Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique’s spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.The work was funded by the Basque Government (IT971-16, IT1162-19, and ELKARTEK KK2018-00090) and has been developed as a Ph.D. project of LMS, who is the recipient of a Predoctoral Fellowship from the Spanish Government (BES- 2016-078721) . The authors are grateful to SGiker Lipidomic Service (UPV/EHU, MICINN, GV/EG, ESF) for the expert advice and technical and human support in MALDI and HPLC- MS analysis

Sixty-five common genetic variants and prediction of type 2 diabetes.

We developed a 65 type 2 diabetes (T2D) variant-weighted gene score to examine the impact on T2D risk assessment in a U.K.-based consortium of prospective studies, with subjects initially free from T2D (N = 13,294; 37.3% women; mean age 58.5 [38-99] years). We compared the performance of the gene score with the phenotypically derived Framingham Offspring Study T2D risk model and then the two in combination. Over the median 10 years of follow-up, 804 participants developed T2D. The odds ratio for T2D (top vs. bottom quintiles of gene score) was 2.70 (95% CI 2.12-3.43). With a 10% false-positive rate, the genetic score alone detected 19.9% incident cases, the Framingham risk model 30.7%, and together 37.3%. The respective area under the receiver operator characteristic curves were 0.60 (95% CI 0.58-0.62), 0.75 (95% CI 0.73 to 0.77), and 0.76 (95% CI 0.75 to 0.78). The combined risk score net reclassification improvement (NRI) was 8.1% (5.0 to 11.2; P = 3.31 × 10(-7)). While BMI stratification into tertiles influenced the NRI (BMI ≤24.5 kg/m(2), 27.6% [95% CI 17.7-37.5], P = 4.82 × 10(-8); 24.5-27.5 kg/m(2), 11.6% [95% CI 5.8-17.4], P = 9.88 × 10(-5); >27.5 kg/m(2), 2.6% [95% CI -1.4 to 6.6], P = 0.20), age categories did not. The addition of the gene score to a phenotypic risk model leads to a potentially clinically important improvement in discrimination of incident T2D

Identifying low density lipoprotein cholesterol associated variants in the Annexin A2 (ANXA2) gene.

BACKGROUND AND AIMS: Annexin-A2 (AnxA2) is an endogenous inhibitor of proprotein convertase subtilisin/kexin type-9 (PCSK9). The repeat-one (R1) domain of AnxA2 binds to PCSK9, blocking its ability to promote degradation of low-density lipoprotein cholesterol-receptors (LDL-R) and thereby regulate low-density lipoprotein cholesterol (LDL-C) levels. Here we identify variants in ANXA2 influencing LDL-C levels and we determine the molecular mechanisms of their effects. RESULTS: The ANXA2 single nucleotide polymorphism (SNP) genotype-phenotype association was examined using the Second-Northwick-Park Heart Study (NPHSII) (n∼2700) and the UCL-LSHTM-Edinburgh-Bristol (UCLEB) consortium (n∼14,600). The ANXA2-R1 domain coding-SNP rs17845226 (V98L) associated with LDL-C, homozygotes for the minor allele having ≈18.8% higher levels of LDL-C (p = 0.004), and higher risk of coronary heart disease (CHD) (p = 0.04). The SNP is in modest linkage disequilibrium (r(2) > 0.5) with two intergenic SNPs, rs17191344 and rs11633032. Both SNPs showed allele-specific protein binding, and the minor alleles caused significant reduction in reporter gene expression (≈18%, p < 0.001). In the expression quantitative trait loci (eQTL) study, minor allele homozygotes have significantly lower levels of ANXA2-mRNA expression (p = 1.36 × 10(-05)). CONCLUSIONS: Both rs11633032 and rs17191344 SNPs are functional variants, where the minor alleles create repressor-binding protein sites for transcription factors that contribute to reduced ANXA2 gene expression. Lower AnxA2 levels could increase plasma levels of PCSK9 and thus increase LDL-C levels and risk of CHD. This supports, for the first time in humans, previous observations in mouse models that changes in the levels of AnxA2 directly influence plasma LDL-C levels, and thus implicate this protein as a potential therapeutic target for LDL-C lowering

Adult height, coronary heart disease and stroke: a multi-locus Mendelian randomization meta-analysis

BACKGROUND: We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis. METHODS: We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D. RESULTS: IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index (P < 0.001), triglycerides (P < 0.001), non high-density (non-HDL) cholesterol (P < 0.001), C-reactive protein (P = 0.042), and systolic blood pressure (P = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity (P < 0.001 for both). CONCLUSIONS: Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure

FR8RAIL: Development of functional requirements for sustainable and attractive European rail freight

The modal share of intra-EU rail freight transport is less than 20% of the freight transport sector. The current rail"br" freight situation is not only due to the existence of legal barriers restricting competition (including the track access"br" regime, taxation, etc.), but also due to limitations of operational and technical nature, which impact the overall"br" capacity and performance of the sector."br" In order to overcome these issues, Shift2Rail set a specific Innovation Programme 5 (IP5) focused on Technologies"br" for Sustainable & Attractive European Rail Freight. In this context, the FR8RAIL project, is working on the"br" “Development of Functional Requirements for Sustainable and Attractive European Rail”."br" To overcome these limitations, a holistic approach involving several technical areas, that form the backbone of the"br" project approach. The outcomes of FR8RAIL will positively contribute to and support the Shift2Rail goals to"br" strengthen the role of the freight rail transport

Railway Wireless Communications Channel Characterization

Railway applications are in continuous evolution with the aim of offering a more efficient, sustainable, and safer transportation system for the users. Generally, these applications are constantly exchanging information between the systems onboard the train and the trackside through a wireless communication. Nowadays, Global System for Mobile communications-Railway (GSM-R) is the technology used by European Train Control System (ETCS), but it is becoming obsolete. Therefore, alternatives for this technology have to be found for the different railway applications. Its natural evolution is to move forward with the latest technology deployed: Long-Term Evolution (LTE), which the Public Land Mobile Networks (PLMN) have already deployed. Therefore, testing the performance of this communication technology in the railway environment could be useful to assess its suitability and reduce the cost of railway network dedicated deployment. In order to do that, a methodology to characterize the communication environment is proposed. The main goal is to measure geolocated impairments of any communication channel in a railway environment being able to determine its behavior of the different communication technologies and find out possible coverage issues. Moreover, it could help in the selection of suitable communication technology for railway. This paper presents a brief description of the communication for railways and its QoS parameters for performance measuring. Afterward, the testing methodology is described, and then, the communication channel measurement campaign on a real track in Spain where the railway environment is variable is presented (tunnels, rural/urban area…). Finally, the measurements and results on this real track in Spain are shown. The results provide suitability of the 4G technologies based on the delay requirements for the implementation of ETCS over it

Big-Data framework-based visualization solution for performance analysis of positioning systems in railway environments

The on-board positioning system provides not only the location estimation but also additional information about the certainty or quality of the provided estimation. Additionally, when developing the positioning system itself and evaluating the performance of the system, it is useful to thoroughly analyze the input parameter values used by the positioning system for each of the location estimates. A visualization platform based on Big-Data frameworks was highly demanded in this context and several alternatives were analyzed. This paper describes the approaches that have been tested and implemented, describes the difficulties and advantages of the alternatives and provides detailed steps for adapting the open-source Big-Data framework-based solutions to other application areas