EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology.Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified  EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity.Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease. It is the fourth leading cause of death in the world and is expected to be the third by 2020. COPD is a heterogeneous and complex disease consisting of obstruction in the small airways, emphysema, and chronic bronchitis. COPD is generally caused by exposure to noxious particles or gases, most commonly from cigarette smoking. However, only 20–25% of smokers develop clinically significant airflow obstruction. Smoking is known to cause epigenetic changes in lung tissues. Thus, genetics, epigenetic, and their interaction with environmental factors play an important role in COPD pathogenesis and progression. Currently, there are no therapeutics that can reverse COPD progression. In order to identify new targets that may lead to the development of therapeutics for curing COPD, we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified  Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease. It is the fourth leading cause of death in the world and is expected to be the third by 2020 Genome-wide association studies (GWAS) have recently identified several risk loci for COPD and/or smoking associated genes cis) or far (trans) proximity to the methylated site. The primary focus of this study is not only to identify those regions that are differentially methylated between COPD cases and controls, but to resolve the gene expression changes that follow as a result of these differentially methylated regions and the biological consequences that these regulatory changes induce with respect to disease development or progression. Our integrative analysis of DNA methylation and gene expression validates the importance of DNA methylation in COPD and enables the direct identification of novel key regulators modulated by epigenetic changes in this multifactorial, systematic disease. When comparing downstream genes controlled by the key regulators with gene sets related to COPD disease severity, we identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple gene sets related to COPD. We further show that EPAS1 protein levels are lower in lung tissues of COPD patients. Epas1 is down-regulated transcriptionally by chronic smoke exposure in mice, and the EPAS1 knockdown signature in human endothelial cells significantly overlaps with our predicted EPAS1 downstream genes. These data combined suggest that our systematic approach can provide important insights into understanding the mechanisms underlying epigenetic regulation, via DNA methylation, that in turn alters transcriptional programs that lead to COPD pathogenesis and progression.In this study we present a novel systematic approach for identifying key regulators in COPD by integrating functional genomic, epigenetic data, and higher order phenotypic data. We studied 100 COPD and 52 control (CTRL) lung samples to investigate the relationship between methylation status of DNA and expression level of a gene either in close (Both genome-wide DNA methylation and gene expression profiles of 62 non-COPD controls (CTRL) and 148 COPD lung samples were obtained from the collaborative project, Lung Genomics Research Consortium (LGRC). To carry out an integrative analysis, we required that methylation and gene expression data were properly aligned. Therefore, we developed a multi-omic data alignment procedure to iteratively match methylation and gene expression profiles within each individual in the study −6). Additional constraints could be applied to further enrich for biologically relevant methylation, such as 1) self-consistent methyl probes , and 2) methyl probes close to transcription start sites (<1 kb). These filters were potentially useful for enriching for genes that are both differentially methylated and expressed . We also identified 92,606 methylation probes corresponding to 8,848 genes that were differentially methylated between the COPD and CTRL groups . There are 990 genes overlapping the set of differentially methylated and expressed genes . Given methylation data are known to be noisy xpressed , but weret al. reported that DNA methylation levels in COPD were different from ones in CTRL samples and 90% of differentially methylated CpG island probes were hypermethylated in small airways epithelium cells from COPD patients In general, when DNA methylation levels of methyl probes in CpG islands for COPD were compared with those of CTRL samples, the COPD samples were predominantly hypermethylated .. Resultet al. also shows that methylation levels of many genes were positively associated with gene expression levels when comparing small airways epithelium cells of non-COPD controls and COPD patients Of the 704 differentially methylated genes within CpG islands that are also differentially expressed between the CTRL and COPD groups, most (696 out of 704) were hypermethylated in COPD, whereas only about half of the corresponding gene expression levels (for 378 genes) were downregulated . The remEP300, EPAS1, FOXF1, FOXA2, KDR, LAMA5, SHH, NKX2-1, VEGFA, FZD1, NUMB, and PKDCC−8), regulation of multicellular organismal development , and tissue morphogenesis . The other set of genes that are hypermethylated and upregulated in COPD are enriched for a number of GO categories as well, including co-translational protein targeting to membrane , protein targeting to ER , translational initiation , translational termination , and cellular protein complex disassembly   . These rCis regulation was defined as significant correlation between the expression levels of a gene and methylation levels in the promoter region of the gene , we observed similar differences after constraining each group to have the same number of samples . However, there are only 171 trans pairs shared between the CTRL and COPD groups . Therefore, the relationships between gene expression and DNA methylation are likely different between the COPD and non-disease CTRL groups.While CpG islands in COPD are hypermethylated in general, variations in the expression levels of individual genes are mainly influenced by cis-acting methylation levels in a given gene's promoter region the gene . DNA met samples .. There cis regulation), changes in gene expression may also be causal for methylation changes via trans regulations that can affect processes such as the transfer of methyl groups cis and trans regulation . To infer the causal relationship between gene expression and methylation variations, we developed a causality test similar to previously developed causality tests trans pairs in the CTRL group (FDR = 0.03) and 362,095 trans pairs in the COPD group (FDR = 0.0014) whose methylation levels likely regulated the expression of trans genes  Body mass index, airflow Obstruction, Dyspnea and Exercise capacity) index Forced Expiratory Volume) percentage predicted Forced Vital Capacity) ratio, and emphysema percentage. DLCO, FEV1 percentage predicted, and FEV1/FVC ratio decrease as COPD severity increases, while BODE index and emphysema percentage increase with disease severity.To further investigate key regulators in COPD development and progression we compared the expression levels of the key regulators and their downstream genes with genes associated with COPD disease severity related clinical features. Five COPD related severity measures were available in the LGRC data set, including DLCO . Expression levels of 4 of the 30 overlapping genes are positively correlated with EPAS1 methylation levels indicating that their expression levels increase as emphysema severity increases. One of the four genes, CD79B, was positively correlated with EPAS1 methylation levels, which is consistent with previous reports that B cell abundance increases as emphysema severity increases EPAS1 methylation levels; their expression levels are expected to decrease as emphysema severity increases. For example, gene expression levels of members of the TGF-beta pathway such as ACVRL1 are inversely correlated with EPAS1 methylation levels. This observation agrees with previous reports in which TGFBR2 was shown to be down regulated in regions of severe emphysema We further compared the downstream genes of key regulators in COPD with known COPD signatures. Recently, Campbell gene set ; EPAS1 iEPAS1's methylation profile and its downstream genes are distinct from ones of other regulators . EPAS1 downstream target genes are enriched for multiple GO biological processes  including anatomical structure formation involved in morphogenesis , adherens junction assembly , locomotion , angiogenesis , and cell division . EPAS1 is differentially expressed and methylated between the CTRL and COPD groups  EPAS1 are not yet fully understood. There have been several studies regarding hypoxic response genes in different tissues including breast, kidney, head and neck, and lung EPAS1 downstream target genes significantly overlapped with HIF regulated genes only in primary human pulmonary artery endothelial cells  EPAS1 may be a unique characteristic of COPD lung samples. In addition to directly binding to HIF response elements, EPAS1 may regulate downstream gene expression by regulating or interacting with other transcription factors such as AREB6/ZEB1 or miRNAs  and categorized EPAS1 abundance. All 4 slides from non-COPD patients contained high levels of EPAS1, and 3 of 5 slides from the COPD patients contained low levels of EPAS1 as shown in TRL lung .. To tesEPAS1 target genes we predicted significantly overlap with genes associated with emphysema caused by smoking in mouse, as indicated above. To investigate whether EPAS1 expression levels change when mice start to develop emphysema after chronic smoking exposure, we checked Epas1 expression levels in two different chronic smoking mouse models using C57BL/6J and A/J mice. C57BL/6J mice start to develop emphysema after 6 month exposure to chronic smoking Epas1 expression levels in smoking mice (6 months of smoking for C57BL/6J and 2 month for A/J) are significantly lower than levels in corresponding age-matched non-smoking mice , given it is also a hypoxia responsive gene. Smoke exposed mice had lower amount of Vegfa expression as well , which suggests that Epas1 downstream target genes were down regulated in the smoke exposed mice at the time when emphysema develops in these models. These results are consistent with our causal predictions relating to EPAS1.The EPAS1 causally regulates the downstream target genes we predicted, we knocked down EPAS1 expression via siRNA in human umbilical vein endothelial cells (HUVEC) and mouse endothelial cell line C166 , including EPAS1 itself  and the EPAS1 downstream target gene VEGFA . The EPAS1 siRNA signatures derived from human and mouse cell lines were highly consistent, with 695 genes in common to both signatures . Both signatures not only significantly overlapped with EPAS1 downstream genes , but also with hypoxia response genes in endothelial cells . Moreover, the EPAS1 siRNA signatures consistently overlapped genes associated with the COPD severity phenotypes  share similar downstream genes with GAK. In addition, some of their methylation levels are highly correlated each other, indicating overall that regulation of downstream genes may be mediated by multiple key regulators in a systematic way rather than by single master controllers.Importantly, beyond the pathway level, we were able to identify genes of importance through looking at the key regulators associated with these cluster. One interesting gene was EPAS1. To our knowledge EPAS1 has not been previously linked with COPD pathophysiology. This is despite the fact that EPAS1 is one of the major mediators of the transcriptional response to physiological hypoxia, an environment typical of lung alveolar as progressive airflow limitation increases with COPD severity. EPAS1 is a hypoxia-responsive transcription factor and is also known as hypoxia-inducible factor 2 alpha (HIF-2α) HIF1a, another key mediator of hypoxic responses, EPAS1 has relatively high levels of expression in the placenta, heart, lung and endothelial cells. Importantly, a previous study reported alveolar hypoxia increases in prevalence as disease severity increases EPAS1 expression as induced by short-term hypoxic exposure, the decreased EPAS1 expression observed in COPD may in fact result in maladaptive hypoxia responses EPAS1 to disease and its mechanisms in it would be very promising for treatment of disease.Other potentially relevant mediators of COPD pathophysiology are those key regulators that showed a different methylation profile and different downstream target gene set as compared to all other regulators, such as was the case with EPAS1 methylation level is significantly associated with disease severity and that an increase in methylation decreases EPAS1 gene expression. Thus we hypothesize that disease severity may be systematically controlled by altered regulation of a large set of EPAS1 downstream genes. Several observations in humans and mouse have demonstrated that altered EPAS1 expression can affect lung physiology. Specifically gain-of-function mutations in humans were associated with pulmonary hypertension, increased cardiac output and heart rate as well as increased pulmonary ventilation relative to metabolism EPAS1 mutant mouse, haploinsufficiency for the oxygen-sensing factor resulted in augmented carotid body sensitivity to hypoxia, including irregular breathing, apneas, hypertension and elevated norephinephrine levels on one mouse strain background, but protection against pulmonary hypertension on a different strain In this study we demonstrate that EPAS1 may be the fact that EPAS1 is a known transcriptional activator of the VEGF EPAS1 downstream genes and one of EPAS1 siRNA signature genes. VEGF expression level is associated with COPD phenotypes and downregulated in COPD samples in the LGRC dataset. VEGF is involved both in the regulation of the bronchial microvascular changes as well as in the inflammatory airway changes in COPD. In patients with emphysema, low levels of VEGF are thought to promote the destruction of alveoli, since VEGF normally acts to induce the expression of anti-apoptotic proteins and acts as a survival factor for endothelial cells. The importance of VEGF in survival signals necessary for the maintenance of normal lung structure and consequences characteristics of emphysema has also been confirmed in animal studies disrupting VEGF signaling either through genetic deletion of lung VEGF or through VEGF receptor blockage. VEGF is also thought to play a dual role in the lung by regulating not only apoptosis but also efferocytosis, which is the process involved in phagocytosis of apoptotic cells. The net effect of efferocytosis is anti-inflammatory because dying cells are removed before they undergo postapoptotic necrosis and anti-inflammatory mediators are released thereby suppressing further adaptive immune responses. Therefore, dysregulation of VEGF via altered EPAS1 regulation could link hypoxia to mechanisms of COPD severity Another possible link between hypoxia mediated COPD disease severity and EPAS1 expression have deficient lung surfactant, such as surfactant D (SP-D), in addition to other lung abnormalities and die of respiratory failure VEGF as VEGF rescue therapy resulted in restoration of surfactant production and less respiratory distress in the EPAS1 null mice compared to wildtype. Surfactants, such as SP-D have many functional properties including anti-inflammatory and anti-oxidant capacities, and protection against respiratory infections. In various mouse models, SP-D appears to play a distinct role in protecting murine lungs from the development of emphysematous changes possibly by reducing inflammation and oxidative stress in the lungs. While in humans, elevated serum SP-D level is an apparent biomarker of COPD, there is a reported inverse relationship with bronchoalveolar lavage fluid levels, whether elevated or decreased levels of SP-D are important in pathogenesis are still unclear EPAS1, through modulation of VEGF, may contribute to the chronic inflammatory response and tissue destruction in COPD through augmented apoptosis, impaired efferocytosis, and abnormal tissue remodeling.One other point of interest is the fact that neonatal mice lacking complete EPAS1 downstream genes, the overlap is marginal significant , but it is the best overlap comparing with other regulator's downstream genes . This enrichment of COPD GWAS genes in EPAS1 downstream further substantiates critical role of EPAS1 in the disease.Many studies focus on genetic contribution to COPD development and phenotypes de novo DNMT activity due to elevated expression of DNMT3B as well as a hypoxia-induced decrease in levels of SAM suggesting an increase in SAM usage in hypoxic cells At present it is still unclear how the methylation level of key regulators, in particular the predominant hypermethylation seen in COPD is regulated upstream. A recent study has also demonstrated that DNA methylation is widely disrupted and predominantly hypermethylated in small airway epithelia of COPD patients trans, the number of inferred relationships that gene expression variations causally regulate methylation variations (gene expression →methylation) in COPD is small . Similar to the methylation → gene expression relationships, the numbers of genes' methylation levels regulated by a gene's expression level in trans follow a scale-free distribution . And among the 44 genes in the overlap, 32 genes methylation levels negatively correlate with CDK5RAP1 expression level and 12 of them positively correlate. This result suggests that one possible mechanism CDK5RAP1 regulating methylation levels of key COPD regulators is through affecting availability of SAM.Compared with the number of inferred relationships that methylation variations causally regulate gene expression (methylation → gene expression) in ribution .. The toIt is worth to note that there are differences between statistical causal and biological causal relationships. Similar to other causal inference studies NOD2RAGEThere are some limitations in the array-based technologies used for measuring gene expression and methylation profiles. Transcript levels of different splicing isoforms were not uniquely measured in the Agilent arrays. Different splicing isoforms of genes, such as cis and trans regulation between DNA methylation and gene expression. This approach provides mechanisms of how variation of the expression of genes is systematically regulated by DNA methylation level of key regulators in COPD. The severity of COPD can be regulated by methylation level of EPAS1 and, in turn, it regulates large numbers of gene expression variations. Therefore, if lowering methylation level of EPAS1 or increasing EPAS1 expression level might be very useful to treat patients with this irreversible disease. This approach can be applied to other diseases where DNA methylation can contribute to disease development such as lung cancer to find key epigenetic contribution to the diseases.In summary, we propose a potential epigenetic mechanism of COPD using a novel systematic approach integrating The LTRC is a resource program of the NHLBI that provides human lung tissues to qualified investigators for use in their research. The program enrolls donor subjects who are anticipating lung surgery, collects blood and extensive phenotypic data from the prospective donors, and then processes their surgical tissues for research use. The diagnoses of COPD are based on clinical, imaging and pathological data including chest CT images, pulmonary function tests, exposure and symptom questionnaires, and exercise tests. The COPD class in this study was based on having a FEV1/FVC<.7 on pulmonary function testing. The “control” lungs consist of adjacent histologically normal lung tissues obtained at time of nodule resection from patients with normal lung function testing parameters. In terms of tissue collection procedure, all lung tissue cores were collected at the time of surgical resection, surgical biopsy or transplantation and flash frozen in liquid nitrogen prior to being stored at −80.http://www.lung-genomics.org). All LGRC lung mRNA data were generated using Agilent V2 human whole genome arrays and were deposited into GEO database as GSE47460 by LGRC consortium. All RNA samples subjected to gene expression profiling were with RIN>7.0. Due to the number of samples, multiple batches of arrays were necessary, so 10% of the arrays were picked at random to have replicates throughout each batch to account for possible batch effects. The feature extracted data was normalized using a pairwise cyclic loess approach, and the probes were collapsed to one probe per gene by selecting the probe with the highest average signal. The processed mRNA arrays data were directly downloaded from the LGRC data portal.Data used in the study were obtained from the publicly available LGRC data portal  of each tiling probe was estimated using the CHARM method Potential biological subtypes in the samples were compared with disease status Diffusing capacity of the Lung for Carbon Monoxide) Body mass index, airflow Obstruction, Dyspnea and Exercise capacity) index Forced Expiratory Volume) percentage predicted Forced Vital Capacity) ratio, and 5) emphysema percentage. For each clinical phenotype, only a part of COPD patients were measured: 85 for DLCO, 98 for BODE, 81 for FEV1 and FEV1/FVC ratio, and 62 for the emphysema percentage.There are 5 different measurements of lung function for patients in the LGRC cohort: 1) DLCO , then applied the t-test to the permuted data to identify significant differentially expressed genes. We performed the permutation test 100 times to estimate FDRs. Similarly, for differentially methylation analysis between COPD and control samples, we permuted sample labels, and applied the permutation scheme 100 times to estimate FDRs for differentially methylated genes at each p-value of the t-test.cis or trans acting methylation-mRNA probe pairs in COPD or control samples we permuted genome-wide gene expression data 5 times, calculated pairwise correlation between methylation and permuted gene expression profiles for all possible pairs, and then counted cis or trans acting pairs in permuted data at each p-value cutoff. Similarly, for association analysis between gene expression and phenotypical data we permuted genome-wide gene expression data 5 times, calculated pairwise correlation between gene expression and phenotypical data for all possible pairs, and then counted significant pairs in permuted data at each p-value cutoff.For estimating FDRs of To identify potential functions of selected gene sets, we compared these gene sets with each GO biological process cis methylation-mRNA relationship for gene trans gene expression of gene cis regulation on genetrans regulates the methylation level of geneet alet alcis and trans regulations determined above) to be significant so that only a small fraction of all possible trios were subjected to the causality test.For simplification purposes, we describe the causality test using the COPD dataset, the corresponding values for the control dataset were generated in a similar fashion. Given a significant , , and  . We focucis associationcis regulation and a trans association If assuming that all methylation levels and gene expression levels are normally distributed and that all causal relationships are linear, the probability oftrans gene expression cis gene expression trans gene expression A similar causality test Immunohistochemistry staining of paraffin embedded human lung tissue of de-identified patients was carried out with the IRB approval (HS#12-00171) from Mount Sinai Hospital. Institutional Animal Care and Use Committee (IACUC) approval (FO0501) was obtained for the chronic smoke exposure mouse model systems at St. Lukes Roosevelt Hospital.3. Animals were sacrificed 12 hours after the last smoke exposure. Comparative analyses were made with age-matched air-exposed C57Bl/6J and A/J mice that were treated in an identical manner.C57Bl/6J and A/J mice  were exposed to cigarette smoke for 6 or 2 months respectively in a specially designed chamber  for 4 hours a day, 5 days per week at a total particulate matter concentration of 80 mg/mEpas1 and Vegfa, respectively. The real-time PCR reactions were carried out following the manufacturer's protocol, and the gene expressions were normalized to Rn18s (Mm03928990_g1).The total RNA from mouse lung tissues was extracted using RNeasy Mini Kit . Then cDNA was synthesized with SuperScript III . For quantitative PCR, we utilized TaqMan gene expression assays , which contain prevalidated primers and TaqMan probe for the individual genes. TaqMan Gene Expression Assay IDs are Mm01236112_m1 and Mm01281449_m1 for mouse The paraffin sections of human lung tissues were provided by Histology Shared Resource Facility of Mount Sinai Hospital with the IRB approval. The immunostaining was performed using Vectastain ABC Elite Kit  with polyclonal anti-EPAS1 antibody . Following deparaffinization and hydration of sections, antigen retrieval with 10 mM citrate buffer and blocking of endogenous peroxidase with 0.3% H2O2-methanol were performed. The tissue sections were blocked with 5% goat serum diluted in 0.1% Tween-20 in phosphate buffered saline (PBS-T) for 30 minutes, and then incubated in anti-EPAS1 (1∶100) at room temperature for 1 hour. The tissue sections were washed and incubated with the secondary antibody anti-rabbit-HRP. After washing, DAB substrate  was utilized to obtain positive reactions.2. The cells were transfected with EPAS1 siRNA and non-targeting negative control siRNA  using Lipofectamine RNAiMAX as recommended transfection protocols by the manufacturer. After the treatments with 5 nM Silencer Select siRNA  for 48 hours, the total RNA was purified with RNeasy Mini Kit . The efficiencies of knocked down the EPAS1 expression were assessed by qPCR with 1.4% for HUVEC, 3.2% for C166.The cell lines of HUVEC  and C166  were cultured in the appropriate media at 37°C with 5% COEPAS1 or Epas1 siRNAs with non-targeting siRNAs at paired t-test p-value cutoff 0.05 with resulting signature sizes of 2,796 and 3,730, and corresponding q-values Approximately 250 ng of total RNA per sample were used for library construction by the TruSeq RNA Sample Prep Kit (Illumina) and sequenced using the Illumina HiSeq 2500 instrument with 100 nt single read setting according to the manufacturer's instructions. The RNAseq data set was deposited in GEO as GSE62974. Sequence reads were aligned to human genome assembly hg19 and mouse genome assembly mm10, respectively, using Tophat S1 FigComparison of DNA methylation profiles between COPD and CTRL samples. DNA methylation level was measure by β value and the mean of β value of methyl probes of CpG islands within 1 million bases is shown for all chromosomes. Global methylation levels were compared between CTRL (red) and COPD (blue) (the upper panel) and most regions were hypermethylated in COPD comparing with CTRL across whole genomes (the lower panel). A) CpG island probes; B) non-CpG island probes.(TIF)Click here for additional data file.S2 Figcis and trans pairs derived using the same number of samples in CTRL and COPD. A) The numbers of cis pairs; B) The numbers of trans pairs.The numbers of (TIF)Click here for additional data file.S3 FigA) The clustering result based on the methylation levels of key regulators. The distance was measured as (1-Spearman correlation coefficient). There were two large clusters of key regulators (shown in red boxes). B) The clustering result based on topological overlaps of key regulators' downstream genes. The distance was measured as Clustering results of 67 CTRL key regulators (TIF)Click here for additional data file.S4 FigA) The clustering result based on similarity of key regulators' methylation levels. The distance between methylation levels of COPD key regulators was measured in the same way as in EPAS1 was not included in any cluster. B) The clustering result based on the topological overlaps of COPD key regulators' downstream genes. There were three distinct clusters of COPD key regulators. The first and second cluster, C1 and C2, shared some common downstream genes but key regulators in the C2 cluster regulated genes involved in immune response and other defense processes specifically. The C3 cluster consisted of regulators involved in ciliary related function. EPAS1 downstream genes were also unique compared to others, and EPAS1 was not included in the three clusters.Clustering results of 126 COPD key regulators. (TIF)Click here for additional data file.S5 FigEPAS1 (marked with the red arrow) was not included in these clusters in COPD.The clustering results of key regulators with higher number of downstream genes>mean+3SD. There were 33 and 60 key regulators for CTRL and COPD set, respectively. Key regulators were clustered based on their methylation profiles or overlaps of their downstream genes. The clustering patterns were similar to the corresponding ones based on key regulators of the number of downstream genes>mean+2SD in (TIF)Click here for additional data file.S6 FigEPAS1 methylation and gene expression levels in CTRL and COPD lung tissues. A) EPAS1 gene expression level was lower in lung tissues of COPD patients; B) Methylation level of EPAS1 promoter region was higher in lung tissues of COPD patients; C) Methylation and gene expression levels of EPAS1 were anti-correlated in lung tissues of COPD patients.(TIF)Click here for additional data file.S7 FigAn example of immunohistochemistry staining of lung tissues from COPD (A) and non-COPD (B) patients using EPAS1 antibody.(TIF)Click here for additional data file.S8 Figtrans regulated a key regulator gene in lung tissues of COPD patients followed a scale-free distribution.Numbers of downstream genes' methylation levels (TIF)Click here for additional data file.S9 FigA) The clustering result of COPD samples by gene expression levels of 1000 genes with largest variances in COPD. COPD samples can be partitioned into two groups based on expression levels of 306 cilium related genes (marked by a red box in the top-left corner). B) The clustering result of CTRL samples based on gene expression levels of 1000 genes with largest variances in CTRL samples. A set of 339 genes classified CTRL samples into two subgroups. 250 of these genes overlap with COPD classifier genes in S9A Fig. C) The clustering result of COPD samples based on methylation profiles of 1000 methylation probes with largest variances in COPD. A set of 447 genes (in the red box) classified COPD samples into two groups. D) The clustering result of CTRL samples based on methylation profiles of 1000 methylation probes with largest variances in CTRL. A set of 391 genes (in the red box) clustered CTRL samples into two groups. Among them, 95 out of 391 genes overlap with the COPD classifier genes in S9C Fig. For figures, rows are molecular traits (mRNA expression or methylation probes) and columns are samples.Heterogeneities of molecular traits in CTRL and COPD lung samples. (TIF)Click here for additional data file.S1 TableDemographic characteristics of samples in LGRC cohort.(PDF)Click here for additional data file.S2 TableCharacteristics of data used in the analysis.(PDF)Click here for additional data file.S3 TableSignificance of overlaps between differentially methylated and expressed genes.(PDF)Click here for additional data file.S4 TableThe distribution of probes differentially methylated between controls and COPD samples.(PDF)Click here for additional data file.S5 TableGene expression levels and DNA methylation levels of 704 genes in (PDF)Click here for additional data file.S6 TableGO enrichment analysis of the 378 genes that were hypermethylated and downregulated in COPD.(PDF)Click here for additional data file.S7 TableGO enrichment analysis of the 318 genes that were hypermethylated and upregulated in COPD.(PDF)Click here for additional data file.S8 Table67 key regulators in CTRL lung tissues that regulated a large number of downstream genes.(PDF)Click here for additional data file.S9 Table126 key regulators in COPD lung tissues that regulated a large number of downstream genes.(PDF)Click here for additional data file.S10 TableCorrelation between key regulators' methylation levels in promoter regions in COPD lung tissues and COPD severity Traits.(PDF)Click here for additional data file.S11 TableOverlap between downstream genes of key regulators in COPD lung tissues and COPD severity signatures in Human.(PDF)Click here for additional data file.S12 TableOverlap between downstream genes of key regulators in COPD lung tissues and COPD emphysema signature in mouse.(PDF)Click here for additional data file.S13 TableEPAS1 downstream genes in COPD.GO enrichment analysis of (PDF)Click here for additional data file.S14 TableMatched methylation and gene expression profile pairs identified by MODMatcher.(PDF)Click here for additional data file.S15 TableGO enrichment analysis of the 306 genes in the upper left corner of (PDF)Click here for additional data file.S16 TableGAK downstream genes in COPD.GO enrichment analysis of (PDF)Click here for additional data file.S17 TableETF1 downstream genes in COPD.GO enrichment analysis of (PDF)Click here for additional data file.S18 TablePAX9 downstream genes in COPD.GO enrichment analysis of (PDF)Click here for additional data file.S19 TableEPAS1 in COPD.Motif enrichment analysis of downstream genes of key regulator (PDF)Click here for additional data file.S1 TextSupplementary results and methods.(DOCX)Click here for additional data file.


ENG) and activin receptor-like kinase 1 (ACVRL1) genes are responsible for HHT1 and HHT2 and are associated with arteriovenous malformations. ENG and ACVRL1 interact with endothelial nitric oxide synthase (eNOS) and regulate its activation. Mice heterozygous for these genes (Eng+/– and Acvrl1+/–) show reduced ENG or ACVRL1 protein levels in endothelial cells causing eNOS uncoupling, generation of ROS rather than nitric oxide (NO•), leading to impaired NO• mediated vasodilation. ROS production is increased in several organs of Eng+/– and Acvrl1+/– mice, including lungs, liver, and colon, affected in HHT. The major source of increased oxidative stress in these tissues is eNOS-derived ROS and not mitochondrial or NADPH oxidase-dependent ROS. Eng+/– and Acvrl1+/– mice also develop with age signs of pulmonary arterial hypertension attributable to eNOS-derived ROS, which was preventable by antioxidant treatment. To date, only one pilot study has been carried out in HHT patients, and it showed beneficial effects of antioxidant therapy on epistaxis. We suggest that more clinical studies are warranted to investigate whether antioxidants would prevent, delay or attenuate manifestations of disease in individuals with HHT, based on our experimental data in mouse models.Oxidative stress causes endothelial dysfunction and is implicated in the pathogenesis of cardiovascular diseases. Our studies suggested that reactive oxygen species (ROS) play a crucial role in hereditary hemorrhagic telangiectasia (HHT) disease, a vascular dysplasia affecting 1 in 5,000–8,000 people. Mutations in endoglin ( Reactive oxygen species (ROS) are important regulators of many processes including intracellular signaling, response to growth factor stimulation and generation of the inflammatory response . DysreguThe major enzymatic sources of ROS in endothelial cells are mitochondrial respiratory enzymes, NADPH oxidases and uncoupled endothelial nitric oxide synthase (eNOS). It is important to mention that increased ROS production together with decreased nitric oxide (NO•) bioavailability can further complicate and worsen endothelial injury . It is a2–; 2O2- and lipid peroxide-induced endothelial oxidative stress  exert some of their beneficial effects by stimulating NO• production and decreasing vascular ROS bioavailability  is an autosomal dominant vascular dysplasia with age-related penetrance, affecting 1 in 5,000–8,000 people worldwide. The external visible signs of HHT are recurrent epistaxis (nosebleeds) and small cutaneous telangiectatic lesions. Imaging studies reveal the presence of arteriovenous malformations (AVMs)—defined as abnormal direct connections between arteries and veins—in lungs, liver, and brain. AVMs are life-threatening because of their potentially lethal complications such as stroke, hemorrhage, and brain abscess. HHT is a genetically heterogeneous disorder, HHT type 1 (HHT1) is caused by mutations in the ENG (endoglin) gene located on chromosome 9, region 9q33-q34, whereas HHT type 2 (HHT2) is caused by mutations in the ACVRL1 (activin receptor-like kinase 1 or ALK-1) gene located on chromosome 12, region 12q11-q14. About 15–20% of HHT families remain unresolved after mutation analysis of these two genes , and twoThe underlying mechanism of HHT1 and HHT2 is haploinsufficiency indicating that reduced amounts of ENG and ACVRL1 lead to endothelial dysfunction and predispose to the clinical signs of disease. The observations that BMP9 is the highest affinity ligand for ACVRL1 and ENG and that Smad4 is a downstream mediator support the hypothesis that BMP9/ACVRL1/ENG/Smad4 mediated pathways are affected in HHT.Despite the fact that vascular stress and multi-organ vascular dysplasia are hallmarks of HHT , only feEng+/– and Acvrl1+/–) mice have been used as models for HHT1 and HHT2 respectively, allowing us to dissect the underlying mechanisms of disease , indicating that ENG is an important regulator in the coupling of eNOS activity , including elevated right ventricular systolic pressure leading to hypertrophy, reduced vascular density, and increased thickness and outward remodeling of pulmonary arterioles, were observed in adult but not newborn Eng+/– and Acvrl1+/– mice relative to wild-type littermate controls. Our observations support the fact that mutations in several genes of the TGF-β superfamily, including BMPR2, ACVRL1, and ENG, predispose to PAH . Our experimental findings suggest that the use of antioxidants could prevent uncoupling of eNOS associated with HHT. Whether it could cause eNOS recoupling in affected organs of HHT patients remains to be tested.We propose that antioxidants are promising tools in HHT, both as preventative and therapeutic options. Prevention of endothelial dysfunction in HHT patients may include simple strategies such as an antioxidant-rich diet, abstinence from smoking, a healthier lifestyle, and regular physical activity and exercise. It has been shown that exercise can prevent eNOS uncoupling, reduce NADPH oxidase activity and decrease endothelial oxidative stress and dysfunction in experimental models and patients with coronary artery disease . The theIn conclusion, oxidative stress plays a causative role in the pathogenesis of endothelial dysplasia and vascular malformations in HHT. The use of antioxidants in the prevention and treatment of HHT should be of benefit to the patients. More experimental and clinical studies are urgently needed to test the most effective ways to use antioxidants to ameliorate the quality of life for patients with HHT.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Allergic reactions can be considered as maladaptive IgE immune responses towards environmental antigens. Intriguingly, these mechanisms are observed to be very similar to those implicated in the acquisition of an important degree of immunity against metazoan parasites (helminths and arthropods) in mammalian hosts. Based on the hypothesis that IgE-mediated immune responses evolved in mammals to provide extra protection against metazoan parasites rather than to cause allergy, we predict that the environmental allergens will share key properties with the metazoan parasite antigens that are specifically targeted by IgE in infected human populations. We seek to test this prediction by examining if significant similarity exists between molecular features of allergens and helminth proteins that induce an IgE response in the human host. By employing various computational approaches, 2712 unique protein molecules that are known IgE antigens were searched against a dataset of proteins from helminths and parasitic arthropods, resulting in a comprehensive list of 2445 parasite proteins that show significant similarity through sequence and structure with allergenic proteins. Nearly half of these parasite proteins from 31 species fall within the 10 most abundant allergenic protein domain families . We identified epitopic-like regions in 206 parasite proteins and present the first example of a plant protein (BetV1) that is the commonest allergen in pollen in a worm, and confirming it as the target of IgE in schistosomiasis infected humans. The identification of significant similarity, inclusive of the epitopic regions, between allergens and helminth proteins against which IgE is an observed marker of protective immunity explains the ‘off-target’ effects of the IgE-mediated immune system in allergy. All these findings can impact the discovery and design of molecules used in immunotherapy of allergic conditions. Allergy is an increasingly widespread clinical problem that leads to various conditions such as allergic asthma and susceptibility to anaphylactic shock. These conditions arise from exposure to a range of environmental and food proteins  that are recognised by a form of immune system antibody called IgE. This part of the immune system is thought to have evolved to provide mammals with additional rapid response mechanisms to combat metazoan parasites. Here, we address the pertinent question, ‘what makes an Allergen an Allergen’ as, although they constitute a very small percentage of known proteins, they appear to be diverse and unrelated. Using computational studies, we have established molecular similarity between parasite proteins and allergens that affect the nature of immune response and are able to predict the regions of parasite proteins that potentially share similarity with the IgE-binding region(s) of the allergens. Our experimental studies support the computational predictions, and we can present the first confirmed example of a plant pollen-like protein in a worm that is targeted by IgE. The results of this study will enable us to predict likely allergens in food and environmental organisms and to help design protein molecules to treat allergy in the future. Allergy is a hypersensitive immune reaction to environmental antigens from diverse sources such as foods, plants and innocuous organisms. The mechanism responsible for eliciting the allergic reaction involves components of the immune system, in particular the IgE antibody isotype, which also mediate the immune response against helminthic infection. Several significant studies have elucidated the mechanisms involved in the immune response to helminth infection and to allergen exposure, and have been comprehensively reviewed in the literature –3.Schistosoma and Echinococcus) [Trichuris and Ascaris) [Extensive studies have correlated high levels of parasite-specific IgE antibody in the host with acquired immunity against both helminth endoparasites such as Platyhelminthes (ococcus) –8 and neAscaris) –11 as weAscaris) –14. AlsoAscaris) –18. ThesS. mansoni allergen-like proteins have been previously studied including members of the Tegumental-Allergen-Like (TAL), Tropomysosin and Venom Allergen-Like (VAL) protein domain families [S. mansoni antigens, including those to members of the TAL and Tropomyosin families have been found to depend on the expression patterns throughout the adult worm and eggs. Constant exposure to antigens may result in the induction of a regulated response against excessive IgE including the decreased production of IgE and increased production of anti-inflammatory IgG4 [Allergenic proteins from a wide variety of sources have been collated and documented in the Allergome database  and clasfamilies –27. Duriory IgG4 .Schistosoma mansoni and haematobium have been observed to alleviate the symptoms of allergy [Such a switch in chronic helminth infections are indicated by a modified T-helper 2 (Th2) cell environment, which is characterized by increased T-regulatory cell levels and a predominant IgG4 antibody profile . Contrar allergy ,34. ThesBased on these observations, Fitzsimmons and Dunne  hypothesIn the quest to strengthen the hypothesis that the IgE-target proteins in metazoan parasites and allergenic molecules share similar molecular features, the systematic exercise of comparing allergenic and parasite proteins and assessing the epitopic regions of allergenic proteins and ‘epitope-like’ regions of parasite proteins becomes of primary importance.Here we present a workflow involving computational analyses supported by experimental verification for detecting putative IgE inducing structure/sequence motifs in proteins encoded in genomes of parasites that share molecular similarity with epitopic regions of members of protein families that are populated predominantly by allergenic proteins.Two main datasets were generated:(a) 2712 unique full-length protein sequences from various sources that are known to cause allergy and/or bind IgE were collated from the Allergome database ; (b) 257Echinococcus granulosus, Fasciola hepatica, Schistosoma haematobium, Schistosoma japonicum, Schistosoma mansoni and Taenia sp. and (ii) nematodes: Ascaris lumbricoides, Anisakis simplex, Brugia malayi, Mansonella perstans, Nippostrongylus brasiliensis, Onchocerca volvulus, Trichinella spiralis and Trichuris trichiura (iii) arthropods (mites): Acarus siro, Aleuroglyphus ovatus, Blomia tropicalis, Dermatophagoides farinae, Dermatophagoides microceras, Dermatophagoides pteronyssinus, Euroglyphus maynei, Glycyphagus domesticus, Lepidoglyphus destructor, Ornithonyssus sylviarum, Psoroptes ovis, Sarcoptes scabiei and Tyrophagus putrescentiae. A total of 70403 protein sequences encoded in genomes of above-mentioned endo- and ecto-parasites constitute dataset 2.Protein sequences encoded in genomes of metazoan parasitic organisms were procured from the UniProt database  . VariousThough the Allfam database provides Pfam domain definitions for allergenic proteins documented in the Allergome database, it has not been updated since 2011. To assign the latest Pfam domain definitions and to include the most recent additions to the Allergome database, we have derived protein domain definitions for dataset 1 and dataset 2 from the Pfam database 27.0. Of these, 10 protein domain families/superfamilies that are reported to represent nearly 45% of all documented allergenic molecules and thus are highly populated with allergenic protein members are considered for further analysis . These pHomologs of allergenic proteins (dataset 1a) have been detected in parasite proteins (dataset 2) by searching Hidden Markov Models (HMM) profiles of the above mentioned 10 Pfam protein domain families/superfamilies using HMMER3 . We searGene3D assigns domains to regions of protein sequences with no known 3D structure based on the CATH classification scheme using more sensitive structure-based HMMs derived from a superfamily. Parasite proteins that did not show an association with any CATH homologous superfamily were searched in the Gene3D database to ascertain if they shared the same topology/fold as an allergenic protein to establish similarity/homologous relationships.Parasite proteins are considered to be a close homolog of the allergenic proteins if both the proteins belong to same family (defined by Pfam) or same homologous superfamily (defined by CATH/Gene3D). However, parasite proteins are regarded as distant homologs if they do not share the same family/superfamily but share a common structure fold with an allergen protein.http://xray.bmc.uu.se/usf/lsqman_man.html). Homology-based structural models that share more than 30% sequence identity with the template sequence (from any source) are considered for the analysis. The global structural similarity between two proteins was measured using TM (template-modeling) score. A TM score of ≥0.5 associated with structure alignment of a pair of proteins is considered to be statistically significant and the two proteins in the alignment are likely to share the same fold [To establish the relationship of parasite proteins with allergenic proteins, we culled 3D coordinates of experimentally known structures (if existing in the Protein Data Bank (PDB)) or from homology based models of both proteins (from Modbase ) and supame fold .Sequence-based approach: We searched epitopic fragments from allergenic proteins (dataset 1b) in parasitic ‘close homologous’ protein sequences to identify putative IgE/IgG4-binding epitopic-like-regions by employing the FASTA program  using deStructure-based approach: We culled structure motifs, using 3D coordinates for the known structures and homology-based models from PDB and Modbase databases respectively, of epitopic region of allergenic proteins and searched against the structure dataset of parasite proteins using a novel algorithm implemented in the BC Search (Binet-Cauchy) program . The BC To observe whether these significantly similar epitopic and epitopic-like regions occur on equivalent positions on respective homologous proteins, a comprehensive analysis was performed by manual inspection/visualization comparing their topology on known 3D structure/models of allergenic and parasite proteins, respectively.A summary of the various steps described in the material and methods section is presented in S. mansoni was used in this study. Total RNA was isolated from adult worms and its integrity was verified using a Bioanalyser  as previously described [A Puerto Rican strain of escribed . cDNA waE. coli cells by heat shock. Sanger Sequencing was used to confirm the CDS sequence that was uploaded to GenBank (Accession No: KM281668).SmBv1L was cloned into the pET15b vector . PCR to generate a gene-specific coding sequence was performed using Phusion High Fidelity DNA polymerase  using the following primers, 5’- TAGGATCCTATGAATGCATATATTATTCG and 5’-ATGGATCCTTATCTAGAGTCGGA at an annealing temperature of 62°C. The PCR product and plasmid were digested with FastDigest BamHI (Thermo Fisher Scientific) and plasmids were treated with FastAP (Thermo Fisher Scientific). Ligation was performed using T4 DNA ligase (Thermo Fisher Scientific) and plasmids transformed into chemically competent DH5alpha E. coli were diluted 1:10, expanded to OD 0.4–0.8 and induced for 3 hours with 1mM IPTG. Pelleted cells were lysed using a French Pressure Cell at ≈10,000 psi and the pellet containing inclusion bodies were isolated by centrifugation at 15,000 x g for 1 hour. Pellets were washed 3 times in cold isolation buffer  and then were incubated in binding buffer  overnight at 4°C. Purification was performed by on-column refolding on a HisTrap FF 1 ml column , after equilibration of the column and sample binding, the column was washed with solubilisation buffer  and the bound protein refolded in a gradient of refolding buffer  and solubilisation buffer. Protein was eluted from the column in a gradient of elution buffer  and collected in fractions 7–20. Refolded SmBv1L was concentrated and buffer exchanged to resuspension buffer , attached to 1 mL washed HisTrap FF and protein eluted by incubation with 150 U/mg protein Thrombin . Thrombin was removed by incubation with benzamadine-agarose beads (Sigma-Aldrich) and the protein buffer exchanged to PBS. Proteins were tested for bacterial contamination by in-house ELISA assay as previously described [Recombinant SmBv1L was produced by isolation from inclusion bodies and on-column refolding using an AKTAPrime+ according to the manufacturer’s instructions . Briefly, overnight cultures of TG2 escribed .S. mansoni) transmission occurred. The 372 plasma donors  were randomly selected from community members who had detectable S. mansoni eggs in a single stool sample . Blood was collected in heparinized tubes at two time-points, immediately before anti-schistosomiasis treatment with praziquantel  and 5 weeks post-treatment. Plasma separated by centrifugation (2000 x g for 5 min) was stored at -80°C until use. This analysis focuses on 222 individuals with full parasitological and serological information available both pre- and post-treatment .Venous plasma samples were collected in the fishing village of Namoni on the shores of Lake Victoria, Mayuge District, Uganda, an area of high year-round schistosomiasis  genomes and poorly represented in bacterial genomes (~1%)  and are The 2712 unique UniProt protein sequence entries corresponding to protein molecules listed in the Allergome database are distributed in 331 Pfam protein domain families. Protein domain families with allergenic entries are relatively few and account for merely 2.2% of total 14831 protein domain families specified in Pfam database . There aA large proportion of known epitopic regions in proteins have been determined by employing a 'peptide fragment approach'. The IEDB database provides a curated list of these epitopic regions along with a limited set of epitopes that are determined by analysing structures of antigen-antibody complexes. The majority (58%) of linear epitopic regions in the IEDB database demonstrated to bind to IgE/IgG4 are within peptides of 10 and 15 amino acid residues length. This is consistent with the average length of an epitope determined based on analysing structures of antigen and antibody complexes .We have chosen 10 protein domain families/superfamilies that have been referred to in the ‘Opinion article’ co-authored by Fitzsimmons and Dunne  for our Cysteine-rich secretory proteins, Antigen 5, and Pathogenesis-related 1 proteins) protein domain families.Protein families categorized in this group are populated with members of allergenic and parasite proteins and hence homologies have already been established. In this group, positive IgE-binding activity has been demonstrated for the parasite proteins, indicating clear-cut evidence for the allergenic potential of proteins. It includes Tropomyosin, EF Hand and CAP  and mite sources are associated with the same Pfam domain families as all allergenic proteins in group A  and three of those in group B . These constitute close homologs of the allergenic proteins. Protein members in families categorised in group A and trypsin-like serine proteases in group B are distributed across prokaryotic and eukaryotic organisms. However, Profilin and Lipocalin families categorised in Group B show representation only from eukaryotic and eukaryotic metazoan organisms, respectively.S. mansoni was chosen for expression and testing in human IgE binding studies (see below).For detecting homologs of allergenic proteins in the 3 remaining group B families , we used parasite protein annotations specified by Gene3D. Allergenic proteins with known PDB structures belonging to families in group B are categorised in the following CATH homologous superfamilies: a) Bet v 1: 3.30.530.20 b) Cupin: 2.60.120.10 c) Expansin proteins : 2.40.40.10 and 2.60.40.760, respectively. For Bet v 1 and Cupin domain families, we detected 58 and 130 parasite proteins that are indexed with CATH accession numbers 3.30.530.20 and 2.60.120.10 respectively and hence are in same homologous superfamily as allergenic proteins. These parasite proteins are considered as close homologs of allergenic proteins. One of the Bet v 1 -like proteins from Prior to this study, databases for the expansin domain family contained no parasite proteins, indicating that no member from a parasite had previously been found.No parasite proteins with CATH accession number 2.40.40.10 and 2.60.40.760 were detected, which indicates that no parasite protein member has previously been found to correspond to expansin proteins from allergenic sources and thus we could not find ‘close homologs’ of allergens in expansin domain family (with same CATH accession number). However, we could find distant homologs’ in metazoan parasites proteome for the same domain family (at protein fold level).Therefore, for establishing distant homology, 1387 parasite proteins that share the same topology/fold as the allergenic expansin proteins were collected. Homologs of allergenic proteins in parasites (belonging to Group A and B) have been listed in Known 3D structures/reliable 3D models of parasite proteins and corresponding allergenic proteins in group B were compared using structure superposition. For further analysis, we restricted the list of parasite proteins that share structural similarity with allergenic proteins with a TM score of ≥0.5. This list constitutes 9 Bet v 1 and 2 Cupin parasite proteins that share homology with allergenic proteins. We also find 15 parasite proteins that are expected to share the same topology as expansin proteins, thereby representing distant homologs. A list of these parasite proteins is provided in S. mansoni (Uniprot accession: G4VGF5) with the prolamin protein  from Triticum aestivum (Wheat) in CATH superfamily 1.10.110.10. The algorithm employed by Gene3D aligns only a small fragment of the worm protein (from residue 406–436) with the wheat protein and is not considered statistically significant.No ‘true’ parasite protein sharing homology or even overall topology/fold with Prolamin could be detected. However, Gene3D does categorize a protein from Glycyphagus domesticus (House itch mite), which shares significant homology with prolamin protein Mal d 3 (UniProt accession: Q9M5X7) from Malus domestica (Apple). However, with careful inspection, we learnt that the mite protein shares a sequence identity of 100% with lipid transfer protein (UniProt accession: M8BYH8) from Aegilops tauschii (Tausch's goatgrass). This finding suggests a possible sequence artifact with regard to the mite protein and hence, is not considered as a true prolamin protein from the mite. At this stage, the absence of parasitic homologs for prolamin can partly be attributed to paucity of data.We also detected a protein (UniProt accession: Q1M2M1) encoded in genome of We next predicted putative IgE/IgG4-binding regions for various family members in parasite proteins. The Allergome database details those proteins encoded in genomes from various sources for which IgE binding activity has already been studied. We have predicted putative IgE binding regions for parasite proteins  by comparing them with fragments of allergens for which IgE binding activity has been ascertained experimentally .Using this approach, we are able to identify parasite proteins belonging to group A and B that share significant sequence similarity with known IgE binding fragments, comprising a total of 177 metazoan parasite proteins . Results corresponding to the predicted IgE binding regions are presented in A total of 344 3D structural motifs that are known to bind IgE/IgG4 were searched in a dataset (3D known structures/3D homology models) of 26 parasite proteins belonging to Bet v1, Cupin and Expansin families  using the BC-search program . BC-searInformation on 3D structural motifs that are known to bind IgE/IgG4 with their structural equivalents on 26 parasite proteins and their corresponding topological positions has been provided in Epitope regions for Class B allergens showing significant matches  with parasite proteins has been provided in Illustrative examples of newly detected metazoan parasite protein which are potential IgE target are discussed in the following section.Schistosoma japonicum (UniProt accession: Q5C262) exhibit similarity with allergenic Parvalbumin protein sequence ‘Sal s 1’ from Atlantic salmon (UniProt accession: B5DH17). Epitopes on the allergenic protein have been mapped using peptide microarray immunoassays [Gallus gallus (PDB accession: 3FS7) as a template. Root mean square deviation values for the generated models  with respect to the template proteins are 0.13Å and 0.21Å respectively. Superposition of 3D models of both the proteins is depicted in EF-hand domain regions from a putative calcium ion binding protein from noassays . While pAscaris lumbricoides (UniProt accession: F1LGV9) belonging to Profilin domain family. The worm protein shares homology with pollen allergen from plant Betula pendula (European white birch). The allergen also has been annotated as a Profilin protein according to the domain definition provided by Pfam. The two proteins share 27% sequence identity. However, the predicted epitopic-like regions of the Ascaris protein (residues 24–42) show significant sequence identity of 61% (similarity of 76%) with known epitopic regions of plant allergen (from residue 28 to 45) [We predict a potential IgE target protein from the nematode worm 8 to 45)   and Brugia malayi  for which IgE activity has been tested in the laboratory. We have confirmed prevalent IgE activity for a Profilin protein from S. mansoni (using human sera) and a lipocalin protein from B. malayi (in vivo studies) when compared with a control protein.Performing a similar analysis, we have also predicted potential IgE targets from Psoroptes ovis (Sheep scab mite), which shares the same topology as an allergenic protein from the expansin family and thus shares distant homology. Overall, this mite protein has only 11.4% sequence identity with ‘Phl p 1’, a major timothy grass pollen . However, epitopes from the plant allergen protein are known and have been identified using IgE binding immunoassays [A further example from group B is the Mite group 2 allergen ‘Pso o 2’ protein (UniProt accession: Q965E2)  from Psonoassays . SuperpoThis analysis establishes a clear similarity between epitope and predicted epitopic-like regions from allergen and mite protein. These regions share sequence identity of 40% and similarity of 63% , thus esThe plant-specific Bet v1 domain family represents the second large family which is highly populated with allergens see . HoweverS. mansoni predicted by our computational analysis to bind IgE and IgG4 in plasma from individuals infected with this parasite. The Bet v 1-like protein from S. mansoni (Uniprot accession: G4VE06) and the plant birch pollen allergen  are categorised in the same homologous superfamily (CATH accession: 3.30.530.20) as described by the CATH database. SmBv1L was cloned and expressed as a recombinant protein in E.coli. Insoluble recombinant protein was extracted from inclusion bodies, purified and refolded on column to give soluble antigen. The presence of a single protein species of approximately 18 kDa, as predicted in silico, was confirmed by a Coomassie blue-stained SDS-PAGE gel.We tested the potential of Bet v 1-like protein (SmBv1L) from S. mansoni-infected individuals from a parasite endemic area in Uganda. Levels of antigen specific responses were measured against IgG1, IgE and IgG4  allergic response.Metazoan parasites are more closely related to their mammalian host than lower taxonomic groups such as bacteria, and viruses. It is remarkable that IgE responses are more strongly targeted to eukaryotic and not prokaryotic proteins. However, based on analyses of three animal allergen protein domain families , Jenkins and co-workers have inferred that allergenic proteins are sufficiently diverged (<62% sequence identity) from the corresponding homologous proteins from the human host . InteresPreviously, IgE binding activity has been studied for certain metazoan parasite proteins corresponding to domain families  that also represent a major proportion of protein sequences from allergenic sources giving an indication about possible sequence and structure similarity with the allergenic proteins . HoweverA novel systematic approach involving sensitive remote homology detection methods has been applied to identify and document proteins encoded in genomes of various metazoan parasites, which share homology (sequence and structure based) with the IgE/IgG4 binding allergenic molecules. Structure-based methods proved to be helpful in establishing remote homology as well as inferring topological similarity of epitopic regions between allergenic and parasite proteins where sequence based methods were not effective. We categorised predicted target parasite proteins into three groups based on (a) if they share homology with allergenic protein (b) if immunoassays have been performed to test IgE/IgG4 activity. Using various computational approaches, we also identified putative epitopic-like regions in parasite proteins that might have potential for IgE binding.S. mansoni using in vitro IgE/IgG4 binding studies. SmBv1L was the target for IgE responses in the inhabitants of a Ugandan schistosomiasis mansoni endemic area, confirming the prediction of the bioinformatics pipeline. The geometric mean IgE level of 56.6 ng/ml (23.6 IU/ml), was comparable to specific IgE responses to common known allergens [S. mansoni allergen-like proteins and in allergy, were induced by SmBv1L [S. mansoni that is phylogenetically disparate from other known allergens of the same family highlights the relevance of the proposed hypothesis and sensitivity of the methodology applied to detect and establish such distant relationships that could be supported by immunological assays performed in vitro.Tropomyosin is the largest family that represents the maximum number of known allergens from worms and arthropods . Howevery SmBv1L –29. To oS. mansoni, in our pipeline for IgE binding structural features and epitopes. These antigens were not predicted to bind IgE by our pipeline, a finding supported by our previously published data [In our recent work, as a control, we also tested Adenylate kinase (AK), protein 14-3-3 and Ubiquitin, antigens that were shown to be prevalent in the human life cycle stages of hed data . This deSchistosoma mansoni protein, but the region detected was too small to be statistically significant. This small region does however map to known epitope regions in prolamin found in wheat. It is tempting to speculate that the region being detected corresponds to the fragment that, by happenchance, shares the IgE interaction motif. Additionally, the lack of detection could be attributed to many factors such as scarcity of information regarding IgE–binding epitopes, incomplete genomes of parasitic organisms and unavailability of 3D structural information regarding allergens and parasite proteins. However, the possibility that this ‘plant storage family’ is indeed absent from metazoan parasites cannot be ruled out completely. Nonetheless, our analyses lend support to our hypothesis by drawing clear comparisons between allergenic and metazoan parasite proteins in rest of the 9 protein domain families.By using our methodology, we have established such relationships for 9 out of 10 protein domain families that contain highest numbers of known allergens. Homology for allergenic prolamin protein members was not established with parasite proteins. Gene3D did detect some similarity between the CATH prolamin superfamily and a domain in a The lack of details for the molecular mechanisms involved in immunity and allergic states and lack of exclusive descriptions of allergenic molecules such as, for example, the presence of conserved motif(s) limit our understanding of immune dysfunction in allergic disease. It is still unclear what molecular mechanisms lead these small epitopes to elicit an IgE-dominated allergic response. By demonstrating that we can detect similarities between epitopes of multicellular parasite proteins and those from allergy-inducing environmental and food proteins, we lay the foundation for studying predicted IgE binding targets, to aid our understanding of the underlying mechanisms involved in both immunity against parasites and in an allergenic response. This understanding is of paramount importance since the IgE response would not have evolved to cause allergy. Defining allergen-like molecules in parasites and understanding their link to the unregulated IgE response will therefore facilitate the discovery and design of molecules for future immunotherapy in allergic conditions.The Ugandan National Council of Science and Technology provided ethical clearance for the human serology studies. Consent forms were translated in the local language and informed written consent was obtained from all adults and from the parents/legal guardians of all children under 15.S1 Table(XLS)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLS)Click here for additional data file.S4 Table(XLS)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 TableBC scores, p-value and RMSD have been calculated for the structural alignments of epitopes and their equivalent motifs on parasite proteins.(XLSX)Click here for additional data file.


Profiling of T cell receptor (TCR) variable gene usage and size distribution of the infiltrating cells revealed marked skewing of the TCR repertoire indicating oligoclonality, but relatively normal distributions in the blood. Although sampling limitation prevented complete assessment of the TCR repertoire, sequencing further identified 11 TCR clonal expansions that persisted through varying degrees of clinical rejection and immunosuppressive therapy. These 11 clones were limited to three TCR beta chain variable (BV) gene families. Overall, these data indicate significant oligoclonality and likely restricted BV gene usage of alloreactive CD8+ T lymphocytes, and suggest that changes in rejection status are more due to varying regulation of their activity or number rather than shifts in the clonal populations in the transplanted organ. Given that controlled animal models produce predictable BV usage in T lymphocytes mediating rejection, understanding the determinants of TCR gene usage associated with rejection in humans may have application in specifically targeted immunotherapy.Immune prophylaxis and treatment of transplanted tissue rejection act indiscriminately, risking serious infections and malignancies. Although animal data suggest that cellular immune responses causing rejection may be rather narrow and predictable based on genetic background, there are only limited data regarding the clonal breadth of anti-donor responses in humans after allogeneic organ transplantation. We evaluated the graft-infiltrating CD8 Solid organ transplantation is frequently the only option for patients with terminal organ failure, but poses a clinical management challenge in balancing the risk of rejection versus infection. The major advance that has made transplantation a viable strategy is the development of immunosuppressive drugs that both prevent and treat immune-mediated graft rejection, most of which act on cellular immunity. While these agents can be highly effective against rejection, their effects are broad and not donor antigen-specific. As a result, immunity against pathogens is also blunted, and infections are the leading cause of morbidity and mortality in transplantation patients .et al [A key mechanism of immune organ rejection is reactivity of host T cells against alloantigens within graft tissue. In normal T cell development, T cell receptors (TCRs) recognizing self-antigens are negatively selected in the thymus. Not having undergone this selective process against differing donor tissue antigens, host T cells react against transplanted donor cells, particularly non-self Major Histocompatibility Complex (MHC) molecules, so-named when discovered as the major determinants of tissue rejection . During et al  examined+ T cells following human hand transplantation, over a period of 178 days. Rather than long-term culture and cloning of T cells as in prior studies, we survey the bulk population of short-term expanded GILs to define the breadth and persistence of clonal expansions.Detailed characterization of the degree of clonal breadth and persistence of GILs in solid organ transplantation has the potential to provide important clinical insights about the diversity of T cells causing graft rejection, as well as designing more targeted therapies. In this study, we assess the graft-infiltrating CD8A 27 year-old woman  was the recipient of a right hand from a male donor . The human leukocyte antigen (HLA) profile was provided by the United Network for Organ Sharing (UNOS). This subject received the experimental hand transplantation under a research protocol approved by the UCLA Institutional Review Board, and provided written informed consent for participation. Detailed clinical data on this subject will be presented in a separate publication.Punch biopsies were obtained from the skin of the transplanted hand and evaluated by the UCLA Pathology Department. Assessment of the inflammatory cell infiltrate was used to assign a rejection grade based on standard Banff Criteria .+ T lymphocytes were selectively expanded from 3mm skin punch biopsies from the transplanted hand by culture of the tissue with 2 x 106 autologous irradiated (3000 rad) PBMCs and a CD3:CD4 bispecific antibody that inhibits CD4+ T cells and stimulates CD8+ T cells [+ T cells by flow cytometry . For cultures that were <70% pure, additional isolation was performed using the EasySep Human CD8+ T Cell Enrichment Kit  or the MACS CD8+ T Cell Isolation Kit  selection.To assess the cytotoxic T lymphocyte population in the transplanted tissue, bulk CD8 T cells , in a 24Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll-Hypaque gradient from heparinized peripheral blood and expanded in parallel with CD3:CD4 bispecific antibody as previously described .+ T cells , and reverse transcribed to cDNA . Quantitative PCR  was performed using alpha or beta variable (AV or BV) region-specific forward primers paired with alpha or beta constant (AC or BC) region-specific reverse primers. For amplification of BV families, quantitation was performed using a 5’-labeled Cy5 probe in the BC region, and the reverse primers were fluorescently tagged with fam, vic, or ned. BV family 6a was excluded from analysis due to primer cross-specificity to BV27. A plasmid containing the BV20 gene served as a quantitation standard. For amplification of AV families, quantitation was performed using a 5’-labeled Cy5 probe in the AC region, and the reverse primers were fluorescently tagged with fam, vic, ned, or pet. A plasmid containing the AV8 gene product served as a quantitation standard. The size distributions of amplified PCR products for each family were assayed by capillary electrophoresis  and analyzed to determine the area under the curve of each peak . The relative concentration of each family was calculated as the ratio of its copy number to the median copy number across all families. The relative concentration of each peak was calculated based on the fraction of the area under the curve of each peak within the total family.Variable gene families are named according to the international ImMunoGeneTics (IMGT) information system nomenclature. TCR alpha and beta chain spectratyping including quantitative PCR was performed as previously described . BrieflyWhen spectratyping revealed a single dominant expansion within a BV family, the PCR product for the whole family was analyzed for a dominant sequence by bulk sequencing as previously described . When thn minimum  ÷ Σn (pa + pb)), where:n corresponds to the peaks in the spectratype, anda and pb correspond to the sizes of the same peak for the two comparison samples a and bpLinear regression analysis was performed for comparison of AV and BV spectratype peak expansions. The Czekanowski Similarity Index was calculated for comparisons of BV spectratype profiles as % Similarity = 200 x  expansions per biopsy . Multiplratyping , althoug2 = 0.42) but significant (p <0.001) correlation of the two biopsies  revealed an average of 5.9 clones, if it is assumed that the 26 repeated BV spectratype expansions  and skin from the transplanted hand (B) was performed as described in the Methods and Materials.Spectratyping of TCR AV genes of CD8(TIF)Click here for additional data file.S2 FigSpectratypes for AV families were performed as in  at the i(TIF)Click here for additional data file.S3 FigThe numbers of AV and BV expansions (>2 relative units magnitude) are plotted for each tested time point. The numbers for day 751 are averaged for the two assays performed that day.(TIF)Click here for additional data file.


Fetal exposure to hyperglycemia impacts negatively kidney development and function.Our objective was to determine whether fetal exposure to moderate hyperglycemia is associated with epigenetic alterations in DNA methylation in peripheral blood cells and whether those alterations are related to impaired kidney function in adult offspring.Twenty nine adult, non-diabetic offspring of mothers with type 1 diabetes (T1D) (case group) were matched with 28 offspring of T1D fathers (control group) for the study of their leukocyte genome-wide DNA methylation profile . In a subset of 19 cases and 18 controls, we assessed renal vascular development by measuring Glomerular Filtration Rate (GFR) and Effective Renal Plasma Flow (ERPF) at baseline and during vasodilatation produced by amino acid infusion.Globally, DNA was under-methylated in cases vs. controls. Among the 87 CpG sites differently methylated, 74 sites were less methylated and 13 sites more methylated in cases vs. controls. None of these CpG sites were located on a gene known to be directly involved in kidney development and/or function. However, the gene encoding DNA methyltransferase 1 (DNMT1)—a key enzyme involved in gene expression during early development–was under-methylated in cases. The average methylation of the 74 under-methylated sites differently correlated with GFR in cases and controls.Alterations in methylation profile imprinted by the hyperglycemic milieu of T1D mothers during fetal development may impact kidney function in adult offspring. The involved pathways seem to be a nonspecific imprinting process rather than specific to kidney development or function. Fetal programming defines a phenomenon by which an alteration of intrauterine environment predisposes to the development of disorders later in life. Evidence came from epidemiological data showing that tobacco exposure, caloric restriction, and severe hyperglycemia during pregnancy as well as severe pregnancy-related hypertension are all determinants of low birth weight , which iA reduced number of nephrons has been associated with primary hypertension and renal and cardiovascular risks in humans , 9. The We previously investigated adult individuals born from type 1 diabetic mothers as a model of fetal exposure to maternal hyperglycemia, taking those born from type 1 diabetic fathers as controls , 13. HenThe molecular mechanisms involved in the development of impaired renal function in offspring of diabetic mothers are yet to be unravelled. Alterations of the expressions of IGFs and their receptors in fetal kidney were reported in rats exposed in utero to maternal hyperglycemia . BecauseIf adverse fetal environment irreversibly programs adult disease, then DNA epigenetic modifications may be involved. DNA methylations and histone modifications are two key epigenetic changes in chromatin structure that directly influence gene transcription, expression, and cellular functions and consequently, tissue development . DNA metIn the present study we used a microarray technique to seek potential alterations in genome-wide DNA methylation in blood cells from adult subjects who had been exposed in utero to maternal type 1 diabetes. We also investigated whether these alterations are associated with renal dysfunction.Participants were direct offspring of type 1 diabetic subjects attending specialized clinics in 6 French hospitals: Hôpital Saint-Louis, Hôpital Bichat–Claude Bernard, Hôtel-Dieu, Institut Montsouris all in Paris, Centre Hospitalier Universitaire in Poitiers, and Centre Hospitalier Sud Francilien in Corbeil, Essonne.Cases and controls were selected to have one parent with type 1 diabetes (as defined by the American Diabetes Association) for at least two years before offspring conception. Eligibility was possible if the other parent was not diabetic at time of study. All mothers did not smoke during pregnancy. Offspring were men or women at least 18 years of age not pregnant at time of investigation for women and without diabetes as checked with an oral glucose tolerance test. They were free of immune marker of type 1 diabetes . Chronic drug intake, acute infection, any chronic disease, and personal or family history of kidney disease, other than possible diabetic nephropathy in their diabetic parents were excluded. Cases were offspring of type 1 diabetic mothers, and controls offspring of type 1 diabetic fathers.The current study is part of a research program designed to investigate the physiological consequences of fetal exposure to maternal type 1 diabetes at adult age in 62 offspring recruited between 2006 and 2009. Genomic DNA isolated from whole blood samples was available for CpG sites methylation assay in 57 offspring, 29 cases and 28 controls. Among them, 19 cases and 18 controls were studied for baseline and amino acid-stimulated Glomerular Filtration Rate (GFR), and Effective Renal Plasma Flow (ERPF), using a 51Cr EDTA plus 123I-hippurate primed constant infusion technique as previously described .The study was approved by the local Ethical Committee  and each participant gave a written informed consent to participate.Methylation of 27,578 CpG sites at 14,475 consensus coding sequencing sites was performed using the Illumina Human Methylation27 BeadChip system at the Integragen SA at Evry, France, as previously described , 23. BriThe detection p-value as provided by Illumina is obtained by comparing the signal generated by each CpG site to negative controls. CpG sites with missing β-values or detection p-value > 0.01 for more than 5 patients were eliminated from the analysis. This strategy led to discard 1509 CpG sites (5.5%), thus leaving 26,069 CpG sites among 57 subjects for the analysis.B = 100 permutations of the t-statistics as described in Storey & Tibshirani  vs 0.013 (0.055–0.002) in offspring of diabetic fathers (p = 0.004).DNMT1 gene and Glomerular Filtration Rate . No correlation was found with other kidney parameters.We then studied possible relationships between the level of methylation in the differentially methylated sites between the 2 groups and kidney function parameters. We found an opposite correlation between the average level of methylation of the 74 sites less methylated in cases and Glomerular Filtration Rate in basal state ; controls: -0.44 ; p = 0.03 for interaction) and in response to amino acid infusion ; controls: -0.47 ; p = 0.06 for interaction). Although non-significant, a similar pattern of correlation was observed between the average level of methylation of the DNMT1) which is known to be involved in early phases of development. Thus, the link between methylation alteration and kidney dysfunction may result from a nonspecific imprinting process.Our results suggest that in utero exposure to hyperglycemia is associated with alterations in genome-wide DNA methylation profile. These alterations were related to kidney dysfunction in adults. We did not identify any differential methylation on genes currently known for their function in kidney development. One explanation could be that DNA methylation varies depending on cell type and we do not have evidences that DNA methylation profile in the kidney is similar to what is observed in peripheral leukocytes, except if DNA methylation changes occurred in the very early fetal development. Interestingly, one of the strongest observed associations was for the methylation of the gene encoding DNA methyltransferase 1  in the adrenal is significantly under-methylated early in offspring life, and in vitro, AT1b gene expression is highly dependent on promoter methylation [IGF2 gene compared with their unexposed, same-sex siblings [IGF2 gene may be targeted by epigenetic modifications participating to fetal programing of renal dysfunction. Unfortunately, in our study, none of the differentially methylated CpGs involved these genes/pathways.The positive correlations observed in the case group between renal function and the average β-value of the 74 CpG sites down-methylated support a potential role for methylation as an epigenetic phenomenon in the programming of renal dysfunction. In rat models of dietary protein restriction, the angiotensin receptor gene 1b  was the methylated gene in cases that has been picked up by the automated method of literature interrogation. It is a key enzyme in maintaining methylation patterns during cell division and it plays a crucial role in maintaining methylation marks of the imprinted genes [DNMT1 causes disruption of the maintenance imprinting leading to fetal death in rodents [DNMT1 promoter is associated with its decreased expression [DNMT1 may represent a potential mechanism of fetal programing by hyperglycemia causing abnormal kidney development through parental imprinting. Changes in gene expression by epigenetic process are not restricted to imprinted genes. DNMT1 is highly expressed in the kidney and Bechtel et al. demonstrated that it is involved in kidney fibrosis by hypermethylating RASAL1, encoding an inhibitor of the Ras oncoprotein associated with the perpetuation of fibroblast activation [DNMT1 affects gene expression by mechanisms independent of DNA methylation, as it has been demonstrated earlier in lung carcinoma [MEST gene but they did not look at DNMT1 [Epigenetic mechanisms such as genomic imprinting may contribute to the programming of health and disease (review in ). While ed genes  and cons rodents . It has pression . Thus, mtivation . Lastly,arcinoma . Studyinat DNMT1 .NFκB p65 in mice endothelial cells [Whether or not fetal exposure to hyperglycemia  impacts tissue DNA methylation is still unanswered. To our knowledge, no data exist regarding kidney development and function. However, the relationships between hyperglycemia and DNA methylation have been studied in other tissues. Using the same Infinium Methylation assay than in our study, Volkmar et al. found 266 CpGs with lower methylation levels and only 10 hyper-methylated CpGs in islets isolated from T2D patients compared with non-diabetic individuals . A subgral cells .We cannot rule out that differences in DNA methylation between cases and controls were related to prematurity rather than fetal exposure to hyperglycemia. However, prematurity was late preterm delivery, occurred in a minority of subjects and was not associated with a low birth weight. In addition other mother environmental factors such as diet, physical exercise, body weight gain, or stress may impact DNA methylation.In conclusion, this study is the first evidence that kidney dysfunction associated with moderate hyperglycemia  during fetal development may be mediated by DNA methylation modifications. Confirmatory results in other groups of subjects are needed as well as investigating the direct biological mechanisms linking DNA methylation status and kidney function.


Tamias striatus) in conjunction with spatially explicit habitat attribute data to evaluate the realized permeability of various landscape elements in a fragmented agricultural ecosystem. To accomplish this we 1) used logistic regression to evaluate whether land cover attributes were most often associated with the matrix between or habitat within genetically identified populations across the landscape, and 2) utilized spatially explicit habitat attribute data to predict genetically-derived Bayesian probabilities of population membership of individual chipmunks in an agricultural ecosystem. Consistency between the results of the two approaches with regard to facilitators and inhibitors of gene flow in the landscape indicate that this is a promising new way to utilize both landscape and genetic data to gain a deeper understanding of human-altered ecosystems.Human-altered environments often challenge native species with a complex spatial distribution of resources. Hostile landscape features can inhibit animal movement , while other landscape attributes facilitate gene flow. The genetic attributes of organisms inhabiting such complex environments can reveal the legacy of their movements through the landscape. Thus, by evaluating landscape attributes within the context of genetic connectivity of organisms within the landscape, we can elucidate how a species has coped with the enhanced complexity of human altered environments. In this research, we utilized genetic data from eastern chipmunks ( Fragmentation of natural landscapes by anthropogenic attributes, such as agriculture, urbanization, and transportation infrastructure, alters the manner in which animals utilize remnant native habitats , 2]. In. In2]. IOf particular concern in fragmented ecosystems is the concept that a long-term reduction in genetic diversity and impediments to gene flow can inhibit future adaptation of species . Howevera priori groupings and genetic patterns can be analyzed at the individual scale. Another benefit of using landscape genetics for fragmentation studies is its ability to disentangle multiple influences on gene flow because genetic variation is often influenced by multiple factors that operate at different spatial . T. T13]. T spatial –18 and t spatial , 20]..a prioriLandscape genetic models often depend on accurate definition of the functional biological extent of populations, particularly in management and conservation efforts , 22]. U. U22]. Uq-values or posterior probabilities) inferred from Bayesian algorithms within landscape genetic models. These genetic variables can act as response variables in statistics that evaluate how landscape parameters influence genetic variation. For example, several studies have utilized genetic surfaces based on ancestry coefficients from Bayesian clustering programs to investigate how specific landscape features  impacted gene flow , ) in the basin are highly fragmented with the largest tracts confined to major drainages where floodplains or locally steep topography prohibits agriculture . I. I2) of iculture . Possibl2 study cells from late May to early August in 2001, 2002, 2003, respectively. Prior to each field season, all 30 X 30 m pixels in each cell were classified into 1 of 5 land cover categories , and then sampled according to a stratified-random design. To capture the variation within the study area, trapping grids were placed in sampling sites based on land cover so that natural land cover types  were disproportionally represented as compared to urban and agriculture . We randomly chose sampling sites  within patches of habitat by randomly selecting pixels of an appropriate habitat according to the predefined proportions stated above within each study cell (n = 35). Forest site selection had an additional step because they were also stratified according to forest patch size , and then were selected according to their log10 area within the three size categories. In total, a maximum of 45 sampling sites were selected per study cell in a summer , a, a2 studa summer . A full a summer .Each sampling site within a cell contained a grid of Fitch live traps (2001), Sherman live traps (2003), or a mixture of both (2002) spaced 15 m apart. Grid dimensions varied by trap year and patch size. Grids in 2001 were primarily 3 traps x 3 traps, with a few 7x7 grids where forest patch sizes were large enough to accommodate this arrangement. In 2002 and 2003, 5x5 grids were used whenever space allowed; otherwise 4x4 or 3x3 grids were used. If a forest patch was not large enough for a 3x3 grid, it was not sampled. Habitat corridors were identified as treed and non-treed land cover features less than 30 m wide and were fitted with 5x2 grids. Simultaneous trapping for raccoons was conducted at the edges of the trap grids to limit disturbance by raccoons to the small mammal traps.Traps were baited with black-oil sunflower seeds. A pre-bait period with traps locked open occurred for 3 days, followed by a 5-day trap-check session, during which traps were checked twice daily. Each site had one trapping session. All animals were handled according to procedures approved by the Purdue Animal Care and Use Committee under protocol #01–024. Ear clips were taken from each individual using sterile scissors, and treated with ferric subsulfate in cases of excess bleeding. Animals were then released, and all tissues were stored in at -80°C prior to DNA extraction.Taq DNA polymerase (NEB) and 2X Thermopol reaction buffer 2SO4, 10 mM KCl, 2 mM MgSO4, 0.1% Triton X-100; NEB). Primer concentrations were adjusted so that intensities of the final products per multiplex reaction were approximately equal  in in34] ink. Five independent runs were performed to ensure consistency in the estimation of k. If there were inconsistencies between runs , we added additional runs with 400,000 iterations . Finally, Geneland may produce empty populations in addition to occupied populations, a phenomenon known as ‘ghost populations’ )a priori assignment of cost values is needed. Instead, regression coefficients derived from models developed in independent landscapes like our study could also be used to parameterize resistance surfaces. Once developed, genetically informed individual-based models could be used for a variety of purposes such as comparison to other parameterization  or optimization Click here for additional data file.S2 TableR), and FIS with the upper and lower 95% confidence intervals are listed per locus and sample cell. Bold FIS values indicate a significant deficiency of heterozygotes.Sample size (N), number of alleles (Na), observed (Ho) and expected heterozygosity (He), allelic richness (A(DOCX)Click here for additional data file.S3 TableST values were calculated for each study cell as well as pair-wise FST values between all putative clusters within a study cell. All but one FST between putative clusters were significantly different from zero.Global F(DOCX)Click here for additional data file.S1 FigWe recorded a positive relationship between geographic and genetic distance, consistent with IBD .(TIF)Click here for additional data file.


There are many ways to perform noninvasive testing in patients with coronary artery disease (CAD), including myocardial perfusion imaging with single-photon emission computed tomography (SPECT), positron-emission tomography (PET), and coronary computed tomography angiography (CTA). Results from series of patients evaluated with single modalities have already been published by many researchers –3, but tThe recently published SPARC registry  in JACC by the group of DiCarli et al.  was a multicentre study designed to collect standardised clinical data on patients undergoing CTA, PET, or SPECT . The priThe main findings were that costs were significantly lower for SPECT compared with CTA or PET in the evaluation of suspected CAD. SPECT was economically attractive compared with PET, whereas CTA was associated with higher costs and no significant difference in mortality compared with SPECT. More specifically, the authors observed that patients who underwent coronary CTA and PET experienced higher rates of subsequent invasive coronary arteriography  as compared with patients who underwent SPECT (7 %). The mean total radiation was significantly higher for CTA (15.1 mSV) compared with SPECT (11.7 mSV), both for the initial tests (13 mSV vs. 11 mSV) and for follow-up tests and procedures (2.1 mSV vs. 0.7 mSV). Exposure from follow-up tests and procedures was higher after PET (2.0 mSV) than after SPECT (0.6 mSV).The findings in favour of SPECT are in line with a decision model by Garber and Solomon , who comAnalysis of the current SPARC registry at least suggests that SPECT is the noninvasive imaging procedure of choice to evaluate patients with suspected CAD in terms of subsequent medical costs. SPECT offered the lowest costs over 2 years of follow-up among patients with suspected CAD. The significantly higher costs among patients undergoing CTA or PET were primarily due to higher rates of subsequent invasive cardiac procedures, because there was little difference in initial costs of testing.To conclude, the use of SPECT myocardial perfusion imaging was associated with lower costs over 2 years of follow-up than the use of CTA or PET, primarily because of fewer subsequent invasive procedures. Consequently, SPECT imaging seems to be the preferred imaging strategy in patients with suspected CAD. The value of SPECT imaging has been underscored by several recent reports –13. Howe