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Too Big (Hot) To Fail John

SVAI Hackathon

San Francisco, CA

June 7-9, 2019

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Notable gene variants identified

  • Intestinal/Digestion
    • TLR6 - Toll-like receptor 6
    • Many mucin genes
  • Immune function
    • PSMB11 - proteasome subunit beta type 11
    • HLA-B - HLA class I histocompatibility protein
    • HLA-DRB1 - HLA class II histocompatibility antigen
  • Inflammation
    • LPL - Lipoprotein lipase
    • IL17RC - Interleukin-17 receptor C
    • TLR6 - Toll-like receptor 6
    • IL1RL1 - Interleukin-1 receptor-like 1
    • GBA - Glucosylceramidase
    • NR1H4 - Bile acid receptor
    • IL1R1 - Interleukin-1 receptor type 1
    • ATM - serine-protein kinase ATM
    • CAMK2G - calcium/calmodulin dependent protein kinase type II subunit gamma

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Notable genes variants identified (cont.)

  • Fatty acid metabolism
    • APOB - Apolipoprotein B-100
    • FASN – Fatty acid synthase
    • NR1H4 – bile acid receptor
    • ACADL – Long chain specific acyl-CoA dehydrogenase
    • ACADS – short chain specific acyl-CoA dehydrogenase
    • CEL – bile salt activated lipase
    • PDPR – pyruvate dehydrogenase phosphatase regulatory subunit
  • Response to stress
    • (29 genes with variants identified)

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Candidate Pathway: mild multisystem mitochondrial disease

Main symptoms from the Medical record: Nausea and Vomiting, Abdominal pain, muscle loss, fatigue, difficulty to gain weight

Candidate genes link to mitochondrial disease

  1. SDHA (frameshift variant: rs112307877)
  2. RRM2B (4 mutations including rs5893603)
  3. POLG (frameshift insertion: 15:89876827-89876860)

Effecting energy production in Kreb’s cycle and oxidative phosphorylation

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Candidate Pathway: Glycosylation Disorder

  • Associated symptoms: Low muscle tone and FTT
  • Evidence:
    • Non-synonymous, rare, non-benign variants present in 11 genes linked to the protein O-glycosylation pathway
    • Mutation found in one of the markers for a subtype of this disorder (ALG9)
    • Many glycosylated proteins are involved in Mitochondrial function, specifically the oxidative phosphorylation pathway
  • Diagnosis/Confirmation: Isoelectric focusing of transferrin and targeted mass spectrometry for protein glycosylation
  • Treatment: Dependent on type of Congenital disorder of glycosylation (CDG), e.g. oral mannose, butyrate administration
  • Resources:

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Possible Chronic Phthalate Exposure

  • Metabolic data from Openome and Prodrome reveal higher levels of phthalate molecules
    • Didodecyl Phthalates containing long hydrophobic carbon chains
  • Man-made chemical found in many common plastics and household products
  • Typical half-life in body is ~5 hrs
    • Therefore high concentrations on results can indicate chronic exposure
  • Hydrophobic phthalates are found in larger quantities in human breast milk
    • Therefore transfering exposure to infants
  • Effects of chronic exposure in humans is not understood well
    • Animal models show endocrine disruption (low sperm count etc.)
  • Unknown if hydrophobic phthlates are cause or effect of poor lipid metabolism

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Next Steps

  • Dive deeper into copy number variants and structural variants as well as other data sets (proteomics, RNAseq)
    • Identify rare structural variants
    • Explore more in chromosome 8
      • additional variation in chr8 (locus 8q21 (8:85865408-103436006) several duplication, deletion and inversion) → microdeletion in chr8 also link to mitochondrial diseases
    • Polygenic score (compared to generic population) of mutation in mitochondrial disease related genes
  • Targeted mass spectrometry for testing glycosylation of proteins
    • Looking for lack of glycosylation that can induce adverse effects
  • Further tests on urine, blood and sweat
    • Further confirm chronic phthalate exposure

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Open Source Resources Used

R

VEP (Variant Effect Predictor)

gnomAD

Gene Ontology

Open-CRAVAT

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Python packages:

Pandas, Numpy, VCF tools, COBRApy

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Proprietary Resources Used (and THANK YOU!)

  • Qiagen IVA
  • OCR read of John’s medical records and secondary text extraction and analysis of medically relevant terms through Amazon Comprehend Medical toolset) , thanks to Jason Chin of DNA Nexus)

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Too Big To Fail John -- Team Members

  • AJ Schick
  • Alex Li
  • Catherine Tcheandjieu
  • Deepika Gunasekaran
  • Matt Aguirre
  • Randi Paynter
  • Sal Palmisano

AND OF COURSE OUR MOST IMPORTANT TEAM MEMBER...

  • John Mickel

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