Pathway-based Analysis Research Articles

EPEN-43. TARGETING INTRA-TUMOUR HETEROGENEITY IN PAEDIATRIC EPENDYMOMA: AN INTEGRATED OMICS STUDY TOWARDS PATIENT-TAILORED THERAPY

Ependymoma (EPN) is the second most common malignant paediatric brain tumour, which despite extensive genomic sequencing, no novel therapeutic options have been discovered. Multi-omics are anticipated to reveal dysregulated pathways that may be predictive of patient-specific biomarkers. Given the close association between gene expression, active biochemical signaling and metabolism, there is an unmet scientific challenge to determine whether EPN gene expression correlates with aberrant metabolic pathways, thus presenting therapeutic vulnerabilities. We first compared two distinct subgroups of EPN, PF-A and ST-RELA, identifying 115 metabolites and 1580 upregulated genes between the two subgroups, therefore validating previously reported genetic clustering of these two subtypes. We next integrated transcriptomics and metabolomics, comparing 28 intra-tumour tissue regions from eight primary PF-A EPN patients. Polar metabolites and RNA were simultaneously extracted from the same population of cells. RNAseq identified dysregulated genes and liquid chromatography-mass spectrometry (LC-MS) detected 98 significantly altered metabolites between 18 multi-regions, the majority mapping onto the arginine and proline pathways. Integration of genes and metabolites using pathway-based network analysis revealed 124 aberrant gene-metabolite interactions between intra-tumour regions, with large numbers occurring in the glucogenesis and glycine metabolic pathways in 6/8 patients. These may represent ubiquitous and therapeutically relevant metabolic pathways critical for EPN survival. Additionally, patients presented at least one unique intra-tumour genomic-metabolomic interaction, applicable for patient-tailored therapy. This is the first exploration of EPN multi-omic integration and intra-tumour heterogeneity. Selected drug targets predicated on aberrant gene-metabolite networks will be validated in multi-region patient-derived cell lines and orthotopic models using repurposed therapeutics.

A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma

BackgroundRenal cell carcinoma (RCC) is a complex disease and is comprised of several histological subtypes, the most frequent of which are clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC) and chromophobe renal cell carcinoma (ChRCC). While lots of studies have been performed to investigate the molecular characterizations of different subtypes of RCC, our knowledge regarding the underlying mechanisms are still incomplete. As molecular alterations are eventually reflected on the pathway level to execute certain biological functions, characterizing the pathway perturbations is crucial for understanding tumorigenesis and development of RCC.MethodsIn this study, we investigated the pathway perturbations of various RCC subtype against normal tissue based on differential expressed genes within a certain pathway. We explored the potential upstream regulators of subtype-specific pathways with Ingenuity Pathway Analysis (IPA). We also evaluated the relationships between subtype-specific pathways and clinical outcome with survival analysis.ResultsIn this study, we carried out a pathway-based analysis to explore the mechanisms of various RCC subtypes with TCGA RNA-seq data. Both commonly altered pathways and subtype-specific pathways were detected. To identify the distinctive characteristics of each subtype, we focused on subtype-specific perturbed pathways. Specifically, we observed that some of the altered pathways were regulated by several recurrent upstream regulators which presenting different expression patterns among distinct RCC subtypes. We also noticed that a large number of perturbed pathways were controlled by the subtype-specific upstream regulators. Moreover, we also evaluated the relationships between perturbed pathways and clinical outcome. Prognostic pathways were identified and their roles in tumor development and progression were inferred.ConclusionsIn summary, we evaluated the relationships among pathway perturbations, upstream regulators and clinical outcome for differential subtypes in RCC. We hypothesized that the alterations of common upstream regulators as well as subtype-specific upstream regulators work together to affect the downstream pathway perturbations and drive cancer initialization and prognosis. Our findings not only increase our understanding of the mechanisms of various RCC subtypes, but also provide targets for personalized therapeutic intervention.

Quantitative acetylome analysis reveals involvement of glucosyltransferase acetylation in Streptococcus mutans biofilm formation.

Streptococcus mutans (S. mutans) effectively utilizes dietary sucrose for the exopolysaccharide productions, which are mostly synthesized by the effects of glucosyltransferases (Gtfs). In the present study, the acetylome of S. mutans was identified and quantitative acetylome analysis of the bacterial biofilm growth (SMB) was compared with that of planktonic growth (SMP). The dynamic changes of protein acetylation were quantified using the integrated approach involving TMT labeling and Kac affinity enrichment followed by high-resolution mass spectrometry-based quantitative proteomics. In total, 973 acetylation sites in 445 proteins were identified, among which 617 acetylation sites in 302 proteins were quantitated. The overall analysis indicated that 22.7% of proteins were acetylated. Among the quantified proteins in SMB, the acetylation degree of lysine in 56 sites increased, while that of lysine decreased in 52 sites. In the acetylome of S. mutans, six significantly enriched motifs were identified and obtained including Kac****K, KacF, Kac****R, KacY, KacH, F*Kac. In addition, KEGG pathway-based enrichment analysis indicated significant enrichments in glycolysis/gluconeogenesis, and RNA degradation. Particularly, most downregulated acetylated lysine proteins were glucosyltransferase-SI, glucosyltransferase-I, and glucosyltransferase-S in S. mutans biofilm, which probably reveals a switch-off mechanism for the regulation of glucosyltransferases function during the biofilm development.

Identification of Candidate Genes and Pathways Associated with Obesity-Related Traits in Canines via Gene-Set Enrichment and Pathway-Based GWAS Analysis.

Simple SummaryObesity is a serious health issue and is increasing at an alarming rate in several dog breeds, but there is limited information on the genetic mechanism underlying it. Moreover, there have been very few reports on genetic markers associated with canine obesity. These studies were limited to the use of a single breed in the association study. In this study, we have performed a GWAS and supplemented it with gene-set enrichment and pathway-based analyses to identify causative loci and genes associated with canine obesity in 18 different dog breeds. From the GWAS, the significant markers associated with obesity-related traits including body weight (CACNA1B, C22orf39, U6, MYH14, PTPN2, SEH1L) and blood sugar (PRSS55, GRIK2), were identified. Furthermore, the gene-set enrichment and pathway-based analysis (GESA) highlighted five enriched pathways (Wnt signaling pathway, adherens junction, pathways in cancer, axon guidance, and insulin secretion) and seven GO terms (fat cell differentiation, calcium ion binding, cytoplasm, nucleus, phospholipid transport, central nervous system development, and cell surface) which were found to be shared among all the traits.The present study aimed to identify causative loci and genes enriched in pathways associated with canine obesity using a genome-wide association study (GWAS). The GWAS was first performed to identify candidate single-nucleotide polymorphisms (SNPs) associated with obesity and obesity-related traits including body weight and blood sugar in 18 different breeds of 153 dogs. A total of 10 and 2 SNPs were found to be significantly (p < 3.74 × 10−7) associated with body weight and blood sugar, respectively. None of the SNPs were identified to be significantly associated with obesity trait. We subsequently followed up the GWAS analysis with gene-set enrichment and pathway analyses. A gene-set with 1057, 1409, and 1243 SNPs annotated to 449, 933 and 820 genes for obesity, body weight, and blood sugar, respectively was created by sub-setting the GWAS result at a threshold of p < 0.01 for the gene-set enrichment analysis. In total, 84 GO and 21 KEGG pathways for obesity, 114 GO and 44 KEGG pathways for blood sugar, 120 GO and 24 KEGG pathways for body weight were found to be enriched. Among the pathways and GO terms, we highlighted five enriched pathways (Wnt signaling pathway, adherens junction, pathways in cancer, axon guidance, and insulin secretion) and seven GO terms (fat cell differentiation, calcium ion binding, cytoplasm, nucleus, phospholipid transport, central nervous system development, and cell surface) that were found to be shared among all the traits. Our data provide insights into the genes and pathways associated with obesity and obesity-related traits.

Mechanistic insight into the progressive retinal atrophy disease in dogs via pathway-based genome-wide association analysis.

The retinal degenerative disease, progressive retinal atrophy (PRA) is a major reason of vision impairment in canine population. Canine PRA signifies an inherently dissimilar category of retinal dystrophies which has solid resemblances to human retinis pigmentosa. Even though much is known about the biology of PRA, the knowledge about the intricate connection among genetic loci, genes and pathways associated to this disease in dogs are still remain unknown. Therefore, we have performed a genome wide association study (GWAS) to identify susceptibility single nucleotide polymorphisms (SNPs) of PRA. The GWAS was performed using a case–control based association analysis method on PRA dataset of 129 dogs and 135,553 markers. Further, the gene-set and pathway analysis were conducted in this study. A total of 1,114 markers associations with PRA trait at p < 0.01 were extracted and mapped to 640 unique genes, and then selected significant (p < 0.05) enriched 35 gene ontology (GO) terms and 5 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways contain these genes. In particular, apoptosis process, homophilic cell adhesion, calcium ion binding, and endoplasmic reticulum GO terms as well as pathways related to focal adhesion, cyclic guanosine monophosphate)-protein kinase G signaling, and axon guidance were more likely associated to the PRA disease in dogs. These data could provide new insight for further research on identification of potential genes and causative pathways for PRA in dogs.

Pathway-Based Integrative Analysis of Metabolome and Microbiome Data from Hepatocellular Carcinoma and Liver Cirrhosis Patients.

Simple SummaryHepatocellular carcinoma (HCC) is one of the diseases associated with human microbiome. The human microbiome is known to affect human disease through the metabolites. The aim of this study was to identify the pathways associated with HCC by integrating microbiome and metabolomic data via a novel pathway-based integrative method named HisCoM-MnM representing Hierarchical structural Component Model for pathway analysis of Microbiome and Metabolome. Application of HisCoM-MnM to datasets from HCC and liver cirrhosis (LC) patients successfully identified HCC-related pathways related to cancer metabolic reprogramming along with the significant metabolome and metagenome that make up those pathways.Aberrations of the human microbiome are associated with diverse liver diseases, including hepatocellular carcinoma (HCC). Even if we can associate specific microbes with particular diseases, it is difficult to know mechanistically how the microbe contributes to the pathophysiology. Here, we sought to reveal the functional potential of the HCC-associated microbiome with the human metabolome which is known to play a role in connecting host phenotype to microbiome function. To utilize both microbiome and metabolomic data sets, we propose an innovative, pathway-based analysis, Hierarchical structural Component Model for pathway analysis of Microbiome and Metabolome (HisCoM-MnM), for integrating microbiome and metabolomic data. In particular, we used pathway information to integrate these two omics data sets, thus providing insight into biological interactions between different biological layers, with regard to the host’s phenotype. The application of HisCoM-MnM to data sets from 103 and 97 patients with HCC and liver cirrhosis (LC), respectively, showed that this approach could identify HCC-related pathways related to cancer metabolic reprogramming, in addition to the significant metabolome and metagenome that make up those pathways.

CFTR Modulator Therapy Enhances Peripheral Blood Monocyte Contributions to Immune Responses in People With Cystic Fibrosis.

BackgroundCFTR modulators decrease some etiologies of CF airway inflammation; however, data indicate that non-resolving airway infection and inflammation persist in individuals with CF and chronic bacterial infections. Thus, identification of therapies that diminish airway inflammation without allowing unrestrained bacterial growth remains a critical research goal. Novel strategies for combatting deleterious airway inflammation in the CFTR modulator era require better understanding of cellular contributions to chronic CF airway disease, and how inflammatory cells change after initiation of CFTR modulator therapy. Peripheral blood monocytes, which traffic to the CF airway, can develop both pro-inflammatory and inflammation-resolving phenotypes, represent intriguing cellular targets for focused therapies. This therapeutic approach, however, requires a more detailed knowledge of CF monocyte cellular programming and phenotypes.Material and MethodsIn order to characterize the inflammatory phenotype of CF monocytes, and how these cells change after initiation of CFTR modulator therapy, we studied adults (n=10) with CF, chronic airway infections, and the CFTR-R117H mutations before and 7 days after initiation of ivacaftor. Transcriptomes of freshly isolated blood monocytes were interrogated by RNA-sequencing (RNA-seq) followed by pathway-based analyses. Plasma concentrations of cytokines and chemokines were evaluated by multiplex ELISA.ResultsRNAseq identified approximately 50 monocyte genes for which basal expression was significantly changed in all 10 subjects after 7 days of ivacaftor. Of these, the majority were increased in expression post ivacaftor, including many genes traditionally associated with enhanced inflammation and immune responses. Pathway analyses confirmed that transcriptional programs were overwhelmingly up-regulated in monocytes after 7 days of ivacaftor, including biological modules associated with immunity, cell cycle, oxidative phosphorylation, and the unfolded protein response. Ivacaftor increased plasma concentrations of CXCL2, a neutrophil chemokine secreted by monocytes and macrophages, and CCL2, a monocyte chemokine.ConclusionsOur results demonstrate that ivacaftor causes acute changes in blood monocyte transcriptional profiles and plasma chemokines, and suggest that increased monocyte inflammatory signals and changes in myeloid cell trafficking may contribute to changes in airway inflammation in people taking CFTR modulators. To our knowledge, this is the first report investigating the transcriptomic response of circulating blood monocytes in CF subjects treated with a CFTR modulator.

Abstract 1315: Identification of actionable targets in advanced cancer patients from circulating tumor DNA using clinical decision support platforms

Abstract BACKGROUND: We are entering exciting times in precision oncology, with next-generation sequencing enabling the individualized screening of multiple patient- and tumor-specific genomic and transcriptomic changes. As new molecular information flows into the clinic, the pursuit of innovative targeted therapies and defining the actionable genome are at the forefront. The amount of molecular information, much of it of unknown clinical relevance, has rendered the interpretation of detected aberrations a daunting task for clinical geneticists and oncologists alike. In this regard, several clinical decision support platforms have emerged on the market and need to be validated before implementation in routine clinical care of advanced cancer patients. METHODS: Here, we present a retrospective, descriptive study in adult patients with solid tumors using plasma DNA for the identification of actionable targets. We generated genomic profiles of 48 selected patients with advanced breast (BC), colorectal (CRC) and non-small cell lung cancer (NSCLC; samples selected had tumor fraction under 5%) using shallow whole-genome sequencing in parallel to the AVENIO ctDNA Expanded Panel, which covers 77 genes spanning 192kb. Somatic copy number alterations (SCNAs) and somatic variants were annotated for pathogenicity and subsequently matched to therapies using the following clinical decision support platforms: NAVIFY Mutation Profiler (NMP, Roche), CureMatch BIONOV (CureMatch) and QCI Interpret (QCI-I, Qiagen). We assessed the various features of each tool, correlated genomic features with actionable targets, compared genomic characteristics between tumor entities and evaluated the alignment of treatment recommendations. RESULTS: Tumor fraction in plasma DNA was highest in patients with BC (24.95% [range 10.52-48.93]) compared to CRC (14.94% [range 4.07-54.69]) and NSCLC (4.46% [range 1.63-45.42]) patients, whereas fraction genome altered was highest in CRC (median FGA = 0.289). Of the total reported aberrations per patient, both CureMatch and NMP identified the highest median percent actionability in CRC patients, whereas NSCLC had the highest actionability according to QCI-I. The total number of matching clinical trials was highest in CRC patients across platforms. CureMatch, a pathway-based analysis, suggested ranked combination therapies to target the entire molecular profile. CONCLUSIONS: This study seeks to provide insight into alternative treatment options and available clinical trials which were possibly previously overlooked due to incomplete molecular knowledge of the patient's tumor. These analyses may prove extremely valuable for increasing oncologists' confidence in and efficiency of employing molecular cancer diagnostics in a routine setting, in turn increasing clinicians' ability to use genomics-guided personalized cancer therapy when deciding on treatments in the future. Citation Format: Samantha O. Perakis, Sabrina Weber, Ricarda Graf, Qing Zhou, Jakob M. Riedl, Nadia Dandachi, Marija Balic, Armin Gerger, Ed Schuuring, Harry J. Groen, Jochen B. Geigl, Michael R. Speicher, Ellen Heitzer. Identification of actionable targets in advanced cancer patients from circulating tumor DNA using clinical decision support platforms [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1315.

An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia

AbstractTargeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

Genetic variants in NECTIN4 encoding an adhesion molecule are associated with continued opioid use.

Methadone is a synthetic opioid used as maintenance treatment for patients addicted to heroin. Skin irritation is one of the adverse events caused by opioid use. 344 methadone maintenance treatment (MMT) patients were recruited with records and measurements on methadone dose, plasma methadone concentrations, and treatment emergent symptom scales (TESS). 15 patients reported with skin irritation. Five SNPs located within the NECTIN4 genetic region were genotyped. The NECTIN4 gene within the adherens junction interaction pathway was associated with methadone dose in pathway-based genome wide association analyses (P = 0.0008). Three highly-linked SNPs, rs11265549, rs3820097, and rs4656978, were significantly associated with methadone dose (P = 0.0003), plasma concentrations of R,S-methadone (P = 0.0004) and TNF-α (P = 0.010) in all 344 MMT patients, and with self-report skin irritation symptom scores (P = 0.010) in the 15 MMT patients who reported with skin irritation. To identify the possible roles of plasma level of Nectin-4 in the responses to MMT and opioid use, additional age- and gender-matched 51 controls and 83 methadone-free abstinent former heroin users were recruited. Plasma level of Nectin-4 was the highest in MMT patients among the three groups. The results suggest involvement of genetic variants on NECTIN4 in methadone dose. Plasma Nectin-4 level is likely an indicator for continued use of opioids.

ScTPA: a web tool for single-cell transcriptome analysis of pathway activation signatures.

At present, a fundamental challenge in single-cell RNA-sequencing data analysis is functional interpretation and annotation of cell clusters. Biological pathways in distinct cell types have different activation patterns, which facilitates the understanding of cell functions using single-cell transcriptomics. However, no effective web tool has been implemented for single-cell transcriptome data analysis based on prior biological pathway knowledge. Here, we present scTPA, a web-based platform for pathway-based analysis of single-cell RNA-seq data in human and mouse. scTPA incorporates four widely-used gene set enrichment methods to estimate the pathway activation scores of single cells based on a collection of available biological pathways with different functional and taxonomic classifications. The clustering analysis and cell-type-specific activation pathway identification were provided for the functional interpretation of cell types from a pathway-oriented perspective. An intuitive interface allows users to conveniently visualize and download single-cell pathway signatures. Overall, scTPA is a comprehensive tool for the identification of pathway activation signatures for the analysis of single cell heterogeneity. http://sctpa.bio-data.cn/sctpa. sujz@wmu.edu.cn or yufulong421@gmail.com or zgj@zjut.edu.cn. Supplementary data are available at Bioinformatics online.

Genomic profiling identified novel prognostic biomarker in Chinsese glioma patients.

e14538 Background: Molecular charactersitcs are essential for the classification and grading of gliomas. However, majority of current understanding is based on public databases that might not accurately reflect the Asian population. Here, we studied the mutation landscape of Chinese glioma patients in hope to provide new insights for glioma prognosis and treatment. Methods: Tissue samples from 112 glioma patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Gene mutations and copy number variations were investigated for their prognostic effect using overall survival data. Pathway-based survival analysis was peformed using top ten predefined oncogenic pathways. Results: We identified similar prevalence of currently established molecular diagnostic markers of glioma, including TP53 (33%), EGFR(26%), TERT (24%), PTEN (21%), ATRX (14%), BRAF (13%) and IDH1/2 (6%). Among all genetic abberations with more than 5% occurrence rate, four mutations and four copy number gains were significantly associated with poor overall survival (univariate, P &lt; 0.05). Of these, TERT mutations (hazard ratio [HR], 3.14; 95% confidence interval [CI], 1.31 to 7.49; P = 0.01) and EGFR amplification (HR, 2.67; 95% CI, 1.20 to 5.95; P = 0.02) remained significant after adjusting for clinical parameters. Similarly, PIK3CA mutations, which was also frequently mutated in glioma but not used for clinical classification, were found to correlate with poor prognosis (HR, 2.61; 95% CI, 1.19 to 5.74; P = 0.02). Additionally, we have also identified MCL1 amplification as a potential novel biomarker for glioma (HR, 2.73; 95% CI, 1.47 to 5.07; P &lt; 0.001), which was seldom reported in the TCGA database and might possibly be ancestral specific giving its high prevelance in our cohort (found in 32% patients). Pathway analyses revealed significantly worse prognosis with abnormal PI3K (HR, 1.81; 95% CI, 1.12 to 2.95; P = 0.02) and cell cycle pathways (HR, 2.04; 95% CI, 1.2 to 3.47; P &lt; 0.001), both of which stayed meaningful after adjusting for clinical factors. Conclusions: In this study, we discovered PIK3CA mutations and MCL1 amplification as novel prognostic markers of glioma. We also demonstrated shorter survival with abnormal PI3K and cell cycle pathways that provided an intergrative understanding of glioma.

Whole exome sequencing in patients with Williams–Beuren syndrome followed by disease modeling in mice points to four novel pathways that may modify stenosis risk

Supravalvular aortic stenosis (SVAS) is a narrowing of the aorta caused by elastin (ELN) haploinsufficiency. SVAS severity varies among patients with Williams-Beuren syndrome (WBS), a rare disorder that removes one copy of ELN and 25-27 other genes. Twenty percent of children with WBS require one or more invasive and often risky procedures to correct the defect while 30% have no appreciable stenosis, despite sharing the same basic genetic lesion. There is no known medical therapy. Consequently, identifying genes that modify SVAS offers the potential for novel modifier-based therapeutics. To improve statistical power in our rare-disease cohort (N = 104 exomes), we utilized extreme-phenotype cohorting, functional variant filtration and pathway-based analysis. Gene set enrichment analysis of exome-wide association data identified increased adaptive immune system variant burden among genes associated with SVAS severity. Additional enrichment, using only potentially pathogenic variants known to differ in frequency between the extreme phenotype subsets, identified significant association of SVAS severity with not only immune pathway genes, but also genes involved with the extracellular matrix, G protein-coupled receptor signaling and lipid metabolism using both SKAT-O and RQTest. Complementary studies in Eln+/-; Rag1-/- mice, which lack a functional adaptive immune system, showed improvement in cardiovascular features of ELN insufficiency. Similarly, studies in mixed background Eln+/- mice confirmed that variations in genes that increase elastic fiber deposition also had positive impact on aortic caliber. By using tools to improve statistical power in combination with orthogonal analyses in mice, we detected four main pathways that contribute to SVAS risk.

Genome-wide association study identifies zonisamide responsive gene in Parkinson\u2019s disease patients

Long-term treatment of Parkinson’s disease (PD) by levodopa leads to motor complication “wearing-off”. Zonisamide is a nondopaminergic antiparkinsonian drug that can improve “wearing-off” although response to the treatment varies between individuals. To clarify the genetic basis of zonisamide responsiveness, we conducted a genome-wide association study (GWAS) on 200 PD patients from a placebo-controlled clinical trial, including 67 responders whose “off” time decreased ≥1.5 h after 12 weeks of zonisamide treatment and 133 poor responders. We genotyped and evaluated the association between 611,492 single nucleotide polymorphisms (SNPs) and “off” time reduction. We also performed whole-genome imputation, gene- and pathway-based analyses of GWAS data. For promising SNPs, we examined single-tissue expression quantitative trait loci (eQTL) data in the GTEx database. SNP rs16854023 (Mouse double minute 4, MDM4) showed genome-wide significant association with reduced “off” time (PAdjusted = 4.85 × 10−9). Carriers of responsive genotype showed >7-fold decrease in mean “off” time compared to noncarriers (1.42 h vs 0.19 h; P = 2.71 × 10−7). In silico eQTL data indicated that zonisamide sensitivity is associated with higher MDM4 expression. Among the 37 pathways significantly influencing “off” time, calcium and glutamate signaling have also been associated with anti-epileptic effect of zonisamide. MDM4 encodes a negative regulator of p53. The association between improved motor fluctuation and MDM4 upregulation implies that p53 inhibition may prevent dopaminergic neuron loss and consequent motor symptoms. This is the first genome-wide pharmacogenetics study on antiparkinsonian drug. The findings provide a basis for improved management of “wearing-off” in PD by genotype-guided zonisamide treatment.

Exome-Wide Association Study Reveals Several Susceptibility Genes and Pathways Associated With Acute Coronary Syndromes in Han Chinese.

Genome-wide association studies have identified more than 150 susceptibility loci for coronary artery disease (CAD); however, there is still a large proportion of missing heritability remaining to be investigated. This study sought to identify population-based genetic variation associated with acute coronary syndromes (ACS) in individuals of Chinese Han descent. We proposed a novel strategy integrating a well-developed risk prediction model into control selection in order to lower the potential misclassification bias and increase the statistical power. An exome-wide association analysis was performed for 1,669 ACS patients and 1,935 healthy controls. Promising variants were further replicated using the existing in silico dataset. Additionally, we performed gene- and pathway-based analyses to investigate the aggregate effect of multiple variants within the same genes or pathways. Although none of the association signals were consistent across studies after Bonferroni correction, one promising variant, rs10409124 at STRN4, showed potential impact on ACS in both European and East Asian populations. Gene-based analysis explored four genes (ANXA7, ZNF655, ZNF347, and ZNF750) that showed evidence for association with ACS after multiple test correction, and identification of ZNF655 was successfully replicated by another dataset. Pathway-based analysis revealed that 32 potential pathways might be involved in the pathogenesis of ACS. Our study identified several candidate genes and pathways associated with ACS. Future studies are needed to further validate these findings and explore these genes and pathways as potential therapeutic targets in ACS.

HisCoM-PCA: software for hierarchical structural component analysis for pathway analysis based using principal component analysis.

In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

Analyzing Genome-Wide Association Study Dataset Highlights Immune Pathways in Lip Bone Mineral Density.

Osteoporosis is a common complex human disease. Until now, large-scale genome-wide association studies (GWAS) using single genetic variant have reported some novel osteoporosis susceptibility variants. However, these risk variants only explain a small proportion of osteoporosis genetic risk, and most genetic risk is largely unknown. Interestingly, the pathway analysis method has been used in investigation of osteoporosis mechanisms and reported some novel pathways. Until now, it remains unclear whether there are other risk pathways involved in BMD. Here, we selected a lip BMD GWAS with 301,019 SNPs in 5,858 Europeans, and conducted a gene-based analysis (SET SCREEN TEST) and a pathway-based analysis (WebGestalt). On the gene level, BMD susceptibility genes reported by previous GWAS were identified to be the top 10 significant signals. On the pathway level, we identified 27 significant KEGG pathways. Three immune pathways including T cell receptor signaling pathway (hsa04660), complement and coagulation cascades (hsa04610), and intestinal immune network for IgA production (hsa04672) are ranked the top three significant signals. Evidence from the PubMed and Google Scholar databases further supports our findings. In summary, our findings provide complementary information to these nine risk pathways.

Abstract P460: Genetic Risk for Obesity Across the Transition From Young to Older Adulthood: A Pathway Based Analysis

Background: Genetics and lifestyle behaviors are key contributors to obesity. However, few studies explicitly examine the differential genetic association with BMI across critical lifecycle periods between young adulthood and later adulthood. Hypothesis: We anticipate that genetic risk will be directly associated with BMI in young adulthood and there will be a strong indirect association with BMI later in life, as a result the increased risk of BMI associated with young adulthood. Methods: For 7,397 Chinese adult participants (age 18 to 65y) of the China Health and Nutrition Survey (CHNS; 1991-2015), we calculated an obesity polygenic risk score (PRS) based on BMI-related SNPs selected from the largest BMI GWAS in 700,000 individuals of European ancestry from UK biobank and GIANT consortium, weighted by effect size estimated from the GWAS study. We used linear mixed models to estimate BMI across all periods of adulthood, adjusting for calendar time and sex. In a subsample of participants with three measurements across 24 years (n=1220), we used pathway based analysis to estimate the direct effects of genetic risk in association with BMI during young (18-35y), middle (35-45y), and later (45-65y) adulthood as well as the indirect genetic effects of at later adulthood through BMI at each of these earlier periods in life. Results: In the full sample, the linear mixed model-adjusted mean BMI (Standard Error (SE)) was 22.4 (0.04) kg/m 2 at young adulthood, 23.1 (0.04) kg/m 2 at middle adulthood and 23.2 (0.04) kg/m 2 at later adulthood, adjusting for sex and calendar year. In the subsample, a one standard deviation higher obesity PRS was directly associated with a 0.38 (0.07 SE) and 0.21 (0.06 SE) kg/m 2 higher BMI in young and middle adulthood, respectively. We found no evidence of a direct estimated effect of PRS in later adulthood (age 45-64y), but evidence of an indirect association between obesity PRS and BMI in later adulthood (age 45-64y). For example, we found a one standard deviation higher PRS was indirectly associated with 0.31 (0.06 SE) kg/m 2 higher BMI at age 35-45y through BMI at age 18-35y, and a 0.25 (0.05 SE) kg/m 2 higher BMI at age 45-65y through BMI at age 18-35y and subsequently BMI at age 35-45y. Conclusion: We observed a strong direct association between polygenic risk for obesity in young adulthood (age 18-35y), with persistence through age 35-45y and into age 45-65y.

A multiscale approach reveals regulatory players of water stress responses in seeds during germination.

Seed germination is regulated by environmental factors, particularly water availability. Water deficits at the time of sowing impair the establishment of crop plants. Transcriptome and proteome profiling was used to document the responses of sunflower (Helianthus annuus) seeds to moderate water stress during germination in two hybrids that are nominally classed as drought sensitive and drought tolerant. Differences in the water stress-dependent accumulation reactive oxygen species and antioxidant enzymes activities were observed between the hybrids. A pathway-based analysis of the hybrid transcriptomes demonstrated that the water stress-dependent responses of seed metabolism were similar to those of the plant, with a decreased abundance of transcripts encoding proteins associated with metabolism and cell expansion. Moreover, germination under water stress conditions was associated with increased levels of transcripts encoding heat shock proteins. Exposure of germinating seeds to water stress specifically affected the abundance of a small number of proteins, including heat shock proteins. Taken together, these data not only identify factors that are likely to play a key role in drought tolerance during seed germination, but they also demonstrate the importance of the female parent in the transmission of water stress tolerance.

Abstract P4-07-05: Matched germline and tumor profiling in male breast cancer for the discovery of molecular subtypes with clinical relevance

Abstract Background: Breast cancer (BC) in men is a rare disease, but morbidity and mortality in male BC (MBC) patients is a serious concern. Because of its rarity, to date, clinical management of men with BC has been informed almost entirely by female BC research. However, BC in men and women may behave differently. Inherited mutations in homologous recombination (HR) genes, mainly BRCA1,BRCA2 and PALB2, play a major role in MBC predisposition. MBCs associated with mutations in HR gene are likely to represent a subgroup of tumors with a peculiar tumor phenotype. Here, we performed a transcriptome analysis of MBCs characterized for germline mutations in HR genes in order to provide insight into underlying HR pathways and characterize distinct molecular subtypes of MBC with possible clinical relevance. Materials and methods: MBC cases were selected to include cases with and without germline mutations in HR genes. Tumor samples with pathology and outcome data were selected within the Italian multicenter study on MBC that comprises 750 MBCs with information on germline mutations in 50 cancer-related genes. To enrich the series of MBC cases with germline mutations in HR genes, tumor samples from kConFab were also included. Overall, 63 tumor samples, including 26 cases with germline mutations in HR genes (BRCA2, BRCA1, PALB2, RAD50 and RAD51D) and 37 without germline mutations, were analyzed. Whole transcriptome data were obtained by RNA-sequencing using Illumina technology. A bioinformatic pipeline including FastQC tool for quality control, STAR for alignment, RSeQC-FPKM for counting reads, DESeq2 package for differential expression and DAVID for enrichment, was used. Tumor immunophenotype was evaluated using CIBERSORT, which accurately determines the fraction of 22 immune cell types. Statistical analyses were performed using Fisher exact test, t-test and log-rank test as appropriate. Results: A total of 724 differentially expressed genes, of which 355 up-regulated and 369 down-regulated, emerged between MBC cases with and without germline mutations in HR genes. Pathway-based analyses revealed different transcriptome profiles for genes involved in key biological processes, including translational initiation, cell cycle, DNA damage and repair. A higher fraction of activated CD4 memory T cells was observed in tumors with germline mutations in HR genes compared to those without mutations (p=0.04). Unsupervised clustering approach, based on the 2000 most variable transcripts among tumors, revealed two distinct subgroups with different biologic features and clinical outcome. In particular, tumors in subgroup 1 showed higher expression of genes involved in cell proliferation, were enriched for cases with germline mutations in HR genes (p=0.03), had lymph node involvement (p=0.04) and displayed a trend toward worse overall survival (p=0.09), when compared to tumors in subgroup 2. Conclusions: Integration of matched germline and tumor profiling seem to be a valuable approach for the identification of biologically and clinically relevant subtypes of MBC. Germline mutations in HR genes could impact on MBC transcriptome, defining molecular subgroups with peculiar biological features. Overall, these results may help to improve the clinical managements of MBC patients. Study supported by AIRC (IG 21389) to L.O. Citation Format: Veronica Zelli, Valentina Silvestri, Virginia Valentini, Agostino Bucalo, Piera Rizzolo, Ines Zanna, Laura Cortesi, Daniele Calistri, Maria Grazia Tibiletti, Giuseppe Giannini, Stephen B Fox, Domenico Palli, Laura Ottini. Matched germline and tumor profiling in male breast cancer for the discovery of molecular subtypes with clinical relevance [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-07-05.