DBnorm as an R package for the comparison and selection of appropriate statistical methods for batch effect correction in metabolomic studies.

As a powerful phenotyping technology, metabolomics provides new opportunities in biomarker discovery through metabolome-wide association studies (MWAS) and the identification of metabolites having a regulatory effect in various biological processes. While mass spectrometry-based (MS) metabolomics assays are endowed with high throughput and sensitivity, MWAS are doomed to long-term data acquisition generating an overtime-analytical signal drift that can hinder the uncovering of real biologically relevant changes. We developed "dbnorm", a package in the R environment, which allows for an easy comparison of the model performance of advanced statistical tools commonly used in metabolomics to remove batch effects from large metabolomics datasets. "dbnorm" integrates advanced statistical tools to inspect the dataset structure not only at the macroscopic (sample batches) scale, but also at the microscopic (metabolic features) level. To compare the model performance on data correction, "dbnorm" assigns a score that help users identify the best fitting model for each dataset. In this study, we applied "dbnorm" to two large-scale metabolomics datasets as a proof of concept. We demonstrate that "dbnorm" allows for the accurate selection of the most appropriate statistical tool to efficiently remove the overtime signal drift and to focus on the relevant biological components of complex datasets

Arsenic induces metabolome remodeling in mature human adipocytes.

Human lifetime exposure to arsenic through drinking water, food supply or industrial pollution leads to its accumulation in many organs such as liver, kidneys, lungs or pancreas but also adipose tissue. Recently, population-based studies revealed the association between arsenic exposure and the development of metabolic diseases such as obesity and type 2 diabetes. To shed light on the molecular bases of such association, we determined the concentration that inhibited 17% of cell viability and investigated the effects of arsenic acute exposure on adipose-derived human mesenchymal stem cells differentiated in vitro into mature adipocytes and treated with sodium arsenite (NaAsO <sub>2</sub> , 10 nM to 10 µM). Untargeted metabolomics and gene expression analyses revealed a strong dose-dependent inhibition of lipogenesis and lipolysis induction, reducing the cellular ability to store lipids. These dysregulations were emphasized by the inhibition of the cellular response to insulin, as shown by the perturbation of several genes and metabolites involved in the mentioned biological pathways. Our study highlighted the activation of an adaptive oxidative stress response with the strong induction of metallothioneins and increased glutathione levels in response to arsenic accumulation that could exacerbate the decreased insulin sensitivity of the adipocytes. Arsenic exposure strongly affected the expression of arsenic transporters, responsible for arsenic influx and efflux, and induced a pro-inflammatory state in adipocytes by enhancing the expression of the inflammatory interleukin 6 (IL6). Collectively, our data showed that an acute exposure to low levels of arsenic concentrations alters key adipocyte functions, highlighting its contribution to the development of insulin resistance and the pathogenesis of metabolic disorders

Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes.

The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers

Metabolomics reveals biomarkers in human urine and plasma to predict cytochrome P450 2D6 (CYP2D6) activity.

Individualized assessment of cytochrome P450 2D6 (CYP2D6) activity is usually performed through phenotyping following administration of a probe drug to measure the enzyme's activity. To avoid any iatrogenic harm (allergic drug reaction, dosing error) related to the probe drug, the development of non-burdensome tools for real-time phenotyping of CYP2D6 could significantly contribute to precision medicine. This study focuses on the identification of markers of the CYP2D6 enzyme in human biofluids using an LC-high-resolution mass spectrometry-based metabolomic approach. Plasma and urine samples from healthy volunteers were analysed before and after intake of a daily dose of paroxetine 20 mg over 7 days. CYP2D6 genotyping and phenotyping, using single oral dose of dextromethorphan 5 mg, were also performed in all participants. We report four metabolites of solanidine and two unknown compounds as possible novel CYP2D6 markers. Mean relative intensities of these features were significantly reduced during the inhibition session compared with the control session (n = 37). Semi-quantitative analysis showed that the largest decrease (-85%) was observed for the ion m/z 432.3108 normalized to solanidine (m/z 398.3417). Mean relative intensities of these ions were significantly higher in the CYP2D6 normal-ultrarapid metabolizer group (n = 37) compared with the poor metabolizer group (n = 6). Solanidine intensity was more than 15 times higher in CYP2D6-deficient individuals compared with other volunteers. The applied untargeted metabolomic strategy identified potential novel markers capable of semi-quantitatively predicting CYP2D6 activity, a promising discovery for personalized medicine

Detecting early myocardial ischemia in rat heart by MALDI imaging mass spectrometry.

Diagnostics of myocardial infarction in human post-mortem hearts can be achieved only if ischemia persisted for at least 6-12 h when certain morphological changes appear in myocardium. The initial 4 h of ischemia is difficult to diagnose due to lack of a standardized method. Developing a panel of molecular tissue markers is a promising approach and can be accelerated by characterization of molecular changes. This study is the first untargeted metabolomic profiling of ischemic myocardium during the initial 4 h directly from tissue section. Ischemic hearts from an ex-vivo Langendorff model were analysed using matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) at 15 min, 30 min, 1 h, 2 h, and 4 h. Region-specific molecular changes were identified even in absence of evident histological lesions and were segregated by unsupervised cluster analysis. Significantly differentially expressed features were detected by multivariate analysis starting at 15 min while their number increased with prolonged ischemia. The biggest significant increase at 15 min was observed for m/z 682.1294 (likely corresponding to S-NADHX-a damage product of nicotinamide adenine dinucleotide (NADH)). Based on the previously reported role of NAD <sup>+</sup> /NADH ratio in regulating localization of the sodium channel (Na <sub>v</sub> 1.5) at the plasma membrane, Na <sub>v</sub> 1.5 was evaluated by immunofluorescence. As expected, a fainter signal was observed at the plasma membrane in the predicted ischemic region starting 30 min of ischemia and the change became the most pronounced by 4 h. Metabolomic changes occur early during ischemia, can assist in identifying markers for post-mortem diagnostics and improve understanding of molecular mechanisms

Separation of blood microsamples by exploiting sedimentation at the microscale.

Microsample analysis is highly beneficial in blood-based testing where cutting-edge bioanalytical technologies enable the analysis of volumes down to a few tens of microliters. Despite the availability of analytical methods, the difficulty in obtaining high-quality and standardized microsamples at the point of collection remains a major limitation of the process. Here, we detail and model a blood separation principle which exploits discrete viscosity differences caused by blood particle sedimentation in a laminar flow. Based on this phenomenon, we developed a portable capillary-driven microfluidic device that separates blood microsamples collected from finger-pricks and delivers 2 µL of metered serum for bench-top analysis. Flow cytometric analysis demonstrated the high purity of generated microsamples. Proteomic and metabolomic analyses of the microsamples of 283 proteins and 1351 metabolite features was consistent with samples generated via a conventional centrifugation method. These results were confirmed by a clinical study scrutinising 8 blood markers in obese patients

Risk factors in ectopic pregnancy and differences between adults and adolescents, is consanguinity important?

The aim of the study was to determine the risk factors of ectopic pregnancy (EP) and to compare them between women over and under 20 years of age. 308 cases of EP (case group) were compared with 616 cases of normal pregnancy. Smoking Ad OR =5.7 (CI 95%=2.8�11.6), p 20-year-old group. Negative Rh p = 0.02, good economic status p = 0.000 and prior STD p = 0.03 were more common in Afghan women. However, previous caesarean delivery p = 0.04 was more in Iranian women. Smoking, previous EP, history of STD, IUD, infertility, previous caesarean delivery and consanguinity are all risk factors for EP. © 2016 Informa UK Limited, trading as Taylor & Francis Group

Proteome and Metabolome of Subretinal Fluid in Central Serous Chorioretinopathy and Rhegmatogenous Retinal Detachment: A Pilot Case Study.

To investigate the molecular composition of subretinal fluid (SRF) in central serous chorioretinopathy (CSCR) and rhegmatogenous retinal detachment (RRD) using proteomics and metabolomics. SRF was obtained from one patient with severe nonresolving bullous CSCR requiring surgical subretinal fibrin removal, and two patients with long-standing RRD. Proteins were trypsin-digested, labeled with Tandem-Mass-Tag and fractionated according to their isoelectric point for identification and quantification by tandem mass spectrometry. Independently, metabolites were extracted on cold methanol/ethanol, and identified by untargeted ultra-high performance liquid chromatography and high-resolution mass spectrometry. Bioinformatics analyses were conducted. In total, 291 proteins and 651 metabolites were identified in SRF samples. Compared with RRD, 128 proteins (77 downregulated; 51 upregulated) and 76 metabolites (43 downregulated; 33 upregulated) differed in the SRF from CSCR. Protein and metabolites notably deregulated in CSCR were related to glycolysis/gluconeogenesis, inflammation (including serum amyloid P component, versican), alternative complement pathway (complement factor H and complement factor H-related protein), cellular adhesion, biliary acid metabolism (farnesoid X receptor/retinoid X receptor), and gluco- and mineralocorticoid systems (aldosterone, angiotensin, and corticosteroid-binding globulin). Proteomics and metabolomics can be performed on SRF. A unique SRF sample from CSCR exhibited a distinct molecular profile compared with RRD. This first comparative multiomics analysis of SRF improved the understanding of CSCR and RRD pathophysiology. It identified pathways potentially involved in the better photoreceptor preservation in CSCR, suggesting neuroprotective targets that will require additional confirmation