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*  The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study
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Christos Pantelis  __
16  Jones DK, Catani M, Pierpaoli C,  et al.  :  Age effects on diffusion
tensor magnetic resonance imaging tractography measures of frontal cortex
connections in schizophrenia  .  **Hum Brain Mapp** 2006  ; 27:230–238 
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T1-weighted MR image preprocessing was performed using automated procedures
included in the Computational Anatomical Toolbox (CAT12), an extension to the
Statistical Parametric Mapping (SPM12) package (  http://www.neuro.uni-
jena.de/cat/  ). First, T1-weighted images
were preprocessed with intensity normalization and skull stripping, followed
by the normalization of the head position along the commissural axis and the
labeling of the cortical and subcortical regions. Second, the images were
segmented into gray matter, white matter, and cerebrospinal fluid with the
parameter of Markov random fields set to 2, and co-registered to a
probabilistic brain atlas with non-linear morphing. According to the
probability that a given location is of a particular tissue class (gray
matter, white matter, and cerebrospinal fluid), the intensity of the image at
the location, and the local spatial configuration of the location related to
the labels, each MRI voxel was assigned to one specific tissue class (  Dahnke
et al., 2013  ). In this process, all T1-weighted images were spatially
normalized using combinations of affine linear transformation and non-linear
registration to the standard Montreal Neurological Institute (MNI) template
and segmented into gray matter, white matter, and cerebrospinal fluid. Third,
a DKT40 labeling atlas was warped from standard space to subject space using
the subject-specific inversed normalization parameters. All results were
estimated in the native space before spatial normalization. Last, an
individual brain atlas that consisted of 68 different gray matter areas was
created for each participant according to the DKT40 parcellation atlas, as
shown in  Figure 2  . The names and the corresponding indices of the
parcellated regions are reported in  Table 2  . The pipeline used topology
correction and spherical mapping to handle the partial volume effect, sulcal
blurring, and asymmetry (  Righart et al., 2017  ).
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*  Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study
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We found larger age-related abnormalities of both gray matter volume and
fractional anisotropy in schizophrenia compared with comparison subjects.
Interestingly, we also found that the time course of these structural
pathologies differed. Specifically, we found that the loss of gray matter
volume in schizophrenia was evident from young adulthood, with the rate of
loss being significantly faster in schizophrenia until middle age, slowing
thereafter to a stable rate. In contrast, the rate of age-related white matter
decline was constant across the lifespan and best modeled as a linear
function. The rate of white matter decline was 60% steeper in schizophrenia
compared with comparison subjects, with significant between-group differences
emerging in midlife and progressively widening between the two groups with
age. These findings suggest that schizophrenia is characterized by early loss
of gray matter followed by white matter deficits that widen with age at a
constant rate. Importantly, while males showed more severe deficits with age,
this pattern of differences by sex did not differ between patients and
comparison subjects (see the  online data supplement

), a finding consistent with other studies (  28  ).
Paul Klauser  __
*  Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker
*  Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study
NeuroImage, Vol. 183
*  Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study
*  Editorial: New insights into investigating schizophrenia as a disorder of molecular pathways
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*  Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture
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25  Nichols T, Hayasaka S  :  Controlling the familywise error rate in
functional neuroimaging: a comparative review  .  **Stat Methods Med Res**
2003  ; 12:419–446  Crossref

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*  Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts
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19  Koutsouleris N, Davatzikos C, Borgwardt S,  et al.  :  Accelerated brain
aging in schizophrenia and beyond: a neuroanatomical marker of psychiatric
disorders  .  **Schizophr Bull** 2014  ; 40:1140–1153  Crossref

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*  Advanced brain age correlates with greater rumination and less mindfulness in schizophrenia
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Publicly available datasets were analyzed in this study. This data can be
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The research is supported in part by the Natural Science Foundation of
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of Houston. Data collection and sharing for this project was funded by the
Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of
Health Grant No. U01AG024904) and DOD ADNI (Department of Defense award number
W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the
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generous contributions from the following: AbbVie, Alzheimer's Association;
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Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.;
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organization is the Northern California Institute for Research and Education.
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Sample characteristics are shown in  Table 1  . Age did not differ
significantly between patients and comparison subjects and did not differ in
distribution in the 25–50 age range (Kolmogorov-Smirnov test, see Figure S1 in
the  online data supplement

). The mean and variance in age between sites did not significantly differ.
Compared with the comparison subjects, the schizophrenia group had lower IQ
(t=11.5, df=507.9, p<0.001) and a greater proportion of males (χ  2  =18.3,
df=1, p<0.001). A breakdown of the medication status of the sample is provided
in Table S1 of the  data supplement

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29  Fusar-Poli P  :  Voxel-wise meta-analysis of fMRI studies in patients at
clinical high risk for psychosis  .  **J Psychiatry Neurosci** 2012  ;
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Statistical inference was performed at the scale of the whole brain and
individual voxels. For whole-brain analyses, total gray matter volume was
averaged over all gray matter voxels, and fractional anisotropy was averaged
over all voxels making up the white matter skeleton. The influence of age on
gray matter volume was modeled as:

where _β_ 1  , _β_ 2  , … _β_ 6  are unknown parameters fitted with least
squares estimation, diagnosis( _i_ ) is a binary indicator of the diagnostic
status of the _i_ th participant (patient: 1, comparison subject: 0), age( _i_
) is the age of the _i_ th participant, _C(i)_ represents nuisance confounds,
and _ε(i)_ is a normally distributed error term. The nuisance confounds were
scanner location, sex, and the interaction between sex and diagnostic status.
Psychiatry Research: Neuroimaging, Vol. 316
##  Methods and Materials
The quadratic regression model was fitted to each gray matter voxel, and
cluster-based inference was used to localize age-related gray matter volume
loss to specific brain regions.  Figure 2A  presents regions of significantly
reduced gray matter volume in schizophrenia relative to comparison subjects
(p<0.05, family-wise error corrected). Brain regions with significant gray
matter volume loss were evident in schizophrenia relative to comparison
subjects at all ages. This loss was primarily circumscribed to frontal and
temporal brain regions in early adulthood, gradually progressing to most
cortical and subcortical areas with advancing age (  Figure 2A  ). Areas most
severely affected were the medial prefrontal cortex, hippocampus, and thalamus
(see  Movie 1

in the online edition of this article).
Jiehui Jiang  ,
Shanghai University, China
*  Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness
23  Jenkinson M, Beckmann CF, Behrens TE,  et al.  :  Fsl  .  **Neuroimage**
2012  ; 62:782–790  Crossref

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10 January 2022 | BMC Psychiatry, Vol. 22, No. 1
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Data used in this study were obtained from the Alzheimer's Disease
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primary goal of ADNI is to identify MRI, PET, biomarkers, and genetic
characteristics that would support the early detection and tracking of AD and
improve the clinical trial design (  Risacher et al., 2009  ;  Jack et al.,
2010a  ;  Petersen et al., 2010  ). Scans were acquired with a 3.0-T head-only
Siemens Medical Solutions MRI scanner (Erlangen, Germany). T1-weighted imaging
parameters were: repetition time = 2,250 ms, echo time = 2.6 ms, flip angle =
9, field of view = 256 × 256 mm, acquisition matrix = 256 × 256, voxel size =
1 mm isotropic, and number of slices = 192. The demographic data of the
subjects are summarized in  Table 1  . The flowchart of the ROI-based surface
morphometry analysis is shown in  Figure 1  .
*  Assessment of brain cholesterol metabolism biomarker 24S-hydroxycholesterol in schizophrenia
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matter in patients with schizophrenia  .  **Am J Psychiatry** 2002  ;
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