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1.  Platelet mitochondrial membrane potential in Parkinson's disease 
Mitochondrial dysfunction is a hallmark of idiopathic Parkinson's disease (IPD), which has been reported not to be restricted to striatal neurons. However, studies that analyzed mitochondrial function at the level of selected enzymatic activities in peripheral tissues have produced conflicting data. We considered the electron transport chain as a complex system with mitochondrial membrane potential as an integrative indicator for mitochondrial fitness.
Twenty-five IPD patients (nine females; mean disease duration, 6.2 years) and 16 healthy age-matched controls (12 females) were recruited. Live platelets were purified using magnetic-activated cell sorting (MACS) and single-cell data on mitochondrial membrane potential (Δψ) were measured by cytometry and challenged with a protonophore agent.
Functional mitochondrial membrane potential was detected in all participants. The challenge test reduced the membrane potential in all IPD patients and controls (P < 0.001). However, the response to the challenge was not significantly different between patients and controls.
While the reported protonophore challenge assay is a valid marker of overall mitochondrial function in live platelets, intact mitochondrial membrane potential in platelets derived from IPD patients suggests that presumed mitochondrial enzymatic deficiencies are compensable in this cell type. In consequence, mitochondrial membrane potential in platelets cannot be used as a diagnostic biomarker for nonstratified IPD but should be further explored in potential Parkinson's disease subtypes and tissues with higher energy demands.
PMCID: PMC4301676  PMID: 25642436
2.  Revolutionizing medicine in the 21st century through systems approaches 
Biotechnology journal  2012;7(8):992-1001.
Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term “personalized medicine”, however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory – a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development and will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type – this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a “holistic systems approach” to disease as we will discuss in this article.
PMCID: PMC3962497  PMID: 22815171
Functional genomics; Network biology; Personalized medicine; Systems medicine
3.  Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map 
Molecular Neurobiology  2013;49(1):88-102.
Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at
Electronic supplementary material
The online version of this article (doi:10.1007/s12035-013-8489-4) contains supplementary material, which is available to authorized users.
PMCID: PMC4153395  PMID: 23832570
Parkinson’s disease; Molecular neuropathology; Knowledge repository; Bioinformatics
4.  PLAU inferred from a correlation network is critical for suppressor function of regulatory T cells 
Network-based analysis of transcriptome dynamics during activation in two human T-cell subpopulations identifies key regulators, and reveals that PLAU plays a critical role in both human and murine regulatory T-cell function.
We construct a Treg-specific correlation network from a high time-resolution transcriptome of human Tregs versus CD4+ T effector cells measured during their very early activation process.We propose a queen bee-surrounding principle to predict key candidate genes from the simplified undirected correlation network rather than an advanced directed transcription regulatory network. These potential key genes would have not been easily identified by a differential expression analysis.We show that the plasminogen activator urokinase (PLAU) is critical for suppressor function of both human and murine Tregs.We further demonstrate that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways.
Human FOXP3+CD25+CD4+ regulatory T cells (Tregs) are essential to the maintenance of immune homeostasis. Several genes are known to be important for murine Tregs, but for human Tregs the genes and underlying molecular networks controlling the suppressor function still largely remain unclear. Here, we describe a strategy to identify the key genes directly from an undirected correlation network which we reconstruct from a very high time-resolution (HTR) transcriptome during the activation of human Tregs/CD4+ T-effector cells. We show that a predicted top-ranked new key gene PLAU (the plasminogen activator urokinase) is important for the suppressor function of both human and murine Tregs. Further analysis unveils that PLAU is particularly important for memory Tregs and that PLAU mediates Treg suppressor function via STAT5 and ERK signaling pathways. Our study demonstrates the potential for identifying novel key genes for complex dynamic biological processes using a network strategy based on HTR data, and reveals a critical role for PLAU in Treg suppressor function.
Network-based analysis of transcriptome dynamics during activation in two human T-cell subpopulations identifies key regulators, and reveals that PLAU plays a critical role in both human and murine regulatory T-cell function.
PMCID: PMC3531908  PMID: 23169000
high time-resolution time series; human CD4 regulatory T cell; infer key genes from undirected gene networks; Plau knockout mice; Treg development and suppressor function
5.  Understanding complexity in neurodegenerative diseases: in silico reconstruction of emergence 
Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent property, emerging from a perturbation of the network. On the one hand, the biomolecular network of every individual is unique and this is evident when similar disease-producing agents cause different individual pathologies. Consequently, a personalized model and approach for every patient may be required for therapies to become effective across mankind. On the other hand, diverse combinations of internal and external perturbation factors may cause a similar shift in network functioning. We offer this as an explanation for the multi-factorial nature of most diseases: they are “systems biology diseases,” or “network diseases.” Here we use neurodegenerative diseases, like Parkinson's disease (PD), as an example to show that due to the inherent complexity of these networks, it is difficult to understand multi-factorial diseases with simply our “naked brain.” When describing interactions between biomolecules through mathematical equations and integrating those equations into a mathematical model, we try to reconstruct the emergent properties of the system in silico. The reconstruction of emergence from interactions between huge numbers of macromolecules is one of the aims of systems biology. Systems biology approaches enable us to break through the limitation of the human brain to perceive the extraordinarily large number of interactions, but this also means that we delegate the understanding of reality to the computer. We no longer recognize all those essences in the system's design crucial for important physiological behavior (the so-called “design principles” of the system). In this paper we review evidence that by using more abstract approaches and by experimenting in silico, one may still be able to discover and understand the design principles that govern behavioral emergence.
PMCID: PMC3429063  PMID: 22934043
systems biology; systems biology diseases; network diseases; weak emergence; strong emergence; computer modeling; neurodegenerative disease; Parkinson's disease (PD)
6.  Systems medicine and integrated care to combat chronic noncommunicable diseases 
Genome Medicine  2011;3(7):43.
We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.
PMCID: PMC3221551  PMID: 21745417
7.  Parkinson’s disease mouse models in translational research 
Mammalian Genome  2011;22(7-8):401-419.
Animal models with high predictive power are a prerequisite for translational research. The closer the similarity of a model to Parkinson’s disease (PD), the higher is the predictive value for clinical trials. An ideal PD model should present behavioral signs and pathology that resemble the human disease. The increasing understanding of PD stratification and etiology, however, complicates the choice of adequate animal models for preclinical studies. An ultimate mouse model, relevant to address all PD-related questions, is yet to be developed. However, many of the existing models are useful in answering specific questions. An appropriate model should be chosen after considering both the context of the research and the model properties. This review addresses the validity, strengths, and limitations of current PD mouse models for translational research.
PMCID: PMC3151483  PMID: 21559878
8.  Finding and sharing: new approaches to registries of databases and services for the biomedical sciences 
The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources.
Database URL:
PMCID: PMC2911849  PMID: 20627863
9.  The European dimension for the mouse genome mutagenesis program 
Nature genetics  2004;36(9):925-927.
The European Mouse Mutagenesis Consortium is the European initiative contributing to the international effort on functional annotation of the mouse genome. Its objectives are to establish and integrate mutagenesis platforms, gene expression resources, phenotyping units, storage and distribution centers and bioinformatics resources. The combined efforts will accelerate our understanding of gene function and of human health and disease.
PMCID: PMC2716028  PMID: 15340424
10.  From mouse genetics to systems biology 
Mammalian Genome  2007;18(6-7):383-388.
PMCID: PMC1998886  PMID: 17668264
11.  Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation 
Genome Biology  2007;8(9):R181.
By combining information on the yeast transcription network and high-resolution time-series data with a series of factors, support is provided for the concept that dynamic cumulative regulation is a major principle of quantitative transcriptional control.
The regulation of genes in multicellular organisms is generally achieved through the combinatorial activity of different transcription factors. However, the quantitative mechanisms of how a combination of transcription factors controls the expression of their target genes remain unknown.
By using the information on the yeast transcription network and high-resolution time-series data, the combinatorial expression profiles of regulators that best correlate with the expression of their target genes are identified. We demonstrate that a number of factors, particularly time-shifts among the different regulators as well as conversion efficiencies of transcription factor mRNAs into functional binding regulators, play a key role in the quantification of target gene expression. By quantifying and integrating these factors, we have found a highly significant correlation between the combinatorial time-series expression profile of regulators and their target gene expression in 67.1% of the 161 known yeast three-regulator motifs and in 32.9% of 544 two-regulator motifs. For network motifs involved in the cell cycle, these percentages are much higher. Furthermore, the results have been verified with a high consistency in a second independent set of time-series data. Additional support comes from the finding that a high percentage of motifs again show a significant correlation in time-series data from stress-response studies.
Our data strongly support the concept that dynamic cumulative regulation is a major principle of quantitative transcriptional control. The proposed concept might also apply to other organisms and could be relevant for a wide range of biotechnological applications in which quantitative gene regulation plays a role.
PMCID: PMC2375019  PMID: 17784952
12.  Targeted Disruption of the Peptide Transporter Pept2 Gene in Mice Defines Its Physiological Role in the Kidney 
Molecular and Cellular Biology  2003;23(9):3247-3252.
The peptide transporter PEPT2 mediates the cellular uptake of di- and tripeptides and selected drugs by proton-substrate cotransport across the plasma membrane. PEPT2 was functionally identified initially in the apical membrane of renal tubular cells but was later shown to be expressed in other tissues also. To investigate the physiological importance of PEPT2 and for a detailed analysis of the protein expression sites, we generated a Pept2 knockout mouse line in which the Pept2 gene was disrupted by insertion of a β-galactosidase gene under the control of the PEPT2 promoter. The Pept2−/− mice showed no obvious phenotypic abnormalities but also no adaptive upregulation in the expression level of related genes in the kidney. The importance of PEPT2 in the reabsorption of filtered dipeptides was demonstrated in knockout animals by significantly reduced renal accumulation of a fluorophore-labeled and a radiolabeled dipeptide after in vivo administration of the tracers. This indicates that PEPT2 is the main system responsible for tubular reabsorption of peptide-bound amino acids, although this does not lead to major changes in renal excretion of protein or free amino acids.
PMCID: PMC153205  PMID: 12697824

Results 1-12 (12)