birth of a singleton gestation is associated with an increased risk of spontaneous preterm birth in a subsequent twin pregnancy., (© 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2012 RCOG.)

Objective: The purpose of this study was to investigate the recurrence risk of preterm birth (<37 weeks' gestation) in a subsequent singleton pregnancy after a previous nulliparous preterm twin delivery., Study Design: We included 1957 women who delivered a twin gestation and a subsequent singleton pregnancy from the Netherlands Perinatal Registry. We compared the outcome of subsequent singleton pregnancy of women with a history of preterm delivery to the pregnancy outcome of women with a history of term twin delivery., Results: Preterm birth in the twin pregnancy occurred in 1075 women (55%) vs 882 women (45%) who delivered at term. The risk of subsequent spontaneous singleton preterm birth was significantly higher after preterm twin delivery (5.2% vs 0.8%; odds ratio, 6.9; 95% confidence interval, 3.1-15.2)., Conclusion: Women who deliver a twin pregnancy are at greater risk for delivering prematurely in a subsequent singleton pregnancy., (Copyright © 2012 Mosby, Inc. All rights reserved.)

Background: In the Netherlands separate reference charts have been developed for native and immigrant groups to deal with differences in growth patterns in later childhood. The use of these charts, however, is complicated by methodological issues; they do not represent all large Dutch immigrant groups in separate charts despite the differences that have been suggested and the evidence of ethnic disparities in growth dates back to 1997., Aim: Anthropometric measurements from a contemporary multi-ethnic cohort study were created to quantify differences in childhood growth by creating growth charts, separately for boys and girls between the ages of 0-3 years., Subjects and Methods: The infants modelled in the charts had a mother born in the Netherlands (n = 3107), Suriname (n = 225), Turkey (n = 203) and Morocco (n = 336). Charts with and without correction for country of origin of the mother were created by using the LMST method., Results: All models including the covariate country of origin of the mother fitted the data better (p < 0.0005), but the observed differences were small., Conclusion: Most remarkable differences were found in the BMI and weight measurements for age charts. Especially girls from mothers born in Turkey and Morocco had an increasingly heavier weight for their age than girls from mothers born in the Netherlands.