360° Diagnostic Tool to Personalize Lifestyle Advice in Primary Care for People With Type 2 Diabetes: Development and Usability Study.

BACKGROUND: Various multifaceted factors need to be addressed to improve the health and quality of life of people with type 2 diabetes (T2D). Therefore, we developed a web-based decision support tool that comprises a more holistic diagnosis (including 4 domains: body, thinking and feeling, behavior, and environment) and personalized advice. This 360° diagnostic tool enables people with T2D and health care professionals at the general practice to obtain an overview of the most important T2D-related issues and, subsequently, determine the most suitable intervention for the person with T2D. OBJECTIVE: This study aimed to describe the systematic and iterative development and evaluation of the web-based 360° diagnostic tool. METHODS: We defined the requirements for the web-based 360° diagnostic tool based on previously developed tools, a literature review, and inputs from a multidisciplinary team of experts. As part of the conceptualization, we defined 3 requirements: diagnostics; feedback; and advice, consultation, and follow-up. Next, we developed and designed the content for each of these requirements. We evaluated the diagnostic part of the tool (ie, measurement instruments and visualization) with a qualitative design, in a usability study with a think-aloud strategy and interview questions, among 8 people with T2D at a Dutch general practice. RESULTS: For each of the 4 domains, specific parameters and underlying elements were selected, and measurement instruments (including clinical data and questionnaires) were chosen. Cutoff values were defined to identify high-, middle-, and low-ranking scores, and decision rules were developed and implemented using R scripts and algorithms. A traffic light color visual design was created (profile wheel) to provide an overview of the scores per domain. We mapped the interventions that could be added to the tool and developed a protocol designed as a card deck with motivational interview steps. Furthermore, the usability study showed that people with T2D perceived the tool as easy to use, useful, easy to understand, and insightful. CONCLUSIONS: Preliminary evaluation of the 360° diagnostic tool by experts, health care professionals, and people with T2D showed that the tool was considered relevant, clear, and practical. The iterative process provided insights into the areas of improvement, which were implemented. The strengths, shortcomings, future use, and challenges are also discussed.

Systems biology of personalized nutrition.

Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person's health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology-based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of "systems flexibility" is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed.

Prediction of the Carcinogenic Potential of Human Pharmaceuticals Using Repeated Dose Toxicity Data and Their Pharmacological Properties.

In an exercise designed to reduce animal use, we analyzed the results of rat subchronic toxicity studies from 289 pharmaceutical compounds with the aim to predict the tumor outcome of carcinogenicity studies in this species. The results were obtained from the assessment reports available at the Medicines Evaluation Board of the Netherlands for 289 pharmaceutical compounds that had been shown to be non-genotoxic. One hundred forty-three of the 239 compounds not inducing putative preneoplastic lesions in the subchronic study did not induce tumors in the carcinogenicity study [true negatives (TNs)], whereas 96 compounds were categorized as false negatives (FNs) because tumors were observed in the carcinogenicity study. Of the remaining 50 compounds, 31 showed preneoplastic lesions in the subchronic study and tumors in the carcinogenicity study [true positives (TPs)], and 19 only showed preneoplastic lesions in subchronic studies but no tumors in the carcinogenicity study [false positives (FPs)]. In addition, we then re-assessed the prediction of the tumor outcome by integrating the pharmacological properties of these compounds. These pharmacological properties were evaluated with respect to the presence or absence of a direct or indirect proliferative action. We found support for the absence of cellular proliferation for 204 compounds (TN). For 67 compounds, the presence of cellular hyperplasia as evidence for proliferative action could be found (TP). Therefore, this approach resulted in an ability to predict non-carcinogens at a success rate of 92% and the ability to detect carcinogens at 98%. The combined evaluation of pharmacological and histopathological endpoints eventually led to only 18 unknown outcomes (17 categorized as FN and 1 as FP), thereby enhancing both the negative and positive predictivity of an evaluation based upon histopathological evaluation only. The data show the added value of a consideration of the pharmacological properties of compounds in relation to potential class effects, both in the negative and positive direction. A high negative and a high positive predictivity will both result in waiving the need for conducting 2-year rat carcinogenicity studies, if this is accepted by Regulatory Authorities, which will save large numbers of animals and reduce drug development costs and time.

Predicting the therapeutic efficacy of MSC in bone tissue engineering using the molecular marker CADM1.

Mesenchymal stromal cells (hMSCs) are advancing into the clinic but the therapeutic efficacy of hMSCs faces the problem of donor variability. In bone tissue engineering, no reliable markers have been identified which are able to predict the bone-forming capacity of hMSCs prior to implantation. To this end, we isolated hMSCs from 62 donors and characterized systematically their in vitro lineage differentiation capacity, gene expression signature and in vivo capacity for ectopic bone formation. Our data confirms the large variability of in vitro differentiation capacity which did not correlate with in vivo ectopic bone formation. Using DNA microarray analysis of early passage hMSCs we identified a diagnostic bone-forming classifier. In fact, a single gene, CADM1, strongly correlated with the bone-forming capacity of hMSCs and could be used as a reliable in vitro diagnostic marker. Furthermore, data mining of genes expressed correlating with in vivo bone formation represented involvement in neurogenic processes and Wnt signaling. We will apply our data set to predict therapeutic efficacy of hMSCs and to gain novel insight in the process of bone regeneration. Our bio-informatics driven approach may be used in other fields of cell therapy to establish diagnostic markers for clinical efficacy.

Unraveling toxicological mechanisms and predicting toxicity classes with gene dysregulation networks.

The use of genes for distinguishing classes of toxicity has become well established. In this paper we combine the reconstruction of a gene dysregulation network (GDN) with a classifier to assign unseen compounds to their appropriate class. Gene pairs in the GDN are dysregulated in the sense that they are linked by a common expression pattern in one class and differ in this pattern in another class. The classifier gives a quantitative measure on this difference by its prediction accuracy. As an in-depth example, gene pairs were selected that were dysregulated between skin cells treated with either sensitizers or irritants. Pairs with known and novel markers were found such as HMOX1 and ZFAND2A, ATF3 and PPP1R15A, OXSR1 and HSPA1B, ZFP36 and MAFF. The resulting GDN proved biologically valid as it was well-connected and enriched in known interactions, processes and common regulatory motifs for pairs. Classification accuracy was improved when compared with conventional classifiers. As the dysregulated patterns for heat shock responding genes proved to be distinct from those of other stress genes, we were able to formulate the hypothesis that heat shock genes play a specific role in sensitization, apart from other stress genes. In conclusion, our combined approach creates added value for classification-based toxicogenomics by obtaining novel, well-distinguishing and biologically interesting measures, suitable for the formulation of hypotheses on functional relationships between genes and their relevance for toxicity class differences.

Plasma metabolomics and proteomics profiling after a postprandial challenge reveal subtle diet effects on human metabolic status.

We introduce the metabolomics and proteomics based Postprandial Challenge Test (PCT) to quantify the postprandial response of multiple metabolic processes in humans in a standardized manner. The PCT comprised consumption of a standardized 500 ml dairy shake containing respectively 59, 30 and 12 energy percent lipids, carbohydrates and protein. During a 6 h time course after PCT 145 plasma metabolites, 79 proteins and 7 clinical chemistry parameters were quantified. Multiple processes related to metabolism, oxidation and inflammation reacted to the PCT, as demonstrated by changes of 106 metabolites, 31 proteins and 5 clinical chemistry parameters. The PCT was applied in a dietary intervention study to evaluate if the PCT would reveal additional metabolic changes compared to non-perturbed conditions. The study consisted of a 5-week intervention with a supplement mix of anti-inflammatory compounds in a crossover design with 36 overweight subjects. Of the 231 quantified parameters, 31 had different responses over time between treated and control groups, revealing differences in amino acid metabolism, oxidative stress, inflammation and endocrine metabolism. The results showed that the acute, short term metabolic responses to the PCT were different in subjects on the supplement mix compared to the controls. The PCT provided additional metabolic changes related to the dietary intervention not observed in non-perturbed conditions. Thus, a metabolomics based quantification of a standardized perturbation of metabolic homeostasis is more informative on metabolic status and subtle health effects induced by (dietary) interventions than quantification of the homeostatic situation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0320-5) contains supplementary material, which is available to authorized users.

'Omics analysis of low dose acetaminophen intake demonstrates novel response pathways in humans.

Acetaminophen is the primary cause of acute liver toxicity in Europe/USA, which led the FDA to reconsider recommendations concerning safe acetaminophen dosage/use. Unfortunately, the current tests for liver toxicity are no ideal predictive markers for liver injury, i.e. they only measure acetaminophen exposure after profound liver toxicity has already occurred. Furthermore, these tests do not provide mechanistic information. Here, 'omics techniques (global analysis of metabolomic/gene-expression responses) may provide additional insight. To better understand acetaminophen-induced responses at low doses, we evaluated the effects of (sub-)therapeutic acetaminophen doses on metabolite formation and global gene-expression changes (including, for the first time, full-genome human miRNA expression changes) in blood/urine samples from healthy human volunteers. Many known and several new acetaminophen-metabolites were detected, in particular in relation to hepatotoxicity-linked, oxidative metabolism of acetaminophen. Transcriptomic changes indicated immune-modulating effects (2g dose) and oxidative stress responses (4g dose). For the first time, effects of acetaminophen on full-genome human miRNA expression have been considered and confirmed the findings on mRNA level. 'Omics techniques outperformed clinical chemistry tests and revealed novel response pathways to acetaminophen in humans. Although no definitive conclusion about potential immunotoxic effects of acetaminophen can be drawn from this study, there are clear indications that the immune system is triggered even after intake of low doses of acetaminophen. Also, oxidative stress-related gene responses, similar to those seen after high dose acetaminophen exposure, suggest the occurrence of possible pre-toxic effects of therapeutic acetaminophen doses. Possibly, these effects are related to dose-dependent increases in levels of hepatotoxicity-related metabolites.

Epigenetics: DNA demethylation promotes skeletal myotube maturation.

Mesenchymal progenitor cells can be differentiated in vitro into myotubes that exhibit many characteristic features of primary mammalian skeletal muscle fibers. However, in general, they do not show the functional excitation-contraction coupling or the striated sarcomere arrangement typical of mature myofibers. Epigenetic modifications have been shown to play a key role in regulating the progressional changes in transcription necessary for muscle differentiation. In this study, we demonstrate that treatment of murine C2C12 mesenchymal progenitor cells with 10 µM of the DNA methylation inhibitor 5-azacytidine (5AC) promotes myogenesis, resulting in myotubes with enhanced maturity as compared to untreated myotubes. Specifically, 5AC treatment resulted in the up-regulation of muscle genes at the myoblast stage, while at later stages nearly 50% of the 5AC-treated myotubes displayed a mature, well-defined sarcomere organization, as well as spontaneous contractions that coincided with action potentials and intracellular calcium transients. Both the percentage of striated myotubes and their contractile activity could be inhibited by 20 nM TTX, 10 µM ryanodine, and 100 µM nifedipine, suggesting that action potential-induced calcium transients are responsible for these characteristics. Our data suggest that genomic demethylation induced by 5AC overcomes an epigenetic barrier that prevents untreated C2C12 myotubes from reaching full maturity.

DNA methylation restricts spontaneous multi-lineage differentiation of mesenchymal progenitor cells, but is stable during growth factor-induced terminal differentiation.

The progressive restriction of differentiation potential from pluripotent embryonic stem cells, via multipotent progenitor cells to terminally differentiated, mature somatic cells, involves step-wise changes in transcription patterns that are tightly controlled by the coordinated action of key transcription factors and changes in epigenetic modifications. While previous studies have demonstrated tissue-specific differences in DNA methylation patterns that might function in lineage restriction, it is unclear at what exact developmental stage these differences arise. Here, we have studied whether terminal, multi-lineage differentiation of C2C12 myoblasts is accompanied by lineage-specific changes in DNA methylation patterns. Using bisulfite sequencing and genome-wide methylated DNA- and chromatin immunoprecipitation-on-chip techniques we show that in these cells, in general, myogenic genes are enriched for RNA polymerase II and hypomethylated, whereas osteogenic genes show lower polymerase occupancy and are hypermethylated. Removal of DNA methylation marks by 5-azacytidine (5AC) treatment alters the myogenic lineage commitment of these cells and induces spontaneous osteogenic and adipogenic differentiation. This is accompanied by upregulation of key lineage-specific transcription factors. We subsequently analyzed genome-wide changes in DNA methylation and polymerase II occupancy during BMP2-induced osteogenesis. Our data indicate that BMP2 is able to induce the transcriptional program underlying osteogenesis without changing the methylation status of the genome. We conclude that DNA methylation primes C2C12 cells for myogenesis and prevents spontaneous osteogenesis, but still permits induction of the osteogenic transcriptional program upon BMP2 stimulation. Based on these results, we propose that cell type-specific DNA methylation patterns are established prior to terminal differentiation of adult progenitor cells. This article is part of a Special Issue entitled: 11th European Symposium on Calcium.

Delineation of amplification, hybridization and location effects in microarray data yields better-quality normalization.

BACKGROUND: Oligonucleotide arrays have become one of the most widely used high-throughput tools in biology. Due to their sensitivity to experimental conditions, normalization is a crucial step when comparing measurements from these arrays. Normalization is, however, far from a solved problem. Frequently, we encounter datasets with significant technical effects that currently available methods are not able to correct. RESULTS: We show that by a careful decomposition of probe specific amplification, hybridization and array location effects, a normalization can be performed that allows for a much improved analysis of these data. Identification of the technical sources of variation between arrays has allowed us to build statistical models that are used to estimate how the signal of individual probes is affected, based on their properties. This enables a model-based normalization that is probe-specific, in contrast with the signal intensity distribution normalization performed by many current methods. Next to this, we propose a novel way of handling background correction, enabling the use of background information to weight probes during summarization. Testing of the proposed method shows a much improved detection of differentially expressed genes over earlier proposed methods, even when tested on (experimentally tightly controlled and replicated) spike-in datasets. CONCLUSIONS: When a limited number of arrays are available, or when arrays are run in different batches, technical effects have a large influence on the measured expression of genes. We show that a detailed modelling and correction of these technical effects allows for an improved analysis in these situations.

Effect of chordin-like 1 on MC3T3-E1 and human mesenchymal stem cells.

Since the discovery that bone morphogenetic proteins (BMPs) are able to induce ectopic bone formation, considerable effort has been devoted to apply it for bone regeneration. BMP activity needs to be temporally and spatially controlled and the organism has devised ways to achieve it. Here we show that the BMP inhibitor chordin-like 1 can interfere with BMP2 signalling thereby affecting the osteogenic differentiation of MC3T3-E1 cells. Besides its function as a BMP antagonist, chordin-like 1 enhanced the proliferation of human mesenchymal stem cells (hMSCs) in a BMP2-independent manner. When MC3T3-E1 cells were exposed to recombinant chordin-like 1 there was an inhibition of alkaline phosphatase (ALP) expression, whereas in the case of hMSCs no effect was observed. However, chordin-like 1 dose-dependently increased the proliferation of hMSCs. This effect is probably BMP2 independent because the chordin-like 1 concentration that stimulates proliferation does not interfere with BMP signalling monitored by a Smad-dependent reporter gene. Our data point towards a novel, BMP-independent role of chordin-like 1 in hMSC proliferation.

Developing computational model-based diagnostics to analyse clinical chemistry data.

This article provides methodological and technical considerations to researchers starting to develop computational model-based diagnostics using clinical chemistry data. These models are of increasing importance, since novel metabolomics and proteomics measuring technologies are able to produce large amounts of data that are difficult to interpret at first sight, but have high diagnostic potential. Computational models aid interpretation and make the data accessible for clinical diagnosis. We discuss the issues that a modeller has to take into account during the design, construction and evaluation phases of model development. We use the example of Particle Profiler development, a model-based diagnostic tool for lipoprotein disorders, as a case study, to illustrate our considerations. The case study also offers techniques for efficient model formulation, model calculation, workflow structuring and quality control.

Osteo-transcriptomics of human mesenchymal stem cells: accelerated gene expression and osteoblast differentiation induced by vitamin D reveals c-MYC as an enhancer of BMP2-induced osteogenesis.

Bone marrow-derived human mesenchymal stem cells (hMSCs) have the in vitro capacity to differentiate into osteoblasts, chondrocytes or adipocytes, depending on the applied stimulus. In order to identify novel regulators of osteogenesis in hMSCs, osteo-transcriptomics was performed whereby differentiation induced by dexamethasone (DEX), DEX+ bone morphogenetic protein 2 (BMP2), and DEX+ Vitamin D(3) (1,25(OH)(2)D(3)) was studied over a course of 12 days. Microarray analysis revealed that 2095 genes were significantly regulated by DEX+ 1,25(OH)(2)D(3), of which 961 showed accelerated expression kinetics compared to treatment by DEX alone. The majority of these genes were accelerated 24-48 h after onset of osteogenic treatment. Gene ontology (GO) analysis of these 1,25(OH)(2)D(3)-accelerated genes indicated their involvement in biological processes related to cellular differentiation and cell cycle regulation. When compared to cells treated with DEX or DEX+BMP2, treatment with DEX+ 1,25(OH)(2)D(3) clearly accelerated osteoprogenitor commitment and osteoblast maturation, as measured by alkaline phosphatase (ALP) activity and calcification of the matrix. Cell cycle progression, as observed after initial growth arrest, was not significantly accelerated by 1,25(OH)(2)D(3) and was not required for onset and progression of osteogenesis. However, expression of c-Myc was accelerated by 1,25(OH)(2)D(3), and binding sites for c-MYC were enriched in promoters of genes accelerated by 1,25(OH)(2)D(3). Lentiviral overexpression of c-MYC strongly promoted DEX+ BMP2-induced osteoblast differentiation and matrix maturation. In conclusion, our studies show for the first time that 1,25(OH)(2)D(3) strongly accelerates expression of genes involved in differentiation of hMSCs and, moreover, identify c-MYC as a novel regulator of osteogenesis.

The role of collagen crosslinking in differentiation of human mesenchymal stem cells and MC3T3-E1 cells.

Collagen is the main protein component of the extracellular matrix of bone, and it has structural and instructive properties. Collagen undergoes many post-translational modifications, including extensive crosslinking. Although defective crosslinking has been implicated in human syndromes (e.g., osteogenesis imperfecta or Ehlers-Danlos syndrome), it is not clear to what extent crosslinking is necessary for collagen's instructive properties during bone formation. Here we report that inhibition of collagen crosslinking in the mouse pre-osteoblast cell line MC3T3-E1 impairs the osteogenic program. Genome-wide expression profiling of beta-aminopropionitrile-treated and control cells revealed that matrix deposition by MC3T3-E1 cells provides a feed back signal, driving cells through the differentiation process, that is strongly impaired when crosslinking is inhibited. Inhibition of crosslinking did not affect osteogenic differentiation of human mesenchymal stem cells (hMSCs), shown by the expression of alkaline phosphatase and genome-wide gene expression analysis, although it enhances matrix mineralization. In conclusion, collagen crosslinking harbors instructive properties in MC3T3-E1 differentiation but plays a more-passive role in differentiation of bone marrow-derived hMSCs.

Gene regulatory network inference: data integration in dynamic models-a review.

Systems biology aims to develop mathematical models of biological systems by integrating experimental and theoretical techniques. During the last decade, many systems biological approaches that base on genome-wide data have been developed to unravel the complexity of gene regulation. This review deals with the reconstruction of gene regulatory networks (GRNs) from experimental data through computational methods. Standard GRN inference methods primarily use gene expression data derived from microarrays. However, the incorporation of additional information from heterogeneous data sources, e.g. genome sequence and protein-DNA interaction data, clearly supports the network inference process. This review focuses on promising modelling approaches that use such diverse types of molecular biological information. In particular, approaches are discussed that enable the modelling of the dynamics of gene regulatory systems. The review provides an overview of common modelling schemes and learning algorithms and outlines current challenges in GRN modelling.

Integration of known transcription factor binding site information and gene expression data to advance from co-expression to co-regulation.

The common approach to find co-regulated genes is to cluster genes based on gene expression. However, due to the limited information present in any dataset, genes in the same cluster might be co-expressed but not necessarily co-regulated. In this paper, we propose to integrate known transcription factor binding site information and gene expression data into a single clustering scheme. This scheme will find clusters of co-regulated genes that are not only expressed similarly under the measured conditions, but also share a regulatory structure that may explain their common regulation. We demonstrate the utility of this approach on a microarray dataset of yeast grown under different nutrient and oxygen limitations. Our integrated clustering method not only unravels many regulatory modules that are consistent with current biological knowledge, but also provides a more profound understanding of the underlying process. The added value of our approach, compared with the clustering solely based on gene expression, is its ability to uncover clusters of genes that are involved in more specific biological processes and are evidently regulated by a set of transcription factors.

Microarray analysis on Runx2-deficient mouse embryos reveals novel Runx2 functions and target genes during intramembranous and endochondral bone formation.

A major challenge in developmental biology is to correlate genome-wide gene expression modulations with developmental processes in vivo. In this study, we analyzed the role of Runx2 during intramembranous and endochondral bone development, by comparing gene expression profiles in 14.5 dpc wild-type and Runx2 (-/-) mice. A total of 1277, 606 and 492 transcripts were found to be significantly modulated by Runx2 in calvaria, forelimbs and hindlimbs, respectively. Bioinformatics analysis indicated that Runx2 not only controls the processes of osteoblast differentiation and chondrocyte maturation, but may also play a role in axon formation and hematopoietic cell commitment during bone development. A total of 41 genes are affected by the Runx2 deletion in both intramembranous and endochondral bone, indicating common pathways between these two developmental modes of bone formation. In addition, we identified genes that are specifically involved in endochondral ossification. In conclusion, our data show that a comparative genome-wide expression analysis of wild-type and mutant mouse models allows the examination of mutant phenotypes in complex tissues.

Microarray analysis reveals expression regulation of Wnt antagonists in differentiating osteoblasts.

Wnt signaling has been implicated in regulating bone formation by controlling osteoblast proliferation and function. Although stabilization of beta-catenin by Wnt has been shown to increase alkaline phosphatase expression and osteoblast differentiation, the precise role of Wnt signaling during the process of osteoblast differentiation is largely unknown. In this study, we used microarray technology to investigate expression regulation of Wnt signaling components during in vitro osteoblast differentiation. Expression was analyzed during bone morphogenetic protein 2 (BMP2)-induced osteoblast differentiation of murine C2C12 and MC3T3 cells and data were compared with expression in BMP2-treated NIH3T3 fibroblasts. During osteoblast differentiation, particularly strong expression regulation of the Wnt antagonists Sfrp2 (secreted frizzled related protein 2) and Wif1 (Wnt inhibitory factor 1) was observed in the late phase of differentiation. In situ expression analysis in murine tail vertebrae supported Wif1 expression during late phase bone cell differentiation, since Wif1 was found to be expressed in vivo in trabecular, but not in cortical bone. We further analyzed the effects of continuous activation of Wnt signaling by lithium chloride and observed that osteoblast differentiation was reduced, as measured by expression of osteoblast marker genes encoding alkaline phosphatase, osteocalcin, and osterix, as well as by the amount of calcium release. Taken together, our data indicate that endogenous expression of Wnt antagonists by osteoblasts provides a negative Wnt feedback loop which is essential in controlling osteoblast maturation.