Fusing metabolomics data sets with heterogeneous measurement errors.

Combining different metabolomics platforms can contribute significantly to the discovery of complementary processes expressed under different conditions. However, analysing the fused data might be hampered by the difference in their quality. In metabolomics data, one often observes that measurement errors increase with increasing measurement level and that different platforms have different measurement error variance.

Varicella zoster virus infection occurs at a relatively young age in The Netherlands.

Introduction: To date, there is no universal varicella vaccination in the Netherlands. We studied the seroprevalence of varicella zoster virus (VZV) specific antibodies and determinants for seropositivity among participants of a serosurveillance study, conducted in 2006/2007 among Dutch inhabitants 0-79 years of age.

Materials And Methods: Serological testing of 6386 blood samples for VZV was performed with a fluorescent bead-based multiplex immunoassay.

Waning of maternal antibodies against measles, mumps, rubella, and varicella in communities with contrasting vaccination coverage.

Background: The combined measles, mumps, and rubella (MMR) vaccine has been successfully administered for >20 years. Because of this, protection by maternal antibodies in infants born to vaccinated mothers might be negatively affected.

Methods:  A large cross-sectional serologic survey was conducted in the Netherlands during 2006-2007.

Seroprevalence of mumps in The Netherlands: dynamics over a decade with high vaccination coverage and recent outbreaks.

Here we present mumps virus specific antibody levels in a large cross-sectional population-based serosurveillance study performed in the Netherlands in 2006/2007 (n = 7900). Results were compared with a similar study (1995/1996) and discussed in the light of recent outbreaks. Mumps antibodies were tested using a fluorescent bead-based multiplex immunoassay.

Age-dependent patterns of infection and severity explaining the low impact of 2009 influenza A (H1N1): evidence from serial serologic surveys in the Netherlands.

Despite considerable research efforts in specific subpopulations, reliable estimates of the infection attack rates and severity of 2009 influenza A (H1N1) in the general population remain scarce. Such estimates are essential to the tailoring of future control strategies. Therefore, 2 serial population-based serologic surveys were conducted, before and after the 2009 influenza A (H1N1) epidemic, in the Netherlands.

Association of repeatedly measured intermediate risk factors for complex diseases with high dimensional SNP data.

Background: The causes of complex diseases are difficult to grasp since many different factors play a role in their onset. To find a common genetic background, many of the existing studies divide their population into controls and cases; a classification that is likely to cause heterogeneity within the two groups. Rather than dividing the study population into cases and controls, it is better to identify the phenotype of a complex disease by a set of intermediate risk factors.

Associating multiple longitudinal traits with high-dimensional single-nucleotide polymorphism data: application to the Framingham Heart Study.

Cardiovascular diseases are associated with combinations of phenotypic traits, which are in turn caused by a combination of environmental and genetic factors. Because of the diversity of pathways that may lead to cardiovascular diseases, we examined the so-called intermediate phenotypes, which are often repeatedly measured. We developed a penalized nonlinear canonical correlation analysis to associate multiple repeatedly measured traits with high-dimensional single-nucleotide polymorphism data.

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks.

Background: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the canonical variates, and we applied ridge penalization to the regression of pathway genes on canonical variates of the non-pathway genes, and the elastic net to the regression of non-pathway genes on the canonical variates of the pathway genes.

Results: We performed a small simulation to illustrate the model's capability to identify new candidate genes to incorporate in the pathway: in our simulations it appeared that a gene was correctly identified if the correlation with the pathway genes was 0.

Correlating multiple SNPs and multiple disease phenotypes: penalized non-linear canonical correlation analysis.

Motivation: Canonical correlation analysis (CCA) can be used to capture the underlying genetic background of a complex disease, by associating two datasets containing information about a patient's phenotypical and genetic details. Often the genetic information is measured on a qualitative scale, consequently ordinary CCA cannot be applied to such data. Moreover, the size of the data in genetic studies can be enormous, thereby making the results difficult to interpret.

Penalized canonical correlation analysis to quantify the association between gene expression and DNA markers.

Inter-individual variation in gene expression levels can arise as an effect of variation in DNA markers. When associating multiple gene expression variables with multiple DNA marker variables, multivariate techniques, such as canonical correlation analysis, should be used to deal with the effect of co-regulating genes. We adapted the elastic net, a penalized approach proposed for variable selection in regression context, to canonical correlation analysis.

Quantifying the association between gene expressions and DNA-markers by penalized canonical correlation analysis.

Multiple changes at the DNA level are at the basis of complex diseases. Identifying the genetic networks that are influenced by these changes might help in understanding the development of these diseases. Canonical correlation analysis is used to associate gene expressions with DNA-markers and thus reveals sets of co-expressed and co-regulated genes and their associating DNA-markers.

Multivariate analysis of complex gene expression and clinical phenotypes with genetic marker data.

This paper summarizes contributions to group 12 of the 15th Genetic Analysis Workshop. The papers in this group focused on multivariate methods and applications for the analysis of molecular data including genotypic data as well as gene expression microarray measurements and clinical phenotypes. A range of multivariate techniques have been employed to extract signals from the multi-feature data sets that were provided by the workshop organizers.

Colocalization of eNOS and the catalytic subunit of PKA in endothelial cell junctions: a clue for regulated NO production.

Localization and coordinate phosphorylation/dephosphorylation of endothelial nitric oxide synthase (eNOS) are critical determinants for the basal and stimulated production of nitric oxide. Several phosphorylation sites in eNOS have been identified as targets of the cAMP-dependent protein kinase A (PKA). Basal eNOS activity is also regulated by interaction with caveolin-1, the major coat protein of caveolae.