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ashg2019

 ashg2019

Leonardo Collado-Torres

October 15, 2019
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  1. 11
    Regional Heterogeneity in Gene
    Expression, Regulation, and Coherence in
    the Frontal Cortex and Hippocampus
    across Development and Schizophrenia
    Leonardo Collado-Torres
    Staff Scientist II
    @fellgernon
    Data Science I with Andrew Jaffe

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  2. URGENT UNMET NEED
    Neuropsychiatric disorders cost the U.S. Economy > $80 billion/year.
    Neuropsychiatric conditions are the leading
    cause of disability in young people worldwide.
    70%
    70% of youth in the
    juvenile justice system
    are living with at least
    one mental health
    condition.
    Traumatic brain injury is
    the leading cause of
    long-term disability in
    children and adults
    younger than 35 years.
    1 in 4 experience
    mental illness in a
    given year.
    More veterans die
    of suicide than in
    combat at rate of
    20 suicides per
    day.
    2

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  3. BrainSeq: A Human Brain Genomics Consortium
    DLPFC
    495 samples
    BrainSeq Phase I
    polyA+
    Jaffe et al., Nature Neuroscience,
    2018
    DLPFC
    453 samples
    HIPPO
    447 samples
    BrainSeq Phase II
    RiboZero
    Neuron, 2015
    Collado-Torres et al, Neuron, 2019
    551 individuals (286
    with schizophrenia)

    View Slide

  4. −6 −4 −2 0 2 4
    −6 −4 −2 0 2 4 6
    t−statistic HIPPO
    t−statistic DLPFC
    r = 0.276
    4
    SCZD expression regional heterogeneity
    48 DE genes in
    hippocampus, 243
    in DLPFC (FDR
    <5%)
    Amy Peterson
    Adjusting for:
    age, sex, chrM
    mapping, rRNA
    mapping, gene
    assignment rate,
    RIN, SNP PCs 1-5,
    quality surrogate
    variables (qSVA)

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  5. Gene Individual 1 Individual 2
    A 10 15
    B 5 22
    C 7 9
    D 100 50
    DLPFC
    Gene Individual 1 Individual 2
    A 10 17
    B 6 16
    C 9 30
    D 120 80
    HIPPO
    correlation( (10, 5, …), (10, 6, …) ) =~ 0.9
    correlation( (15, 22, …), (17, 16, …) ) =~ 0.7
    Individual 1
    Individual 2
    Control vs SCZD

    View Slide

  6. p-values:
    Gene: 0.0164
    Exon: 0.0499
    Jxn: 1.72 * 10-5
    Tx: 0.00992
    Control SCZD
    0.54 0.55 0.56 0.57
    cleaned expr (keeping Dx) − jxnRp10m
    p−value: 1.72e−05
    Correlation
    Decreased regional coherence in SCZD
    Control SCZD
    Correlation

    View Slide

  7. 7
    HIPPO eQTLs 11,237,357 eQTL associations (FDR <1%)
    across genes, exons and junctions
    corresponding to 17,719 genes
    Emily E. Burke
    2061
    3183
    2163
    274
    5945
    2915
    1178
    gene exon
    jxn
    eQTLs grouped by gene id
    Includes 60 risk SNPs from PGC2
    8
    +,332
    E
    0 1 2
    −1 0 1 2 3 4
    chr2:5822204358229ï-[Q
    rs74563533:58250433:G:A
    r2:58 250 433
    Residualized Expression







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    0 1 2
    −1 0 1 2 3 4
    chr2:5822204358229ï-[Q
    rs75575209:58138192:A:T
    r2:58 138 192
    Residualized Expression



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    p=5.75e−34
    p=3.82e−81
    F

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  8. 8
    205,618 region-dependent eQTLs (FDR <1%)
    corresponding to 1,484 genes
    Emily E. Burke
    Bill Ulrich
    eQTL browser at
    http://eqtl.brainseq.org/

    View Slide

  9. Analysis with PCG2 risk SNPs and proxies identifies
    eQTLs (FDR <1%) in risk loci
    HIPPO DLPFC
    # unique SNPs (unique
    index SNPs)
    5510 (103) 6780 (116)
    # unique features 1731 2525
    # Unique genes 123 171
    # Unique transcripts 244 332
    # Unique exons 857 1363
    # Unique junctions 507 659
    Emily E. Burke
    21 8
    95
    DLPFC HIPPO
    In BSP2: 163/179 (91.1%)
    FDR <1%: 124/163 (76.6%)

    View Slide

  10. Gusev et al, Nature Genetics, 2016
    Transcriptome Wide Association Study (TWAS)

    View Slide

  11. −5
    0
    5
    −5 0 5
    DLPFC
    HIPPO
    in_both
    FALSE
    TRUE
    FDR.5perc
    None
    DLPFC
    HIPPO
    Both
    TWAS Z by brain region
    Removed sex, SNP
    PCs 1-5, expression
    PCs
    Kept diagnosis
    jaffelab::cleaningY()
    TWAS Z scores are correlated among DLPFC &
    HIPPO
    GWAS: CLOZUK

    View Slide

  12. rho=−1.26e−03
    rho=−8.50e−03
    rho=7.27e−03
    rho=4.54e−02
    DLPFC HIPPO
    Other Risk Locus
    −5 0 5 −5 0 5
    −6
    −3
    0
    3
    6
    −6
    −3
    0
    3
    6
    TWAS Z score
    SCZD vs control t−statistic
    BEST GWAS
    p < 5e−08
    FALSE
    TRUE
    TWAS vs SCZD differential expression
    Risk Loci by BEST GWAS
    TWAS and SCZD statistics are not related

    View Slide

  13. Risk Loci Category HIPPO DLPFC Intersection Union
    With eQTLs <1% 103 116 95 124
    With TWAS weights 86 (83.5%) 93 (80.2%) 78 (82.1%) 101 (81.5%)
    TWAS FDR <5% 79 (91.9%) 88 (93.5%) 73 (93.6%) 94 (93.1%)
    TWAS Bonferroni <5% 61 (70.9%) 68 (73.1%) 54 (69.2%) 75 (74.3%)
    TWAS results are complementary to eQTLs in risk loci
    ~80% of risk loci with eQTLs have TWAS weights,
    ~90% and ~70% of these are FDR or Bonferroni significant

    View Slide

  14. doi.org/10.1016/j.neuron.2019.05.013
    • Dorsolateral prefrontal cortex and hippocampus
    gene expression across development
    • Novel region-specific schizophrenia genetic risk
    features
    • Decreased regional functional coherence in
    schizophrenia
    • Public brain gene expression and eQTL resource
    at http://eqtl.brainseq.org/phase2
    BrainSeq Phase II summary

    View Slide

  15. Dentate Gyrus LCM-seq finds cell type specific eQTLs
    Jaffe, Hoeppner et al., bioRxiv, 2019

    View Slide

  16. snRNA-seq for profiling cell types in brain & spatially
    [08] In
    [09] In
    [11] In
    [12] Ex+In
    [10] Ex
    [07] Ex
    [05] Ex
    [13] NPC
    [00] Oligo
    [02] Oligo
    [06] OPC
    [03] Astro
    [04] Micro
    [01] Ambig
    SNAP25
    GAD1
    CAMK2A
    SLC17A7
    SOX11
    FOXP2
    MBP
    PDGFRA
    GFAP
    CD74
    −2
    −1
    0
    1
    2
    [00] Oligo
    [04] Micro
    [02] Oligo
    [06] OPC
    [11] In
    [03] Astro
    [05] Ex
    [08] In
    [10] Ex
    [12] Ex+In
    [13] NPC
    [09] In
    [01] Ambig
    [07] Ex
    −25
    0
    25
    −50 −25 0 25 50
    tSNE_1
    tSNE_2
    Nguyen & Maynard, In prep

    View Slide

  17. Authors
    • Leonardo Collado-Torres
    o [email protected]
    o @fellgernon
    • Emily E. Burke
    • Amy Peterson
    • Joo Heon Shin
    • Richard E. Straub
    • Anandita Rajpurohit
    • Stephen A. Semick
    • William S. Ulrich
    • Amanda J. Price
    • Cristian Valencia
    • Ran Tao
    • Amy Deep-Soboslay
    • Thomas M. Hyde
    • Joel E. Kleinman
    • Daniel R. Weinberger+
    • Andrew E. Jaffe+
    o [email protected]
    o @andrewejaffe
    17
    • BrainSeq Consortium
    • LIBD @lieberinstitute
    Funding
    github.com/LieberInstitute/brainseq_phase2
    doi.org/10.1016/j.neuron.2019.05.013

    View Slide