Alexessander Couto Alves

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Rationale Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10−8) and three variants reported as suggestive (P<5×10−7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10−9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (P Stage1+Stage2 = 1.1x10−9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (P Stage1+Stage2 = 1.1x10−8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.

Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization

Allergen-specific immunoglobulin E (present in allergic sensitization) has a central role in the pathogenesis of allergic disease. We performed the first large-scale genome-wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up the top SNP at each of 26 loci in 6,114 affected individuals and 9,920 controls. We increased the number of susceptibility loci with genome-wide significant association with allergic sensitization from three to ten, including SNPs in or near TLR6, C11orf30, STAT6, SLC25A46, HLA-DQB1, IL1RL1, LPP, MYC, IL2 and HLA-B. All the top SNPs were associated with allergic symptoms in an independent study. Risk-associated variants at these ten loci were estimated to account for at least 25% of allergic sensitization and allergic rhinitis. Understanding the molecular mechanisms underlying these associations may provide new insights into the etiology of allergic disease.

Optimization and Evaluation of Metabolite Extraction Protocols for Untargeted Metabolic Profiling of Liver Samples by UPLC-MS

A series of six protocols were evaluated for UPLC-MS based untargeted metabolic profiling of liver extracts in terms of reproducibility and number of metabolite features obtained. These protocols, designed to extract both polar and nonpolar metabolites, were based on (i) a two stage extraction approach or (ii) a simultaneous extraction in a biphasic mixture, employing different volumes and combinations of extraction and resuspension solvents. A multivariate statistical strategy was developed to allow comparison of the multidimensional variation between the methods. The optimal protocol for profiling both polar and nonpolar metabolites was found to be an aqueous extraction with methanol/water followed by an organic extraction with dichloromethane/methanol, with resuspension of the dried extracts in methanol/water before UPLC-MS analysis. This protocol resulted in a median CV of feature intensities among experimental replicates of <20% for aqueous extracts and <30% for organic extracts. These data demonstrate the robustness of the proposed protocol for extracting metabolites from liver samples and make it well suited for untargeted liver profiling in studies exploring xenobiotic hepatotoxicity and clinical investigations of liver disease. The generic nature of this protocol facilitates its application to other tissues, for example, brain or lung, enhancing its utility in clinical and toxicological studies.

Analytic Properties of Statistical Total Correlation Spectroscopy Based Information Recovery in 1H NMR Metabolic Data Sets

Structural assignment of resonances is an important problem in NMR spectroscopy, and statistical total correlation spectroscopy (STOCSY) is a useful tool aiding this process for small molecules in complex mixture analysis and metabolic profiling studies. STOCSY delivers intramolecular information (delineating structural connectivity) and in metabolism studies can generate information on pathway-related correlations. To understand further the behavior of STOCSY for structural assignment, we analyze the statistical distribution of structural and nonstructural correlations from 1050 (1)H NMR spectra of normal rat urine samples. We find that the distributions of structural/nonstructural correlations are significantly different (p < 10(-112)). From the area under the curve of the receiver operating characteristic (ROC AUC) we show that structural correlations exceed nonstructural correlations with probability AUC = 0.98. Through a bootstrap resampling approach, we demonstrate that sample size has a surprisingly small effect (e.g., AUC = 0.97 for a sample size of 50). We identify specific signatures in the correlation maps resulting from small matrix-derived variations in peak positions but find that their effect on discrimination of structural and nonstructural correlations is negligible for most metabolites. A correlation threshold of r > 0.89 is required to assign two peaks to the same metabolite with high probability (positive predictive value, PPV = 0.9), whereas sensitivity and specificity are equal at 93% for r = 0.22. To assess the wider applicability of our results, we analyze (1)H NMR spectra of urine from rats treated with 115 model toxins or physiological stressors. Across the data sets, we find that the thresholds required to obtain PPV = 0.9 are not significantly different and the degree of overlap between the structural and nonstructural distributions is always small (median AUC = 0.97). The STOCSY method is effective for structural characterization under diverse biological conditions and sample sizes provided the degree of correlation resulting from nonstructural associations (e.g., from nonstationary processes) is small. This study validates the use of the STOCSY approach in the routine assignment of signals in NMR metabolic profiling studies and provides practical benchmarks against which researchers can interpret the results of a STOCSY analysis.

Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms

BackgroundComplex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.ResultsWe identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.ConclusionsModules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.

Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation.

Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P<5 × 10−8) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.

Rapid identification of bacterial isolates from wheat roots by high resolution whole cell MALDI-TOF MS analysis.

Whole-cell mass spectrometry analysis is a powerful tool to rapidly identify microorganisms. Several studies reported the successful application of this technique to identify a variety of bacterial species with a discriminatory power at the strain level, mainly for bacteria of clinical importance. In this study we used matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to assess the diversity of wheat-associated bacterial isolates. Wheat plants cultivated in non-sterile vermiculite, under greenhouse conditions were used for bacterial isolation. Total cellular extracts of 138 isolates were analyzed by MALDI-TOF MS and the mass spectra were used to cluster the isolates. Taxonomic identification and phylogenetic reconstruction based on 16S rRNA gene sequences showed the presence of Pseudomonas, Pantoea, Acinetobacter, Enterobacter and Curtobacterium. The 16S rRNA gene sequence analyses were congruent with the clusterization from mass spectra profile. Moreover, MALDI-TOF whole cell mass profiling allowed a finer discrimination of the isolates, suggesting that this technique has the potential of differentiating bacterial isolates at the strain level.

Novel association approach for variable number tandem repeats (VNTRs) identifies DOCK5 as a susceptibility gene for severe obesity.

Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.2 encompassing the dedicator of cytokinesis 5 (DOCK5) gene. The region includes two VNTRs of complex sequence composition which flank a common 3975 bp deletion, all three of which were genotyped by polymerase chain reaction and fragment analysis in a total of 2744 subjects. We have developed a novel VNTR association method named VNTRtest, suitable for association analysis of multi-allelic loci with binary and quantitative outcomes, and have used this approach to show significant association of the DOCK5 VNTRs with childhood and adult severe obesity (P(empirical)= 8.9 × 10(-8) and P= 3.1 × 10(-3), respectively) which we estimate explains ~0.8% of the phenotypic variance. We also identified an independent association between the 3975 base pair (bp) deletion and obesity, explaining a further 0.46% of the variance (P(combined)= 1.6 × 10(-3)). Evidence for association between DOCK5 transcript levels and the 3975 bp deletion (P= 0.027) and both VNTRs (P(empirical)= 0.015) was also identified in adipose tissue from a Swedish family sample, providing support for a functional effect of the DOCK5 deletion and VNTRs. These findings highlight the potential role of DOCK5 in human obesity and illustrate a novel approach for analysis of the contribution of VNTRs to disease susceptibility through association studies.

Multiple measures of adiposity are associated with mean leukocyte telomere length in the Northern Finland birth cohort 1966

Studies of leukocyte telomere length (LTL) and adiposity have produced conflicting results, and the relationship between body mass index (BMI) and telomere length throughout life remains unclear. We therefore tested association of adult LTL measured in 5,598 participants with: i) childhood growth measures (BMI and age at adiposity rebound (AR)); ii) change in BMI from childhood to adulthood and iii) adult BMI, waist-to-hip ratio (WHR), body adiposity index (BAI). Childhood BMI at AR was positively associated with LTL at 31 years in women (P = 0.041). Adult BMI and WHR in both men (P = 0.025 and P = 0.049, respectively) and women (P = 0.029 and P = 0.008, respectively), and BAI in women (P = 0.021) were inversely associated with LTL at 31 years. An increase in standardised BMI between early childhood and adulthood was associated with shorter adult LTL in women (P = 0.008). We show that LTL is inversely associated with multiple measures of adiposity in both men and women. Additionally, BMI increase in women from childhood to adulthood is associated with shorter telomeres at age 31, potentially indicating accelerated biological ageing.

Integrative Pathway Genomics of Lung Function and Airflow Obstruction

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10s role in influencing lungs susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.