Predictive genomics in asthma management using probabilistic graphical models

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007.Includes bibliographical references (leaves 126-142).Complex traits are conditions that, as a result of the complex interplay among genetic and environmental factors, have wide variability in progression and manifestation. Because most common diseases with high morbidity and mortality are complex traits, uncovering the genetic architecture of these traits is an important health problem. Asthma, a chronic inflammatory airway disease, is one such trait that affects over 300 million people around the world. Although there is a large amount of human genetic information currently available and expanding at a rapid pace, traditional genetic studies have not provided a concomitant understanding of complex traits, including asthma and its related phenotypes. Despite the intricate genetic background underlying complex traits, most traditional genetic studies focus on individual genetic variants. New methods that consider multiple genetic variants are needed in order to accelerate the understanding of complex traits. In this thesis, the need for better analytic approaches for the study of complex traits is addressed with the creation of a novel method. Probabilistic graphical models (PGMs) are a powerful technique that can overcome limitations of conventional association study approaches.(cont.) Going beyond single or pairwise gene interactions with a phenotype, PGMs are able to account for complex gene interactions and make predictions of a phenotype. Most PGMs have limited scalability with large genetic datasets. Here, a procedure called phenocentric Bayesian networks that is tailored for the discovery of complex multivariate models for a trait using large genomic datasets is presented. Resulting models can be used to predict outcomes of a phenotype, which allows for meaningful validation and potential applicability in a clinical setting. The utility of phenocentric Bayesian networks is demonstrated with the creation of predictive models for two complex traits related to asthma management: exacerbation and bronchodilator response. The good predictive accuracy of each model is established and shown to be superior to single gene analysis. The results of this work demonstrate the promise of using the phenocentric Bayesian networks to study the genetic architecture of complex traits, and the utility of multigenic predictive methods compared to traditional single-gene approaches.by Blanca Elena Himes.Ph.D

Genome-Wide Association Analysis in Asthma Subjects Identifies SPATS2L as a Novel Bronchodilator Response Gene

Bronchodilator response (BDR) is an important asthma phenotype that measures reversibility of airway obstruction by comparing lung function (i.e. FEV1) before and after the administration of a short-acting β2-agonist, the most common rescue medications used for the treatment of asthma. BDR also serves as a test of β2-agonist efficacy. BDR is a complex trait that is partly under genetic control. A genome-wide association study (GWAS) of BDR, quantified as percent change in baseline FEV1 after administration of a β2-agonist, was performed with 1,644 non-Hispanic white asthmatic subjects from six drug clinical trials: CAMP, LOCCS, LODO, a medication trial conducted by Sepracor, CARE, and ACRN. Data for 469,884 single-nucleotide polymorphisms (SNPs) were used to measure the association of SNPs with BDR using a linear regression model, while adjusting for age, sex, and height. Replication of primary P-values was attempted in 501 white subjects from SARP and 550 white subjects from DAG. Experimental evidence supporting the top gene was obtained via siRNA knockdown and Western blotting analyses. The lowest overall combined P-value was 9.7E-07 for SNP rs295137, near the SPATS2L gene. Among subjects in the primary analysis, those with rs295137 TT genotype had a median BDR of 16.0 (IQR = [6.2, 32.4]), while those with CC or TC genotypes had a median BDR of 10.9 (IQR = [5.0, 22.2]). SPATS2L mRNA knockdown resulted in increased β2-adrenergic receptor levels. Our results suggest that SPATS2L may be an important regulator of β2-adrenergic receptor down-regulation and that there is promise in gaining a better understanding of the biological mechanisms of differential response to β2-agonists through GWAS

Rapamycin-independent <i>IGF2</i> expression in <i>Tsc2</i>-null mouse embryo fibroblasts and human lymphangioleiomyomatosis cells

<div><p>Lymphangioleiomyomatosis (LAM) is a rare, almost exclusively female lung disease linked to inactivating mutations in <i>tuberous sclerosis complex 2</i> (<i>TSC2)</i>, a tumor suppressor gene that controls cell metabolic state and growth via regulation of the mechanistic target of rapamycin (mTORC1) signaling. mTORC1 is frequently activated in human cancers and, although the mTORC1 inhibitor rapamycin has a cytostatic effect, it is, in general, unable to elicit a robust curative effect or tumor regression. Using RNA-Seq, we identified (1) <i>Insulin-like Growth Factor</i> (<i>IGF2</i>) as one of the genes with the highest fold-change difference between human <i>TSC</i>2-null and <i>TSC</i>2-expressing angiomyolipoma cells from a patient with LAM, and (2) the mouse <i>IGF2</i> homolog <i>Igf2</i>, as a top-ranking gene according to fold change between <i>Tsc</i>2^-/- and <i>Tsc</i>2^+/+ mouse embryo fibroblasts (MEFs). We extended transcript-level findings to protein level, observing increased Igf2 protein expression and Igf2 secretion by <i>Tsc</i>2^-/- MEFs. Increased Igf2 expression was not due to epigenetic imprinting, but was partially mediated through the Stat3 pathway and was completely insensitive to rapamycin treatment. An siRNA-mediated decrease of Igf2 resulted in decreased Stat3 phosphorylation, suggesting presence of an autocrine Igf2/Stat3 amplification cycle in <i>Tsc2</i>^<i>-/-</i> MEFs. In human pulmonary LAM lesions and metastatic cell clusters, high levels of IGF2 were associated with mTORC1 activation. In addition, treatment of three primary IGF2-expressing LAM lung cell lines with rapamycin did not result in IGF2 level changes. Thus, targeting of IGF2 signaling may be of therapeutic value to LAM patients, particularly those who are unresponsive to rapamycin.</p></div

Increased expression of <i>IGF2</i> transcripts in TSC2— human LAM cells and <i>Tsc2</i>^<i>-/-</i> MEFs.

<p>(A) TSC2 levels in human TSC2-null LAM 621–102 cells (TSC2—) cells and TSC2 re-expressing 621–103 LAM (TSC2++) cells. (B) RNA-Seq results show increased <i>IGF2</i> transcripts per kilobase million (TPM) in TSC2— cells. (C) Corresponding plot of mapped reads along the hg38 reference genome corresponding to <i>IGF2</i>. (D) Verification that <i>Tsc2</i> is not expressed in <i>Tsc2</i>^<i>-/-</i> MEFs. (E) RNA-Seq results show increased <i>Igf2</i> TPMs in <i>Tsc2</i>^<i>-/-</i> vs. <i>Tsc2</i>^<i>+/+</i> MEFs. (F) Corresponding plot of mapped reads along the mm10 reference genome corresponding to <i>Igf2</i>.</p

IGF2 expression is rapamycin-insensitive in <i>Tsc2</i>^<i>-/-</i> MEFs and human LAM cells.

<p><i>Tsc2</i>^<i>-/-</i> and <i>Tsc2</i>^<i>+/+</i> MEFs were grown to near confluence, serum deprived for 2 hr and treated with indicated concentrations of rapamycin for 24 hr, followed by western blot analysis with indicated antibodies. (A) Treatment with 10nM rapamycin for 24 hr did not decrease Igf2 protein expression, although this dose completely suppressed pS6. (B) Igf2, Stat3, and pStat3 protein expression levels were unaffected by rapamycin treatment over a range of concentrations, while it completely inhibited pS6 at 2nM and 20nM concentrations. (C) IGF2 protein levels did not change in TSC2— and TSC2++ cells that were serum deprived for 2 hr and treated with 20nM rapamycin for 24 hr, as measured by western blot analysis. (D) IGF2 protein levels did not change in primary human LAM cells (LAM 111, LAM 105, LAM116) that were serum deprived for 2 hr and treated with 10nM rapamycin for 16 hr, as measured by western blot analysis. Images are representative of western blot analysis performed at least in three separate experiments.</p

STAT3-dependent upregulation of IGF2 in TSC2-null cells.

<p>(A) Re-expression of TSC2 (TSC2++) in TSC2-null LAM 102 (TSC2—) cells decreased STAT3 expression and activation. (B) siRNA-induced knockdown of STAT3 decreased STAT3 levels in TSC2— cells. (C) RNA-Seq results show upregulated <i>IGF2</i> transcripts per kilobase million (TPM) in TSC2— cells transfected with either NT siRNA (Control) or STAT3 siRNA (siSTAT3). (D) STAT3 binding sites in human IGF2 and mouse Igf2 promoter regions. STAT3 enrichment in specific promoter regions of (E) human <i>IGF2</i> and (F) mouse <i>Igf2</i> genes was detected by ChIP-qPCR. Treatment of <i>Tsc2</i>^<i>-/-</i> MEFs with Stat3 inhibitor S3I-201 (100 nM for 18 hr) decreased Igf2 protein (G) expression as measured via Western blot and (H) secretion as measured via ELISA. (I) siRNA-mediated Stat3 knockdown also decreased Igf2 protein expression in <i>Tsc2</i>^<i>-/-</i> MEFs. (J) siRNA-mediated Igf2 knockdown decreased Stat3 phosphorylation but not total Stat3.</p

IGF2 expression in LAM lungs and <i>Tsc2</i>^<i>-/-</i> MEFs.

<p>Representative images of IHC analysis show IGF2 expression in (A) LAM lesion and (B) LAM cluster detected with specific antibodies. Non-immune IgG was used as a control (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0197105#pone.0197105.s001" target="_blank">S1 Fig</a>). Igf2 expression in <i>Tsc2</i>^<i>-/-</i> MEFs was detected by (C) qPCR (D) Western blot and (E) ELISA. (F) <i>Tsc2</i>^<i>-/-</i> MEFs were transfected with 50nM <i>Igf2</i> siRNA (siIGF2) or NT siRNA (siNT) for 48 hrs. Decreased levels of Igf2 protein expression were confirmed via western blot with β-actin as an internal loading control. (G) Decreased Igf2 protein secretion was confirmed via ELISA. Igf2 knockdown resulted in (H) increased cleaved caspase-3 levels as measured via immunocytostaining and flow for Alexa Fluor® 488 -Cleaved Caspase 3 where the population of positively stained MEFs was normalized to the control population, and (J) decreased cell viability as assessed by 0.4% Trypan Blue staining normalized to the control cell viability. Student's t-tests were used to determine the statistical significance of the differences, and <i>p</i>-values reflect a sample size of 3 replicates.</p