Neurostructural, Neurofunctional, and Clinical Features of Chronic, Untreated Schizophrenia: A Narrative Review

Abstract

Studies of individuals with chronic, untreated schizophrenia (CUS) can provide important insights into the natural course of schizophrenia and how antipsychotic pharmacotherapy affects neurobiological aspects of illness course and progression. We systematically review 17 studies on the neuroimaging, cognitive, and epidemiological aspects of CUS individuals. These studies were conducted at the Shanghai Mental Health Center, Institute of Mental Health at Peking University, and Huaxi MR Research Center between 2013 and 2021. CUS is associated with cognitive impairment, severe symptoms, and specific demographic characteristics and is different significantly from those observed in antipsychotic-treated individuals. Furthermore, CUS individuals have neurostructural and neurofunctional alterations in frontal and temporal regions, corpus callosum, subcortical, and visual processing areas, as well as default-mode and somatomotor networks. As the disease progresses, significant structural deteriorations occur, such as accelerated cortical thinning in frontal and temporal lobes, greater reduction in fractional anisotropy in the genu of corpus callosum, and decline in nodal metrics of gray mater network in thalamus, correlating with worsening cognitive deficits and clinical outcomes. In addition, striatal hypertrophy also occurs, independent of antipsychotic treatment. Contrasting with the negative neurostructural and neurofunctional effects of short-term antipsychotic treatment, long-term therapy frequently results in significant improvements. It notably enhances white matter integrity and the functions of key subcortical regions such as the amygdala, hippocampus, and striatum, potentially improving cognitive functions. This narrative review highlights the progressive neurobiological sequelae of CUS, the importance of early detection, and long-term treatment of schizophrenia, particularly because treatment may attenuate neurobiological deterioration and improve clinical outcomes.

Introduction

Neurodegenerative effects in schizophrenia have been observed for several decades, and these neurostructural changes are accompanied by progressive worsening of clinical symptoms, deteriorating social functioning, and cognitive performance.^1–4 Interestingly, in some samples of acute, untreated schizophrenia, cognitive impairments^5–7 and neurostructural/neurofunctional changes^8–10 appear stable, including gray matter abnormalities in frontotemporal, thalamocortical, and subcortical circuits, and brain activity in frontoparietal and default-mode networks. However, long-term studies on schizophrenia reveal significant heterogeneity in these effects,^11–15 ostensibly due to the confounding effects of antipsychotic treatment, which impact not only target symptoms but also brain structure and function.^16,17 Specifically, most studies suggest improvement in positive symptoms over the long-term course of illness. In contrast, negative symptoms and cognitive deficits frequently persist,¹¹ with some reports of varying rates of cognitive decline.^18–20 Conversely, neurostructural changes exhibit variable loss over time in most^4,12,15 but not all studies.¹⁴ Consequently, distinguishing between changes that result from the natural progression of the disease and those related to long-term medication is challenging, which complicates our understanding of abnormalities at later stages in the illness and the trajectory of these effects over time.

Studying chronic, untreated schizophrenia (CUS) can provide critical insights into the underlying pathophysiology of schizophrenia. Cross-sectional data from various stages of schizophrenia provide important insights into changes in brain structure and function that may subtend the clinical progression of schizophrenia.^21,22 Moreover, comparing individuals with CUS to those who have been engaged in treatment may enhance our understanding of the effects of treatment on the neurobiology of schizophrenia.

CUS, which remains prevalent in rural communities of low- and middle-income countries such as China, provides a unique opportunity to understand the progression of this complex illness. CUS exists in such areas because of myriad factors,^17,22,23 including family stigma concerns, a lack of understanding and recognition of the severity of the illness, socioeconomic challenges, and rejection of treatment by some families. Moreover, the significant stigma and burden experienced by family and caregivers of individuals with schizophrenia in rural China further exacerbates the situation.

China’s national public health initiative^24,25 has facilitated the identification and treatment of individuals with CUS in rural areas. It provides a unique opportunity to study social functioning in addition to neurostructural and neurofunctional sequelae. Studies of these individuals have been primarily conducted at the Shanghai Mental Health Center, the Institute of Mental Health at Peking University, and Huaxi MR Research Center from 2013 to 2021. The participants were primarily recruited from the rural areas across Ningxia, Guangxi Autonomous Region, Chengdu, Hebei Province, and Chaoyang Districts in Beijing. These studies primarily focus on cognitive impairments and alterations in brain structure and function, shedding light on the broader implications for understanding and managing schizophrenia in similar contexts globally. Despite potential concerns about the generalizability of findings from specific geographic and ethnic backgrounds, prior studies^17,26 have demonstrated that schizophrenia exhibits consistent neural deficits across ethnically diverse groups. The insights from China, due to unique regional factors such as accessibility, socioeconomic status, and cultural perceptions of mental health, have substantial implications for other countries facing similar challenges, offering a framework for exploring schizophrenia’s untreated trajectory and enhancing the generalizability of our findings. Though there is no universal definition for the term “chronic,” we have focused on individuals with a duration of untreated psychosis (DUP) over 5 years^22,23,27 who have never received antipsychotic medication or have had only minimal antipsychotic medication exposure.

This narrative review comprehensively summarizes magnetic resonance imaging (MRI) findings in CUS, including biomarkers and their relationship to clinical symptoms and cognitive impairment. It also summarizes the effects of illness progression and antipsychotic treatment on brain structure and function and provides a framework for understanding the neurobiology of CUS.

Literature Review Protocol

B.T. and L.Y. independently conducted literature searches in Web of Science, PubMed, and Embase until April 1, 2024, using keywords such as “schizophrenia” plus “chronic” or “long-term” plus “never treated” or “never medicated” or “untreated” or “unmedicated” or “medicated-naïve” or “antipsychotic-naïve” or “treatment-naïve” or “drug-naïve.” The references of all included articles were checked manually for additional relevant studies. Inconsistencies were discussed and a consensus was reached. After exclusion criteria were applied, 17 studies were retained. Of these, 13 were neuroimaging studies, the features of which are summarized in Table 1. The remaining four studies concentrated on the clinical and epidemiological characteristics of chronic, untreated schizophrenia.^23,39–41

Clinical Characteristics of Chronic, Untreated Schizophrenia

Studies of psychiatric symptoms, social functioning, cognitive, and long-term outcomes of CUS are all from China,^23,39–41 with no studies from other countries found. Shanghai Mental Health Center recruited relatively large cohorts of individuals with CUS and patients with chronic schizophrenia who were receiving treatment in addition to healthy controls (HC) from rural areas of Ningxia Hui Autonomous Region and Guangxi Zhuang Autonomous Region in China. In this sample, individuals with CUS (n = 233, mean age = 52.6 ± 12.4 years, mean DUP = 23.9 ± 12.8 years) had impaired social cognition compared to treated patients with chronic schizophrenia and then HC, with the latter group having the best performance among the three groups.⁴² Another study from the same center found that a longer DUP had more severe cognitive deficits in CUS (n = 197, mean age = 52.1 ± 11.8 years, mean DUP = 23.5 ± 12.3 years), suggesting a progressive decline of cognitive function.²³ These cognitive deficits in CUS suggest progressive neurodegenerative changes over illness duration²³ and these findings contrast with shorter-term DUP studies, which report stable cognitive deficits independent of DUP,^5–7 thereby highlighting different patterns of cognitive function across various stages of schizophrenia.

Studies from Huaxi MR Research Center (HMRRC) of West China Hospital examining individuals with CUS (from within 35 km of downtown Chengdu, with sample sizes ranging from 21 to 35) and chronically treated patients with schizophrenia found clinical symptoms were greatest in untreated patients, followed by treated patients, highlighting the efficacy of long-term antipsychotic treatment.^{27,30,31,33,34} In a related study, Ran et al. conducted a 14-year longitudinal survey of individuals in rural areas surrounding Chengdu and found that patients with never-treated schizophrenia (baseline: n = 156, mean age = 48.2 ± 15.2 years, mean DUP = 13.7 ± 12.2 years; remaining untreated after 10 years: n = 67, mean age = 60.2 ± 12.3 years, mean DUP = 26.7 ± 11.1 years) had poorer long-term outcomes (eg, homelessness, increased mortality, lower rates of remission, more severe psychotic symptoms, and worse social functioning) compared to treated patients.³⁹ These findings highlight the effects of long DUP on cognitive functions, symptom severity, and outcomes, emphasizing the critical need for early and effective treatment strategies for schizophrenia patients, especially in rural and marginalized areas.

Similarly, an international study from Ireland, following first-episode psychosis for 20 years, consistent with these findings in China, demonstrates that shorter DUP are associated with better long-term psychopathology, functionality, and quality-of-life outcomes.⁴³ This study highlights the enduring benefits of early intervention and suggests that the patterns observed in China may be globally applicable, highlighting the need for prompt and effective treatment for schizophrenia worldwide.

Neuroimaging Findings in Chronic, Untreated Schizophrenia

Neurostructural and neurofunctional changes of schizophrenia have been well established and—across studies—correlate with symptom severity and cognitive deficits.^44,45

Structural Findings

Studies of CUS have examined multiple aspects of brain structure, including cortical thickness, gray matter volume, white matter integrity, and structural topological connectivity. In studies of CUS (n = 17, mean age = 38.5 ± 3.9 years, mean DUP = 15.4 ± 6.3 years) from the Institute of Mental Health, Peking University, gray matter volumes in the left superior and inferior temporal lobes,²⁸ left rostral anterior and posterior cingulate cortex²⁹ were decreased compared to HC. Notably, a significant correlation was also observed between the left posterior cingulate cortex volume and working memory performance in these patients.²⁹ The follow-up CUS studies from HMRRC by Zhang et al. (n = 25, mean age = 46.7 ± 13.5 years, mean DUP = 21.0 ± 12.0 years) and Liu et al. (n = 35, mean age = 48.0 ± 13.4 years, mean DUP = 20.2 ± 12.4 years) further reported deficits in cortical thickness, volume, and surface area across several key regions, including the frontal and temporal lobes, when compared to HC.^22,30 Conversely, increased cortical thickness in the left superior parietal lobe and increased volumes of the bilateral putamen have been observed in CUS. They may reflect the adaptive changes or abnormal development in response to the chronic untreated symptoms of schizophrenia.²² In another study of CUS (n = 29, mean age = 45.8 ± 13.0 years, mean DUP = 18.2 ± 11.4 years) from the same center, Hu et al. found volume reductions in bilateral hippocampus and across subfields compared to HC.³¹ Furthermore, compared to HC, individuals with CUS had accelerated cortical thinning in specific regions, such as the right ventromedial prefrontal cortex, left superior temporal gyrus, and right pars triangularis.²² Similarly, greater volume reductions in multiple hippocampal subfields were associated with longer DUP in CUS.³¹ In contrast, slower age-related cortical thinning of the superior parietal cortex and striatal volumetric abnormalities indicated a pattern of neurostructural deterioration or potential compensatory responses in CUS.²²

Using diffusion tensor imaging (DTI), multiple studies reveal white matter deficit in schizophrenia.^46,47 Fractional anisotropy (FA) and mean diffusivity (MD) were two crucial characteristics that assess the directionality and rate of water diffusion within the tissue, respectively, and can be used to probe white matter integrity in schizophrenia. In a study from Peking University, Liu et al. observed reduced FA in the left inferior fronto-occipital fasciculus and left inferior longitudinal fasciculus in CUS compared to HC,²⁸ and CUS individuals (n = 17) with more reduction had slower processing speeds and reduced verbal and visual learning.³² In a sample of CUS (n = 31, mean age = 46.4 ± 13.2 years, mean DUP = 21.3 ± 12.1 years) from HMRRC, Xiao and colleagues found widespread FA reductions in CUS, including in the genu of the corpus callosum and the right superior longitudinal fasciculus that was associated with total PANSS scores.³⁴ Furthermore, the faster age-related FA reduction in the genu of corpus callosum has been observed in CUS compared to HC, raising the possibility of progressive alterations because schizophrenia persists, particularly in individuals without treatment. Finally, Tao et al. from the same center reported altered white matter integrity of entire and subregional corpus callosum in CUS (n = 23, mean age = 44.3 ± 13.6 years, mean DUP = 16.4 ± 10.9 years) compared to HC.³⁵

Increasing recognition of brain dysconnectivity in schizophrenia has shifted the focus from isolated regional analyses to connectome networks^48,49 and this shift has enhanced our understanding of complex brain alterations in schizophrenia. For example, in a case/control comparisons of individuals with short-term (n = 156, mean age = 23.7 ± 7.3 years, mean DUP = 0.7 ± 0.9 years) and long-term untreated schizophrenia (n = 35, mean age = 47.8 ± 13.4 years, mean DUP 20.0 ± 12.6 years) from HMRRC,²¹ found distinct patterns of change in the thalamus, characterized by an increase in nodal centrality properties (such as nodal degree and efficiency) in the network in the early course of illness. This was followed by a decline of nodal connections later in the course of illness compared to HC. A similar pattern of early increase and subsequent normalization was also observed in the global metric of assortativity (quantifies the extent to which nodes with similar degrees are connected) and nodal efficiency of the left superior temporal pole. In addition, network abnormalities in the left thalamus were more pronounced in patients with longer DUP and more severe negative symptoms.²¹ Another study from the same center by Luo et al. explored white matter structural networks in individuals with CUS (n = 17, mean age = 47.3 ± 10.1 years, mean DUP = 18.9 ± 10.8 years).³³ They demonstrated reduced global efficiency and increased path length in CUS compared with HC. These effects were primarily restricted to subcortical and prefrontal regions, indicating a broad disruption in white matter network organization in CUS.

Functional Findings

Functional MRI (fMRI) has become an indispensable tool for investigating brain function and related circuitry^17,50 and reveals disruptions in sensory, cognitive, and affective brain circuitry in schizophrenia.⁵⁰ Wang et al.³⁷ studied minimally treated chronic schizophrenia patients (n = 21, mean age = 35.5 ± 7.1 years, mean DUP = 15.2 ± 7.1 years) in Hebei and Chaoyang Districts in Beijing and found widespread significant disruptions in both short-range and long-range functional connectivity. Short-range functional connectivity is reduced in chronic schizophrenia patients in the bilateral sensorimotor cortex, right lateral prefrontal cortex, left insula, and right lingual gyrus, compared to HC. In contrast, long-range functional connectivity strength decreased in the bilateral posterior cingulate cortex/precuneus and increased in the right lateral prefrontal cortex and lingual gyrus. These alterations correlated with the illness duration and negative symptom severity for short-range disruptions and with verbal learning, speed of processing, reasoning, and problem-solving for long-range disruptions, suggesting distinct neural circuitry changes contribute to neurocognitive and psychotic symptoms without long-term exposure to antipsychotic medications in chronic schizophrenia.³⁷ In studies conducted at HMRRC, Yao et al. employed graph theory to analyze functional brain networks in CUS (n = 21, mean age = 45.6 ± 12.0 years, mean DUP = 16.8 ± 11.1 years) and revealed altered nodal centralities in the left pre-/postcentral gyri compared to controls.²⁷ Individuals with CUS had reduced global efficacy and nodal centralities in the right amygdala/hippocampus and bilateral putamen/caudate, suggesting functional segregation and integration impairments. In contrast to previous reports of accentuated age-related reductions in gray and white matter in individuals with CUS,^22,34 no differential age-related effects were seen across groups in brain functional metrics.²⁷ Yang et al. from HMRRC focused on white matter function and demonstrated lower amplitude of low-frequency fluctuations in the splenium of corpus callosum in CUS individuals (n = 25, mean age = 47.1 ± 12.4 years, mean DUP = 18.1 ± 11.9 years).³⁶ This finding of decreased connectivity in the splenium of corpus callosum provides new perspectives on the functional alterations of white matter in CUS, consistent with structural findings,^34,35 highlighting the critical role of corpus callosum in the pathophysiological alterations in CUS individuals. Collectively, these fMRI studies offer invaluable insights into the functional brain alterations in CUS and underscore that brain functional disruptions are not just in specific regions but across extensive neural networks.

Furthermore, Zeng et al. at HMRRC employed the machine learning approach to identify significant regional structural alterations across multiple brain regions in patients with long-term illness, including the inferior temporal cortex, pars triangularis, hippocampus, calcarine cortex, and middle occipital regions.³⁸ Functionally, notable regional brain changes were observed in the inferior occipital cortex, rolandic operculum, and angular gyrus. Interestingly, these significant brain alterations were not detected in patients with a short-term illness, regardless of treatment status, pointing to the progressive nature of neuroanatomical and functional changes over the course of schizophrenia.³⁸ These findings have significantly improved our understanding of brain changes in chronic, untreated schizophrenia. It’s important to note, however, that the reliability and generalizability of machine learning models are contingent upon external validation using independent samples, making it essential for future research to include such validations to ensure robustness and applicability.

Overview of Neuroimaging Findings and Their Clinical Correlations

Neuroimaging studies of CUS in China, without the confounding effects of medication, have revealed widespread structural abnormalities in the later stages of schizophrenia, notably in the frontal and temporal lobes, corpus callosum, subcortical areas, and visual processing areas, while functional disruptions mainly involved in the default-mode network, subcortical-limbic, and somatomotor networks (Figure 1). These structural and functional abnormalities correlate with various symptoms and cognitive deficits. Notably, reductions in FA across multiple white matter tracts are associated with cognitive impairments and overall PANSS symptom severity. In addition, abnormal nodal gray matter network metrics in the thalamus correlate with the severity of negative PANSS symptoms. These findings highlight the critical impact of neural circuitry disruptions on both cognitive and psychotic symptoms in CUS patients, independent of antipsychotic medication effects. Contrast with the relative stability observed in brain measurements during the first few years after disease onset,^8–10 the later stages of schizophrenia exhibited progressive structural deteriorations, such as accelerated cortical thinning in the frontal and temporal lobes, more pronounced age-related reduction in FA in the genu of corpus callosum, and decline in nodal metrics of gray mater network in the thalamus, relative to HC. Hypertrophic changes were observed in the striatum and were not attributed to antipsychotic treatment. In addition, no differential age-related effects were observed between individuals with CUS and HC in brain functional metrics, indicating a complex interplay between structural and functional brain changes in schizophrenia over time. Table 1 provides an overview of published neuroimaging studies on individuals with CUS.

Long-Term Treatment Effects

Several neuroimaging studies have explored the short-term effects of antipsychotic treatment and have revealed widespread structural and functional changes involving prefrontal, temporal, and parietal cortices and basal ganglia.^51–55 However, withholding treatment is unethical and precludes longitudinal placebo-controlled studies. Eo ipso, this limits our understanding of the long-term effects of antipsychotic medication on schizophrenia. However, cross-sectional studies comparing individuals with CUS with DUP-matched chronically treated schizophrenia patients offer valuable insights into the impacts of longer-term antipsychotic medication on the brain. Further research focusing on specific medications, carefully characterizing specific symptoms, cognitive deficits, and other disease-modifying factors, may elucidate the long-term mechanisms of different medicines and other factors. Such studies will improve our understanding of their distinct effects on brain structure and function.

Long-Term Effects of Antipsychotic Medications on the Brain

Compared to chronically treated patients, individuals with CUS have greater volume reductions in multiple hippocampal subfields in the right hemisphere,³¹ greater FA decrease in various brain regions,^34,35 greater functional impairments in brain areas associated with emotion processing and cognition, including the amygdala, hippocampus, and striatum,²⁷ and hypoactivity in the splenium of corpus callosum (Figure 1).³⁶ These findings support the neuroprotective potential of antipsychotic treatment in mitigating the structural and functional deterioration associated with the long-term course of the illness.

Early effects of antipsychotic treatment have been reported to include an acute reduction in white matter integrity, particularly around the anterior cingulate gyrus and the anterior corona radiata of the frontal lobe.⁵⁶ While these initial changes in white matter might suggest adverse effects of early antipsychotic medication, they might not persist and may even show widespread improvements in white matter integrity with long-term treatment,^33,34 suggesting a complex interplay between antipsychotic medications and brain white matter that may allow for recovery or adaptation over time. Antipsychotic medications exhibit rapid effects on cerebral function, with increased synchronous neural activity mainly in frontal and parietal regions observed after short-term antipsychotic treatment.^54,57 Despite these positive early effects, some adverse outcomes like reduced activity in the dorsomedial thalamus and decreased connectivity in the mediodorsal thalamus and cerebellum have been reported.^54,58 Over the long-term, antipsychotic medications contribute to the improvement of functions in the basal ganglia, such as the amygdala, hippocampus, and striatum, reflecting a balance between remediation and adaptation driven by dopaminergic modulation.²⁷ This modulation, particularly D2 receptor antagonism in subcortical areas, which are heavily implicated in the pathophysiology of schizophrenia, is crucial not only for symptom relief but also for promoting neuroplastic changes, such as increased synapse number and connections, particularly in the striatum.⁵⁹

While long-term antipsychotic use is associated with potential increases in gray matter volume in regions like multiple hippocampal subfields—likely due to the neuroprotective effects of second-generation antipsychotics³¹—it may also lead to reductions in the frontal and temporal lobes. Liu et al. reported chronic schizophrenia patients with long-term antipsychotic treatment (n = 40) had reduced gray matter volumes in the bilateral prefrontal, temporal, and left inferior parietal lobules compared to individuals with CUS (n = 35) (Figure 1).³⁰ These findings were consistent with the prior studies revealing reduced gray matter, mainly in the prefrontal and temporal lobes, after short-term treatment in schizophrenia patients.^51,60–62 Furthermore, Zeng et al. used machine learning-based analysis to distinguish between treated and untreated patients with schizophrenia, across different illness durations.³⁸ In this study, treated patients had gray matter structural alterations primarily in the frontal and temporal regions, and regional functional activity alterations in the right superior frontal gyrus, but these effects were not observed in untreated patients, illustrating the specific impacts of antipsychotic treatment regardless of illness duration. The altered gray matter volume in these areas following long-term antipsychotic treatment has also been observed in longitudinal studies in first-episode schizophrenia patients⁶³ and controlled studies in macaque monkeys.^64–66 Studies have demonstrated that long-term antipsychotic-related volume reductions in the frontal, temporal, and parietal lobes,^64–66 and these reductions are associated with distinct neuropathological changes (eg, decreased astrocyte numbers, diminished dendritic arborization, and reduced dendritic spine density).^64–66

Different Long-Term Effects of Monotherapy With Antipsychotic Medications on the Brain

Clozapine and risperidone—the first atypical antipsychotics—differ significantly in their mechanisms^67–69 and may differentially affect neurostructural and cognitive outcomes compared to first-generation antipsychotics.^70–72 Comparing individuals with CUS to those receiving long-term antipsychotics provides insights into the medication-specific effects on neural structures and function, and may clarify the effects of disease progression and outcomes from those attributable to the medication. For example, Tao et al.³⁵ demonstrated that risperidone—(n = 19) but not clozapine-treated (n = 23) had increased mid-anterior corpus callosum volumes compared to individuals with CUS (n = 23). In another study, risperidone-treated patients with chronic schizophrenia (n = 17) had milder white matter disruptions compared to clozapine-treated patients with chronic schizophrenia (n = 17) and individuals with CUS (n = 34).³³ In addition, Liu et al.³⁰ reported that long-term clozapine-treated patients (n = 20) had greater gray matter reductions in the bilateral prefrontal cortex compared to risperidone-treated patients (n = 20). Collectively, these studies suggest that while both long-term clozapine and risperidone treatment influence brain structure in schizophrenia, their effects differ significantly and may involve unique brain regions. Risperidone may have neuroprotective benefits, especially for white matter structure,^33,35 and could potentially improve cognitive functions due to its dopaminergic and serotonergic antagonist properties, which contribute to these effects.⁷³ In contrast, clozapine, with its unique anticholinergic properties and receptor pharmacology, may produce different structural changes over time compared to risperidone, and relatively modest neurocognitive benefit of clozapine treatment.^33,74,75 However, these findings should be interpreted cautiously given that clozapine is frequently reserved for use in patients with treatment refractory schizophrenia. Because the more modest improvements observed in this sample may relate to the more severe psychopathology and greater treatment resistance rather than to the specific effects of clozapine, the specificity of these findings with regard to the two antipsychotics is difficult to establish.

Challenges and Limitations in Chronic But Untreated Schizophrenia

Neuroimaging studies offer invaluable insights into the pathophysiology of CUS. However, several limitations and challenges warrant additional discussion. First, while providing valuable insights into the neurobiology of CUS, cross-sectional designs^22,27,34 limit our ability to longitudinally examine age-related and duration-related changes in the brain. However, ethical considerations prohibit longitudinal studies that withhold treatment. Moreover, the cross-sectional approach limits our understanding of the dynamic effects of antipsychotic medications on brain function and structure. Second, small sample sizes limit the statistical power and generalizability of findings, particularly compared to studies of first-episode patients. These effects are amplified by the accumulation of confounding factors and greater heterogeneity, including diverse environmental influences and illness stages in CUS studies.⁷⁶ Third, the reproducibility of results may be negatively influenced by variability in study designs, methodologies, and participant selection criteria across studies.⁷⁷ In addition, many of the neuroimaging studies of CUS were conducted at a small number of sites (i.e., predominantly conducted at the HMRRC in Southwest China and the Institute of Mental Health at Peking University in Northern China). This may limit the generalizability of findings. Fourth, the long-term nature of antipsychotic treatment, perhaps with variable adherence and dosing, complicates the assessment of treatment effects on the neurocircuitry of schizophrenia. Fifth, neuroimaging techniques, particularly fMRI and DTI are encumbered by technical and methodological challenges. These techniques indirectly measure brain activity and microstructural integrity of white matter but are influenced by myriad factors (eg, scanner artifacts, participant motion, and physiology). The resolution limitations of fMRI and DTI and the limited direction of DTI, particularly with 15 direction protocols common in schizophrenia research,^33,34 may limit the detection of microstructural integrity of white matter, especially in superficial areas (eg, U-fibers).³³ Moreover, the variability in MR analytical approaches (eg, software and analysis pipelines) introduces variability in results.²¹ These challenges are not unique to CUS but are endemic in neuroimaging studies in psychiatric conditions.⁷⁸ However, they highlight the need for larger sample sizes, standardized experimental methods, and harmonization of analytic approaches. These efforts are key to developing robust neuroimaging biomarkers and more effective treatment strategies, ultimately bridging the translational gap in neuroimaging research of schizophrenia.

Future Directions

Longitudinal Study of Treatments

Longitudinal studies focused on monotherapy may clarify the impact of specific medications on disease progression. They may help to identify additional factors that influence disease course and these neurostructural and neurofunctional changes. Recently, factors such as social isolation,^79,80 comorbidity,^81,82 and age of onset have been shown to influence the disease course in schizophrenia. However, our understanding of the effects of these characteristics on the brain is unclear. These first-episode studies allow researchers and clinicians to understand how treatment response in individual patients relates to the brain findings described herein, which may provide critical insights into personalized treatment strategies.

Symptom/Cognition Characterization

Future studies should integrate neuroimaging, comprehensive symptom measures (both primary and co-occurring), and neurocognitive functioning in individuals with CUS to identify how specific symptoms and deficits contribute to the neurobiology of CUS.^83,84 Incorporating samples with specific symptoms with detailed neuropsychological assessments and integrating these with neuroimaging data may advance our understanding of the complex interactions between brain structure, function, and clinical course of schizophrenia.

Multimodal Neuroimaging and Biomarker Integration

Recent advances in neuroimaging, including high-resolution magnetic resonance spectroscopy and arterial spin labeling, provide the opportunity to understand the abnormalities in schizophrenia, including later in the course of illness. These approaches offer glimpses into the neurochemistry,⁸⁵ excitatory/inhibitory imbalance, and blood flow perfusion. Integrating multimodal information from MRI and positron emission tomography (PET), PET-MRI allows metabolic and functional abnormalities to be integrated, which may reveal alterations in neuronal activity and energy consumption that subtend the progressive degenerative changes described herein. In addition, applying multimodal MRI techniques and novel analytical methods such as individualized network analysis,⁸⁶ network controllability,^87,88 functional gradients,⁸⁹ and radiomics,⁹⁰ provides multidimensional features and insights that significantly enhance our understanding of the intricate brain alterations in CUS. Individualized network analysis highlights the need for personalized treatments by highlighting individual-specific connectivity patterns, reflecting the heterogeneity of CUS.⁸⁶ Network controllability quantifying the brain’s ability to transition between different states, identifies key neural hubs for therapeutic targeting.^87,88 Functional gradients provide a deeper understanding of how brain regions integrate or segregate, critical for addressing cognitive and perceptual disturbances in schizophrenia.⁸⁹ Radiomics quantifies subtle brain abnormalities in brain structure and function by extracting a vast array of features from imaging data, identifying biomarkers for disease progression, and informing treatment strategies.⁹⁰ Together, these approaches provide a comprehensive framework for understanding the pathophysiological mechanisms.⁹¹ These approaches could allow a better understanding of the individual differences among individuals with CUS who have slower or faster deterioration and may benefit from specific interventions to ameliorate this degradation, including inflammatory-focused strategies,⁹² cognitive remediation,⁹³ etc.

Clinical Applications and Individualized Treatment

Translating these neurostructural and neurofunctional findings in CUS requires a multifaceted approach integrating advanced neuroimaging techniques with genetic, cognitive, and environmental data. Ultimately, understanding these processes in schizophrenia—both treated and untreated—may decrease treatment resistance in schizophrenia⁹⁴ and help to identify interventions that may attenuate disease progression. Applying data-driven and machine learning algorithms in neuroimaging studies can potentially transform neuroimaging findings into personalized diagnosis and treatment strategies for individuals with CUS. For example, by identifying specific disruptions in neural circuits associated with cognitive deficits, these approaches can guide the development of targeted neuromodulation therapies. This approach personalizes treatment based on the individual’s unique neural disruptions, potentially enhancing outcomes in CUS.

Acknowledgments

Dr Su Lui acknowledges the support from the Humboldt Foundation Friedrich Wilhelm Bessel Research Award and Chang Jiang Scholars (Program No. T2019069).

Funding

This study was supported by National Key R&D Program of China (Project Nos. 2022YFC2009901 and 2022YFC2009900), the National Natural Science Foundation of China (Project Nos. 82120108014, 82071908, and 82102007), Sichuan Science and Technology Program (Project No. 2021JDTD0002), Chengdu Science and Technology Office, Major Technology Application Demonstration Project (Project Nos. 2022-YF09-00062-SN and 2022-GH03-00017-HZ), 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (Project No. ZYGD23003), and the Fundamental Research Funds for the Central Universities (Project No. ZYGX2022YGRH008).

Conflict of Interest

Dr Zhang is a consultant to VeraSci. Dr Strawn has received research support from the National Institutes of Health (NIMH/NIEHS) and material support from Myriad Genetics. He receives royalties from Springer and Cambridge University Press, honoraria from the Neuroscience Education Institute and Medscape, and serves as an author for UpToDate. He has provided consultation to Otsuka, Cerevel, Alkermes, and Genomind. Dr Strawn also receives research support from the Yung Family Foundation. The remaining authors have declared that they have no conflicts of interest.

References

Author notes