The Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Positive and Negative Syndrome Scale for Schizophrenia (PANSS) are the most widely used schizophrenia symptom rating scales, but despite their co-existence for 25 years no easily usable between-scale conversion mechanism exists. The aim of this study was to provide equations for between-scale symptom rating conversions. Two- hundred-and-five schizophrenia patients [mean age±SD=39.5±11.6), 156 males] were assessed with the SANS, SAPS, and PANSS. Pearson’s correlations between symptom scores from each of the scales were computed. Linear regression analyses, on data from 176 randomly selected patients, were performed to derive equations for converting ratings between the scales. Intraclass correlations, on data from the remaining 29 patients, not part of the regression analyses, were performed to determine rating conversion accuracy. Between-scale positive and negative symptom ratings were highly correlated. Intraclass correlations between the original positive and negative symptom ratings and those obtained via conversion of alternative ratings using the conversion equations were moderate to high (ICCs = 0.65 to 0.91). Regression-based equations may be useful for conversion between schizophrenia symptom severity as measured by the SANS/SAPS and PANSS, though additional validation is warranted. This study’s conversion equations, implemented at http::/converteasy.org, may aid in the comparison of medication efficacy studies, in meta- and mega-analyses examining symptoms as moderator variables, and in retrospective combination of symptom data in multi-center data sharing projects that need to pool symptom rating data when such data are obtained using different scales.
schizophrenia; symptoms; Marder; conversion; meta; multi-center
MicroRNAs (miRNAs) are small non-coding RNAs that act as potent regulators of gene expression. A recent GWAS reported the rs1625579 SNP, located downstream of miR-137, as the strongest new association with schizophrenia (Ripke et al., 2011). Prior to this GWAS finding, a schizophrenia imaging-genetic study found miR-137 target genes significantly enriched for association with activation in the dorsolateral prefrontal cortex (DLPFC) (Potkin et al., 2010).
We investigated the expression levels of miR-137 and three candidate target genes (ZNF804A, CACNA1C, TCF4) in the DLPFC of postmortem brain tissue from 2 independent cohorts: 1) 26 subjects (10 control (CTR), 7 schizophrenia (SZ), 9 bipolar disorder (BD)) collected at the UCI brain bank; and 2) 99 subjects (33 CTR, 35 SZ, 31 BD) obtained from the Stanley Medical Research Institute (SMRI). MiR-137 expression in the DLPFC did not differ between diagnoses. We also explored the relationship between rs1625579 genotypes and miR-137 expression. Significantly lower miR-137 expression levels were observed in the homozygous TT subjects compared to TG and GG subjects in the control group (30% decrease, p-value=0.03). Moreover, reduced miR-137 levels in TT subjects corresponded to increased levels of the miR-137 target gene TCF4. The miR-137 expression pattern in 9 brain regions was significant for regional effect (ANOVA p-value=1.83E-12), with amygdala and hippocampus having the highest miR-137 expression level. In conclusion, decreased miR-137 expression is associated with the SZ risk allele of rs1625579, and potential regulation of TCF4, another SZ candidate gene. This study offers additional support for involvement of miR-137 and downstream targets as mechanisms of risk for psychiatric disorders.
schizophrenia; bipolar disorder; rs1625579; miR-137; TCF4; gene expression
Multi-site longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures.
Magnetic Resonance Imaging; Neuroanatomy; Reproducibility of Results; Computer-Assisted Image Processing; Cerebral Cortex; Thalamus; Hippocampus; Amygdala
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site
There is a major resurgence of interest in brown adipose tissue (BAT) biology, particularly regarding its determinants and consequences in newborns and infants. Reliable methods for non-invasive BAT measurement in human infants have yet to be demonstrated. The current study first validates methods for quantitative BAT imaging of rodents post mortem followed by BAT excision and re-imaging of excised tissues. Identical methods are then employed in a cohort of in vivo infants to establish the reliability of these measures and provide normative statistics for BAT depot volume and fat fraction. Using multi-echo water-fat MRI, fat- and water-based images of rodents and neonates were acquired and ratios of fat to the combined signal from fat and water (fat signal fraction) were calculated. Neonatal scans (n = 22) were acquired during natural sleep to quantify BAT and WAT deposits for depot volume and fat fraction. Acquisition repeatability was assessed based on multiple scans from the same neonate. Intra- and inter-rater measures of reliability in regional BAT depot volume and fat fraction quantification were determined based on multiple segmentations by two raters. Rodent BAT was characterized as having significantly higher water content than WAT in both in situ as well as ex vivo imaging assessments. Human neonate deposits indicative of bilateral BAT in spinal, supraclavicular and axillary regions were observed. Pairwise, WAT fat fraction was significantly greater than BAT fat fraction throughout the sample (ΔWAT-BAT = 38%, p<10−4). Repeated scans demonstrated a high voxelwise correlation for fat fraction (Rall = 0.99). BAT depot volume and fat fraction measurements showed high intra-rater (ICCBAT,VOL = 0.93, ICCBAT,FF = 0.93) and inter-rater reliability (ICCBAT,VOL = 0.86, ICCBAT,FF = 0.93). This study demonstrates the reliability of using multi-echo water-fat MRI in human neonates for quantification throughout the torso of BAT depot volume and fat fraction measurements.
This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery.
Functional magnetic resonance imaging; fMRI; multi-center; multi-site; FIRST Biomedica Informatics Research Network; FBIRN
Structural brain measures are employed as endophenotypes in the search for schizophrenia susceptibility genes. We analyzed two independent structural imaging datasets with voxel-based morphometry and with source-based morphometry, a multivariate, independent components analysis, to determine the stability and heritability of regional gray matter concentration abnormalities in schizophrenia. The samples comprised 209 and 102 patients with schizophrenia and 208 and 96 healthy volunteers, respectively. The second sample additionally included non-ill siblings of participants with and without schizophrenia. A standard voxel-based analysis showed reproducible regional gray matter deficits in the affected participants compared with unrelated, unaffected controls in both datasets: patients showed significant gray matter concentration deficits in cortical frontal, temporal, and insular lobes. Source-based morphometry (SBM) was applied to the gray matter images of the entire sample to determine the effects of diagnosis on networks of covarying structures. The SBM analysis extracted 24 significant sets of covarying regions (components). Four of these components showed significantly lower gray matter concentrations in patients (p < .05). We determined the familiality of the observed SBM components based on 66 sibling pairs (25 discordant for schizophrenia). Two components, one including the medial frontal, insular, inferior frontal, and temporal lobes, and the other including the posterior occipital lobe, showed significant familiality (p < .05). We conclude that structural brain deficits in schizophrenia are replicable, and that SBM can extract unique familial and likely heritable components. SBM provides a useful data reduction technique that can provide measures that may serve as endophenotypes for schizophrenia.
Schizophrenia; brain structure; heritability; Independent Components Analysis
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer’s disease1,2 and is reduced in schizophrenia3, major depression4 and mesial temporal lobe epilepsy5. Whereas many brain imaging phenotypes are highly heritable6,7, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10−16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10−12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10−7).
Why do memory abilities vary so greatly across individuals and cognitive domains? Although memory functions are highly heritable, what exactly is being genetically transmitted? Here we review evidence for the contribution of both common and partially independent inheritance of distinct aspects of memory function. We begin by discussing the assessment of long-term memory and its underlying neural and molecular basis. We then consider evidence for both specialist and generalist genes underlying individual variability in memory, indicating that carving memory into distinct subcomponents may yield important information regarding its genetic architecture. And finally we review evidence from both complex and single-gene disorders, which provide insight into the molecular mechanisms underlying the genetic basis of human memory function.
heritability; declarative memory; schizophrenia; Alzheimer’s Disease; Neurofibromatosis I
Background: This multi-site study compares resting state fMRI amplitude of low frequency fluctuations (ALFF) and fractional ALFF (fALFF) between patients with schizophrenia (SZ) and healthy controls (HC).
Methods: Eyes-closed resting fMRI scans (5:38 min; n = 306, 146 SZ) were collected from 6 Siemens 3T scanners and one GE 3T scanner. Imaging data were pre-processed using an SPM pipeline. Power in the low frequency band (0.01–0.08 Hz) was calculated both for the original pre-processed data as well as for the pre-processed data after regressing out the six rigid-body motion parameters, mean white matter (WM) and cerebral spinal fluid (CSF) signals. Both original and regressed ALFF and fALFF measures were modeled with site, diagnosis, age, and diagnosis × age interactions.
Results: Regressing out motion and non-gray matter signals significantly decreased fALFF throughout the brain as well as ALFF in the cortical edge, but significantly increased ALFF in subcortical regions. Regression had little effect on site, age, and diagnosis effects on ALFF, other than to reduce diagnosis effects in subcortical regions. There were significant effects of site across the brain in all the analyses, largely due to vendor differences. HC showed greater ALFF in the occipital, posterior parietal, and superior temporal lobe, while SZ showed smaller clusters of greater ALFF in the frontal and temporal/insular regions as well as in the caudate, putamen, and hippocampus. HC showed greater fALFF compared with SZ in all regions, though subcortical differences were only significant for original fALFF.
Conclusions: SZ show greater eyes-closed resting state low frequency power in frontal cortex, and less power in posterior lobes than do HC; fALFF, however, is lower in SZ than HC throughout the cortex. These effects are robust to multi-site variability. Regressing out physiological noise signals significantly affects both total and fALFF measures, but does not affect the pattern of case/control differences.
resting state fMRI; LFO; ALFF; schizophrenia; multi-site studies; effect size
Callosal volume reduction has been observed in patients with bipolar disorder, but whether these deficits reflect genetic vulnerability to the illness remains unresolved. Here, we used computational methods to map corpus callosum abnormalities in a population-based sample of twin pairs discordant for bipolar disorder. Twenty-one probands with bipolar I disorder (mean age 44.4 ± 7.5 years; 48% female), 19 of their non-bipolar co-twins, and 34 demographically matched control twin individuals underwent magnetic resonance imaging. Three-dimensional callosal surface models were created to visualize its morphologic variability and to localize group differences. Neurocognitive correlates of callosal area differences were additionally investigated in a subsample of study participants. Bipolar (BPI) probands, but not their co-twins, showed significant callosal thinning and area reduction, most pronounced in the genu and splenium, relative to healthy twins. Altered callosal curvature was additionally observed in BPI probands. In bipolar probands and co-twins, genu and splenium midsagittal areas were significantly correlated with verbal processing speed and response inhibition. These findings suggest that aberrant connections between cortical regions—possibly reflecting decreased myelination of white matter tracts—may be involved in bipolar pathophysiology. However, findings of callosal thinning appear to be disease related, rather than reflecting genetic vulnerability to bipolar illness.
magnetic resonance imaging; mood disorders; myelination; processing speed; twin study
No objective diagnostic biomarkers or laboratory tests have yet been developed for psychotic illness. Magnetic resonance imaging (MRI) studies consistently find significant abnormalities in multiple brain structures in psychotic patients relative to healthy control subjects, but these abnormalities show substantial overlap with anatomic variation that is in the normal range and therefore nondiagnostic. Recently, efforts have been made to discriminate psychotic patients from healthy individuals using machine-learning-based pattern classification methods on MRI data.
Three-dimensional cortical gray matter density (GMD) maps were generated for 36 patients with recent-onset psychosis and 36 sex- and age-matched control subjects using a cortical pattern matching method. Between-group differences in GMD were evaluated. Second, the sparse multinomial logistic regression classifier included in the Multivariate Pattern Analysis in Python machine-learning package was applied to the cortical GMD maps to discriminate psychotic patients from control subjects.
Patients showed significantly lower GMD, particularly in prefrontal, cingulate, and lateral temporal brain regions. Pattern classification analysis achieved 86.1% accuracy in discriminating patients from controls using leave-one-out cross-validation.
These results suggest that even at the early stage of illness, psychotic patients present distinct patterns of regional cortical gray matter changes that can be discriminated from the normal pattern. These findings indicate that we can detect complex patterns of brain abnormality in early stages of psychotic illness, which has critical implications for early identification and intervention in individuals at ultra-high risk for developing psychosis/schizophrenia.
Classification; cortical pattern matching; MRI; psychosis; PyMVPA; schizophrenia
Although schizophrenia is highly heritable, the search for susceptibility genes has been challenging. The “endophenotype” approach is an alternative method for measuring phenotypic variation that may make it easier to identify susceptibility genes in the context of complexly inherited traits. Neuroimaging methods in particular offer a powerful way to bridge the neurobiology of genes and behavior. Such investigations may be further empowered by complementary strategies involving chromosomal abnormalities associated with schizophrenia, which can help to localize causative genes and better understand the genetic complexity of the illness. Here, we illustrate our use of these convergent approaches, with a focus on neuroimaging studies using novel computational brain mapping algorithms, to investigate genetic influences on brain structure in the development of psychosis. These studies provide compelling evidence that specific genetic loci suspected to predispose to schizophrenia may affect quantitative variation in neural indicators underlying the neurobehavioral phenotype, and illustrate how genetic-neuroimaging paradigms can improve our understanding of the pathogenesis of this highly disabling mental illness.
psychosis; brain mapping; genetic; neuroanatomy; chromosome 22q11.2; velocardiofacial syndrome; twin study; DISC1
Language processing abnormalities are a hallmark feature of schizophrenia. Yet, no study to date has investigated underlying neural networks associated with discourse processing in adolescents at clinical high risk (CHR) for developing psychosis.
Forty CHR youth and 24 demographically comparable healthy controls underwent functional magnetic resonance imaging while performing a naturalistic discourse processing paradigm. We assessed differences in blood oxygenation level-dependent (BOLD) activity between task conditions (Topic Maintenance vs. Reasoning) and between groups. Furthermore, we examined the association of regional brain activity with symptom severity and social outcome at follow-up, 6 to 24 months after the scan.
Relative to controls, CHR participants showed increased neural activity in a network of language-associated brain regions, including the medial prefrontal cortex bilaterally, left inferior frontal (LIFG; BA44/45, 47) and middle temporal gyri, and the anterior cingulate (BA24&32). Further, increased activity in the superior temporal gyrus (STG), caudate, and LIFG distinguished those who subsequently developed psychosis. Within the CHR sample, severity of positive formal thought disorder at follow-up was positively correlated with signal change in the LIFG, superior frontal gyrus, and inferior/middle temporal gyri, whereas social outcome was inversely correlated with signal change in the LIFG and anterior cingulate.
These findings are consistent with a neural inefficiency hypothesis in those at greatest risk for psychosis, and additionally suggest that baseline activation differences may predict symptomatic and functional outcome. These results highlight the need to further investigate the neural systems involved in conversion to psychosis, and how language disruption changes over time in at-risk adolescents.
fMRI; schizophrenia; inferior frontal gyrus; psychosis prodrome; discourse; functional neuroimaging
Patients with schizophrenia show altered patterns of functional activation during working memory processing; specifically, high-performing patients appear to hyper-activate and low-performing patients appear to hypo-activate when compared with controls. It remains unclear how these individual differences in neurophysiological activation relate to the clinical presentation of the syndrome. In this study, this relationship is examined using partial least squares (PLS), a multivariate statistical technique that selects underlying latent variables based on the covariance between two sets of variables, in this case, clinical variables and regional fMRI activations during a verbal working memory task. The PLS analysis extracted two latent variables, and the significance of these associations was confirmed through permutation. Lower levels of activation during task performance across frontal and parietal regions of interest in the left hemisphere was found to covary with poorer role functioning and greater severity of negative and disorganized symptoms, while lower activation in right frontal and subcortical regions of interest was found to covary with better social functioning and fewer positive symptoms. These results suggest that appropriately lateralized patterns of functional activation during working memory processing are related to the severity of negative and disorganized symptoms and level of role and social functioning in schizophrenia.
fMRI; partial least squares; verbal working memory
Previous neuroimaging studies of working memory (WM) in schizophrenia have generated conflicting findings of hypo- and hyper-frontality, discrepancies potentially driven by differences in task difficulty and/or performance. This study proposes and tests a new model of the performance-activation relationship in schizophrenia by combining changes by load with overall individual differences in performance. Fourteen patients with recent-onset schizophrenia and eighteen controls underwent functional magnetic resonance imaging while performing a parametric verbal WM task. Group level differences followed a linear “cross-over” pattern, such that in controls, activation in the dorsolateral prefrontal cortex (DLPFC) increased as performance decreased, while patients showed the opposite. Overall, low performing patients were hypoactive and high performing patients hyperactive relative to controls. However, patients and controls showed similar functions of activation by load in which activation rises with task difficulty but levels off or slightly decreases at higher loads. Moreover, across all loads and at their own WM capacity, higher performing patients showed greater DLPFC activation than controls, while lower performing patients activated least. This study establishes a novel framework for predicting the relationship between functional activation and WM performance by combining changes of activation by WM load occurring within each subject with the overall differences in activation associated with general WM performance. Essentially, increasing task difficulty correlates asymptotically with increasing activation in all subjects, but depending on their behavioral performance, patients show overall hyper-versus hypofrontality, a pattern potentially derived from individual differences in underlying cellular changes that may relate to levels of functional disability.
prefrontal cortex; magnetic resonance imaging; efficiency; task performance; memory; schizophrenia; brain; cognition
Schizophrenia and related psychoses are associated with brain structural abnormalities. Recent findings in ‘at risk’ populations have identified progressive changes in various brain regions preceding illness onset, while changes especially in prefrontal and superior temporal regions have been demonstrated in first-episode schizophrenia patients. However, the timing of the cortical changes and their regional extent, relative to the emergence of psychosis, has not been clarified. We followed individuals at high-risk for psychosis to determine whether structural changes in the cerebral cortex occur with the onset of psychosis. We hypothesized that progressive volume loss occurs in prefrontal regions during the transition to psychosis.
35 individuals at ultra-high risk (UHR) for developing psychosis, of whom 12 experienced psychotic onset by 1-year follow-up (‘converters’), participated in a longitudinal structural MRI study. Baseline and follow-up T1-weighted MR images were acquired and longitudinal brain surface contractions were assessed using Cortical Pattern Matching.
Significantly greater brain contraction was found in the right prefrontal region in the ‘converters’ compared with UHR cases who did not develop psychosis (‘non-converters’).
These findings show cortical volume loss is associated with the onset of psychosis, indicating ongoing pathological processes during the transition stage to illness. The prefrontal volume loss is in line with structural and functional abnormalities in schizophrenia, suggesting a critical role for this change in the development of psychosis.
schizophrenia; MRI; brain mapping; longitudinal; prodrome; ultra-high risk
The 22q11.2 deletion syndrome (velocardiofacial/DiGeorge syndrome, 22q11.2DS) involves cardiac and craniofacial anomalies, marked deficits in visuospatial cognition, and elevated rates of psychosis. Although the mechanism is unknown, characteristic brain alterations may predispose to development of psychosis and cognitive deficits in 22q11DS. We applied cortical pattern matching and new methods for measuring cortical thickness in millimeters to structural magnetic resonance images of 21 children with confirmed 22q11.2 deletions and 13 demographically matched healthy comparison subjects. Thickness was mapped at 65 536 homologous points, based on 3-dimensional distance from the cortical gray-white matter interface to the external gray-cerebrospinal fluid boundary. A pattern of regionally specific cortical thinning was observed in superior parietal cortices and right parietooccipital cortex, regions critical for visuospatial processing, and bilaterally in the most inferior portion of the inferior frontal gyrus (pars orbitalis), a key area for language development. Several of the 30 genes encoded in the deleted segment are highly expressed in the developing brain and known to affect early neuronal migration. These brain maps reveal how haploinsufficiency for such genes can affect cortical development and suggest a possible underlying pathophysiology of the neurobehavioral phenotype.
brain mapping; chromosome 22; genetics; MRI; velocardiofacial syndrome
The 22q11.2 deletion syndrome (velocardiofacial/DiGeorge syndrome) is a neurogenetic condition associated with visuospatial deficits, as well as elevated rates of attentional disturbance, mood disorder, and psychosis. Previously, we detected pronounced cortical thinning in superior parietal and right parieto-occipital cortices in patients with this syndrome, regions critical for visuospatial processing. Here we applied cortical pattern-matching algorithms to structural magnetic resonance images obtained from 21 children with confirmed 22q11.2 deletions (ages 8–17) and 13 demographically matched comparison subjects, in order to map cortical thickness across the medial hemispheric surfaces. In addition, cortical models were remeshed in frequency space to compute their surface complexity. Cortical maps revealed a pattern of localized thinning in the ventromedial occipital–temporal cortex, critical for visuospatial representation, and the anterior cingulate, a key area for attentional control. However, children with 22q11.2DS showed significantly increased gyral complexity bilaterally in occipital cortex. Regional gray matter volumes, particularly in medial frontal cortex, were strongly correlated with both verbal and nonverbal cognitive functions. These findings suggest that aberrant parieto-occipital brain development, as evidenced by both increased complexity and cortical thinning in these regions, may be a neural substrate for the deficits in visuospatial and numerical understanding characteristic of this syndrome.
brain mapping; cognition; genetics; MRI; velocardiofacial syndrome
Regional gray matter (GM) abnormalities are well known to exist in patients with chronic schizophrenia. Voxel-based morphometry (VBM) has been previously used on structural magnetic resonance images (MRI) data to characterize these abnormalities. Two multisite schizophrenia studies, the Functional Biomedical Informatics Research Network and the Mind Clinical Imaging Consortium, which include 9 data collection sites, are evaluating the efficacy of pooling structural imaging data across imaging centers. Such a pooling of data could yield the increased statistical power needed to elucidate effects that may not be seen with smaller samples. VBM analyses were performed to evaluate the consistency of patient versus control gray matter concentration (GMC) differences across the study sites, as well as the effects of combining multisite data. Integration of data from both studies yielded a large sample of 503 subjects, including 266 controls and 237 patients diagnosed with schizophrenia, schizoaffective or schizophreniform disorder. The data were analyzed using the combined sample, as well as analyzing each of the 2 multisite studies separately. A consistent pattern of reduced relative GMC in schizophrenia patients compared with controls was found across all study sites. Imaging center-specific effects were evaluated using a region of interest analysis. Overall, the findings support the use of VBM in combined multisite studies. This analysis of schizophrenics and controls from around the United States provides continued supporting evidence for GM deficits in the temporal lobes, anterior cingulate, and frontal regions in patients with schizophrenia spectrum disorders.
schizophrenia; VBM; gray matter concentration; multisite; multicenter; multiscanner
AKT1, encoding the protein kinase B, has been associated with the genetic etiology of schizophrenia and bipolar disorder. However, minuscule data exist on the role of different alleles of in measurable quantitative endophenotypes, such as cognitive abilities and neuroanatomical features, showing deviations in schizophrenia and bipolar disorder. We evaluated the contribution of AKT1 to quantitative cognitive traits and 3D high-resolution neuroanatomical images in a Finnish twin sample consisting of 298 twins: 61 pairs with schizophrenia (8 concordant), 31 pairs with bipolar disorder (5 concordant) and 65 control pairs matched for age, sex and demographics. An AKT1 allele defined by the SNP rs1130214 located in the UTR of the gene revealed association with cognitive traits related to verbal learning and memory (P=0.0005 for a composite index). This association was further fortified by a higher degree of resemblance of verbal memory capacity in pairs sharing the rs1130214 genotype compared to pairs not sharing the genotype. Furthermore, the same allele was also associated with decreased gray matter density in medial and dorsolateral prefrontal cortex (P < 0.05). Our findings support the role of AKT1 in the genetic background of cognitive and anatomical features, known to be affected by psychotic disorders. The established association of the same allelic variant of AKT1 with both cognitive and neuroanatomical aberrations could suggest that AKT1 exerts its effect on verbal learning and memory via neural networks involving prefrontal cortex.
AKT1; quantitative trait loci; magnetic resonance imaging; association
Neuroimaging methods offer a powerful way to bridge the gaps between genes, neurobiology and behavior. Such investigations may be further empowered by complementary strategies involving chromosomal abnormalities associated with particular neurobehavioral phenotypes, which can help to localize causative genes and better understand the genetics of complex traits in the general population. Here we review the evidence from studies using these convergent approaches to investigate genetic influences on brain structure: 1) Studies of common genetic variation associated with particular neuroanatomic phenotypes, and 2) Studies of possible ‘genetic subtypes’ of neuropsychiatric disorders with very high penetrance, with a focus on neuroimaging studies using novel computational brain mapping algorithms. Finally, we discuss the contribution of behavioral neurogenetics research to our understanding of the genetic basis of neuropsychiatric disorders in the broader population.
Brain; Genetic; Neuroimaging; Psychosis; Chromosome 22q11.2; Fragile X; COMT; velocardiofacial syndrome; Williams Syndrome; neurofibromatosis I
The nature, neural underpinnings, and etiology of deficits in verbal declarative memory in patients with schizophrenia remain unclear. To examine the contributions of genes and environment to verbal recall and recognition performance in this disorder, the California Verbal Learning Test was administered to a large population-based Finnish twin sample, which included schizophrenic and schizoaffective patients, their non-ill monozygotic (MZ) and dizygotic (DZ) co-twins, and healthy control twins. Compared with controls, patients and their co-twins showed relatively greater performance deficits on free recall compared with recognition. Intra-pair differences between patients and their non-ill co-twins in hippocampal volume and memory performance were highly positively correlated. These findings are consistent with the view that genetic influences are associated with reduced verbal recall in schizophrenia, but that non-genetic influences further compromise these abnormalities in patients who manifest the full-blown schizophrenia phenotype, with this additional degree of disease-related declarative memory deficit mediated in part by hippocampal pathology.
CVLT; Twin; Neuropsychology; Memory; Genes; Environment; Hippocampus
Deficits in learning and memory are among the most robust correlates of schizophrenia. It has been hypothesized that these deficits are in part due to reduced conscious recollection and increased reliance on familiarity assessment as a basis for retrieval. The Remember-Know (R-K) paradigm was administered to 35 patients with chronic schizophrenia and 35 healthy controls. In addition to making “remember” and “know” judgments, the participants were asked to make forced choice recognition judgments with regard to details about the learning episode. Analyses comparing response types showed a significant reduction in “remember” responses and a significant increase in “know” responses in schizophrenia patients relative to controls. Both patients and controls recalled more details of the learning episode for “remember” compared to “know” responses, although, in particular for “remember” responses, patients recalled fewer details compared with controls. Notably, patients recognized fewer inter-item but not intra-item stimulus features compared with controls. These findings suggest deficits in organizing and integrating relational information during the learning episode and/or using relational information for retrieval. A Dual-Process Signal Detection interpretation of these findings suggests that recollection in chronic schizophrenia is significantly reduced, while familiarity is not. Additionally, a unidimensional Signal Detection Theory interpretation suggests that chronic schizophrenia patients show a reduction in memory strength, and an altered criterion on the memory strength distribution for detecting new compared with old stimuli but not for detecting stimuli that are remembered versus familiar. Taken together, these findings are consistent with a deficit in recollection and increased reliance on familiarity in making recognition memory judgments in chronic schizophrenia.
schizophrenia; psychosis; chronic; memory; episodic; recognition; recollection; familiarity; context; remember; know