A Bridge of Light: Toward Chinese and Western Medicine Perspectives Through Ultraweak Photon Emissions.

The gap between Western medicine and traditional Chinese medicine (CM) is closely related to the diversity in culture, philosophy, and scientific developments. Although numerous studies have evaluated the efficacy of acupuncture, the gap in explanatory disease models has not been bridged so far. Developments in research of ultraweak photon emission (UPE) and organized dynamics of metabolism and its relationship with technological advances in metabolomics have created the conditions to bring the basics of the medicines of the West and East together which might open the avenue for a scientific dialogue. The paper discusses (1) the UPE in relation to Qi energy, meridians and acupuncture points in CM, (2) the biochemical explanation of photon emission of living systems in Western biomedicine, and (3) the progress in research on the large-scale organization and dynamics of the metabolic network including photon metabolism.

Role of amino acids in rheumatoid arthritis studied by metabolomics.

BACKGROUND: Rheumatoid arthritis (RA) is a complex, chronic autoimmune disease characterized by various inflammatory symptoms, including joint swelling, joint pain, and both structural and functional joint damage. The most commonly used animal model for studying RA is mice with collagen-induced arthritis (CIA); the wide use of this model is due primarily to many similarities with RA in human patients. Metabolomics is used increasingly in biological studies for diagnosing disease and for predicting and evaluating drug interventions, as a large number of disease-associated metabolites can be analyzed and interpreted from a biological perspective. AIM: To profile free amino acids and their biogenic metabolites in CIA mice plasma. METHOD: Ultra-high-performance liquid chromatography/tandem mass spectrometry coupled with multiple reaction monitoring (MRM) was used for metabolomics study. RESULTS: Profile of 45 amine metabolites, including free amino acids and their biogenic metabolites in plasma was obtained from CIA mice. We found that the plasma levels of 20 amine metabolites were significantly decreased in the CIA group. CONCLUSION: The results suggest that a disordered amine response is linked to RA-associated muscle wasting and energy expenditure.

Grip on health: A complex systems approach to transform health care.

This article addresses the urgent need for a transition in health care to deal with the increasing prevalence of chronic diseases and associated rapid rise of health care costs. Chronic diseases evolve and are predominantly related to lifestyle and environment. A shift is needed from a reductionist repair mode of thinking, toward a more integrated biopsychosocial way of thinking about health. The aim of this article is to discuss the opportunities that complexity science offer for transforming health care toward optimal treatment and prevention of chronic lifestyle diseases. Health and health care is discussed from a complexity science perspective. The benefits of concepts developed in the field of complexity science for stimulating transitions in health care are explored. Complexity science supports the elucidation of the essence of health processes. It provides a unique perspective on health with a focus on the relationships within networks of dynamically interacting factors and the emergence of health out of the organization of those relationships. Novel types of complexity science-based intervention strategies are being developed. The first application in practice is the integrated obesity treatment program currently piloted in the Netherlands, focusing on health awareness and healing relationships. Complexity science offers various theories and methods to capture the path toward unhealthy and healthy states, facilitating the development of a dynamic integrated biopsychosocial perspective on health. This perspective offers unique insights into health processes for patients and citizens. In addition, dynamic models driven by personal data provide simulations of health processes and the ability to detect transitions between health states. Such models are essential for aligning and reconnecting the many institutions and disciplines involved in the health care sector and evolve toward an integrated health care ecosystem.

Cellular glutathione levels in HL-60 cells during respiratory burst are not correlated with ultra-weak photon emission.

Recently, ultra-weak photon emission (UPE) was developed as a novel tool for measuring oxidative metabolic processes, as its generation is related to reactive oxygen species (ROS). Both an imbalance in ROS or the uncontrolled production of ROS can lead to oxidative stress, which is commonly associated with many diseases. In addition to playing several biological functions, the thiol amino acid glutathione has an important antioxidant function in the body's defense against ROS. Specifically, glutathione is an important endogenous antioxidant that helps maintain oxidant levels. At the cellular level, glutathione is present in its reduced form (GSH) at relatively high concentrations (in the millimolar range) and in its oxidized form (GSSG) at low concentrations (in the micromolar range). Thus, the GSH/GSSG ratio is often used as an indicator of cellular redox state. Here, we used the HL-60 cell line as a model system in order to determine whether UPE is correlated with intracellular GSH and GSSG levels. HL-60 cells were differentiated into neutrophil-like cells and then stimulated to undergo respiratory burst. We then recorded UPE in real time for 9000 seconds and used capillary electrophoresis coupled to mass spectrometry to measure GSH and GSSG levels in cell extracts. We found that although respiratory burst significantly decreased the GSH/GSSG ratio, this change was not significantly correlated with the UPE profile.

Spontaneous ultra-weak photon emission in correlation to inflammatory metabolism and oxidative stress in a mouse model of collagen-induced arthritis.

The increasing prevalence of rheumatoid arthritis has driven the development of new approaches and technologies for investigating the pathophysiology of this devastating, chronic disease. From the perspective of systems biology, combining comprehensive personal data such as metabolomics profiling with ultra-weak photon emission (UPE) data may provide key information regarding the complex pathophysiology underlying rheumatoid arthritis. In this article, we integrated UPE with metabolomics-based technologies in order to investigate collagen-induced arthritis, a mouse model of rheumatoid arthritis, at the systems level, and we investigated the biological underpinnings of the complex dataset. Using correlation networks, we found that elevated inflammatory and ROS-mediated plasma metabolites are strongly correlated with a systematic reduction in amine metabolites, which is linked to muscle wasting in rheumatoid arthritis. We also found that increased UPE intensity is strongly linked to metabolic processes (with correlation co-efficiency |r| value >0.7), which may be associated with lipid oxidation that related to inflammatory and/or ROS-mediated processes. Together, these results indicate that UPE is correlated with metabolomics and may serve as a valuable tool for diagnosing chronic disease by integrating inflammatory signals at the systems level. Our correlation network analysis provides important and valuable information regarding the disease process from a system-wide perspective.

Characterization of the therapeutic properties of Chinese herbal materials by measuring delayed luminescence and dendritic cell-based immunomodulatory response.

Based on the traditional Chinese medicine theory, the Chinese pharmacopeia assigns a therapeutic description of "taste" to all herbs; thus, an herb's "taste" is valued in traditional Chinese medicine as a major ethnopharmacological category and reflects the herb's therapeutic properties. These properties guide the practitioner with respect to preparing a specific herbal formula in order to provide each patient with a personalized intervention. The key challenge in evidence-based medicine is to characterize herbal therapeutic properties from a multi-target, multi-dimensional systems pharmacology perspective. Here, we used delayed luminescence (DL, the slowly decaying emission of photons following excitation with light) as a rapid, direct, highly sensitive indicator to characterize the properties of herbal medicines. The DL parameters were able to reliably identify a specific category of herbal materials with the so-called "sweet" taste. To support the DL results and provide biological relevance to the DL results, we used a murine bone marrow-derived dendritic cell-based assay to examine the immunomodulatory effects of herbal extracts from various "taste" categories. Our results indicate that DL may serve as a robust and sensitive tool for evaluating the therapeutic properties of herbs based on the traditional Chinese medicine classification of "taste". Thus, DL provides a promising technological platform for investigating the properties of Chinese herbal medicines both qualitatively and quantitatively.

Measuring ultra-weak photon emission as a non-invasive diagnostic tool for detecting early-stage type 2 diabetes: A step toward personalized medicine.

The global prevalence of type 2 diabetes is estimated to reach 4.4% by 2030, placing a significant burden on our healthcare system. Therefore, the ability to identify patients in early stages of the disease is essential for both prevention and effective management, and diagnostic methods based on traditional Chinese medicine (TCM) may be suitable for identifying patients with early-stage type 2 diabetes. Here, a panel of three physicians trained in TCM classified 44 pre-diabetic subjects into three syndrome subtypes using TCM-based diagnostics. In addition, ultra-weak photon emission (UPE) was measured at four anatomical sites in each subject. Ten properties encompassing 40 parameters were then extracted from the UPE time series. Statistical analyses, including multinomial logistic regression, were performed using the results of each parameter measured at the four sites. Sixteen UPE parameters were then selected and used to discriminate between the three subtypes of pre-diabetic subjects. Next, Spearman's correlation coefficient was used to quantify the correlation between the 16 UPE parameters and the TCM-based diagnoses. The resulting correlation networks accurately reflected the differences between the three syndrome subtypes. These results suggest that UPE is a suitable tool for detecting subtypes in early-stage type 2 diabetes. In addition, our results provide evidence that TCM may represent an important step toward personalized medicine.

Crossing the Boundaries of Our Current Healthcare System by Integrating Ultra-Weak Photon Emissions with Metabolomics.

The current healthcare system is hampered by a reductionist approach in which diagnostics and interventions focus on a specific target, resulting in medicines that center on generic, static phenomena while excluding inherent dynamic nature of biological processes, let alone psychosocial parameters. In this essay, we present some limitations of the current healthcare system and introduce the novel and potential approach of combining ultra-weak photon emission (UPE) with metabolomics technology in order to provide a dynamic readout of higher organizational systems. We argue that the combination of metabolomics and UPE can bring a new, broader, view of health state and can potentially help to shift healthcare toward more personalized approach that improves patient well-being.

Differences between serum polar lipid profiles of male and female rheumatoid arthritis patients in response to glucocorticoid treatment.

OBJECTIVE: As there are pharmacological differences between males and females, and glucocorticoid (GC) treatment is associated with increased cardiovascular mortality rate in rheumatoid arthritis (RA) patients, it is important to study serum polar lipid profiles of male and female patients in response to GC therapy. Gender differences may require an adjustment to the treatment strategy for a selection of patients. METHODS: Serum samples from 281 RA patients were analysed using a targeted lipidomics platform. The differences in GC use and gender on polar lipid profiles were cross sectionally examined by multiple linear regressions, while correcting for confounding factors. RESULTS: Differences in polar lipids between GC users and non-GC users in females and males were merely restricted to lysophospholipids (lysophosphatidylcholines and lysophosphatidylethanolamines). Lysophospholipids in female patients treated with GCs were significantly higher than female patients not treated with GCs (p = 6.0 E-6), whereas no significant difference was observed in male GC users versus non-users (p = 0.397). CONCLUSION: The lysophospholipid profiles in response to GCs were significantly different between male and female RA patients, which may have implications for the cardiovascular risk of GC treatment.

Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction model for response to TNFi therapy, containing metabolites and clinical parameters. Associations between metabolites and disease activity may help elucidate additional pathologic mechanisms behind RA.

Tracking biochemical changes correlated with ultra-weak photon emission using metabolomics.

Ultra-weak photon emission (UPE) is light emitted spontaneously by biological systems without the use of specific luminescent complexes. UPE is emitted in the near-UV/UV-Vis/near-IR spectra during oxidative metabolic reactions; however, the specific pathways involved in UPE remain poorly understood. Here, we used HL-60 cells, a human promyelocytic cell line that is often used to study respiratory burst, as a model system to measure UPE kinetics together with metabolic changes. HL-60 cells were differentiated into neutrophil-like cells by culturing in all-trans-retinoic acid for 7days. We then used a targeted metabolomics approach with capillary electrophoresis-mass spectrometry to profile intracellular metabolites in HL-60 cells and to investigate the biochemical changes based on the measured UPE profile. Our analysis revealed that the levels of specific metabolites, including putrescine, creatine, ß-alanine, methionine, hydroxyproline, serine, and S-adenosylmethionine, were significantly altered in HL-60 cells after inducing respiratory burst. A comparison with recorded UPE data revealed that the changes in putrescine, glutathione, sarcosine, creatine, ß-alanine, methionine, and hydroxyproline levels were inversely correlated with the change in UPE intensity. These results suggest that these metabolic pathways, particular the methionine pathway, may play a role in the observed changes in UPE in HL-60 cells and therefore demonstrate the potential for using UPE to monitor metabolic changes.

Metabolomics profiling of the free and total oxidised lipids in urine by LC-MS/MS: application in patients with rheumatoid arthritis.

Oxidised lipids, covering enzymatic and auto-oxidation-synthesised mediators, are important signalling metabolites in inflammation while also providing a readout for oxidative stress, both of which are prominent physiological processes in a plethora of diseases. Excretion of these metabolites via urine is enhanced through the phase-II conjugation with glucuronic acid, resulting in increased hydrophilicity of these lipid mediators. Here, we developed a bovine liver-ß-glucuronidase hydrolysing sample preparation method, using liquid chromatography coupled to tandem mass spectrometry to analyse the total urinary oxidised lipid profile including the prostaglandins, isoprostanes, dihydroxy-fatty acids, hydroxy-fatty acids and the nitro-fatty acids. Our method detected more than 70 oxidised lipids biosynthesised from two non-enzymatic and three enzymatic pathways in urine samples. The total oxidised lipid profiling method was developed and validated for human urine and was demonstrated for urine samples from patients with rheumatoid arthritis. Pro-inflammatory mediators PGF2α and PGF3α and oxidative stress markers iPF2α- IV, 11-HETE and 14-HDoHE were positively associated with improvement of disease activity score. Furthermore, the anti-inflammatory nitro-fatty acids were negatively associated with baseline disease activity. In conclusion, the developed methodology expands the current metabolic profiling of oxidised lipids in urine, and its application will enhance our understanding of the role these bioactive metabolites play in health and disease.

Effects of growth altitude on chemical constituents and delayed luminescence properties in medicinal rhubarb.

To improve the quality control of herbal drugs, there has been a major shift from evaluating individual chemicals to evaluating multiple-constituent chemicals, given the multi-pharmacology nature of herbal drugs. Therefore, rapid, systematic assays are needed in order to assess the quality of medicinal herbs using a comprehensive, integrated approach. Light-induced delayed luminescence (DL) is used to measure decaying long-term ultra-weak photon emissions following excitation with light. DL is considered to be a sensitive indicator for characterizing the properties of biological systems and herbal medicines with various therapeutic properties. The aim of this study was to examine the feasibility of using DL as a novel quality-assessment tool using rhubarb material as a model system, and to establish the correlation between DL parameters and the chemical constituents of rhubarb. Raw roots and rhizomes were collected from rhubarb (Rheum palmatum L.) at various elevations in western China. HPLC analysis was used to identify fourteen bioactive constituents. Five DL parameters were calculated from the DL decay curves of the rhubarb samples. Statistical tools, including principal component analysis, were used to classify the rhubarb samples using data obtained using two different assays. Finally, Spearman's correlation coefficient was calculated to quantify the correlation between the bioactive compounds and corresponding DL parameters. We found that both the chemical analysis and DL measurements reflect variations in the quality of rhubarb due to environment factor. The DL parameters were correlated significantly with the bioactive chemical constituents. Our results indicate that DL is a promising tool for evaluating multiple constituents and for assessing the therapeutic properties of herbal medicines. Thus, DL may be used as part of a comprehensive system for assessing the quality and/or therapeutic properties of herbal medicines.

A Chinese literature overview on ultra-weak photon emission as promising technology for studying system-based diagnostics.

To present the possibilities pertaining to linking ultra-weak photon emission (UPE) with Chinese medicine-based diagnostics principles, we conducted a review of Chinese literature regarding UPE with respect to a systems view of diagnostics. Data were summarized from human clinical studies and animal models published from 1979 through 1998. The research fields can be categorized as follows: (1) human physiological states measured using UPE; (2) characteristics of human UPE in relation to various pathological states; and (3) the relationship between diagnosis (e.g., Chinese syndromes) and the dynamics of UPE in animal models. We conclude that UPE has clear potential in terms of understanding the systems view on health and disease as described using Chinese medicine-based diagnostics, particularly from a biochemistry-based regulatory perspective. Linking UPE with metabolomics can further bridge biochemistry-based Western diagnostics with the phenomenology-based Chinese diagnostics, thus opening new avenues for studying systems diagnostics in the early stage of disease, for prevention-based strategies, as well as for systems-based intervention in chronic disease.

Delayed luminescence: an experimental protocol for Chinese herbal medicines.

In Chinese medicine, raw herbal materials are used in processed and unprocessed forms aiming to meet the different requirements of clinical practice. To assure the chemical quality and therapeutic properties of the herbs, fast and integrated systematic assays are required. So far, such assays have not been established. Delayed luminescence (DL) refers to a decaying long-term ultraweak photon emission after exposure to light. Its decay kinetics under certain conditions may be a sensitive indicator reflecting the internal structural and chemical/physiological state of a biological system. DL measurements have been used in many applications for quality control. However, relatively little research has been reported on dried plant material such as Chinese herbs. The objective of the present study is to establish a protocol for direct and rapid DL measurements of dried Chinese herbal materials, including the determination of the dependence on: (a) the optimal excitation time utilizing a white light source; (b) the optimal size of the grinded herbal particle; and (c) the humidity conditions before and during measurement. Results indicate that stable and reproducible curves of DL photon emission depend mainly on the water content of herbal materials. To investigate the application of the established DL measurement protocol, non-processed and processed Aconitum (Aconitum carmichaelii Debx.), wild and cultivated rhubarb (Rheum palmatum L.) and ginseng (Panax ginseng C.A.Mey) of different ages were measured using DL. The results suggest that DL technology is a potential tool for assessment of dried Chinese herb qualities. The results warrant a further exploration of this technique in relation to therapeutic properties of the herbs. Copyright © 2016 John Wiley & Sons, Ltd.

Collagen Induced Arthritis in DBA/1J Mice Associates with Oxylipin Changes in Plasma.

Oxylipins play important roles in various biological processes and are considered as mediators of inflammation for a wide range of diseases such as rheumatoid arthritis (RA). The purpose of this research was to study differences in oxylipin levels between a widely used collagen induced arthritis (CIA) mice model and healthy control (Ctrl) mice. DBA/1J male mice (age: 6-7 weeks) were selected and randomly divided into two groups, namely, a CIA and a Ctrl group. The CIA mice were injected intraperitoneally (i.p.) with the joint cartilage component collagen type II (CII) and an adjuvant injection of lipopolysaccharide (LPS). Oxylipin metabolites were extracted from plasma for each individual sample using solid phase extraction (SPE) and were detected with high performance liquid chromatography/tandem mass spectrometry (HPLC-ESI-MS/MS), using dynamic multiple reaction monitoring (dMRM). Both univariate and multivariate statistical analyses were applied. The results in univariate Student's t-test revealed 10 significantly up- or downregulated oxylipins in CIA mice, which were supplemented by another 6 additional oxylipins, contributing to group clustering upon multivariate analysis. The dysregulation of these oxylipins revealed the presence of ROS-generated oxylipins and an increase of inflammation in CIA mice. The results also suggested that the collagen induced arthritis might associate with dysregulation of apoptosis, possibly inhibited by activated NF-κB because of insufficient PPAR-γ ligands.

The hypothalamic-pituitary-adrenal-leptin axis and metabolic health: a systems approach to resilience, robustness and control.

Glucocorticoids contribute to obesity and metabolic syndrome; however, the mechanisms are unclear, and prognostic measures are unavailable. A systems level understanding of the hypothalamic-pituitary-adrenal (HPA)-leptin axis may reveal novel insights. Eighteen obese premenopausal women provided blood samples every 10 min over 24 h, which were assayed for cortisol, adrenocorticotropin releasing hormone (ACTH) and leptin. A published personalized HPA systems model was extended to incorporate leptin, yielding three parameters: (i) cortisol inhibitory feedback signalling, (ii) ACTH-adrenal signalling, and (iii) leptin-cortisol antagonism. We investigated associations between these parameters and metabolic risk profiles: fat and lean body mass (LBM; using dual-energy X-ray absorptiometry), and insulin resistance. Decreased cortisol inhibitory feedback signalling was significantly associated with greater fat (kg; p = 0.01) and insulin resistance (p = 0.03) but not LBM. Leptin significantly antagonized cortisol dynamics in eight women, who exhibited significantly lower 24 h mean leptin levels, LBM and higher ACTH-adrenal signalling nocturnally (all p < 0.05), compared with women without antagonism. Traditional neuroendocrine measures did not predict metabolic health, whereas a dynamic systems approach revealed that lower central inhibitory cortisol feedback signalling was significantly associated with greater metabolic risk. While exploratory, leptin-cortisol antagonism may reflect a 'neuroendocrine starvation' response.

Of monkeys and men: a metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species.

BACKGROUND: Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the variation of intrinsic (such as (epi)genetic variation, gut microbiota, etc.) and extrinsic factors (such as dietary habits, life-style and environmental conditions). Understanding the relative contributions of these factors is essential to establish the robustness of the healthy individual metabolic phenotype. METHODS: To assess the relative contribution of intrinsic and extrinsic factors we compared multilevel analysis results obtained from subjects of Homo sapiens and Macaca mulatta, the latter kept in a controlled environment with a standardized diet by making use of previously published data and results. RESULTS: We observed similarities for the two species and found the diversity of urinary metabolic phenotypes as identified by nuclear magnetic resonance (NMR) spectroscopy could be ascribed to the complex interplay of intrinsic factors and, to a lesser extent, of extrinsic factors in particular minimizing the role played by diet in shaping the metabolic phenotype. Moreover, we show that despite the standardization of diet as the most relevant extrinsic factor, a clear individual and discriminative metabolic fingerprint also exists for monkeys. We investigate the metabolic phenotype both at the static (i.e., at the level of the average metabolite concentration) and at the dynamic level (i.e., concerning their variation over time), and we show that these two components sum up to the overall phenotype with different relative contributions of about 1/4 and 3/4, respectively, for both species. Finally, we show that the great degree diversity observed in the urinary metabolic phenotype of both species can be attributed to differences in both the static and dynamic part of their phenotype.

Phenotypic flexibility as key factor in the human nutrition and health relationship.

Metabolic adaptation to a disturbance of homeostasis is determined by a series of interconnected physiological processes and molecular mechanisms that can be followed in space (i.e., different organs or organelles) and in time. The amplitudes of these responses of this "systems flexibility network" determine to what extent the individual can adequately react to external challenges of varying nature and thus determine the individual's health status and disease predisposition. Connected pathways and regulatory networks act as "adaptive response systems" with metabolic and inflammatory processes as a core-but embedded into psycho-neuro-endocrine control mechanisms that in their totality define the phenotypic flexibility in an individual. Optimal metabolic health is thus the orchestration of all mechanisms and processes that maintain this flexibility in an organism as a phenotype. Consequently, onset of many chronic metabolic diseases results from impairment or even loss of flexibility in parts of the system. This also means that metabolic diseases need to be diagnosed and treated from a systems perspective referring to a "systems medicine" approach. This requires a far better understanding of the mechanisms involved in maintaining, optimizing and restoring phenotypic flexibility. Although a loss of flexibility in a specific part of the network may promote pathologies, this not necessarily takes place in the same part because the system compensates. Diagnosis at systems level therefore needs the quantification of the response reactions of all relevant parts of the phenotypic flexibility system. This can be achieved by disturbing the homeostatic system by any challenge from extended fasting, to intensive exercise or a caloric overload.

Correlated measurement error hampers association network inference.

Modern chromatography-based metabolomics measurements generate large amounts of data in the form of abundances of metabolites. An increasingly popular way of representing and analyzing such data is by means of association networks. Ideally, such a network can be interpreted in terms of the underlying biology. A property of chromatography-based metabolomics data is that the measurement error structure is complex: apart from the usual (random) instrumental error there is also correlated measurement error. This is intrinsic to the way the samples are prepared and the analyses are performed and cannot be avoided. The impact of correlated measurement errors on (partial) correlation networks can be large and is not always predictable. The interplay between relative amounts of uncorrelated measurement error, correlated measurement error and biological variation defines this impact. Using chromatography-based time-resolved lipidomics data obtained from a human intervention study we show how partial correlation based association networks are influenced by correlated measurement error. We show how the effect of correlated measurement error on partial correlations is different for direct and indirect associations. For direct associations the correlated measurement error usually has no negative effect on the results, while for indirect associations, depending on the relative size of the correlated measurement error, results can become unreliable. The aim of this paper is to generate awareness of the existence of correlated measurement errors and their influence on association networks. Time series lipidomics data is used for this purpose, as it makes it possible to visually distinguish the correlated measurement error from a biological response. Underestimating the phenomenon of correlated measurement error will result in the suggestion of biologically meaningful results that in reality rest solely on complicated error structures. Using proper experimental designs that allow for the quantification of the size of correlated and uncorrelated errors, can help to identify suspicious connections in association networks constructed from (partial) correlations.