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• eMERGE Geisinger eGenomic Medicine (GeM) Abdominal Aortic Aneurysm Project (AAAP)

  A large research cohort of Geisinger Abdominal Aortic Aneurysm (AAA) patients was created by enrolling and consenting patients of the Geisinger Department of Vascular Surgery. Consented patients provide blood, serum and DNA samples for research and authorize use of data in their medical record for research. They also complete a data questionnaire that asks information about family history of AAA and other vascular diseases, as well as information on known or suspected AAA risk factors, including smoking history, body mass index, hypertension, type 2 diabetes, and atherosclerotic disease. The AAA cases are 78% male, with a mean age of 74 years; 39% have undergone surgical or endovascular repair; more than 85% or current or past smokers; approximately 20% of cases report a positive family history of AAA. Geisinger AAA patients undergo regular imaging studies, typically every 6 months, to monitor the progression of aneurysm expansion. This allows the growth rates of their aneurysm to be calculated. DNA samples from a total of 910 AAA patients were used for whole genome genotyping; these results are included in the dbGaP.

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• Estrogen Receptor Positive Breast Cancer: Aromatase Inhibitor Response Study

  Highly variable outcomes are observed in patients with estrogen receptor positive (ER+) breast cancer who undergo preoperative estrogen deprivation therapy with aromatase inhibitors (AI). In this study, 46 baseline tumor and normal genomes and 31 baseline tumor/normal exomes of participants selected from two clinical trials of neoadjuvant AI therapy on ER+ breast cancer were sequenced to identify somatic alterations that correlate with response to AI, to screen for therapeutic targets and to elucidate the genetic landscape of ER+ breast cancer. From the same set of patients we later performed deep genomic characterization of a subset of matched primary tumors after four months of AI therapy, generating comprehensive information about the range of changes that occur when ER+ breast cancers are subjected to estrogen deprivation. This data includes whole genome sequence and transcriptome data. To better understand tumor heterogeneity and the evolution of resistance to estrogen-deprivation therapy, a subset of these tumours, along with 38 additional cases were sequenced to greater depth using targeted capture with a gene panel.

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• Single-Cell DNA and RNA Sequencing over A 29-Year Period of A CLL Patient Demonstrating Evolution of Multiple Cell Clones

  Chronic lymphocytic leukemia (CLL) is a frequent B-cell malignancy characterized by recurrent somatic chromosome alterations and a low level of point mutations. Here we present single nucleotide polymorphism (SNP) microarray analyses of a single CLL patient over 29-years of observation and treatment, and transcriptome and whole genome sequencing at selected timepoints. We identified chromosome alterations of 13q14-, 6q- and 12q+ in early cell clones, elimination of clonal populations following therapy, and subsequent appearance of a clone containing trisomy 12 and a chromosome 10 copy neutral loss of heterogeneity (LOH) that marks a major population dominant at death. Serial single cell RNA sequencing revealed elevated mRNA expression of the FOS, JUN and KLF4 genes just before the appearance of acute disease requiring therapy. This gene expression pattern became undetectable following therapy, but reoccurred following relapse. Transcriptome evolution indicates that complex expression changes occur over time. In conclusion, CLL can evolve gradually during indolent phases, and undergo rapid changes following therapy.

  Study phs001181

• The Cardiopulmonary Effects of Particulate Exposure

  The study was initially designed as a longitudinal cohort study of cardiovascular effects of particulate exposure. Participants were boilermaker construction workers who were exposed to particulate matter (PM) component (e.g. a focus on metal constituents) while performing welding, grinding or cutting work in the welding plants. Participants were followed up approximately half a year for a non-work day and a work day from 1999 to 2012, and blood, urine, blood pressure, as well as real-time PM2.5 samples were collected from each participant. In this specific study, we conducted epigenome-wide DNA methylation profiling through Center for Inherited Disease Research (CIDR) services using Illumina Infinium HumanMethylation450, which will give us more compete epigenome-wide coverage. Genome-wide DNA methylation was carried out on paired samples pre- and post-work shift at a welding apprentice school. With transcriptomic and metabolomic data already generated from the same panel study, we will be able to conduct integrative analysis to gain insights into mechanisms of gene-metal interactions and maximize the probability of finding genes functionally relevant to PM-induced adverse cardiovascular outcomes.

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• CPTAC: Microscaled Proteogenomic Methods for Precision Oncology

  Cancer proteogenomics combines genomics, transcriptomics and mass spectrometry-based proteomics to gain insights into cancer biology and treatment outcomes. To promote clinical investigation, we developed a "microscaled" proteogenomics approach for tumor-rich frozen core needle biopsies. Tissue-sparing specimen processing ("Biopsy Trifecta EXTraction", BioTExt) and microscaled proteomics (MiProt) generated deep-scale proteogenomics datasets. As a proofof- concept, biopsies were accrued from ERBB2 positive (ERBB2+) breast cancers before and 48 to 72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy. Multi-omics comparisons were conducted between samples associated with residual disease versus complete pathological response (pCR). Integrated analyses diagnosed diverse molecular causes of treatmentresistance including: 1) absence of ERBB2 amplification (false-ERBB2&#43); 2) insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2&#43); 3) resistance features in true-ERBB2+ cases including androgen receptor signaling, mucin expression and an inactive immune microenvironment; 4) lack of acute phospho-ERBB2 down-regulation in nonpCR cases. We conclude microscaled cancer proteogenomics could improve diagnostic precision.

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• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

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• NHLBI GO-ESP: Family Studies (Dilated Cardiomyopathy)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The goals for this project are to conduct exome sequencing for novel dilated cardiomyopathy (DCM) gene discovery in families with DCM. These families have already been sequenced for 15 DCM genes, accounting for approximately 75% of known genetic cause, without rare coding variants identified.

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• Epigenome Wide DNA Methylation Study for Osteoporosis Risk

  Osteoporosis is characterized by low bone mineral density (BMD). The advancement of high-throughput technologies and integrative approaches provided an opportunity for deciphering the mechanisms underlying osteoporosis. In this study, we generated genomic (from whole blood DNA), transcriptomic and methylomic (from peripheral blood monocytes, PBMs), and serum metabolomic datasets from 143 premenopausal Caucasian females aged 25-40 years, including 74 with relatively high hip BMD (Z scores ≥ 0.8) and 69 with relatively low hip BMD (Z scores ≤ -0.8). The BMD Z score was defined as the number of standard deviations a subject's BMD differed from the mean BMD of their age-, gender-, and ethnicity-matched population. We identified differentially methylated CpG sites (DMCs) in peripheral blood monocytes (PBMs) at the whole methylome level between premenopausal women with high BMD and those with low BMD and deciphered how the DMCs influence the BMD variation through affecting the expression of the relevant genes. We also performed differential gene expression and metabolic analysis to assess their biological interaction and causal mechanisms. Our study provided novel insights into the pathogenesis of osteoporosis.

  Study phs001960

• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

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• Circulating, Cell-Free DNA Methylation Patterns Indicate Cellular Sources of Allograft Injury after Liver Transplant

  Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed longitudinal blood samples collected from patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to an atlas of cell-type-specific DNA methylation patterns derived from 476 methylomes of purified cells. For liver cell types, DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and regulatory regions functionally important for the respective cell types. We find that multi-tissue cellular damage post-transplant recovers in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA within the first month indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and timely intervention.

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