Data intensive scientific analysis with grid computing

At the end of September 2009, a new Italian GPS receiver for radio occultation was launched from the Satish Dhawan Space Center (Sriharikota, India) on the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to implement the overall processing radio occultation chain. After a brief description of the adopted algorithms, which can be used to characterize the temperature, pressure and humidity, the contribution will focus on a method for automatic processing these data, based on the use of a distributed architecture. This paper aims at being a possible application of grid computing for scientific research

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk.

Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.This research utilizes resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), National Human Genome Research Institute (NHGRI), National Institute of Child Health and Human Development (NICHD), and Juvenile Diabetes Research Foundation International (JDRF) and supported by U01 DK062418. This work is supported in part by funding from the National Institutes of Health (5R01AR062886-02 (PIdB), 1R01AR063759 (SR), 5U01GM092691-05 (SR), 1UH2AR067677-01 (SR), R01AR065183 (PIWdB)), a Doris Duke Clinical Scientist Development Award (SR), the Wellcome Trust (JAT) and the National Institute for Health Research (JAT and JMMH), and a Vernieuwingsimpuls VIDI Award (016.126.354) from the Netherlands Organization for Scientific Research (PIWdB). TLL was supported by the German Research Foundation (LE 2593/1-1 and LE 2593/2-1).This is the accepted manuscript. The final version is available at http://www.nature.com/ng/journal/v47/n8/full/ng.3353.html

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures

Geographic population structure analysis of worldwide human populations infers their biogeographical origins

The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing

Carotid beta stiffness association with thyroid function

Background: Thyroid hormone modulation of cardiovascular function has been associated with cardiovascular disease. Recent evidence suggests that free thyroxine (FT4) levels are associated with an increase in systemic arterial stiffness, but little is known about the effects of FT4 at the local level of the common carotid artery. β-stiffness index is a local elastic parameter usually determined by carotid ultrasound imaging. Methods: We conducted a cross-sectional analysis in the ProgeNIA cohort, including 4846 subjects across a broad age range. For the purpose of this study, we excluded subjects with increased thyrotropin (TSH) levels and those treated with levothyroxine or thyrostatic. We assessed β stiffness, strain, wall–lumen ratio, carotid cross-sectional area (CSA), and stress and flow in the right common carotid artery. We tested whether FT4, heart rate, and their interactions were associated with carotid parameters. Results: FT4 was positively and independently associated with β stiffness index (β = 0.026, p = 0.041), and had a negative association with strain (β = −0.025, p = 0.009). After adding heart rate and the interaction between FT4 and heart rate to the model, FT4 was still associated with the β stiffness index (β = 0.186, p = 0.06), heart rate was positively associated with the stiffness index (β = 0.389, p < 0.001) as well as their interaction (β = 0.271, p = 0.007). Conclusion: This study suggests that higher FT4 levels increase arterial stiffness at the common carotid level, consistent with a detrimental effect on elastic arteries. The effect of FT4 is likely to be primarily attributable to its effect on heart rate

Software Defined Radio system for GNSS-Refectometry: activities performed at the Politecnico of Turin (Italy)

The GNSS signals are an important active source for Earth’s remote sensing in L band. Experiments performed over sea and land surfaces demonstrated the capability of GNSS-Reflected signals (GNSS-R) for remote sensing purposes. Presently, many research groups are focusing their efforts in developing GNSS-R sensors for soil moisture, sea, sea-ice, and snow cover monitoring. Applications like drought monitoring, farm production, irrigation planning, flood protection, fire prevention, and meteorological forecasts can take advantage from retrieved soil moisture content. Detected sea-surface winds could help to identify adverse meteorological conditions far from coastal zones. Sea altimetry measurements could be used to monitor tides and to identify natural hazards (i.e. tsunamis). Sea-ice topographic changes in the Arctic and Antarctic regions and dry ice stratification could be monitored in order to improve polar climatology knowledge. Recently the Remote Sensing Group of Politecnico of Turin and NavSAS laboratory of ISMB (Istituto Superiore Mario Boella) starts the design and implementation of a fully reconfigurable GNSS-R instrument for research activities, following a Software Defined Radio approach. Using this solution, the hardware is reduced to the RF stages only (i.e. antennas, demodulation, sampling) and the processing starts from the IF (Intermediate Frequency) samples of the raw signal. This is a low-cost portable observing system, designed to be easily placed for example also on board small aircrafts (also unmanned). In this sense, the system components were carefully chosen to minimize size and weight of the complete observing system. Together with the system definition, a user interface is started to be developed. Actually the interface allows a quasi real time control of the received signal. The correct estimation of the whole correlation function profile (in range and frequency space) is achieved by keeping the noise level as low as possible and increasing the SNR. Therefore, it is important to optimally process signals even when long - non coherent integration time is necessary. The interface we developed is able to process such signals using FFT (Fast Fourier Transform) based acquisition algorithms. In addition, an optimized procedure is implemented to compensate for a residual code delay, enhancing the detection of weak signals. The interface allows also experimental activities planning, since it shows specular reflection points and isorange lines (inside receiver antenna’s footprint), computed knowing estimated or predicted satellite positions. All the information are georeferenced using UTM (Universal Transverse Mercator) coordinate system and projected on Google© static maps. Thus, this user friendly interface is a helpful tool able to generate all the necessary output for the geophysical applications performed exploiting GNSS-R signals. In order to test instrument and interface, some experimental activities were recently done by placing the instrument on a high cliff to collect some looks from the sea surface and on board an aircraft to collects measurements from soil reflections (rice fields water flooding, soil moisture, altimetry). Another important activity is to adapt our GNSS-R system for space-based measurements in the framework of an educational project which is being carried out by students belonging to the Aerospace and ICT Engineering faculties of Politecnico of Turin. This student project is going to be developed in the framework of an initiative offered by the Education Office of the European Space Agency. We are trying to design and develop on a system level a space-based test bed for an Earth’s Remote Sensing payload to be placed on-board a small Cubesat. This is the P-GRESSION payload (Payload for GNSS REmote Sensing and Signal detectION). It will try to demonstrate the feasibility of existing applications based on observations normally carried out by costly and operative space receivers. Two concepts will be tested. The first one is a twofold GNSS Remote Sensing experiment: 1) the GNSS Radio Occultation experiment, for the profiling of atmospheric refractivity, temperature, water vapour and electron density, which are very important for climate and meteorological purposes, and 2) The GNSS-R experiment for the land and sea surface parameters sensing. It is worth noting that, for both these GNSS-based experiments, global world coverage of observations is assured in all weather conditions. Finally, the current development/improvement of future global GNSS systems will enlarge the number of offered GNSS signals, improving consequently the resolution in time and space of the remote sensing observables. The second concept is based on signal identification. In particular P-GRESSION will acquire signals coming from ground-based radars, in C and/or X frequency bands, both for detection and for calibration purposes. All the experiments will be based on the same Software Defined Radio approach, since after standard radio acquisition with low cost front ends and antennas, all operations will be performed by softwar