98 research outputs found

    Refining susceptibility loci of chronic obstructive pulmonary disease with lung eqtls

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    Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of mortality worldwide. Recent genome-wide association studies (GWAS) have identified robust susceptibility loci associated with COPD. However, the mechanisms mediating the risk conferred by these loci remain to be found. The goal of this study was to identify causal genes/variants within susceptibility loci associated with COPD. In the discovery cohort, genome-wide gene expression profiles of 500 non-tumor lung specimens were obtained from patients undergoing lung surgery. Blood-DNA from the same patients were genotyped for 1,2 million SNPs. Following genotyping and gene expression quality control filters, 409 samples were analyzed. Lung expression quantitative trait loci (eQTLs) were identified and overlaid onto three COPD susceptibility loci derived from GWAS; 4q31 (HHIP), 4q22 (FAM13A), and 19q13 (RAB4B, EGLN2, MIA, CYP2A6). Significant eQTLs were replicated in two independent datasets (n = 363 and 339). SNPs previously associated with COPD and lung function on 4q31 (rs1828591, rs13118928) were associated with the mRNA expression of HHIP. An association between mRNA expression level of FAM13A and SNP rs2045517 was detected at 4q22, but did not reach statistical significance. At 19q13, significant eQTLs were detected with EGLN2. In summary, this study supports HHIP, FAM13A, and EGLN2 as the most likely causal COPD genes on 4q31, 4q22, and 19q13, respectively. Strong lung eQTL SNPs identified in this study will need to be tested for association with COPD in case-control studies. Further functional studies will also be needed to understand the role of genes regulated by disease-related variants in COPD

    Imaging the functional connectivity of the Periaqueductal Gray during genuine and sham electroacupuncture treatment

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    Background Electroacupuncture (EA) is currently one of the most popular acupuncture modalities. However, the continuous stimulation characteristic of EA treatment presents challenges to the use of conventional functional Magnetic Resonance Imaging (fMRI) approaches for the investigation of neural mechanisms mediating treatment response because of the requirement for brief and intermittent stimuli in event related or block designed task paradigms. A relatively new analysis method, functional connectivity fMRI (fcMRI), has great potential for studying continuous treatment modalities such as EA. In a previous study, we found that, compared with sham acupuncture, EA can significantly reduce Periaqueductal Gray (PAG) activity when subsequently evoked by experimental pain. Given the PAG's important role in mediating acupuncture analgesia, in this study we investigated functional connectivity with the area of the PAG we previously identified and how that connectivity was affected by genuine and sham EA. Results Forty-eight subjects, who were randomly assigned to receive either genuine or sham EA paired with either a high or low expectancy manipulation, completed the study. Direct comparison of each treatment mode's functional connectivity revealed: significantly greater connectivity between the PAG, left posterior cingulate cortex (PCC), and precuneus for the contrast of genuine minus sham; significantly greater connectivity between the PAG and right anterior insula for the contrast of sham minus genuine; no significant differences in connectivity between different contrasts of the two expectancy levels. Conclusions Our findings indicate the intrinsic functional connectivity changes among key brain regions in the pain matrix and default mode network during genuine EA compared with sham EA. We speculate that continuous genuine EA stimulation can modify the coupling of spontaneous activity in brain regions that play a role in modulating pain perception.National Center for Complementary and Alternative Medicine (U.S.) (PO1-AT002048)National Center for Complementary and Alternative Medicine (U.S.) (R01AT005280)National Center for Complementary and Alternative Medicine (U.S.) (R21AT00949)National Center for Complementary and Alternative Medicine (U.S.) (KO1AT003883)National Center for Complementary and Alternative Medicine (U.S.) (R21AT004497)National Center for Complementary and Alternative Medicine (U.S.) (K24AT004095)National Center for Research Resources (U.S.) (Clinical Research Center Biomedical Imaging Core, M01-RR-01066)National Center for Research Resources (U.S.) (Clinical Research Center Biomedical Imaging Core, UL1 RR025758-01)National Center for Research Resources (U.S.) (Center for Functional Neuroimaging Technologies, P41RR14075

    Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis

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    Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption is limited by the technicalities of training these networks. To address this translation gap between medical researchers and neural networks in the field of pathology, we have created an intuitive interface which utilizes the commonly used whole slide image (WSI) viewer, Aperio ImageScope (Leica Biosystems Imaging, Inc.), for the annotation and display of neural network predictions on WSIs. Leveraging this, we propose the use of a human-in-the-loop strategy to reduce the burden of WSI annotation. We track network performance improvements as a function of iteration and quantify the use of this pipeline for the segmentation of renal histologic findings on WSIs. More specifically, we present network performance when applied to segmentation of renal micro compartments, and demonstrate multi-class segmentation in human and mouse renal tissue slides. Finally, to show the adaptability of this technique to other medical imaging fields, we demonstrate its ability to iteratively segment human prostate glands from radiology imaging data.Comment: 15 pages, 7 figures, 2 supplemental figures (on the last page

    Impact of Statins on Gene Expression in Human Lung Tissues

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    Statins are 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors that alter the synthesis of cholesterol. Some studies have shown a significant association of statins with improved respiratory health outcomes of patients with asthma, chronic obstructive pulmonary disease and lung cancer. Here we hypothesize that statins impact gene expression in human lungs and may reveal the pleiotropic effects of statins that are taking place directly in lung tissues. Human lung tissues were obtained from patients who underwent lung resection or transplantation. Gene expression was measured on a custom Affymetrix array in a discovery cohort (n = 408) and two replication sets (n = 341 and 282). Gene expression was evaluated by linear regression between statin users and non-users, adjusting for age, gender, smoking status, and other covariables. The results of each cohort were combined in a meta-analysis and biological pathways were studied using Gene Set Enrichment Analysis. The discovery set included 141 statin users. The lung mRNA expression levels of eighteen and three genes were up-regulated and down-regulated in statin users (FDR < 0.05), respectively. Twelve of the up-regulated genes were replicated in the first replication set, but none in the second (p-value < 0.05). Combining the discovery and replication sets into a meta-analysis improved the significance of the 12 up-regulated genes, which includes genes encoding enzymes and membrane proteins involved in cholesterol biosynthesis. Canonical biological pathways altered by statins in the lung include cholesterol, steroid, and terpenoid backbone biosynthesis. No genes encoding inflammatory, proteases, pro-fibrotic or growth factors were altered by statins, suggesting that the direct effect of statin in the lung do not go beyond its antilipidemic action. Although more studies are needed with specific lung cell types and different classes and doses of statins, the improved health outcomes and survival observed in statin users with chronic lung diseases do not seem to be mediated through direct regulation of gene expression in the lung

    Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

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    Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55 × 10(-151)). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases
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