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The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders.

ABSTRACT: We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, (2) it leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches, with a higher incidence of both long-range and local correlation differences that favor the Autism Spectrum Disorder group, (3) the strongest group differences under other preprocessing approaches are the ones most altered by Global Signal Regression, and (4) locations showing group differences no longer agree with those showing correlations with behavioral symptoms within the Autism Spectrum Disorder group. The correlation matrices of both participant groups under Global Signal Regression were well predicted by our previous mathematical analyses, demonstrating that there is nothing mysterious about these results. Finally, when independent physiological nuisance measures are lacking, we provide a simple alternative approach for assessing and lessening the influence of global correlations on group comparisons that replicates our previous findings. While this alternative performs less well for symptom correlations than our favored preprocessing approach that includes removal of independent physiological measures, it is preferable to the use of Global Signal Regression, which prevents unequivocal conclusions about the direction or location of group differences.

SUBMITTER: Gotts SJ

PROVIDER: S-EPMC3709423 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders.

Gotts Stephen J SJ Saad Ziad S ZS Jo Hang Joon HJ Wallace Gregory L GL Cox Robert W RW Martin Alex A

Frontiers in human neuroscience 20130712

We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than sim ...[more]

PMID: 23874279

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Project description:Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, likely due to different etiologies, complicates genetic/biological analyses of these disorders. DNA microarray analyses were conducted on 116 lymphoblastoid cell lines (LCL) from individuals with idiopathic autism who are divided into 3 phenotypic subgroups according to severity scores from the commonly used Autism Diagnostic Interview-Revised questionnaire and age-matched, nonautistic controls. Statistical analyses of gene expression data from control LCL against that of LCL from ASD probands identify genes for which expression levels are either quantitatively or qualitatively associated with phenotypic severity. Comparison of the significant differentially expressed genes from each subgroup relative to the control group reveals differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Among the findings unique to the most severely affected ASD group are genes that regulate circadian rhythm, which has been shown to have multiple effects on neurological as well as metabolic functions commonly dysregulated in autism. Among the genes common to all 3 subgroups of ASD are 5 novel genes which appear to associate with androgen sensitivity, which may underlie the strong 4:1 bias towards affected males. Gene expression profiling of 116 LCL from autistic (87) and nonautistic (29) individuals were obtained using a custom-printed DNA microarray containing 39,936 elements (TIGR 40K Human array, GPL3427) and a reference design in which each sample was compared to the Stratagene Universal Human RNA standard. The 87 autistic samples were divided into phenotypic subgroups (language, mild, savant) on the basis of cluster analyses of scores from an autism diagnostic questionnaire, the Autism Diagnostic Interview-Revised instrument. Differentially expressed genes were determined for all autistic vs. control groups, as well as for each of 3 phenotypic ASD groups and controls.

Project description:Autism is currently considered a multigene disorder with epigenetic influences. To investigate the contribution of DNA methylation to autism spectrum disorders, we have recently completed large-scale methylation profiling by CpG island microarray analysis of lymphoblastoid cell lines (LCL) derived from monozygotic twins discordant for diagnosis of autism and their nonautistic siblings. Methylation profiling revealed many candidate genes differentially methylated between discordant MZ twins as well as between both twins and nonautistic siblings. Bioinformatics analysis of the differentially methylated genes demonstrated enrichment for high level functions including gene transcription, nervous system development, cell death/survival, and other biological processes implicated in autism. The methylation status of two of these candidate genes, BCL-2 and retinoic acid receptor (RAR)-related orphan receptor alpha (RORA), was further confirmed by bisulfite sequencing and methylation-specific PCR, respectively. Immunohistochemical analyses of tissue arrays containing slices of the cerebellum and frontal cortex of autistic and age- and sex-matched control subjects revealed decreased expression of RORA and BCL-2 proteins in the autistic brain. Our data thus confirm the role of epigenetic regulation of gene expression via differential DNA methylation in idiopathic autism, and furthermore link molecular changes in a peripheral cell model with brain pathobiology in autism. Global methylation profiling was performed on lymphoblastoid cell lines (LCLs) derived from three pairs of male monozygotic twins discordant for diagnosis of autism as determined by the Autism Diagnostic Interview-Revised (ADI-R). As controls, cell lines derived from non-autistic siblings of two pairs of twins were also included in the analyses, in addition to cell lines derived from a set of monozygotic twins unaffected by autism. For all paired analyses, a direct comparison was performed in which the methylation-enriched fractions from two individuals were pooled and hybridized onto the same microarray. In addition, indirect comparisons were performed by co-hybridizing the methylation-enriched (MIRA) fraction with the respective unenriched DNA fraction obtained from the same individual. For each paired analysis (between autistic MZ twins and/or between autistic co-twin and unaffected sibling), a total number of 4 replicates were performed, including direct and indirect comparisons.

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The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders.

Publications

The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders.

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