Brain derived neurotrophic factor (BDNF) is a critical component of the molecular mechanism of memory formation. Variation in the BDNF gene, particularly the rs6265 (val(66)met) single nucleotide ...polymorphism (SNP), has been linked to variability in human memory performance and to both the structure and physiological response of the hippocampus, which plays a central role in memory processing. However, these effects have not been consistently reported, which may reflect the modest size of the samples studied to date. Employing a meta-analytic approach, we examined the effect of the BDNF val(66)met polymorphism on human memory (5922 subjects) and hippocampal structure (2985 subjects) and physiology (362 subjects). Our results suggest that variations in the rs6265 SNP of the BDNF gene have a significant effect on memory performance, and on both the structure and physiology of the hippocampus, with carriers of the met allele being adversely affected. These results underscore the role of BDNF in moderating variability between individuals in human memory performance and in mediating some of the neurocognitive impairments underlying neuropsychiatric disorders.
Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the ...multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. To evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls), patients were differentiated from controls with a sensitivity of 80.3% (95% CI: 76.7-83.5%) and a specificity of 80.3% (95% CI: 76.9-83.3%). Analysis of neuroimaging modality indicated higher sensitivity (84.46%, 95% CI: 79.9-88.2%) and similar specificity (76.9%, 95% CI: 71.3-81.6%) of rsfMRI studies as compared with structural MRI studies (sensitivity: 76.4%, 95% CI: 71.9-80.4%, specificity of 79.0%, 95% CI: 74.6-82.8%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019), and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% sensitivity and specificity.
Neuroimaging studies of schizophrenia have indicated that the development of auditory verbal hallucinations (AVHs) is associated with altered structural and functional connectivity within the ...perisylvian language network. However, these studies focussed mainly on either structural or functional alterations in patients with chronic schizophrenia. Therefore, they were unable to examine the relationship between the 2 types of measures and could not establish whether the observed alterations would be expressed in the early stage of the illness. We used diffusion tensor imaging and functional magnetic resonance imaging to examine white matter integrity and functional connectivity within the left perisylvian language network of 46 individuals with an at risk mental state for psychosis or a first episode of the illness, including 28 who had developed AVH group and 18 who had not (nonauditory verbal hallucination nAVH group), and 22 healthy controls. Inferences were made at P < .05 (corrected). The nAVH group relative to healthy controls showed a reduction of both white matter integrity and functional connectivity as well as a disruption of the normal structure-function relationship along the fronto-temporal pathway. For all measures, the AVH group showed intermediate values between healthy controls and the nAVH group. These findings seem to suggest that, in the early stage of the disorder, a significant impairment of fronto-temporal connectivity is evident in patients who do not experience AVHs. This is consistent with the hypothesis that, whilst mild disruption of connectivity might still enable the emergence of AVHs, more severe alterations may prevent the occurrence of the hallucinatory experience.
Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, ...these alterations are present in SIB to a lesser extent and are more pronounced during high cognitive demand, thus possibly representing one of the pathways in which familial risk is translated into the SCZ phenotype. Our aim is to measure the separability of SCZ and SIB from healthy controls (HC) using attentional control-dependent FC patterns, and to test to which extent these patterns span a continuum of neurofunctional alterations between HC and SCZ. 65 SCZ with 65 age and gender-matched HC and 39 SIB with 39 matched HC underwent the Variable Attentional Control (VAC) task. Load-dependent connectivity matrices were generated according to correct responses in each VAC load. Classification performances of high, intermediate and low VAC load FC on HC-SCZ and HC-SIB cohorts were tested through machine learning techniques within a repeated nested cross-validation framework. HC-SCZ classification models were applied to the HC-SIB cohort, and vice-versa. A high load-related decreased FC pattern discriminated between HC and SCZ with 66.9% accuracy and with 57.7% accuracy between HC and SIB. A high load-related increased FC network separated SIB from HC (69.6% accuracy), but not SCZ from HC (48.5% accuracy). Our findings revealed signatures of attentional FC abnormalities shared by SCZ and SIB individuals. We also found evidence for potential, SIB-specific FC signature, which may point to compensatory neurofunctional mechanisms in persons at familial risk for schizophrenia.
Two decades of studies suggest that computerized cognitive training (CCT) has an effect on cognitive improvement and the restoration of brain activity. Nevertheless, individual response to CCT ...remains heterogenous, and the predictive potential of neuroimaging in gauging response to CCT remains unknown. We employed multivariate pattern analysis (MVPA) on whole-brain resting-state functional connectivity (rsFC) to (neuro)monitor clinical outcome defined as psychosis-likeness change after 10-hours of CCT in recent onset psychosis (ROP) patients. Additionally, we investigated if sensory processing (SP) change during CCT is associated with individual psychosis-likeness change and cognitive gains after CCT. 26 ROP patients were divided into maintainers and improvers based on their SP change during CCT. A support vector machine (SVM) classifier separating 56 healthy controls (HC) from 35 ROP patients using rsFC (balanced accuracy of 65.5%, P < 0.01) was built in an independent sample to create a naturalistic model representing the HC-ROP hyperplane. This model was out-of-sample cross-validated in the ROP patients from the CCT trial to assess associations between rsFC pattern change, cognitive gains and SP during CCT. Patients with intact SP threshold at baseline showed improved attention despite psychosis status on the SVM hyperplane at follow-up (p < 0.05). Contrarily, the attentional gains occurred in the ROP patients who showed impaired SP at baseline only if rsfMRI diagnosis status shifted to the healthy-like side of the SVM continuum. Our results reveal the utility of MVPA for elucidating treatment response neuromarkers based on rsFC-SP change and pave the road to more personalized interventions.
Reserve in aging and Alzheimer's disease (AD) is defined as maintaining cognition at a relatively high level in the presence of neurodegeneration, an ability often associated with higher education ...among other life factors. Recent evidence suggests that higher resting-state functional connectivity within the frontoparietal control network, specifically the left frontal cortex (LFC) hub, contributes to higher reserve. Following up these previous resting-state fMRI findings, we probed memory-task related functional connectivity of the LFC hub as a neural substrate of reserve. In elderly controls (CN, n = 37) and patients with mild cognitive impairment (MCI, n = 17), we assessed global connectivity of the LFC hub during successful face-name association learning, using generalized psychophysiological interaction analyses. Reserve was quantified as residualized memory performance, accounted for gender and proxies of neurodegeneration (age, hippocampus atrophy, and APOE genotype). We found that greater education was associated with higher LFC-connectivity in both CN and MCI during successful memory. Furthermore, higher LFC-connectivity predicted higher residualized memory (i.e., reserve). These results suggest that higher LFC-connectivity contributes to reserve in both healthy and pathological aging.
Previous studies have shown that structural brain changes are among the best-studied candidate markers for schizophrenia (SZ) along with functional connectivity (FC) alterations of resting-state (RS) ...patterns. This study aimed to investigate effects of clinical and sociodemographic variables on the classification by applying multivariate pattern analysis (MVPA) to both gray matter (GM) volume and FC measures in patients with SZ and healthy controls (HC). RS and structural magnetic resonance imaging data (sMRI) from 74 HC and 71 SZ patients were obtained from a Mind Research Network COBRE dataset available via COINS (http://coins.mrn.org/dx). We used a MVPA framework using support-vector machines embedded in a repeated, nested cross-validation to generate a multi-modal diagnostic system and evaluate its generalizability. The dependence of neurodiagnostic performance on clinical and sociodemographic variables was evaluated. The RS classifier showed a slightly higher accuracy (70.5%) compared to the structural classifier (69.7%). The combination of sMRI and RS outperformed single MRI modalities classification by reaching 75% accuracy. The RS based moderator analysis revealed that the neurodiagnostic performance was driven by older SZ patients with an earlier illness onset and more pronounced negative symptoms. In contrast, there was no linear relationship between the clinical variables and neuroanatomically derived group membership measures. This study achieved higher accuracy distinguishing HC from SZ patients by fusing 2 imaging modalities. In addition the results of RS based moderator analysis showed that age of patients, as well as their age at the illness onset were the most important clinical features.
To date, the MRI-based individualized prediction of psychosis has only been demonstrated in single-site studies. It remains unclear if MRI biomarkers generalize across different centers and MR ...scanners and represent accurate surrogates of the risk for developing this devastating illness. Therefore, we assessed whether a MRI-based prediction system identified patients with a later disease transition among 73 clinically defined high-risk persons recruited at two different early recognition centers. Prognostic performance was measured using cross-validation, independent test validation, and Kaplan-Meier survival analysis. Transition outcomes were correctly predicted in 80% of test cases (sensitivity: 76%, specificity: 85%, positive likelihood ratio: 5.1). Thus, given a 54-month transition risk of 45% across both centers, MRI-based predictors provided a 36%-increase of prognostic certainty. After stratifying individuals into low-, intermediate-, and high-risk groups using the predictor's decision score, the high- vs low-risk groups had median psychosis-free survival times of 5 vs 51 months and transition rates of 88% vs 8%. The predictor's decision function involved gray matter volume alterations in prefrontal, perisylvian, and subcortical structures. Our results support the existence of a cross-center neuroanatomical signature of emerging psychosis enabling individualized risk staging across different high-risk populations. Supplementary results revealed that (1) potentially confounding between-site differences were effectively mitigated using statistical correction methods, and (2) the detection of the prodromal signature considerably depended on the available sample sizes. These observations pave the way for future multicenter studies, which may ultimately facilitate the neurobiological refinement of risk criteria and personalized preventive therapies based on individualized risk profiling tools.
Background
Formal thought disorder (FTD) has been associated with more severe illness courses and functional deficits in patients with psychotic disorders. However, it remains unclear whether the ...presence of FTD characterises a specific subgroup of patients showing more prominent illness severity, neurocognitive and functional impairments. This study aimed to identify stable and generalizable FTD-subgroups of patients with recent-onset psychosis (ROP) by applying a comprehensive data-driven clustering approach and to test the validity of these subgroups by assessing associations between this FTD-related stratification, social and occupational functioning, and neurocognition.
Methods
279 patients with ROP were recruited as part of the multi-site European PRONIA study (Personalised Prognostic Tools for Early Psychosis Management; www.pronia.eu). Five FTD-related symptoms (conceptual disorganization, poverty of content of speech, difficulty in abstract thinking, increased latency of response and poverty of speech) were assessed with Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS).
Results
The results with two patient subgroups showing different levels of FTD were the most stable and generalizable clustering solution (predicted clustering strength value = 0.86). FTD-High subgroup had lower scores in social (
p
fdr
< 0.001) and role (
p
fdr
< 0.001) functioning, as well as worse neurocognitive performance in semantic (
p
fdr
< 0.001) and phonological verbal fluency (
p
fdr
< 0.001), short-term verbal memory (
p
fdr
= 0.002) and abstract thinking (
p
fdr
= 0.010), in comparison to FTD-Low group.
Conclusions
Clustering techniques allowed us to identify patients with more pronounced FTD showing more severe deficits in functioning and neurocognition, thus suggesting that FTD may be a relevant marker of illness severity in the early psychosis pathway.
Abstract Previous studies have reported alterations in grey matter volume and cortical thickness in individuals at high risk of developing psychosis and patients in the early stages of the disorder. ...Because these studies have typically focused on either grey matter volume or cortical thickness separately, the relationship between these two types of alterations is currently unclear. In the present investigation we used both voxel-based cortical thickness (VBCT) and voxel-based morphometry (VBM) to examine neuroanatomical differences in 21 individuals with an At Risk Mental State (ARMS) for psychosis, 26 patients with a First Episode of Psychosis (FEP) and 24 healthy controls. Statistical inferences were made at P < 0.05 after correction for multiple comparisons. Cortical thinning in the right superior temporal gyrus was observed in both individuals at high risk of developing psychosis and patients with a first episode of the disorder, and therefore is likely to represent a marker of vulnerability. In contrast, the right posterior cingulate cortex showed cortical thinning in FEP patients relative to individuals at high risk, and therefore appears to be implicated in the onset of the disease. These neuroanatomical differences were expressed in terms of cortical thickness but not in terms of grey matter volume, and therefore may reflect specific cortical atrophy as opposed to variations in sulcal and gyral morphology.
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