Real-time monitoring of an endogenous Fgf8a gradient attests to its role as a morphogen during zebrafish gastrulation.

Morphogen gradients impart positional information to cells in a homogenous tissue field. Fgf8a, a highly conserved growth factor, has been proposed to act as a morphogen during zebrafish gastrulation. However, technical limitations have so far prevented direct visualization of the endogenous Fgf8a gradient and confirmation of its morphogenic activity. Here, we monitor Fgf8a propagation in the developing neural plate using a CRISPR/Cas9-mediated EGFP knock-in at the endogenous fgf8a locus. By combining sensitive imaging with single-molecule fluorescence correlation spectroscopy, we demonstrate that Fgf8a, which is produced at the embryonic margin, propagates by diffusion through the extracellular space and forms a graded distribution towards the animal pole. Overlaying the Fgf8a gradient curve with expression profiles of its downstream targets determines the precise input-output relationship of Fgf8a-mediated patterning. Manipulation of the extracellular Fgf8a levels alters the signaling outcome, thus establishing Fgf8a as a bona fide morphogen during zebrafish gastrulation. Furthermore, by hindering Fgf8a diffusion, we demonstrate that extracellular diffusion of the protein from the source is crucial for it to achieve its morphogenic potential.

Alpha-1-antitrypsin-deficiency is associated with lower cardiovascular risk: an approach based on federated learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory multisystemic disease caused by environmental exposures and/or genetic factors. Inherited alpha-1-antitrypsin deficiency (AATD) is one of the best recognized genetic factors increasing the risk for an early onset COPD with emphysema. The aim of this study was to gain a better understanding of the associations between comorbidities and specific biomarkers in COPD patients with and without AATD to enable future investigations aimed, for example, at identifying risk factors or improving care. METHODS: We focused on cardiovascular comorbidities, blood high sensitivity troponin (hs-troponin) and lipid profiles in COPD patients with and without AATD. We used clinical data from six German University Medical Centres of the MIRACUM (Medical Informatics Initiative in Research and Medicine) consortium. The codes for the international classification of diseases (ICD) were used for COPD as a main diagnosis and for comorbidities and blood laboratory data were obtained. Data analyses were based on the DataSHIELD framework. RESULTS: Out of 112,852 visits complete information was available for 43,057 COPD patients. According to our findings, 746 patients with AATD (1.73%) showed significantly lower total blood cholesterol levels and less cardiovascular comorbidities than non-AATD COPD patients. Moreover, after adjusting for the confounder factors, such as age, gender, and nicotine abuse, we confirmed that hs-troponin is a suitable predictor of overall mortality in COPD patients. The comorbidities associated with AATD in the current study differ from other studies, which may reflect geographic and population-based differences as well as the heterogeneous characteristics of AATD. CONCLUSION: The concept of MIRACUM is suitable for the analysis of a large healthcare database. This study provided evidence that COPD patients with AATD have a lower cardiovascular risk and revealed that hs-troponin is a predictor for hospital mortality in individuals with COPD.

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups.

In settings requiring synthetic data generation based on a clinical cohort, e.g., due to data protection regulations, heterogeneity across individuals might be a nuisance that we need to control or faithfully preserve. The sources of such heterogeneity might be known, e.g., as indicated by sub-groups labels, or might be unknown and thus reflected only in properties of distributions, such as bimodality or skewness. We investigate how such heterogeneity can be preserved and controlled when obtaining synthetic data from variational autoencoders (VAEs), i.e., a generative deep learning technique that utilizes a low-dimensional latent representation. To faithfully reproduce unknown heterogeneity reflected in marginal distributions, we propose to combine VAEs with pre-transformations. For dealing with known heterogeneity due to sub-groups, we complement VAEs with models for group membership, specifically from propensity score regression. The evaluation is performed with a realistic simulation design that features sub-groups and challenging marginal distributions. The proposed approach faithfully recovers the latter, compared to synthetic data approaches that focus purely on marginal distributions. Propensity scores add complementary information, e.g., when visualized in the latent space, and enable sampling of synthetic data with or without sub-group specific characteristics. We also illustrate the proposed approach with real data from an international stroke trial that exhibits considerable distribution differences between study sites, in addition to bimodality. These results indicate that describing heterogeneity by statistical approaches, such as propensity score regression, might be more generally useful for complementing generative deep learning for obtaining synthetic data that faithfully reflects structure from clinical cohorts.

Effect of nusinersen on motor, respiratory and bulbar function in early-onset spinal muscular atrophy.

5q-associated spinal muscular atrophy is a rare neuromuscular disorder with the leading symptom of a proximal muscle weakness. Three different drugs have been approved by the European Medicines Agency and Food and Drug Administration for the treatment of spinal muscular atrophy patients, however, long-term experience is still scarce. In contrast to clinical trial data with restricted patient populations and short observation periods, we report here real-world evidence on a broad spectrum of patients with early-onset spinal muscular atrophy treated with nusinersen focusing on effects regarding motor milestones, and respiratory and bulbar insufficiency during the first years of treatment. Within the SMArtCARE registry, all patients under treatment with nusinersen who never had the ability to sit independently before the start of treatment were identified for data analysis. The primary outcome of this analysis was the change in motor function evaluated with the Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders and motor milestones considering World Health Organization criteria. Further, we evaluated data on the need for ventilator support and tube feeding, and mortality. In total, 143 patients with early-onset spinal muscular atrophy were included in the data analysis with a follow-up period of up to 38 months. We observed major improvements in motor function evaluated with the Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders. Improvements were greater in children >2 years of age at start of treatment than in older children. 24.5% of children gained the ability to sit independently. Major improvements were observed during the first 14 months of treatment. The need for intermittent ventilator support and tube feeding increased despite treatment with nusinersen. Our findings confirm the increasing real-world evidence that treatment with nusinersen has a dramatic influence on disease progression and survival in patients with early-onset spinal muscular atrophy. Major improvements in motor function are seen in children younger than 2 years at the start of treatment. Bulbar and respiratory function needs to be closely monitored, as these functions do not improve equivalent to motor function.

App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer Undergoing Radiotherapy: Results From a Prospective Randomized Controlled Trial.

BACKGROUND: Head and neck cancers (HNCs) are very common malignancies, and treatment often requires multimodal approaches, including radiotherapy and chemotherapy. Patients with HNC often display a high symptom burden, both due to the disease itself and the adverse effects of the multimodal therapy. Close telemonitoring of symptoms and quality of life during the course of treatment may help to identify those patients requiring early medical support. OBJECTIVE: The App-Controlled Treatment Monitoring and Support for Patients With Head and Neck Cancer (APCOT) trial aimed to investigate the feasibility of integrating electronic patient-reported outcomes (ePROs) in the treatment surveillance pathway of patients with HNC during the course of their radiotherapy. Additionally, the influence of app-based ePRO monitoring on global and disease-specific quality of life and patient satisfaction with treatment was assessed. METHODS: Patients undergoing radiotherapy for histologically proven HNCs at the Department of Radiation Oncology, University Medical Center Freiburg, Germany, were enrolled in this trial and monitored by weekly physician appointments. Patients were randomized between additional ePRO monitoring on each treatment day or standard-of-care monitoring. Feasibility of ePRO monitoring was defined as ≥80% of enrolled patients answering ≥80% of their daily app-based questions. Quality of life and patient satisfaction were assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (QLQ-C30), the head and neck cancer module (H&N35), and the validated Patient Satisfaction Questionnaire Short Form (PSQ-18) at the completion of treatment and compared between trial arms. RESULTS: A total of 100 patients were enrolled in this trial, and 93 patients were evaluable. All patients (100%) in the experimental arm answered ≥80% of the ePRO questions during treatment, reaching the predefined threshold for the feasibility of ePRO monitoring (P<.001 in the binomial test). No clinical or patient-specific factor was found to influence feasibility. Global health and most domains of the general quality of life were comparable between trial arms, but an increased HNC-specific symptom burden was reported by patients undergoing ePRO surveillance. ePRO monitoring resulted in improved patient satisfaction regarding interpersonal manners (P=.01), financial aspects (P=.01), and time spent with a doctor (P=.01). CONCLUSIONS: This trial demonstrated the feasibility of incorporating daily app-based ePRO surveillance for patients with HNC undergoing radiotherapy. Our data, for the first time, demonstrate that telemonitoring in this setting led to increased reporting of HNC-specific symptom burden and significantly improved several domains of patient satisfaction. Further analyses are needed to assess whether our findings hold true outside the context of a clinical trial. TRIAL REGISTRATION: German Clinical Trials Register DRKS00020491; https://drks.de/search/en/trial/DRKS00020491.

Altered cortical thickness development in 22q11.2 deletion syndrome and association with psychotic symptoms.

Schizophrenia has been extensively associated with reduced cortical thickness (CT), and its neurodevelopmental origin is increasingly acknowledged. However, the exact timing and extent of alterations occurring in preclinical phases remain unclear. With a high prevalence of psychosis, 22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that represents a unique opportunity to examine brain maturation in high-risk individuals. In this study, we quantified trajectories of CT maturation in 22q11DS and examined the association of CT development with the emergence of psychotic symptoms. Longitudinal structural MRI data with 1-6 time points were collected from 324 participants aged 5-35 years (N = 148 22q11DS, N = 176 controls), resulting in a total of 636 scans (N = 334 22q11DS, N = 302 controls). Mixed model regression analyses were used to compare CT trajectories between participants with 22q11DS and controls. Further, CT trajectories were compared between participants with 22q11DS who developed (N = 61, 146 scans), or remained exempt of (N = 47; 98 scans) positive psychotic symptoms during development. Compared to controls, participants with 22q11DS showed widespread increased CT, focal reductions in the posterior cingulate gyrus and superior temporal gyrus (STG), and accelerated cortical thinning during adolescence, mainly in frontotemporal regions. Within 22q11DS, individuals who developed psychotic symptoms showed exacerbated cortical thinning in the right STG. Together, these findings suggest that genetic predisposition for psychosis is associated with increased CT starting from childhood and altered maturational trajectories of CT during adolescence, affecting predominantly frontotemporal regions. In addition, accelerated thinning in the STG may represent an early biomarker associated with the emergence of psychotic symptoms.

[Sex- and Regionalspecific Differences in Child Abuse and Violence Before the German Reunification. Results from GESA, a Multi-Cohort Study]. / Geschlechts- und regionalspezifische Unterschiede von Kindesvernachlässigung und Gewalt vor der deutschen Wiedervereinigung. Ergebnisse aus GESA, einem Multi-Kohorten Konsortium.

Results from a population-based study suggest sex-specific patterns of self-reported child maltreatment, more frequently reported in former West than East Germany. Aim of the current study was to examine these patterns in two regional samples of the former East- (SHIP, 2008 - 2012) and West German (KORA, 2013 - 2014) population. Child maltreatment was assessed using the Childhood Trauma Screener (CTS). Overall, child maltreatment was less often reported in the East German sample, compared to the West German sample. The most prominent differences were identified in self-rated emotional violence (east 6.1%, west 8.7%), physical violence (east 5.7%, west 10.3%) and physical neglect (east 10.0%, west 19.2%). However, we could not find differences in sex-specific patterns between the East and West German samples. Results were discussed within a historical context, since the events took place before the German reunification in two oppose political systems.

Structural control energy of resting-state functional brain states reveals less cost-effective brain dynamics in psychosis vulnerability.

How the brain's white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brain's functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; that is, the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a deficiency in the ability to reduce energy through brain activation. In summary, our results provide initial insights into the functional implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.

Positive psychotic symptoms are associated with divergent developmental trajectories of hippocampal volume during late adolescence in patients with 22q11DS.

Low hippocampal volume is a consistent finding in schizophrenia and across the psychosis spectrum. However, there is a lack of studies investigating longitudinal hippocampal development and its relationship with psychotic symptoms. The 22q11.2 deletion syndrome (22q11DS) has proven to be a remarkable model for the prospective study of individuals at high risk of schizophrenia to unravel the pathophysiological processes predating the onset of psychosis. Repeated cerebral MRIs were acquired from 140 patients with 22q11DS (53 experiencing moderate-to-severe psychotic symptoms) and 135 healthy controls aged from 6 to 35 years and with up to 5 time points per participant. Hippocampal subfield analysis was conducted using FreeSurfer-v.6 and FIRST-FSL. Then, whole hippocampal and subfield volumes were compared across the groups. Relative to controls, patients with 22q11DS showed a remarkably lower volume of all subfields except for CA2/3. No divergent trajectories in hippocampal development were found. When comparing patients with 22q11DS exhibiting psychotic symptoms to those without psychosis, we detected a volume decrease during late adolescence, starting in CA1 and spreading to other subfields. Our findings suggested that hippocampal volume is consistently smaller in patients with 22q11DS. Moreover, we have demonstrated that patients with 22q11DS and psychotic symptoms undergo a further decrease in volume during adolescence, a vulnerable period for the emergence of psychosis. Interestingly, CA2/3, despite being affected in patients with psychotic symptoms, was the only area not reduced in patients with 22q11DS relative to controls, thus suggesting that its atrophy exclusively correlates with the presence of positive psychotic symptoms.

Bidimensional structure and measurement equivalence of the Patient Health Questionnaire-9: sex-sensitive assessment of depressive symptoms in three representative German cohort studies.

BACKGROUND: The Patient Health Questionnaire-9 (PHQ-9) has been proposed as a reliable and valid screening instrument for depressive symptoms with one latent factor. However, studies explicitly testing alternative model structures found support for a two-dimensional structure reflecting a somatic and a cognitive-affective dimension. We investigated the bidimensional structure of the PHQ-9, with a somatic (sleeping problems, fatigability, appetitive problems, and psychomotor retardation) and a cognitive-affective dimension (lack of interest, depressed mood, negative feelings about self, concentration problems, and suicidal ideation), and tested for sex- and regional-differences. METHODS: We have included data from the GEnder-Sensitive Analyses of mental health trajectories and implications for prevention: A multi-cohort consortium (GESA). Privacy-preserving analyses to provide information on the overall population and cohort-specific information and analyses of variance to compare depressive, somatic and cognitive-affective symptoms between sexes and cohorts were executed in DataSHIELD. In order to determine the dimensionality and measurement invariance of the PHQ-9 we tested three models (1 factor, 2 correlated factors, and bifactor) via confirmatory analyses and performed multi-group confirmatory factor analysis. RESULTS: Differences between sex and cohorts exist for PHQ-9 and for both of its dimensions. Women reported depressive symptoms in general as well as somatic and cognitive-affective symptoms more frequently. For all tested models an acceptable to excellent fit was found, consistently indicating a better model fit for the two-factor and bifactor model. Scalar measurement invariance was established between women and men, the three cohorts, and their interaction. CONCLUSIONS: The two facets of depression should be taken into account when using PHQ-9, while data also render support to a general factor. Somatic and cognitive-affective symptoms assessed by the PHQ-9 can be considered equivalent across women and men and between different German populations from different regions.

Agito ergo sum: Correlates of spatio-temporal motion characteristics during fMRI.

The impact of in-scanner motion on functional magnetic resonance imaging (fMRI) data has a notorious reputation in the neuroimaging community. State-of-the-art guidelines advise to scrub out excessively corrupted frames as assessed by a composite framewise displacement (FD) score, to regress out models of nuisance variables, and to include average FD as a covariate in group-level analyses. Here, we studied individual motion time courses at time points typically retained in fMRI analyses. We observed that even in this set of putatively clean time points, motion exhibited a very clear spatio-temporal structure, so that we could distinguish subjects into separate groups of movers with varying characteristics. Then, we showed that this spatio-temporal motion cartography tightly relates to a broad array of anthropometric and cognitive factors. Convergent results were obtained from two different analytical perspectives: univariate assessment of behavioural differences across mover subgroups unraveled defining markers, while subsequent multivariate analysis broadened the range of involved factors and clarified that multiple motion/behaviour modes of covariance overlap in the data. Our results demonstrate that even the smaller episodes of motion typically retained in fMRI analyses carry structured, behaviourally relevant information. They call for further examinations of possible biases in current regression-based motion correction strategies.

Automatic variable selection for exposure-driven propensity score matching with unmeasured confounders.

Multivariable model building for propensity score modeling approaches is challenging. A common propensity score approach is exposure-driven propensity score matching, where the best model selection strategy is still unclear. In particular, the situation may require variable selection, while it is still unclear if variables included in the propensity score should be associated with the exposure and the outcome, with either the exposure or the outcome, with at least the exposure or with at least the outcome. Unmeasured confounders, complex correlation structures, and non-normal covariate distributions further complicate matters. We consider the performance of different modeling strategies in a simulation design with a complex but realistic structure and effects on a binary outcome. We compare the strategies in terms of bias and variance in estimated marginal exposure effects. Considering the bias in estimated marginal exposure effects, the most reliable results for estimating the propensity score are obtained by selecting variables related to the exposure. On average this results in the least bias and does not greatly increase variances. Although our results cannot be generalized, this provides a counterexample to existing recommendations in the literature based on simple simulation settings. This highlights that recommendations obtained in simple simulation settings cannot always be generalized to more complex, but realistic settings and that more complex simulation studies are needed.

Association of smoking but not HLA-DRB1*15:01, APOE or body mass index with brain atrophy in early multiple sclerosis.

BACKGROUND: The course of multiple sclerosis (MS) shows substantial inter-individual variability. The underlying determinants of disease severity likely involve genetic and environmental factors. OBJECTIVE: The aim of this study was to assess the impact of APOE and HLA polymorphisms as well as smoking and body mass index (BMI) in the very early MS course. METHODS: Untreated patients ( n = 263) with a recent diagnosis of relapsing-remitting (RR) MS or clinically isolated syndrome underwent standardized magnetic resonance imaging (MRI). Genotyping was performed for single-nucleotide polymorphisms (SNPs) rs3135388 tagging the HLA-DRB1*15:01 haplotype and rs7412 (Ɛ2) and rs429358 (Ɛ4) in APOE. Linear regression analyses were applied based on the three SNPs, smoking and BMI as exposures and MRI surrogate markers for disease severity as outcomes. RESULTS: Current smoking was associated with reduced gray matter fraction, lower brain parenchymal fraction and increased cerebrospinal fluid fraction in comparison to non-smoking, whereas no effect was observed on white matter fraction. BMI and the SNPs in HLA and APOE were not associated with structural MRI parameters. CONCLUSIONS: Smoking may have an unfavorable effect on the gray matter fraction as a potential measure of MS severity already in early MS. These findings may impact patients' counseling upon initial diagnosis of MS.

Norovirus Gastroenteritis among Hospitalized Patients, Germany, 2007-2012.

We estimated numbers of hospitalizations for norovirus gastroenteritis (NGE) and associated medical costs in Germany, where norovirus testing is high because reimbursement is affected. We extracted aggregate data for patients hospitalized with a primary or secondary code from the International Classification of Diseases, 10th Revision (ICD-10), NGE diagnosis during 2007-2012 from the German Federal Statistics Office. We assessed reliability of the coding system in patient records from a large academic hospital. Approximately 53,000-90,000 NGE hospitalizations occurred annually in Germany (21,000-33,000 with primary and 32,000-57,000 with secondary ICD-10-coded NGE diagnoses). Rates of hospitalization with NGE as primary diagnosis were highest in children <2 years of age; rates of hospitalization with NGE as secondary diagnosis were highest in adults >85 years of age. The average annual reimbursed direct medical cost of NGE hospitalizations was €31-43 million. Among patients with a NGE ICD-10 code, 87.6% had positive norovirus laboratory results.

Cortical morphology development in patients with 22q11.2 deletion syndrome at ultra-high risk of psychosis.

BACKGROUND: Patients with 22q11.2 deletion syndrome (22q11DS) present a high risk of developing psychosis. While clinical and cognitive predictors for the conversion towards a full-blown psychotic disorder are well defined and largely used in practice, neural biomarkers do not yet exist. However, a number of investigations indicated an association between abnormalities in cortical morphology and higher symptoms severities in patients with 22q11DS. Nevertheless, few studies included homogeneous groups of patients differing in their psychotic symptoms profile. METHODS: In this study, we included 22 patients meeting the criteria for an ultra-high-risk (UHR) psychotic state and 22 age-, gender- and IQ-matched non-UHR patients. Measures of cortical morphology, including cortical thickness, volume, surface area and gyrification, were compared between the two groups using mass-univariate and multivariate comparisons. Furthermore, the development of these measures was tested in the two groups using a mixed-model approach. RESULTS: Our results showed differences in cortical volume and surface area in UHR patients compared with non-UHR. In particular, we found a positive association between surface area and the rate of change of global functioning, suggesting that higher surface area is predictive of improved functioning with age. We also observed accelerated cortical thinning during adolescence in UHR patients with 22q11DS. CONCLUSIONS: These results, although preliminary, suggest that alterations in cortical volume and surface area as well as altered development of cortical thickness may be associated to a greater probability to develop psychosis in 22q11DS.

Early Adaptive Functioning Trajectories in Preschoolers With Autism Spectrum Disorders.

Background: In preschoolers with autism spectrum disorder (ASD) symptom, severity has a negative impact on the development of adaptive functioning, with critical consequences on the quality of life of those children. Developmental features such as reduced social interest or the presence of behavioral problems can further impede daily life learning experiences. Objectives: The first aim of this study is to confirm the negative impact of high symptom severity on adaptive functioning trajectories in preschoolers with ASD. The second objective intends to explore whether reduced social interest and severe behavioral problems negatively affect developmental trajectories of adaptive functioning in young children with ASD. Methods: In total, 68 children with ASD and 48 age and gender-matched children with typical development (TD) between 1.6 and 6 years were included in our study, and longitudinal data on adaptive functioning were collected (mean length of the longitudinal data collection was 1.4 years ± 0.6). Baseline measures of symptom severity, social interest, and behavioral problems were also obtained. Results: We confirmed that children with ASD show parallel developmental trajectories but a significantly lower performance of adaptive functioning compared with children with TD. Furthermore, analyses within ASD children demonstrated that those with higher symptom severity, reduced social interest, and higher scores of behavioral problems exhibited especially lower or faster declining trajectories of adaptive functioning. Conclusions: These findings bolster the idea that social interest and behavioral problems are crucial for the early adaptive functioning development of children with autism. The current study has clinical implications in pointing out early intervention targets in children with ASD.

Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome.

Although often ignored in fMRI studies, moment-to-moment variability of blood oxygenation level dependent (BOLD) signals reveals important information about brain function. Indeed, higher brain signal variability has been associated with better cognitive performance in young adults compared to children and elderly adults. Functional connectivity, a very common approach in resting-state fMRI analysis, is scaled for variance. Thus, alterations might be confounded or driven by BOLD signal variance alterations. Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder that is associated with a vast cognitive and clinical phenotype. To date, several resting-state fMRI studies reported altered functional connectivity in 22q11.2DS, however BOLD signal variance has not yet been analyzed. Here, we employed PLS correlation analysis to reveal multivariate patterns of diagnosis-related alterations and age-relationship throughout the cortex of 50 patients between 9 and 25 years old and 50 healthy controls in the same age range. To address how functional connectivity in the default mode network is influenced by BOLD signal fluctuations, we conducted the same analysis on seed-to-voxel connectivity of the posterior cingulate cortex (PCC) and compared resulting brain patterns. BOLD signal variance was lower mainly in regions of the default mode network and in the dorsolateral prefrontal cortex, but higher in large parts of the temporal lobes. In those regions, BOLD signal variance was correlated with age in healthy controls, but not in patients, suggesting deviant developmental trajectories from child- to adulthood. Positive connectivity of the PCC within the default mode network as well as negative connectivity towards the frontoparietal network were weaker in patients with 22q11.2DS. We furthermore showed that lower functional connectivity of the PCC was not driven by higher BOLD signal variability. Our results confirm the strong implication of BOLD variance in aging and give an initial insight in its relationship with functional connectivity in the DMN.

Simulation of complex data structures for planning of studies with focus on biomarker comparison.

BACKGROUND: There are a growing number of observational studies that do not only focus on single biomarkers for predicting an outcome event, but address questions in a multivariable setting. For example, when quantifying the added value of new biomarkers in addition to established risk factors, the aim might be to rank several new markers with respect to their prediction performance. This makes it important to consider the marker correlation structure for planning such a study. Because of the complexity, a simulation approach may be required to adequately assess sample size or other aspects, such as the choice of a performance measure. METHODS: In a simulation study based on real data, we investigated how to generate covariates with realistic distributions and what generating model should be used for the outcome, aiming to determine the least amount of information and complexity needed to obtain realistic results. As a basis for the simulation a large epidemiological cohort study, the Gutenberg Health Study was used. The added value of markers was quantified and ranked in subsampling data sets of this population data, and simulation approaches were judged by the quality of the ranking. One of the evaluated approaches, the random forest, requires original data at the individual level. Therefore, also the effect of the size of a pilot study for random forest based simulation was investigated. RESULTS: We found that simple logistic regression models failed to adequately generate realistic data, even with extensions such as interaction terms or non-linear effects. The random forest approach was seen to be more appropriate for simulation of complex data structures. Pilot studies starting at about 250 observations were seen to provide a reasonable level of information for this approach. CONCLUSIONS: We advise to avoid oversimplified regression models for simulation, in particular when focusing on multivariable research questions. More generally, a simulation should be based on real data for adequately reflecting complex observational data structures, such as found in epidemiological cohort studies.

Generation of a conditional lima1a allele in zebrafish using the FLEx switch technology.

Gene trapping has emerged as a valuable tool to create conditional alleles in various model organisms. Here we report the FLEx-based gene trap vector SAGFLEx that allows the generation of conditional mutations in zebrafish by gene-trap mutagenesis. The SAGFLEx gene-trap cassette comprises the rabbit ß-globin splice acceptor and the coding sequence of GFP, flanked by pairs of inversely oriented heterotypic target sites for the site-specific recombinases Cre and Flp. Insertion of the gene-trap cassette into endogenous genes can result in conditional mutations that are stably inverted by Cre and Flp, respectively. To test the functionality of this system we performed a pilot screen and analyzed the insertion of the gene-trap cassette into the lima1a gene locus. In this lima1a allele, GFP expression faithfully recapitulated the endogenous lima1a expression and resulted in a complete knockout of the gene in homozygosity. Application of either Cre or Flp was able to mediate the stable inversion of the gene trap cassette and showed the ability to conditionally rescue or reintroduce the gene inactivation. Combined with pharmacologically inducible site specific recombinases the SAGFLEx vector insertions will enable precise conditional knockout studies in a spatial- and temporal-controlled manner.

Stagewise pseudo-value regression for time-varying effects on the cumulative incidence.

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event status is replaced by a jackknife pseudo-value based on the Aalen-Johansen method. We combine a stagewise regression technique with the pseudo-value approach to provide variable selection while allowing for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application using clinical cancer registry data from hepatocellular carcinoma patients. The results are contrasted with traditional hazard-based modeling. In addition to a more straightforward interpretation, when using the proposed technique, the identification of time-varying effect patterns on the cumulative incidence is seen to be feasible with a moderate number of observations.