The MCIC Collection: A Shared Repository of Multi-Modal, Multi-Site Brain Image Data from a Clinical Investigation of Schizophrenia

Abstract

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, www.mrn.org), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.

Schizophrenia Prediction Using Integrated Imaging Genomic Networks

“…After a series of quality controls, we selected 184 subjects, including 80 SZ cases (age: 34 ± 11, 20 females and 60 males) and 104 healthy controls (age:32 ± 11, 38 females and 66 males). After pre-processing, 27,508 DNA methylation sites, 41,s236 fMRI voxels and 722,177 SNP loci were obtained for the subsequent biomarker selections [22,23,24,25,26,27].…”

Myelination-related genes are associated with decreased white matter integrity in schizophrenia

“…24 In summary, the curated diffusion tensor imaging (DTI) sample consisted of 114 subjects with schizophrenia and 138 controls with available genetic data. Subjects were recruited from four sites: Massachusetts General Hospital in Boston (MGH) (N = 60; 29 cases and 31 controls), University of Iowa (UI) (N = 92; 38 cases and 54 controls), University of Minnesota (UMN) (N = 53; 25 cases and 28 controls), and University of New Mexico (UNM) (N = 47; 22 cases and 25 controls).…”

“…24 In summary, structural MRI data were acquired with either a Siemens (Erlangen, Germany) 1.5-Tesla (MGH, UI, and UNM) or a Siemens 3-Tesla (UMN) MR scanner. The T 1 -weighted structural brain scans at each of the four sites were acquired with an in-plane resolution of 0.625 × 0.625 mm 2 , a slice thickness of 1.5 mm, and a flip angle of 7 degrees.…”

“…After QC, 710 224 SNPs remained for association analysis (the total genotyping rate in remaining individuals was 0.9989). As previously published, 24 owing to consortium agreements and IRB restrictions, the raw genotypic data used in the study is not publically available, but genome-wide association study (GWAS) analysis results obtained as part of the gene set analysis are publically available at GWAS Central: http://www.gwascentral.org/ study/HGVST1829.…”

Joint sparse canonical correlation analysis for detecting differential imaging genetics modules

“…Next, we apply the JSCCA method to a schizophrenia dataset with 92 cases and 116 controls. The data include functional magnetic resonance imaging (fMRI) and single-nucleotide polymorphism (SNP) data, collected by The Mind Clinical Imaging Consortium (Gollub et al, 2013). We found a number of SNP-voxel modules with significantly increased correlation for schizophrenia patients.…”