Decomposition of brain diffusion imaging data uncovers latent schizophrenias with distinct patterns of white matter anisotropy

Structural and functional alterations in different types of delusions across schizophrenia spectrum: A systematic review

BACKGROUND

Despite the high clinical role of delusions as a transnosological psychopathological phenomenon, the number of experimental studies on the different types of delusions across schizophrenia spectrum is still relatively small, and their results are somehow inconsistent. We aimed to understand the current state of knowledge regarding the structural and functional brain alterations in delusions to determine whether particular types of delusions are associated with specific brain changes and to identify common alterations underlying the formation and persistence of delusions regardless of their content.

METHODS

For this systematic review, we followed PRISMA guidelines to search in PubMed for English papers published between 1953 and September 30, 2023. The initial inclusion criteria for screening purposes were articles that investigated delusions or subclinical delusional beliefs in schizophrenia spectrum disorders, high clinical or genetic risk for schizophrenia using fMRI, sMRI or/and dwMRI methods. Exclusion criteria during the screening phase were articles that investigated lesion-induced or substance-induced delusions, delusions in Alzheimer's disease and other neurocognitive disorders, single case studies and non-human studies. The publication metadata were uploaded to the web-tool for working on systematic reviews, Rayyan. For each of the studies, a table was filled out with detailed information.

RESULTS

We found 1752 records, of which 95 full-text documents were reviewed and included in the current paper. Both nonspecific and particular types of delusions were associated with widespread structural and functional alterations. The most prominent areas affected across all types of delusions were the superior temporal cortex (predominantly left language processing areas), anterior cingulate/medial prefrontal cortex and insula. The most reproducible findings in paranoia may be alterations in the functioning of the amygdala and its interactions with other regions. Somatic delusions and delusional infestation were mostly characterized by alterations in the insula and thalamus.

DISCUSSION

The data are ambiguous; however, in general the predictive processing framework seems to be the most widely accepted approach to explaining different types of delusions. Aberrant prediction errors signaling during processing of social, self-generated and sensory information may lead to inaccuracies in assessing the intentions of others, self-relevancy of ambiguous stimuli, misattribution of self-generated actions and unusual sensations, which could provoke delusional ideation with persecutory, reference, control and somatic content correspondingly. However, currently available data are still insufficient to draw conclusions about the specific biological mechanisms of predictive coding account of delusions. Thus, further studies exploring more homogeneous groups and interaction of diagnoses by types of delusions are needed. There are also some limitations in this review. Studies that investigate delusions induced by lesions, substance abuse or neurodegeneration and studies using modalities other than fMRI, sMRI or dwMRI were not included in the review. Due to the relatively small number of publications, we systematized them based on a certain type of delusions, while the results could also be affected by the diagnosis of patients, the presence and type of therapy, illness duration etc.

Application of a localized morphometrics approach to imaging-derived brain phenotypes for genotype-phenotype associations in pediatric mental health and neurodevelopmental disorders

Introduction

Quantitative global or regional brain imaging measurements, known as imaging-specific or -derived phenotypes (IDPs), are commonly used in genotype-phenotype association studies to explore the genomic architecture of the brain and how it may be affected by neurological diseases (e.g., Alzheimer's disease), mental health (e.g., depression), and neurodevelopmental disorders (e.g., attention-deficit hyperactivity disorder [ADHD]). For this purpose, medical images have been used as IDPs using a voxel-wise or global approach via principal component analysis. However, these methods have limitations related to multiple testing or the inability to isolate high variation regions, respectively.

Methods

To address these limitations, this study investigates a localized, principal component analysis-like approach for dimensionality reduction of cross-sectional T1-weighted MRI datasets utilizing diffeomorphic morphometry. This approach can reduce the dimensionality of images while preserving spatial information and enables the inclusion of spatial locality in the analysis. In doing so, this method can be used to explore morphometric brain changes across specific components and spatial scales of interest and to identify associations with genome regions in a multivariate genome-wide association study. For a first clinical feasibility study, this method was applied to data from the Adolescent Brain Cognitive Development (ABCD) study, including adolescents with ADHD (n = 1,359), obsessive-compulsive disorder (n = 1,752), and depression (n = 1,766).

Results

Meaningful associations of specific morphometric features with genome regions were identified with the data and corresponded to previous found brain regions in the respective mental health and neurodevelopmental disorder cohorts.

Discussion

In summary, the localized, principal component analysis-like approach can reduce the dimensionality of medical images while still being able to identify meaningful local brain region alterations that are associated with genomic markers across multiple scales. The proposed method can be applied to various image types and can be easily integrated in many genotype-phenotype association study setups.

Diffusion Basis Spectrum Imaging of White Matter in Schizophrenia and Bipolar Disorder

Background

Multiple studies point to the role of neuroinflammation in the pathophysiology of schizophrenia (SCZ), however, there have been few in vivo tools for imaging brain inflammation. Diffusion basis spectrum imaging (DBSI) is an advanced diffusion-based MRI method developed to quantitatively assess microstructural alternations relating to neuroinflammation, axonal fiber, and other white matter (WM) pathologies.

Methods

We acquired one-hour-long high-directional diffusion MRI data from young control (CON, n = 27), schizophrenia (SCZ, n = 21), and bipolar disorder (BPD, n = 21) participants aged 18-30. We applied Tract-based Spatial Statistics (TBSS) to allow whole-brain WM analyses and compare DBSI-derived isotropic and anisotropic diffusion measures between groups. Clinical relationships of DBSI metrics with clinical symptoms were assessed across SCZ and control participants.

Results

In SCZ participants, we found a generalized increase in DBSI-derived cellularity (a putative marker of neuroinflammation), a decrease in restricted fiber fraction (a putative marker of apparent axonal density), and an increase in extra-axonal water (a putative marker of vasogenic edema) across several WM tracts. There were only minimal WM abnormalities noted in BPD, mainly in regions of the corpus callosum (increase in DTI-derived RD and extra-axonal water). DBSI metrics showed significant partial correlations with psychosis and mood symptoms across groups.

Conclusion

Our findings suggest that SCZ involves generalized white matter neuroinflammation, decreased fiber density, and demyelination, which is not seen in bipolar disorder. Larger studies are needed to identify medication-related effects. DBSI metrics could help identify high-risk groups requiring early interventions to prevent the onset of psychosis and improve outcomes.

White matter microstructure alterations of the posterior limb of internal capsule in first-episode drug naive schizophrenia patients

OBJECTIVES

Previous studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores.

METHODS

Thirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated.

RESULTS

The Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR_P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST_P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (fSTR_P) and NDI deviation in STR_P and CST_P compared to PLIC region (fPLIC) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of fPLIC reaching 0.872.

CONCLUSION

The study's findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology.

The Neurobiology of Formal Thought Disorder

The concept of Formal Thought Disorder (FTD) is an ambiguous and disputed one, even though it has endured as a core psychopathological construct in clinical Psychiatry. FTD can be summarized as a multidimensional construct, reflecting difficulties or idiosyncrasies in thinking, language, and communication in general and is usually subdivided into positive versus negative. In this article, we aim to explore the putative neurobiology of FTD, ranging from changes in neurotransmitter systems to alterations in the functional anatomy of the brain. We also discuss recent critiques of the operationalist view of FTD and how they might fit in its biological underpinnings. We conclude that FTD might be the observable phenotype of many distinct underlying alterations in different proportions.

Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis

The human brain's resting-state functional connectivity (rsFC) provides stable trait-like measures of differences in the perceptual, cognitive, emotional, and social functioning of individuals. The rsFC of the prefrontal cortex is hypothesized to mediate a person's rational self-government, as is also measured by personality, so we tested whether its connectivity networks account for vulnerability to psychosis and related personality configurations. Young adults were recruited as outpatients or controls from the same communities around psychiatric clinics. Healthy controls (n = 30) and clinically stable outpatients with bipolar disorder (n = 35) or schizophrenia (n = 27) were diagnosed by structured interviews, and then were assessed with standardized protocols of the Human Connectome Project. Data-driven clustering identified five groups of patients with distinct patterns of rsFC regardless of diagnosis. These groups were distinguished by rsFC networks that regulate specific biopsychosocial aspects of psychosis: sensory hypersensitivity, negative emotional balance, impaired attentional control, avolition, and social mistrust. The rsFc group differences were validated by independent measures of white matter microstructure, personality, and clinical features not used to identify the subjects. We confirmed that each connectivity group was organized by differential collaborative interactions among six prefrontal and eight other automatically-coactivated networks. The temperament and character traits of the members of these groups strongly accounted for the differences in rsFC between groups, indicating that configurations of rsFC are internal representations of personality organization. These representations involve weakly self-regulated emotional drives of fear, irrational desire, and mistrust, which predispose to psychopathology. However, stable outpatients with different diagnoses (bipolar or schizophrenic psychoses) were highly similar in rsFC and personality. This supports a diathesis-stress model in which different complex adaptive systems regulate predisposition (which is similar in stable outpatients despite diagnosis) and stress-induced clinical dysfunction (which differs by diagnosis).

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture

BACKGROUND

Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

METHOD

A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

RESULTS

We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

CONCLUSION

The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence

Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.

Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review

Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.

The role of white matter abnormality in the left anterior corona radiata: In relation to formal thought disorder in patients with schizophrenia

White matter abnormality has been widely reported in patients with schizophrenia (Sz). However, few studies have focused on the relationship between the white matter deficit and formal thought disorder (FTD). Moreover, the role of genetic high risk in FTD-related white matter deficit remains unclear. The present study recruited 46 Sz patients, 18 unaffected first-degree relatives of Sz patients, and 29 healthy controls. There was a widespread fractional anisotropy (FA) reduction in Sz. In addition, reduced FA in the left anterior corona radiata was related to more severe FTD symptoms in Sz. However, the genetic high-risk group only showed lower mean FA in the left anterior limb of the internal capsule than healthy controls. Our findings suggest that abnormality in the left anterior corona radiata may only occur in Sz but not in the genetic high-risk group. Such an abnormality might be associated with the severity of FTD symptoms. Meanwhile, genetic vulnerability may contribute to the abnormality in the left anterior limb of the internal capsule. Better analytical methods are needed to validate our results.

Personality Traits as Markers of Psychosis Risk in Kenya: Assessment of Temperament and Character

Specific personality traits have been proposed as a schizophrenia-related endophenotype and confirmed in siblings at risk for psychosis. The relationship of temperament and character with psychosis has not been previously investigated in Africa. The study was conducted in Kenya, and involved participants at clinical high-risk (CHR) for psychosis (n = 268) and controls (n = 251), aged 15–25 years. CHR status was estimated using the Structured Interview of Psychosis-Risk Syndromes (SIPS) and the Washington Early Psychosis Center Affectivity and Psychosis (WERCAP) Screen. Student’s t-tests were used to assess group differences on the Temperament and Character Inventory (TCI). Neurocognitive functioning, stress severity, and substance use were correlated with the TCI, correcting for psychosis severity. CHR participants were more impulsive (ie, higher novelty seeking [NS]) and asocial (ie, lower reward dependence) than controls. They were also more schizotypal (ie, high self-transcendence [ST] and lower self-directedness [SD] and cooperativeness [CO] than controls). CO was related to logical reasoning, abstraction, and verbal memory. Stress severity correlated with high HA and schizotypal character traits. Lifetime tobacco use was related to NS, and lifetime marijuana use to high NS, low SD and high ST. Temperament and character of Kenyan CHR youth is similar to that observed in schizophrenia. Psychosis risk in Kenya is associated with impulsive, asocial, and schizotypal traits. CHR adolescents and young adults with schizophrenia-specific personality traits may be most at risk for developing a psychotic disorder and to require early intervention to improve outcomes.

Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth

Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

Overdispersed gene expression in schizophrenia

Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants a daunting task. Gene expression analyses hold the promise of revealing connections between dysregulated transcription and underlying variants in SCZ. However, the most commonly used differential expression analysis often assumes grouped samples are from homogeneous populations and thus cannot be used to detect expression variance differences between samples. Here, we applied the test for equality of variances to normalized expression data, generated by the CommonMind Consortium (CMC), from brains of 212 SCZ and 214 unaffected control (CTL) samples. We identified 87 genes, including VEGFA (vascular endothelial growth factor) and BDNF (brain-derived neurotrophic factor), that showed a significantly higher expression variance among SCZ samples than CTL samples. In contrast, only one gene showed the opposite pattern. To extend our analysis to gene sets, we proposed a Mahalanobis distance-based test for multivariate homogeneity of group dispersions, with which we identified 110 gene sets with a significantly higher expression variability in SCZ, including sets of genes encoding phosphatidylinositol 3-kinase (PI3K) complex and several others involved in cerebellar cortex morphogenesis, neuromuscular junction development, and cerebellar Purkinje cell layer development. Taken together, our results suggest that SCZ brains are characterized by overdispersed gene expression-overall gene expression variability among SCZ samples is significantly higher than that among CTL samples. Our study showcases the application of variability-centric analyses in SCZ research.

Uncovering Tumour Heterogeneity through PKR and nc886 Analysis in Metastatic Colon Cancer Patients Treated with 5-FU-Based Chemotherapy

Colorectal cancer treatment has advanced over the past decade. The drug 5-fluorouracil is still used with a wide percentage of patients who do not respond. Therefore, a challenge is the identification of predictive biomarkers. The protein kinase R (PKR also called EIF2AK2) and its regulator, the non-coding pre-mir-nc886, have multiple effects on cells in response to numerous types of stress, including chemotherapy. In this work, we performed an ambispective study with 197 metastatic colon cancer patients with unresectable metastases to determine the relative expression levels of both nc886 and PKR by qPCR, as well as the location of PKR by immunohistochemistry in tumour samples and healthy tissues (plasma and colon epithelium). As primary end point, the expression levels were related to the objective response to first-line chemotherapy following the response evaluation criteria in solid tumours (RECIST) and, as the second end point, with survival at 18 and 36 months. Hierarchical agglomerative clustering was performed to accommodate the heterogeneity and complexity of oncological patients' data. High expression levels of nc886 were related to the response to treatment and allowed to identify clusters of patients. Although the PKR mRNA expression was not associated with chemotherapy response, the absence of PKR location in the nucleolus was correlated with first-line chemotherapy response. Moreover, a relationship between survival and the expression of both PKR and nc886 in healthy tissues was found. Therefore, this work evaluated the best way to analyse the potential biomarkers PKR and nc886 in order to establish clusters of patients depending on the cancer outcomes using algorithms for complex and heterogeneous data.

Uncovering the complex genetics of human character

Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

Uncovering the complex genetics of human temperament

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

The complex genetics and biology of human temperament: a review of traditional concepts in relation to new molecular findings

Recent genome-wide association studies (GWAS) have shown that temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term learning and memory. The results were replicated in three independent samples despite variable cultures and environments. The identified genes were enriched in pathways activated by behavioral conditioning in animals, including the two major molecular pathways for response to extracellular stimuli, the Ras-MEK-ERK and the PI3K-AKT-mTOR cascades. These pathways are activated by a wide variety of physiological and psychosocial stimuli that vary in positive and negative valence and in consequences for health and survival. Changes in these pathways are orchestrated to maintain cellular homeostasis despite changing conditions by modulating temperament and its circadian and seasonal rhythms. In this review we first consider traditional concepts of temperament in relation to the new genetic findings by examining the partial overlap of alternative measures of temperament. Then we propose a definition of temperament as the disposition of a person to learn how to behave, react emotionally, and form attachments automatically by associative conditioning. This definition provides necessary and sufficient criteria to distinguish temperament from other aspects of personality that become integrated with it across the life span. We describe the effects of specific stimuli on the molecular processes underlying temperament from functional, developmental, and evolutionary perspectives. Our new knowledge can improve communication among investigators, increase the power and efficacy of clinical trials, and improve the effectiveness of treatment of personality and its disorders.

N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia

OBJECTIVE

We propose and develop a novel biclustering (N-BiC) approach for performing N-way biclustering of neuroimaging data. Our approach is applicable to an arbitrary number of features from both imaging and behavioral data (e.g., symptoms). We applied it to structural MRI data from patients with schizophrenia.

METHODS

It uses a source-based morphometry approach [i.e., independent component analysis of gray matter segmentation maps] to decompose the data into a set of spatial maps, each of which includes regions that covary among individuals. Then, the loading parameters for components of interest are entered to an exhaustive search, which incorporates a modified depth-first search technique to carry out the biclustering, with the goal of obtaining submatrices where the selected rows (individuals) show homogeneity in their expressions of selected columns (components) and vice versa.

RESULTS

Findings demonstrate that multiple biclusters have an evident association with distinct brain networks for the different types of symptoms in schizophrenia. The study identifies two components: inferior temporal gyrus (16) and brainstem (7), which are related to positive (distortion/excess of normal function) and negative (diminution/loss of normal function) symptoms in schizophrenia, respectively.

CONCLUSION

N-BiC is a data-driven method of biclustering MRI data that can exhaustively explore relationships/substructures from a dataset without any prior information with a higher degree of robustness than earlier biclustering applications.

SIGNIFICANCE

The use of such approaches is important to investigate the underlying biological substrates of mental illness by grouping patients into homogeneous subjects, as the schizophrenia diagnosis is known to be relatively nonspecific and heterogeneous.

What is the natural measurement unit of temperament: single traits or profiles?

There is fundamental doubt about whether the natural unit of measurement for temperament and personality corresponds to single traits or to multi-trait profiles that describe the functioning of a whole person. Biogenetic researchers of temperament usually assume they need to focus on individual traits that differ between individuals. Recent research indicates that a shift of emphasis to understand processes within the individual is crucial for identifying the natural building blocks of temperament. Evolution and development operate on adaptation of whole organisms or persons, not on individual traits or categories. Adaptive functioning generally depends on feedback among many variable processes in ways that are characteristic of complex adaptive systems, not machines with separate parts. Advanced methods of unsupervised machine learning can now be applied to genome-wide association studies and brain imaging in order to uncover the genotypic-phenotypic architecture of traits like temperament, which are strongly influenced by complex interactions, such as genetic epistasis, pleiotropy and gene-environment interactions. We have found that the heritability of temperament can be nearly fully explained by a large number of genetic variants that are unique for multi-trait profiles, not single traits. The implications of this finding for research design and precision medicine are discussed.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

White matter integrity in schizophrenia and bipolar disorder: Tract- and voxel-based analyses of diffusion data from the Connectom scanner

Background

Diffusion imaging abnormalities have been associated with schizophrenia (SZ) and bipolar disorder (BD), indicating impaired structural connectivity. Newer methods permit the automated reconstruction of major white matter tracts from diffusion-weighted MR images in each individual's native space. Using high-definition diffusion data from SZ and BP subjects, we investigated brain white matter integrity using both an automated tract-based and voxel-based methods.

Methods

Using a protocol matched to the NIH (Young-Adult) Human Connectome Project (and collected on the same customized ‘Connectom’ scanner), diffusion scans were acquired from 87 total participants (aged 18–30), grouped as SZ (n = 24), BD (n = 33) and healthy controls (n = 30). Fractional anisotropy (FA) of eighteen white matter tracks were analyzed using the TRACULA software. Voxel-wise statistical analyses of diffusion data was carried out using the tract-based spatial statistics (TBSS) software. TRACULA group effects and clinical correlations were investigated using analyses of variance and multiple regression.

Results

TRACULA analysis identified a trend towards lower tract FA in SZ patients, most significantly in the left anterior thalamic radiation (ATR; p = .04). TBSS results showed significantly lower FA voxels bilaterally within the cerebellum and unilaterally within the left ATR, posterior thalamic radiation, corticospinal tract, and superior longitudinal fasciculus in SZ patients compared to controls (FDR corrected p < .05). FA in BD patients did not significantly differ from controls using either TRACULA or TBSS. Multiple regression showed FA of the ATR as predicting chronic mania (p = .0005) and the cingulum-angular bundle as predicting recent mania (p = .02) in patients. TBSS showed chronic mania correlating with FA voxels within the left ATR and corpus callosum.

Conclusions

White matter abnormality in SZ varies in severity across different white matter tract regions. Our results indicate that voxel-based analysis of diffusion data is more sensitive than tract-based analysis in identifying such abnormalities. Absence of white matter abnormality in BD may be related to medication effects and age.

•

Our study investigated white matter integrity in 87 young schizophrenia, bipolar disorder and control subjects with a tract-based (TRACULA) and a voxel-based (TBSS) approach, using high-definition diffusion imaging data obtained from the Human Connectome Project ‘Connectom’ scanner.

•

TRACULA evaluated fractional anisotropy (FA) from 18 white matter tracts. TBSS evaluated regional white matter FA.

•

TRACULA identified a trend towards lower tract FA in schizophrenia subjects across multiple tracts. TBSS results showed mainly unilaterally decreased FA voxels in schizophrenia subjects. FA in bipolar patients did not significantly differ from controls with either method.

•

With TRACULA, multiple regression showed that anterior thalamic radiation FA predicted chronic affectivity and cingulum-angular bundle FA predicted recent mania in patients. With TBSS, chronic mania correlated with FA voxels within the left anterior thalamic radiation and corpus callosum.

Formal thought disorder is related to aberrations in language-related white matter tracts in patients with schizophrenia

This study examined the hypothesis that a fronto-temporal disconnection in the language network underpins formal thought disorder (FTD) in schizophrenia. Forty-nine patients with a schizophrenia spectrum disorder (27 with mild FTD, 22 with severe FTD) and 26 healthy controls (HC) were included. Overall psychopathology and FTD were assessed by the Positive and Negative Syndrome Scale and the Thought, Language, and Communication scale, respectively. White matter (WM) microstructure was analysed using Tract-Based Spatial Statistics. In patients, severity of overall FTD (TLC Sum Score) was predicted by decreased fractional anisotropy (FA) in the right superior longitudinal fasciculus (SLF), and severity of negative FTD (TLC Emptiness subscale) was predicted by increased FA in the left SLF and arcuate fasciculus (AF). Notably, these results were no longer significant after correction for multiple comparisons. Compared with HC, patients showed lower FA in all the investigated language-related WM tracts as well as across the whole WM skeleton. No difference in FA was found between patients with severe and patients with mild FTD. Our results are compatible with earlier studies reporting impairments in widely spread WM tracts including those related to language processing in patients with schizophrenia.

Corpus callosum shape and morphology in youth across the psychosis Spectrum

The corpus callosum is the largest white matter tract in the human brain connecting and coordinating homologous regions of the right and left hemispheres and has been strongly implicated in the pathogenesis of psychosis. We investigated corpus callosum morphology in a large community cohort of 917 individuals (aged 8-21), including 267 endorsing subsyndromal or threshold psychotic symptoms (207 on the psychosis spectrum and 60 with limited psychosis based on previously published criteria) and 650 non-psychotic volunteers. We used a highly reliable and previously published algorithm to automatically identify the midsagittal plane and to align the corpus callosum along the anterior and posterior commissures for segmentation, thereby eliminating these sources of error variance in dependent measures, which included perimeter, length, mean thickness and shape (circularity). The parcellation scheme divided the corpus callosum into 7 subregions that consisted of the rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium. Both individuals endorsing psychotic symptoms and those with limited psychosis had significantly (p<.05) smaller area and lower thickness measures compared to healthy volunteers, but did not differ significantly from each other. Findings were relatively widespread indicating a relatively global effect not circumscribed to any particular corpus callosum subregion. These data are consistent with the hypothesis that corpus callosum abnormalities may be evident early in the course of illness and predate the onset of frank psychosis. Given that these measures can be easily obtained and are highly reliable they may assist in the identification of individuals at future risk for psychosis.

Is formal thought disorder in schizophrenia related to structural and functional aberrations in the language network? A systematic review of neuroimaging findings

Formal thought disorder (FTD) is a core feature of schizophrenia, a marker of illness severity and a predictor of outcome. The underlying neural mechanisms are still a matter of debate. This study aimed at 1) reviewing the literature on the neural correlates of FTD in schizophrenia, and 2) testing the hypothesis that FTD correlates with structural and functional aberrations in the language network. Medline, PsychInfo, and Embase were searched for neuroimaging studies, which applied a clinical measure to assess FTD in adults with schizophrenia and were published in English or German in peer-reviewed journals until December 2016. Of 412 articles identified, 61 studies were included in the review. Volumetric studies reported bilateral grey matter deficits (L > R) to be associated with FTD in the inferior frontal gyrus, the superior temporal gyrus and the inferior parietal lobe. The same regions showed hyperactivity in resting state functional magnetic resonance imaging (fMRI) studies and both hyper- and hypoactivity in fMRI studies that employed semantic processing or free speech production tasks. Diffusion tensor imaging studies demonstrated white matter aberrations in fibre tracts that connect the frontal and temporo-parietal regions. FTD in schizophrenia was found to be associated with structural and functional aberrations in the language network. However, there are studies that did not find an association between FTD and neural aberrations of the language network and regions not included in the language network have been associated with FTD. Thus, future research is needed to clarify the specificity of the language network for FTD in schizophrenia.

A systematic review of task-based functional neuroimaging studies investigating language, semantic and executive processes in thought disorder

The aim of the current systematic review was to synthesise the research that has investigated thought disorder (TD) using task-based functional neuroimaging techniques to target executive, language, or semantic functions. Thirty-five pertinent studies were identified from January 1990 to August 2016. Functional correlates of TD included the superior and middle temporal, fusiform, and inferior frontal gyri bilaterally, as well as the left and right cingulate cortex, the right caudate nucleus, and the cerebellum. TD-related increases and decreases in activation were both evident in most of these regions. However, the specificity of these correlates from general clinical and cognitive influences is unknown. The cortical regions implicated overlap with those thought to contribute to language and semantic systems. Cortico-striatal circuitry may also play a role in some aspects of TD through aberrant salience representation and inappropriate attentional prioritisation. To advance the field further, greater integration across structural, functional, and behavioural measures is required, in addition to non-unitary considerations of TD.

An Update on Promising Biomarkers in Schizophrenia

Given the heterogeneity of symptoms in patients with schizophrenia and current treatment limitations, biomarkers may play an important role in diagnosis, subtype stratification, and the assessment of treatment response. Though many potential biomarkers have been studied, we have chosen to focus on some of the most promising and potentially clinically relevant biomarkers to review herein. These include markers of inflammation, neuroimaging biomarkers, brain-derived neurotrophic factor, genetic/epigenetic markers, and speech analysis. This will provide a broad overview of putative biomarkers that could become clinically relevant in the future, though none currently appear ready to assist the clinician in identifying cases of schizophrenia, subtypes of the disorder, treatment choice, or response. Nonetheless, some biomarkers, such as C-reactive protein (CRP), may be useful at identifying individuals who may be more highly inflamed, which could drive treatment choice. Though checking CRP is not a standard of practice, this is one example of how biomarkers may drive treatment decisions in the future, supporting precision medicine. Similarly, technological advances may one day allow clinicians to detect changes in speech patterns, which could represent a noninvasive, clinically useful tool in the future. We conclude the review by highlighting two important potential clinical uses for biomarkers in schizophrenia: the identification of individuals who may convert from clinical high risk and the stratification of patients via different biomarkers that may supersede clinical diagnosis. Given the enormous burden of illness of schizophrenia, the search for clinically relevant biomarkers is of great importance to improve the lives of patients with the disorder.

Elucidation of shared and specific white matter findings underlying psychopathology clusters in schizophrenia

BACKGROUND

Schizophrenia is associated with diverse white matter (WM) brain abnormalities. In this study, we sought to examine the WM microstructural findings which underlie clinical psychopathology clusters in schizophrenia and hypothesized that these symptom clusters are associated with common and unique WM tracts.

METHODS

Overall, 76 healthy controls (HC), and 148 patients with schizophrenia (SZ) were recruited and severity of symptomatology in schizophrenia was assessed using the Positive and Negative Syndrome Scale. WM fractional anisotropy (FA) values were extracted from their diffusion tensor images. Psychopathology clusters were first determined using factor analysis and the relationship between these symptom factors and FA values were then assessed with structural equation modelling, which included covariates such as age, sex, duration of illness and medications prescribed.

RESULTS

Patients with schizophrenia had reduced FA in the genu of corpus callosum (gCC) compared to HC. A three-factor model, namely Positive, Negative, Disorganised factors, was determined as the best fit for the data. All three psychopathology factors were associated with decreased FA in the gCC and bilateral cingulate gyrus. Higher Negative factor scores were uniquely associated with decreased FA in the right sagittal striatum and right superior longitudinal fasciculus.

CONCLUSIONS

This study found shared and specific WM changes and their associations with specific symptom clusters, which potentially allows for monitoring of such white matter findings associated with clinical presentations in schizophrenia over treatment and illness course.

Chronic Ketamine Exposure Causes White Matter Microstructural Abnormalities in Adolescent Cynomolgus Monkeys

Acute and repeated exposures to ketamine mimic aspects of positive, negative, and cognitive symptoms of schizophrenia in humans. Recent studies by our group and others have shown that chronicity of ketamine use may be a key element for establishing a more valid model of cognitive symptoms of schizophrenia. However, current understanding on the long-term consequences of ketamine exposure on brain circuits has remained incomplete, particularly with regard to microstructural changes of white matter tracts that underpin the neuropathology of schizophrenia. Thus, the present study aimed to expand on previous investigations by examining causal effects of repeated ketamine exposure on white matter integrity in a non-human primate model. Ketamine or saline (control) was administered intravenously for 3 months to male adolescent cynomolgus monkeys (n = 5/group). Diffusion tensor imaging (DTI) experiments were performed and tract-based spatial statistics (TBSS) was used for data analysis. Fractional anisotropy (FA) was quantified across the whole brain. Profoundly reduced FA on the right side of sagittal striatum, posterior thalamic radiation (PTR), retrolenticular limb of the internal capsule (RLIC) and superior longitudinal fasciculus (SLF), and on the left side of PTR, middle temporal gyrus and inferior frontal gyrus were observed in the ketamine group compared to controls. Diminished white matter integrity found in either fronto-thalamo-temporal or striato-thalamic connections with tracts including the SLF, PTR, and RLIC lends support to similar findings from DTI studies on schizophrenia in humans. This study suggests that chronic ketamine exposure is a useful pharmacological paradigm that might provide translational insights into the pathophysiology and treatment of schizophrenia.

Proteome dynamics during postnatal mouse corpus callosum development

Formation of cortical connections requires the precise coordination of numerous discrete phases. This is particularly significant with regard to the corpus callosum, whose development undergoes several dynamic stages including the crossing of axon projections, elimination of exuberant projections, and myelination of established tracts. To comprehensively characterize the molecular events in this dynamic process, we set to determine the distinct temporal expression of proteins regulating the formation of the corpus callosum and their respective developmental functions. Mass spectrometry-based proteomic profiling was performed on early postnatal mouse corpus callosi, for which limited evidence has been obtained previously, using stable isotope of labeled amino acids in mammals (SILAM). The analyzed corpus callosi had distinct proteomic profiles depending on age, indicating rapid progression of specific molecular events during this period. The proteomic profiles were then segregated into five separate clusters, each with distinct trajectories relevant to their intended developmental functions. Our analysis both confirms many previously-identified proteins in aspects of corpus callosum development, and identifies new candidates in understudied areas of development including callosal axon refinement. We present a valuable resource for identifying new proteins integral to corpus callosum development that will provide new insights into the development and diseases afflicting this structure.

Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia

Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz) has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores. We, therefore, present a novel data-driven framework using biclustered independent component analysis to detect subtypes from the reliable and stable gray matter concentration (GMC) of patients with Sz. The developed methodology consists of the following steps: source-based morphometry (SBM) decomposition, selection and sorting of two component loadings, subtype component reconstruction using group information-guided ICA (GIG-ICA). This framework was applied to the top two group discriminative components namely the insula/superior temporal gyrus/inferior frontal gyrus (I-STG-IFG component) and the superior frontal gyrus/middle frontal gyrus/medial frontal gyrus (SFG-MiFG-MFG component) from our previous SBM study, which showed diagnostic group difference and had the highest effect sizes. The aggregated multisite dataset consisted of 382 patients with Sz regressed of age, gender, and site voxelwise. We observed two subtypes (i.e., two different subsets of subjects) each heavily weighted on these two components, respectively. These subsets of subjects were characterized by significant differences in positive and negative syndrome scale (PANSS) positive clinical symptoms (p = 0.005). We also observed an overlapping subtype weighing heavily on both of these components. The PANSS general clinical symptom of this subtype was trend level correlated with the loading coefficients of the SFG-MiFG-MFG component (r = 0.25; p = 0.07). The reconstructed subtype-specific component using GIG-ICA showed variations in voxel regions, when compared to the group component. We observed deviations from mean GMC along with conjunction of features from two components characterizing each deciphered subtype. These inherent variations in GMC among patients with Sz could possibly indicate the need for personalized treatment and targeted drug development.

Neural substrates underlying delusions in schizophrenia

Delusions are cardinal positive symptoms in schizophrenia; however, the neural substrates of delusions remain unknown. In the present study, we investigated the neural correlates of delusions in schizophrenia using multi-modal magnetic resonance imaging (MRI) techniques. Diffusion, structural and perfusion MRIs were performed in 19 schizophrenia patients with severe delusions, 30 patients without delusions and 30 healthy controls. Fractional anisotropy (FA), gray matter volume (GMV) and cerebral blood flow (CBF) were voxel-wisely compared among the three groups. Although patients without delusions exhibited decreased FA in white matter regions and decreased GMV in gray matter regions relative to controls, patients with severe delusions demonstrated comparable FA in all of these white matter regions and similar GMV in most of these gray matter regions. Both patient subgroups had less GMV in the amygdala and anterior cingulate cortex than controls. Although two patient subgroups showed consistent CBF changes relative to controls, only CBF in the anterior cingulate cortex was lower in patients with severe delusions than in patients without delusions. These findings suggest that schizophrenia patients with severe delusions have relatively normal structural integrity. Importantly, the excessively reduced perfusion in the anterior cingulate cortex may be associated with the development of delusions in schizophrenia.

Strategies for Advancing Disease Definition Using Biomarkers and Genetics: The Bipolar and Schizophrenia Network for Intermediate Phenotypes

It is critical for psychiatry as a field to develop approaches to define the molecular, cellular, and circuit basis of its brain diseases, especially for serious mental illnesses, and then to use these definitions to generate biologically based disease categories, as well as to explore disease mechanisms and illness etiologies. Our current reliance on phenomenology is inadequate to support exploration of molecular treatment targets and disease formulations, and the leap directly from phenomenology to disease biology has been limiting because of broad heterogeneity within conventional diagnoses. The questions addressed in this review are formulated around how we can use brain biomarkers to achieve disease categories that are biologically based. We have grouped together a series of vignettes as examples of early approaches, all using the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP) biomarker database and collaborators, starting off with describing the foundational statistical methods for these goals. We use primarily criterion-free statistics to identify pertinent groups of involved genes related to psychosis as well as symptoms, and finally, to create new biologically based disease cohorts within the psychopathological dimension of psychosis. Although we do not put these results forward as final formulations, they represent a novel effort to rely minimally on phenomenology as a diagnostic tool and to fully embrace brain characteristics of structure, as well as molecular and cellular characteristics and function, to support disease definition in psychosis.

Cerebral white matter structure is associated with DSM-5 schizophrenia symptom dimensions

Diffusion tensor imaging (DTI) studies have provided evidence of widespread white matter (WM) abnormalities in schizophrenia. Although these abnormalities appear clinically significant, the relationship to specific clinical symptoms is limited and heterogeneous. This study examined the association between WM microstructure and the severity of the five main DSM-5 schizophrenia symptom dimensions. DTI was measured in forty patients with schizophrenia spectrum disorders. Using Tract-Based Spatial Statistics controlling for age, gender and antipsychotic dosage, our analyses revealed significant negative relationships between WM microstructure and two DSM-5 symptom dimensions: Whereas abnormal psychomotor behavior was particularly related to WM of motor tracts, negative symptoms were associated with WM microstructure of the prefrontal and right temporal lobes. However, we found no associations between WM microstructure and delusions, hallucinations or disorganized speech. These data highlight the relevance of characteristic WM disconnectivity patterns as markers for negative symptoms and abnormal psychomotor behavior in schizophrenia and provide evidence for relevant associations between brain structure and aberrant behavior.

•

DTI study of brain-behavior associations of the new DSM-5 schizophrenia dimensions.

•

The severity of the DSM-5 abnormal psychomotor behavior dimension is related to white matter microstructure in motor tracts.

•

Associations of the DSM-5 negative symptom dimension with white matter microstructure are found in prefrontal and temporal clusters.

•

Characteristic patterns of white matter microstructure argue for relevant associations between brain structure and aberrant behavior in schizophrenia.

Collection of developmental history in the evaluation of schizophrenia spectrum disorders

BACKGROUND

Schizophrenia is a heterogeneous disorder that is characterized by varying levels of hallucinations, delusions, negative symptoms, and disorganized features. The presence and severity of neurodevelopmental precursors and premorbid psychopathology also vary among individuals. To fully understand individual patients and to sort out phenotypic heterogeneity for genetic research studies, instruments designed to collect developmental history relevant to schizophrenia may be helpful.

OBJECTIVE

The goal was to describe a pair of self-report and parent-report instruments developed for the purpose of collecting the developmental history of patients with known or suspected schizophrenia spectrum disorders.

METHOD

Two developmental history instruments were designed for use in studies of brain morphology and cognition in schizophrenia probands and their unaffected siblings. The instruments focus mainly on motor abnormalities and other features that have been described as schizophrenia precursors.

RESULTS

The Motor Skills History Form is a brief self-report form that asks about patients' childhood and adolescent motor abilities as well as their current motor functioning. The Developmental & Motor History Form is a more detailed parent-rated form that covers aspects of patients' early (infant/preschool) development; their childhood and adolescent motor abilities; any childhood behaviors that may be related to later psychosis risk; and their history of any neurological, emotional, or cognitive disorders diagnosed during childhood or adolescence. The instruments can be used either for interviews or as self-administered questionnaires. The parent-rated form has been used for research and for the clinical assessment of children and adolescents with complex neurodevelopmental presentations with or without strong evidence of schizophrenia risk.

CONCLUSIONS

The collection of developmental history information is important when evaluating individuals with schizophrenia and related disorders. The Motor Skills History Form and the Developmental & Motor History Form can be used to collect this information for clinical evaluation or research purposes.

Diffusion Imaging of White Matter In Schizophrenia: Progress and Future Directions

Diffusion tensor imaging (DTI) is a powerful tool for the in-vivo assessment of white matter microstructure. The application of DTI methodologies to the study of schizophrenia has supported and advanced the hypothesis of schizophrenia as a disorder of disrupted connectivity. In the context of impaired structural connectivity, the extended time frame of white matter development may offer unique opportunities for treatment that can capitalize on the neural flexibility that is still present in the period leading up to and after disease onset. Therefore, it is important to gain a clear understanding of white matter deficits and how they may emerge and change across the illness. However, while there is broad consistency in the findings of white matter deficits in patients with schizophrenia, there is also a great deal of variability in specific findings across studies. In this review, the aim is to move beyond summarizing case-control analyses, to consider the many factors that may impact DTI measures, to explain variability of findings, and to explore future directions for the field. The topics explored include ways to parse DTI patterns associated with different disease subtypes, ways in which novel and established treatments might interact with or enhance white matter, ways of dissociating developmental change from the disease process itself, and understanding the role of emerging analytic methodologies.