Research ArticleAutism Spectrum Disorder

Patients with autism spectrum disorders display reproducible functional connectivity alterations

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Science Translational Medicine  27 Feb 2019:
Vol. 11, Issue 481, eaat9223
DOI: 10.1126/scitranslmed.aat9223
  • Fig. 1 Outcomes of DC comparisons between individuals with ASD and TD.

    (A) Representative reconstruction of a brain illustrating regions showing significant DC increases (red) and decreases (blue) in individuals with ASD in the reference EU-AIMS LEAP cohort. (B) Distribution of DC values (first eigenvariate over the masks’ voxels) across subjects for the hyperconnected (top row, red) and hypoconnected (bottom row, blue) network separately for individuals with ASD and TD. (C) Unthresholded t-maps showing regions with increased (warm colors) and decreased (cold colors) DC in individuals with ASD as compared to TD. (D) Spatial correspondence of the t-maps between the reference dataset (EU-AIMS LEAP) and all remaining replication datasets (ABIDE I, ABIDE II, and InFoR) in the form of a pairwise correlation matrix and individual correlation plots. A, anterior; d, Cohen’s d effect size; FWE, family-wise error; L, left; P, posterior; R, right; ns, not significant. *P < 0.05, **P < 0.01, ***P < 0.001 as obtained using independent-samples t tests (B) and Pearson correlation analyses (D).

  • Fig. 2 Functional connectivity indices and their effect size.

    (A) Distribution of the Pearson’s correlation coefficients between pairs of voxel-wise blood oxygen level dependence activity time courses observed in ASD and TD in the EU-AIMS LEAP cohort. (B) Effect sizes of the functional connectivity indices based on DC masks for the contrasts ASD > TD (left) and TD > ASD (right). Indices: mean connectivity (μ), variance of connectivity (σ), and proportion of connected voxels (π) within (1), outside (2), and from within to outside (3) the DC alteration masks and shifts in connectivity from within to outside (π4) and from outside to within (π5) the DC alteration mask. Details on computation are provided in fig. S2. *P < 0.05, **P < 0.01, ***P < 0.001 as obtained using independent-samples t tests. (C) Effect size for the hyper- and hypoconnectivity indices obtained in the EU-AIMS LEAP dataset plotted versus the applied correlational threshold. Dashed line indicates the correlational threshold used for the initial DC computation.

  • Fig. 3 Relationships between hyper- and hypoconnectivity indices, age, and clinical outcomes.

    (A) Effect size of the hyperconnectivity index for all patients and split by age groups [children (<12 years), adolescents (12 to 18 years), and adults (>18 years)] for contrast ASD > TD (red). (B) Equivalent of (A) for the hypoconnectivity index (blue). (C) Correlations of the hyperconnectivity indices with ASD clinical scales in the EU-AIMS LEAP and ABIDE I datasets (adjusted for the effects of age, sex, site, and IQ). (D) Correlations between ADI communication and VABS daily living skills and communication subscales. *P < 0.05, **P < 0.01, ***P < 0.001 as obtained using independent-samples t tests.

  • Table 1 Clinical and demographic characteristics.

    ADI, autism diagnostic interview; ADOS, autism diagnostic observation schedule; PDD-NOS, pervasive developmental disorder not otherwise specified; RRB, restricted and repetitive behaviors; SRS, social responsiveness scale.

    EU-AIMS LEAPABIDE IABIDE IIInFoR
    ASDTDStats
    (test value,
    df, and
    P value)
    ASDTDStats
    (test value,
    df, and
    P value)
    ASDTDStats
    (test value,
    df, and
    P value)
    ASDTDStats (test value, df, and P value)
    n2021922993763063913425
    Male/female142/
    60
    124/
    68
    1.5, 1,
    0.226
    268/31313/635.7, 1,
    0.017
    262/
    44
    263/
    127
    30.4, 1,
    <0.001
    26/819/60.0, 1,
    0.967
    Age ± SD17.5 ±
    5.3
    17.4 ±
    5.7
    0.1, 392,
    0.915
    17.5 ±
    7.7
    17.7 ±
    7.8
    −0.3, 673,
    0.776
    14.0 ±
    6.8
    13.6 ± 6.20.8, 695,
    0.428
    29.5 ±
    8.9
    30.6 ±
    8.3
    0.5, 57,
    0.638
    Child/
    adolescent/
    adult
    35/76/
    91
    43/71/
    78
    1.7, 2,
    0.434
    69/118/
    112
    85/147/
    144
    0.1, 2,
    0.974
    147/85/
    74
    234/77/
    80
    10.3, 2,
    0.006
    0/0/
    34
    0/0/
    25
    IQ (mean ±
    SD, n)
    106 ±
    14.9
    109 ±
    12.6
    −2.1, 392,
    0.033
    106.3 ±
    16.0
    112.0 ±
    12.1
    −5.3, 673,
    <0.001
    107.0 ±
    16.0
    115.7 ±
    12.5
    −8.0, 695,
    <0.001
    104.3 ±
    18.7
    108.6 ±
    17.5
    0.9, 54,
    0.392
    DSM IV
    diagnosis
    (none/ASD/
    Asperger/
    PDD-NOS)
    16/204/
    60/16
    121/55/
    78/52
    On medication (n)5426118117
    ADOS total
    (mean ± SD, n)
    10.1 ±
    4.9, 170
    11.9 ±
    3.7, 259
    1.3 ±
    1.4, 30
    15.4, 287,
    <0.001
    10 ±
    3.7, 167
    1.8 ±
    1.7, 38
    13.4, 203,
    <0.001
    ADI social
    (mean ± SD, n)
    15.7 ±
    6.7, 191
    19.9 ±
    5.4, 184
    18.7 ±
    5.8, 217
    16.2 ±
    6.4, 25
    ADI
    communication
    (mean ± SD, n)
    12.9 ±
    5.8, 191
    15.8 ±
    4.7, 185
    14.9 ±
    4.6, 217
    9.4 ±
    5.3, 25
    ADI RRB
    (mean ± SD, n)
    4.1 ±
    2.6, 191
    6.1 ±
    2.5, 185
    5.5 ±
    2.5, 217
    2.2 ±
    1.3, 22
    SRS t-score68.9 ±
    11.9,
    165
    45.9 ±
    7.5, 90
    16.6, 253,
    <0.001
    75.4 ±
    13.5, 256
    VABS adaptive
    behavior
    composite
    (mean ± SD, n)
    70.0 ±
    12.3, 87
    77.3 ±
    13.7, 60
    82.8 ±
    10.9, 61
    VABS daily
    living skills
    (mean ± SD, n)
    71.0 ±
    13.5, 87
    83.2 ±
    15.2, 60
    87.4 ±
    10.4, 61
    VABS
    socialization
    (mean ± SD, n)
    69.3 ±
    16.6, 88
    75.0 ±
    16.5, 60
    82.5 ±
    12.5, 61
    VABS
    communication
    (mean ± SD, n)
    77.3 ±
    14.9, 88
    79.3 ±
    15.5, 60
    87.3 ±
    13.9, 61
  • Table 2 Regions showing significant DC differences in the EU-AIMS LEAP cohort between individuals with ASD and TD.

    ContrastAnatomical
    region
    Cluster sizeExact cluster
    P value
    T valueMNI coordinates
    [x y z]
    ASD > TDBilateral: Parietal,
    posterior cingulate,
    precuneus, primary visual
    30660.0085.35*−33 54 39
    ASD > TDBilateral: Lateral and medial
    prefrontal, premotor,
    supplementary motor,
    anterior cingulate
    48510.0015.33*36 42 3
    Right: Anterior
    insula, caudate
    TD > ASDBilateral: Primary sensory,
    primary motor,
    middle cingulate
    5777<0.0015.41*12 –33 69
    Right: Posterior insula,
    temporal cortex, amygdala,
    hippocampus, entorhinal

    *Significant at a whole-brain voxel-wise family-wise error-corrected threshold of P < 0.05.

    • Table 3 Effect sizes and P values for the hyper- and hypoconnectivity indices computed using cortical, subcortical, and cerebellar subregions comparing ASD and TD.

      “Outside” regionHyperconnectivity
      index
      (Cohen’s d; P)
      Hypoconnectivity
      index
      (Cohen’s d; P)
      Cerebellar−0.12; 0.2330.05; 0.619
      Cortical−0.76; <0.0010.46; <0.001
      Subcortical0.05; 0.604−0.10; 0.332
    • Table 4 Results of correlations between hyper- and hypoconnectivity indices and clinical scales.

      Significant (P < 0.05) relationships between functional connectivity indices and respective clinical scales are indicated in bold.

      ScaleConnectivity measureEU-AIMS LEAPABIDE IABIDE II
      ADI communication totalHyperconnectivity indexF1,182 = 5; P = 0.026F1,171 = 8.7; P = 0.004F1,204 = 0.3; P = 0.602
      VABS daily living standardHyperconnectivity indexF1,80 = 5.3; P = 0.024F1,55 = 4.1; P = 0.048F1,55 = 0.1; P = 0.75

    Supplementary Materials

    • www.sciencetranslationalmedicine.org/cgi/content/full/11/481/eaat9223/DC1

      Materials and Methods

      Fig. S1. Significant DC differences between ASD and TD observed in the EU-AIMS LEAP dataset with and without control for motion in the group comparisons.

      Fig. S2. Connectivity indices computed based on the identified DC alterations.

      Fig. S3. Correlations between the initial DC findings and derived connectivity indices showing the largest effect sizes for differentiation between ASD and TD.

      Fig. S4. Plots of comorbidity status versus DC and hyper- and hypoconnectivity indices from ABIDE II cohort.

      Table S1. Mean motion in ASD and TD.

      Table S2. Results of analyses of variance testing for age category–by–diagnosis and sex-by-diagnosis interactions on the hyper- and hypoconnectivity indices.

      Table S3. Effects of medication on functional connectivity measures.

      Table S4. Contingency table of psychiatric comorbidity versus current medication status in ASD from ABIDE II.

      Table S5. Outcomes of EU-AIMS LEAP GLM analysis using ASD indices to predict clinical scores.

      Table S6. Age characteristics of the ADI and VABS subpopulations used for correlation with clinical scales.

      Table S7. Volumetric comparisons between ASD and TD in the EU-AIMS LEAP cohort.

      Table S8. Associations between structural and functional connectivity measures in the EU-AIMS LEAP cohort.

      Table S9. Additional clinical characteristics of the EU-AIMS LEAP population.

      Table S10. Additional clinical characteristics of the ABIDE I population.

      Table S11. Additional clinical characteristics of the ABIDE II population.

      Table S12. Summary of scanning parameters for each participating site in the EU-AIMS LEAP consortium.

      Table S13. Summary of scanning parameters for each participating site in the ABIDE I cohort.

      Table S14. Summary of scanning parameters for each participating site in the ABIDE II cohort.

      Table S15. Summary of scanning parameters used in the InFoR cohort.

      References (60, 61)

    • This PDF file includes:

      • Materials and Methods
      • Fig. S1. Significant DC differences between ASD and TD observed in the EU-AIMS LEAP dataset with and without control for motion in the group comparisons.
      • Fig. S2. Connectivity indices computed based on the identified DC alterations.
      • Fig. S3. Correlations between the initial DC findings and derived connectivity indices showing the largest effect sizes for differentiation between ASD and TD.
      • Fig. S4. Plots of comorbidity status versus DC and hyper- and hypoconnectivity indices from ABIDE II cohort.
      • Table S1. Mean motion in ASD and TD.
      • Table S2. Results of analyses of variance testing for age category–by–diagnosis and sex-by-diagnosis interactions on the hyper- and hypoconnectivity indices.
      • Table S3. Effects of medication on functional connectivity measures.
      • Table S4. Contingency table of psychiatric comorbidity versus current medication status in ASD from ABIDE II.
      • Table S5. Outcomes of EU-AIMS LEAP GLM analysis using ASD indices to predict clinical scores.
      • Table S6. Age characteristics of the ADI and VABS subpopulations used for correlation with clinical scales.
      • Table S7. Volumetric comparisons between ASD and TD in the EU-AIMS LEAP cohort.
      • Table S8. Associations between structural and functional connectivity measures in the EU-AIMS LEAP cohort.
      • Table S9. Additional clinical characteristics of the EU-AIMS LEAP population.
      • Table S10. Additional clinical characteristics of the ABIDE I population.
      • Table S11. Additional clinical characteristics of the ABIDE II population.
      • Table S12. Summary of scanning parameters for each participating site in the EU-AIMS LEAP consortium.
      • Table S13. Summary of scanning parameters for each participating site in the ABIDE I cohort.
      • Table S14. Summary of scanning parameters for each participating site in the ABIDE II cohort.
      • Table S15. Summary of scanning parameters used in the InFoR cohort.
      • References (60, 61)

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