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A Systems Approach to Personalized Medicine


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Talk and Discussion
Mountain View, CA

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A Systems Approach to Personalized Medicine

  1. 1. “A Systems Approach to Personalized Medicine” Talk and Discussion NASA Ames Mountain View, CA March 28, 2013 Dr. Larry SmarrDirector, California Institute for Telecommunications and Information Technology Harry E. Gruber Professor, Dept. of Computer Science and Engineering 1 Jacobs School of Engineering, UCSD
  2. 2. From One to a Billion Data Points Defining Me:The Exponential Rise in Body Data in Just One Decade! Billion:Microbial Genome My Full DNA, MRI/CT Images Improving Body SNPs Million: My DNA SNPs, Zeo, FitBit Discovering Disease Blood Variables One: Hundred: My Blood Variables Weight Weight My
  3. 3. From Measuring Macro-Variablesto Measuring Your Internal Variables
  4. 4. Visualizing Time Series of150 LS Blood and Stool Variables, Each Over 5 Years Calit2 64 megapixel VROOM
  5. 5. Only One of My Blood MeasurementsWas Far Out of Range--Indicating Chronic Inflammation 27x Upper Limit Episodic Peaks in Inflammation Followed by Spontaneous Drops Antibiotics Antibiotics Normal Range<1 mg/L Normal Complex Reactive Protein (CRP) is a Blood Biomarker for Detecting Presence of Inflammation
  6. 6. High Values of Lactoferrin (Shed from Neutrophils)From Stool Sample Suggested Inflammation in Colon 124x Upper Limit Typical Lactoferrin Value for Stool Samples Analyzed Active by IBD Antibiotics Antibiotics Normal Range <7.3 µg/mL Lactoferrin is a Sensitive and Specific Biomarker for Detecting Presence of Inflammatory Bowel Disease (IBD)
  7. 7. High Lactoferrin Biomarker Led Me to Hypothesis I Had Inflammatory Bowel Disease (IBD) IBD is an Autoimmune Disease Which Comes in Two Subtypes: Crohn’s and Ulcerative Colitis Scand J Gastroenterol. 42, 1440-4 (2007) My Values May 2011 My Values 2009-10 Colonoscopy Revealed Inflamed Tissue
  8. 8. Colonoscopy Images Show Sigmoid Colon InflammationDec 2010 May 2011
  9. 9. Confirming the IBD (Crohn’s) Hypothesis: Finding the “Smoking Gun” with MRI Imaging Liver I Obtained the MRI Slices Transverse Colon From UCSD Medical Services and Converted to Interactive 3D Working With Small Intestine Calit2 Staff & DeskVOX Software Descending Colon MRI Jan 2012Cross Section Diseased Sigmoid Colon Major Kink Sigmoid Colon Threading Iliac Arteries
  10. 10. Comparison of DeskVOX with Clinical MRI Slice Program
  11. 11. An MRI Shows Sigmoid Colon Wall ThickenedIndicating Probable Diagnosis of Crohn’s Disease
  12. 12. Why Did I Have an Autoimmune Disease like IBD? Despite decades of research, the etiology of Crohns disease remains unknown. Its pathogenesis may involve a complex interplay between host genetics, immune dysfunction, and microbial or environmental factors. --The Role of Microbes in Crohns Disease So I Set Out to Quantify All Three! Paul B. Eckburg & David A. Relman Clin Infect Dis. 44:256-262 (2007) 
  13. 13. I Wondered if Crohn’s is an Autoimmune Disease, Did I Have a Personal Genomic Polymorphism? From Polymorphism in Interleukin-23 Receptor Gene — 80% Higher Risk ATG16L1 of Pro-inflammatory Immune Response IRGM NOD2 SNPs Associated with CD Now Comparing 163 Known IBD SNPs with 23andme SNP Chip
  14. 14. Four Immune Biomarkers Over Time Compared with Four Signs/Symptoms Gut Microbiome Samples1/2009 1/2010 1/2011 1/2012 1/2013 Here Immune biomarkers are normalized 0 to 1, with 1 being the highest value in five years Source: Photo of Calit2 64-megapixel VROOM
  15. 15. However, Most Biological Diversity on Earth is in the Microbial World You Are Here So You Have Many Phyla of Microbes Within You! Source: Carl Woese, et al
  16. 16. Cultured Bacteria From Stool TestsShowed Large Time Variations in Gut Microbiome 16 = All 4 at Full Strength Antibiotics Antibiotics Antibiotics: Levaquin & Metronidaloze Values From stool test
  17. 17. But How Can You Determine Which Microbes Are Within You? “The emerging fieldNRC Report: of metagenomics, where the DNA of entireMetagenomic communities of microbes data should is studied simultaneously, be made presents the greatest opportunity publicly -- perhaps since the invention of available in the microscope –international to revolutionize understanding of archives as the microbial world.” – rapidly as possible. National Research Council March 27, 2007
  18. 18. Intense Scientific Research is Underwayon Understanding the Human Microbiome June 8, 2012 June 14, 2012 From Culturing Bacteria to Sequencing Them
  19. 19. To Map My Gut Microbes, I Sent a Stool Sample to the Venter Institute for Metagenomic Sequencing Sequencing Shipped Stool Sample Funding Provided by December 28, 2011 UCSD School of Health Sciences I Received a Disk Drive April 3, 2012 With 35 GB FASTQ Files Weizhong Li, UCSD NGS Pipeline: 230M Reads Only 0.2% Human Required 1/2 cpu-yr Per Person Analyzed! Gel Image of Extract from Smarr Sample-Next is Library Construction Manny Torralba, Project Lead - Human Genomic Medicine J Craig Venter Institute January 25, 2012
  20. 20. We Used Weizhong Li Group’s Metagenomic Computational NextGen Sequencing Pipeline Reads QC Raw reads Raw reads HQ reads: HQ reads: Bowtie/BWA against Bowtie/BWA against Filter human Human genome and Human genome and mRNAs mRNAs Filtered reads Filtered reads Filter duplicate CD-HIT-Dup CD-HIT-Dup For single or PE reads For single or PE reads Unique reads Unique reads FR-HIT against FR-HIT against Non-redundant Read recruitment Filter errors Cluster-based Cluster-based Non-redundantmicrobial genomes Denoising Denoising microbial genomes Further filtered Further filtered Taxonomy binning Taxonomy binning Velvet, Velvet, reads reads SOAPdenovo, SOAPdenovo, FRV Assemble Abyss Abyss ------- ------- Contigs K-mer setting K-mer setting Visualization Visualization Contigs Mapping BWA Bowtie BWA Bowtie Contigs with ORF-finder Contigs with ORFs Abundance Megagene ORFs Abundance tRNA-scan Pfam Pfam Cd-hit at 95% Tigrfam rRNA - HMM Hmmer Tigrfam Non redundant COG COG Non redundant RPS-blast tRNAs tRNAs ORFs KOG KOG ORFs blast rRNAs rRNAs PRK PRK Cd-hit at 60% KEGG KEGG eggNOG eggNOG Core ORF clusters Core ORF clusters Cd-hit at 30% 1e-6 Function Function Pathway Pathway Protein families Protein families Annotation Annotation PI: (Weizhong Li, UCSD): NIH R01HG005978 (2010-2013, $1.1M)
  21. 21. Computations Reveal Gut Microbial Phyla Abundance: LS, Crohn’s, UC, and Healthy Subjects Source: Weizhong Li, UCSD; Calit2 FuturePatient ExpeditionLS Crohn’s Ulcerative Healthy Colitis Bacterial Phyla Toward Noninvasive Microbial Ecology Diagnostics
  22. 22. We Used SDSC’s Gordon Data-Intensive Supercomputer to Analyze JCVI Sequences of LS Gut Microbiome• Analyzed Healthy and IBD Patients: Venter Sequencing of – LS, 13 Crohns Disease & LS Gut Microbiome: 230 M Reads 11 Ulcerative Colitis Patients, 101 Bases Per Read + 150 HMP Healthy Subjects 23 Billion DNA Bases• Gordon Compute Time – ~1/2 CPU-Year Per Sample – > 200,000 CPU-Hours so far Enabled by• Gordon RAM Required a Grant of Time – 64GB RAM for Most Steps on Gordon from – 192GB RAM for Assembly SDSC Director Mike Norman• Gordon Disk Required – 8TB for All Subjects – Input, Intermediate and Final Results
  23. 23. Analysis of Clusters of Orthologous Groups (COGs) - Gene Family Distribution in LS Gut Microbiome Analysis: Weizhong Li & Sitao Wu, UCSD
  24. 24. Using Calit2’s 64 Megapixel Tiled Display Wall To Analyze Human Microbiome Complexity Comparing 3 LS Time Snapshots (Left) with Healthy, Crohn’s, UC (Right Top to Bottom) Calit2 VROOM-FuturePatient Expedition
  25. 25. LS Gut Microbe Species 12/28/11 (red) compared to Average of Healthy Subjects (blue) Species are Organized by Microbial Phyla Each Species is a Bar, Height is Logarithmic Abundance,Derived from metagenomic sequencing of LS stool sample. Source: Photo of Calit2 64-megapixel VROOM
  26. 26. Almost All Abundant Species (≥1%) in Healthy Subjects Are Severely Depleted in LS Gut
  27. 27. Top 20 Most Abundant Microbial Species In LS vs. Average Healthy Subject152x Number Above LS Blue Bar is Multiple of LS Abundance 765x Compared to Average 148x Healthy Abundance Per Species 849x 483x 220x 201x169x 522x Source: Sequencing JCVI; Analysis Weizhong Li, UCSD LS December 28, 2011 Stool Sample
  28. 28. 200 LS Gut Microbe Species at 3 Times 12/28/11, 4/3/12, 8/7/12 Red is at Highest Value of CRPBlue is the Day After End of Antibiotic/Prednisone Therapy Green is Four Months Later Source: Photo of Calit2 64-megapixel VROOM
  29. 29. Closeup of Uncommon LS Microbes 12/28/11 Stool Sample Two separate 45x research teamsReduced have found strikingly high By 8% 90x concentrationsTherapy Increased Reduced of Fusobacterium in tumor samples By By collected from Therapy Therapy colorectal cancer patients. October 18, 2011
  30. 30. DIY Systems Biology - Toward P4 Healthcare Over 1000 Downloads So Far Download pdfs from Journal:
  31. 31. Proposed UCSDIntegrated Omics Pipeline Source: Nuno Bandiera, UCSD
  32. 32. CAMERA as an Examplefor the NOMIC Portal Query/Hierarchy System Source: Jeff Grethe, CRBS, UCSD
  33. 33. Ecosystem to Amplify Understanding ofMicrobial Community Structure & Function Source: Jeff Grethe, CRBS, UCSD
  34. 34. Access to Computing Resources Tailored by User’s Requirements and ResourcesCore CAMERA HPC Resource UCSD Triton NSF/SDSC NSF/SDSC NSF/TACC NSF/TACC NSF/RCAC Gordon Trestles Lonestar Ranger SteeleInfrastructure Services Extend Infrastructure Services Extend CAMERA Computations to CAMERA Computations to 3rdrd Party Compute Resources 3 Party Compute Resources Source: EAGER: Multi-Domain, Workflow-Driven Jeff Grethe, Computation System for CRBS, UCSD Microbial Ecology Research and Analysis
  35. 35. PhyloMETARE Explore, Analyze & Compare TranscriptomesData P Source: Jeff Grethe,Data Analysis CRBS, UCSD Diverse Analysis Functions A new community resource for comparing complex microbial gene expression patterns
  36. 36. VIROME Explore, Analyze &Compare Viral Genomes/MetagenomesData Resource for analysis of viral metagenomesData Analysis Source: Jeff Grethe, CRBS, UCSD Diverse Analysis Functions
  37. 37. Fragment Recruitment Viewer (FRV) InterfaceX-axis is the genome coordinate, and y-axis is alignment identity (%). The top is genome coverage.The bottom shows genes or other genomic features. Users can zoom, resize, and pan the plot bymouse or using icons at corners in a similar way as Google Maps. Right illustrates new functionsand interface to be implemented in order to handle multiple integrated omics data types by usingmultiple synchronized FRV panels. Source: Weizhong Li, UCSD
  38. 38. Combined 16S, Metagenomics and Metatranscriptomics Pipeline Pooled 16S Pooled 16S WGS, transcriptomics WGS, transcriptomics Raw reads Raw reads Raw reads Raw reads Internal Internal Internal scripts to deconvolve QC QC scripts QC scripts Human Human pooled samples, trim barcode 1 Human seq. BWA, Bowtie, BWA, Bowtie, genome genome and primer sequences, and QC HQ reads removal FR-HIT, Blat etc & mRNAs FR-HIT, Blat etc & mRNAs HQ reads data 2 Artificial duplicates Cd-hit-dup Cd-hit-dup removal 3 rRNA removal Sample2 Sample nn Meta-RNA Meta-RNA Sample 11 Sample Sample2 Sample Taxonomy Transcriptomics Taxonomy Taxonomy profiling Filtered Filtered only ChimeraSlayer Ribosomal ChimeraSlayer Ribosomal Seq. error & K-mer based profile profile FR-HIT, Blat, Blast reads reads K-mer based Mothur Mothur Database Database FR-HIT, Blat, Blast redundancy Clustering-based Clustering-based Cd-hit-otu Cd-hit-otu Project Project Curated ref. Curated ref. MGAviewer MGAviewer removal genomes genomes Denoised Denoised Taxonomic classification Taxonomic classification Alignment reads Alignment reads Velvet Velvet identification of identification of Visualization Visualization Assembly SOAPdenovo SOAPdenovoOperational Taxonomic Units, Operational Taxonomic Units, Abyss Metagenome Reads Assembled Abyss computation of community computation of community Metagenome Assembled richness and diversity Abundance Abundance mapping metagenomes metagenomes ORF_finder richness and diversity BWA, Bowtie BWA, Bowtie ORF_finder ORF call Metagene Metagene FragGeneScan FragGeneScan Multivariate Gene Gene Multivariate Genes Genes Statistical approaches Statistical approaches Abundance Abundance Tigrfam Tigrfam Blastp Blastp Pfam, COG Annotation RPS-blast RPS-blast Pfam, COG Sample comparison Function, pathway HMMER3 KOG, KEGG HMMER3 KOG, KEGG Sample comparison Function, pathway eggNOG eggNOG clustering clustering annotation annotation ordination ordination (a) Legend: Data Tool Database Data Tool Database Proteomics (b) Proteomics analysis analysis Source: Weizhong Li, UCSD
  39. 39. UCSD Center for Computational Mass Spectrometry Becoming Global MS Repository ProteoSAFe: Compute-intensive MassIVE: repository anddiscovery MS at the click of a button identification platform for all MS data in the world Source: Nuno Bandeira, Vineet Bafna, Pavel Pevzner, Ingolf Krueger, UCSD
  40. 40. Metaproteomics Analyses Work Flow Source: Nuno Bandeira, UCSD
  41. 41. Creating a Big Data Freeway System:NSF Has Awarded Prism@UCSD Optical Switch Phil Papadopoulos, SDSC, Calit2, PI
  42. 42. PRISM@UCSD EnablesConnection to Remote Campus Compute & Storage Clusters