Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP.

Spatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts

GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals.

Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies' findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community

Association Between Genetic Variants on Chromosome 15q25 Locus and Objective Measures of Tobacco Exposure

BACKGROUND Two single-nucleotide polymorphisms, rs1051730 and rs16969968, located within the nicotinic acetylcholine receptor gene cluster on chromosome 15q25 locus, are associated with heaviness of smoking, risk for lung cancer, and other smoking-related health outcomes. Previous studies have typically relied on self-reported smoking behavior, which may not fully capture interindividual variation in tobacco exposure. METHODS We investigated the association of rs1051730 and rs16969968 genotype (referred to as rs1051730–rs16969968, because these are in perfect linkage disequilibrium and interchangeable) with both self-reported daily cigarette consumption and biochemically measured plasma or serum cotinine levels among cigarette smokers. Summary estimates and descriptive statistical data for 12 364 subjects were obtained from six independent studies, and 2932 smokers were included in the analyses. Linear regression was used to calculate the per-allele association of rs1051730–rs16969968 genotype with cigarette consumption and cotinine levels in current smokers for each study. Meta-analysis of per-allele associations was conducted using a random effects method. The likely resulting association between genotype and lung cancer risk was assessed using published data on the association between cotinine levels and lung cancer risk. All statistical tests were two-sided. RESULTS Pooled per-allele associations showed that current smokers with one or two copies of the rs1051730–rs16969968 risk allele had increased self-reported cigarette consumption (mean increase in unadjusted number of cigarettes per day per allele = 1.0 cigarette, 95% confidence interval [CI] = 0.57 to 1.43 cigarettes, P = 5.22 × 10−6) and cotinine levels (mean increase in unadjusted cotinine levels per allele = 138.72 nmol/L, 95% CI = 97.91 to 179.53 nmol/L, P = 2.71 × 10−11). The increase in cotinine levels indicated an increased risk of lung cancer with each additional copy of the rs1051730–rs16969968 risk allele (per-allele odds ratio = 1.31, 95% CI = 1.21 to 1.42). CONCLUSIONS Our data show a stronger association of rs1051730–rs16969968 genotype with objective measures of tobacco exposure compared with self-reported cigarette consumption. The association of these variants with lung cancer risk is likely to be mediated largely, if not wholly, via tobacco exposure

Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan

The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes

Associations of Body Mass and Fat Indexes With Cardiometabolic Traits

Background Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear. Objectives The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood. Methods BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children. Results Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index. Conclusions The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects

Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan

The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes

A genome-wide association study for corneal curvature identifies the platelet-derived growth factor receptor alpha gene as a quantitative trait locus for eye size in white Europeans

2012-2013 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies

This is the final version. Available on open access from the Public Library of Science via the DOI in this recordData Availability: We used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data as follows: Journal published and website summary data were used for generating the genetic scores of birth weight, fasting glucose and systolic blood pressure. The references to those published data sources are provided in the main paper. We used individual participant data from ALSPAC, EFSOCH and NFBC cohorts. The data in ALSPAC are fully available, via managed systems, to any researchers. The managed system is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. Researchers have to pay for a dataset to be prepared for them. ALSPAC. The ALSPAC data management plan (http://www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-management-plan.pdf) describes in detail the policy regarding data sharing, which is through a system of managed open access. The steps below highlight how to apply for access to the data included in this paper and all other ALSPAC data. 1. Please read the ALSPAC access policy (PDF, 627kB) which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so. 2. You may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011. 3. Please submit your research proposal for consideration by the ALSPAC Executive Committee. You will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please email [email protected]. EFSOCH. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility [email protected]. NFBC: Data is available from the Northern Finland Birth Cohort (NFBC) for researchers who meet the criteria for accessing confidential data. Please, contact NFBC project center ([email protected]) and visit the cohort website (www.oulu.fi/nfbc) for more information.Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) 90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model. Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal=0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal=0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal=0.014, Pmaternal=0.062). Higher maternal SBP GS was associated with higher odds of SGA P=0.005 . We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.Wellcome TrustRoyal SocietyNational Institute for Health Research (NIHR

Evaluating the Quality of Research into a Single Prognostic Biomarker: A Systematic Review and Meta-analysis of 83 Studies of C-Reactive Protein in Stable Coronary Artery Disease

Background Systematic evaluations of the quality of research on a single prognostic biomarker are rare. We sought to evaluate the quality of prognostic research evidence for the association of C-reactive protein (CRP) with fatal and nonfatal events among patients with stable coronary disease. Methods and Findings We searched MEDLINE (1966 to 2009) and EMBASE (1980 to 2009) and selected prospective studies of patients with stable coronary disease, reporting a relative risk for the association of CRP with death and nonfatal cardiovascular events. We included 83 studies, reporting 61,684 patients and 6,485 outcome events. No study reported a prespecified statistical analysis protocol; only two studies reported the time elapsed (in months or years) between initial presentation of symptomatic coronary disease and inclusion in the study. Studies reported a median of seven items (of 17) from the REMARK reporting guidelines, with no evidence of change over time. The pooled relative risk for the top versus bottom third of CRP distribution was 1.97 (95% confidence interval [CI] 1.78–2.17), with substantial heterogeneity (I2 = 79.5). Only 13 studies adjusted for conventional risk factors (age, sex, smoking, obesity, diabetes, and low-density lipoprotein [LDL] cholesterol) and these had a relative risk of 1.65 (95% CI 1.39–1.96), I2 = 33.7. Studies reported ten different ways of comparing CRP values, with weaker relative risks for those based on continuous measures. Adjusting for publication bias (for which there was strong evidence, Egger's p<0.001) using a validated method reduced the relative risk to 1.19 (95% CI 1.13–1.25). Only two studies reported a measure of discrimination (c-statistic). In 20 studies the detection rate for subsequent events could be calculated and was 31% for a 10% false positive rate, and the calculated pooled c-statistic was 0.61 (0.57–0.66). Conclusion Multiple types of reporting bias, and publication bias, make the magnitude of any independent association between CRP and prognosis among patients with stable coronary disease sufficiently uncertain that no clinical practice recommendations can be made. Publication of prespecified statistical analytic protocols and prospective registration of studies, among other measures, might help improve the quality of prognostic biomarker research