White-matter free-water diffusion mri in schizophrenia: a systematic review and meta-analysis

ABSTRACT White-matter abnormalities, including increases in extracellular free-water, are implicated in the pathophysiology of schizophrenia. Recent advances in diffusion magnetic resonance

imaging (MRI) enable free-water levels to be indexed. However, the brain levels in patients with schizophrenia have not yet been systematically investigated. We aimed to meta-analyse

white-matter free-water levels in patients with schizophrenia compared to healthy volunteers. We performed a literature search in EMBASE, MEDLINE, and PsycINFO databases. Diffusion MRI

studies reporting free-water in patients with schizophrenia compared to healthy controls were included. We investigated the effect of demographic variables, illness duration, chlorpromazine

equivalents of antipsychotic medication, type of scanner, and clinical symptoms severity on free-water measures. Ten studies, including five of first episode of psychosis have investigated

free-water levels in schizophrenia, with significantly higher levels reported in whole-brain and specific brain regions (including corona radiata, internal capsule, superior and inferior

longitudinal fasciculus, cingulum bundle, and corpus callosum). Six studies, including a total of 614 participants met the inclusion criteria for quantitative analysis. Whole-brain

free-water levels were significantly higher in patients relative to healthy volunteers (Hedge’s _g_ = 0.38, 95% confidence interval (CI) 0.07–0.69, _p_ = 0.02). Sex moderated this effect,

such that smaller effects were seen in samples with more females (_z_ = −2.54, _p_ < 0.05), but antipsychotic dose, illness duration and symptom severity did not. Patients with

schizophrenia have increased free-water compared to healthy volunteers. Future studies are necessary to determine the pathological sources of increased free-water, and its relationship with

illness duration and severity. SIMILAR CONTENT BEING VIEWED BY OTHERS CHARACTERIZATION OF THE EXTRACELLULAR FREE WATER SIGNAL IN SCHIZOPHRENIA USING MULTI-SITE DIFFUSION MRI HARMONIZATION

Article 24 April 2023 WHITE MATTER MICROSTRUCTURE ALTERATIONS IN EARLY PSYCHOSIS AND SCHIZOPHRENIA Article Open access 23 May 2025 IN VIVO 7-TESLA MRI INVESTIGATION OF BRAIN IRON AND ITS

METABOLIC CORRELATES IN CHRONIC SCHIZOPHRENIA Article Open access 26 October 2022 INTRODUCTION Schizophrenia is characterised by psychotic, negative and cognitive symptoms and is a leading

cause of global disability [1]. Although its pathophysiology is still unknown, evidence indicates the involvement of disrupted early neurodevelopment, and aberrant function of cortical

microcircuits, leading to a widespread network dysfunction and a cortical excitatory-inhibitory imbalance [1]. Current treatments target the dopaminergic system and are largely ineffective

for the negative and cognitive symptoms of schizophrenia, the main contributors to the burden and morbidity of this disorder [2]. This highlights the need for greater understanding of the

pathophysiology of the disorder to identify new treatment targets [3, 4]. Multiple studies have found brain structural abnormalities in schizophrenia [5,6,7,8]. These have included studies

using diffusion magnetic resonance imaging (dMRI) to measure white-matter microstructure by characterising the amplitude and anisotropy of water diffusion, based on the principle that water

tends to diffuse more freely along the longitudinal axis of axons than along their perpendicular axis [9]. Diffusion tensor imaging (DTI) provides unique information about white-matter

microstructural properties that are useful in characterising pathophysiology in brain disorders [10]. Changes in fractional anisotropy (FA) and mean diffusivity (MD) are indicative of

white-matter pathology [11]. Studies using dMRI have shown reduced FA and altered MD in individuals with schizophrenia relative to controls [12,13,14]. However, one key limitation of DTI is

that alterations in fast diffusing extraceullular water, such as free-water (FW), can bias the estimation of DTI indices, confounding the interpretation of the signal changes. Increases in

extracellular water can occur due to processes such as atrophy, changes in the extracellular matrix, and also due to inflammation [15,16,17,18] which, given the hypothesised role of

neuroinflammation in schizophrenia [19,20,21], is of particular interest in the disorder. Thus, it is important to determine if there are alterations in extracellular water in schizophrenia.

Extracellular water can be quantified using FW imaging [22]. This uses a bi-tensor model to characterise water diffusion as two compartments: one consisting of an unrestricted, isotropic

compartment with a fixed diffusivity of FW, and another consisting of all remaining water molecules that are hindered or restricted by tissue membranes. From the tissue compartment, a

measure of diffusion FA within the tissue (FAT) can be calculated. Because partial volume confounders from FW-contaminated voxels (e.g., CSF) are eliminated [23], the FAT measure is more

specific to tissue alterations than FA measured using standard DTI [24,25,26]. There have been a number of recent studies to investigate FW in schizophrenia. However, the magnitude of

findings and the relationship to symptoms is not clear. To address this, we conducted a systematic review and meta-analysis to determine if there are significant FW alterations in

schizophrenia, and to estimate the magnitude of any alterations, if relevant. In addition, we investigated methodological and clinical factors, including age, sex, duration of illness,

treatment and symptom severity, that may influence findings. We hypothesised that patients with schizophrenia would have higher FW values compared to healthy volunteers, and that illness

severity would be positively associated with FW values. METHOD SEARCH STRATEGY In accordance with the PRISMA guidelines, EMBASE, MEDLINE, and PsycINFO databases were systematically searched

from 2009 to 23 October 2020 using the following search terms: (1) “free-water” OR “free?water” AND (2) “diffusion tensor imaging” OR “diffusion magnetic resonance imaging” OR “dti” OR

“diffusion mri” OR “neuroimaging” OR “imaging” AND (3) “schizophrenia” OR “psychosis” OR “psychotic”. The search criteria were registered on the international prospective register for

systematic reviews (registration number CRD42020182173, review protocol accessible). The search and data extraction were independently checked by two different investigators (ICF and FB).

ELIGIBILITY CRITERIA The inclusion criteria for the systematic review and meta-analysis were as follows: (1) original research article; (2) use of DTI and the FW bi-tensor model; (3) reports

of FW values, with sufficient information to determine the group mean and variance or effect size; (4) inclusion of schizophrenia, schizoaffective, or schizophreniform patients as

determined by the Diagnostic and Statistical Manual of Mental Disorders; (5) inclusion of a control group of healthy volunteers with no history of psychiatric conditions. Exclusion criteria

for the systematic review were as follows: (1) studies that did not report original, peer-reviewed data, such as review articles and conference abstracts; (2) studies that did not report FW

imaging values; (3) studies not including patients with schizophrenia; (4) not including a healthy volunteer comparison group; (5) studies only reporting a FW analysis in grey matter; (6)

use of concurrent environmental manipulations (e.g. stress or food deprivation models). A meta-analysis was conducted if there were at least three studies that used the same population,

region of interest in the brain, type of analysis (i.e. whole-brain analysis, brain regions of interest), and FW imaging method. All datasets included in the meta-analysis were independent.

DATA EXTRACTION In accordance with the PRISMA guidelines, the following variables were extracted from all studies: (1) authors; (2) year of publication; (3) sample characteristics (sex

(%female), age, diagnosis, duration of illness, medication status as reported chlorpromazine-equivalent estimates, duration of antipsychotic treatment, and sample size per group; (4) FW

imaging methods used, either multi or using a code adapted for single-shell; (5) regions of interest included (brain regions, white-matter tracts, and hemispheres); (6) type of analysis used

(voxel-wise analysis, and tract-based spatial statistics (TBSS)); (7) results (mean and variance of FW values). In cases where the mean and variance of FW values were not reported, the mean

and variance were extracted from tables or graphs using Web plot digitizer (WebPlotDigitizer 2018). In cases where it was unclear if datasets were independent, authors were contacted to

confirm that this was the case. In cases where whole-brain analysis was separated into left vs. right hemispheres, authors were contacted to provide whole-brain mean and standard deviation

values. Studies where only a cluster of regions of interest were included in data analysis, were excluded from the analysis. When reported, we have converted the total BPRS score to an

equivalent total PANSS score using the method described by Leucht et al. [27]. STATISTICAL ANALYSIS The main outcome measure in our analysis was the summary effect size (Hedge’s _g_) for the

difference in FW values between patients with schizophrenia and healthy controls. All comparisons were conducted with the statistical programming language R Studio (version 3.3.2) using the

“metafor” package. Standardised effect sizes (Hedges’ _g_ using a 95% confidence interval (CI) and a significance level of _p_ < 0.05 (two-tailed)) for individual studies were first

estimated. An overall summary effect size was then calculated by entering these individual study effect sizes into a random effects meta-analytic model using restricted maximum likelihood

estimation. ASSESSMENT OF INCONSISTENCY AND BIAS Between-study inconsistency was estimated using the _I_2 value (_I_2 < 50% indicates low to moderate inconsistency, whereas _I_2 > 50%

indicates moderate to high inconsistency). Publication bias was assessed in cases where there were at least five available studies by visual inspection of a funnel plot and the use of the

Egger’s test. In cases where publication bias was suspected, a trim-fill analysis was conducted. If at least five studies were included in a meta-analysis, a leave-one-out sensitivity

analysis was conducted to ensure that the results were not driven by a single study. SENSITIVITY ANALYSES Since previous literature has shown age, sex [28], and duration of illness-dependent

effects on white-matter microstructure [12], meta-regressions were conducted to examine the effect of age, gender, duration of illness and symptom severity on FW values. We then compared

studies including patients with first episode psychosis (FEP) and chronic schizophrenia (CSZ) by fitting a meta-regression model where the subgroup category acted as the moderating variable

of interest. If there was a statistically significant difference between subgroups, a separate random effects meta-analysis was conducted for each subgroup. Meta-regressions were also used

to investigate the effect of age (mean), gender (%male), type of scanner (1.5 vs. 3.0 Tesla), antipsychotic chlorpromazine-equivalent doses (mean), duration of illness (mean months) on FW

for the entire dataset. Given the evidence supporting significant FW differences dependent on illness status [25], the meta-regressions were also used separately for patients with FEP and

CSZ. If at least three studies reported symptom severity using the same scale (e.g. Brief Psychiatry Rating Scale, and/or Positive and Negative Symptoms Scale (PANSS), and/or Global

Assessment of Functioning), we conducted a meta-regression to investigate the association between symptom severity and FW for the entire sample, and separately for FEP, CSZ and healthy

volunteers. RESULTS STUDY SAMPLE AND METHODOLOGICAL CHARACTERISTICS The literature search identified 106 records. These were manually screened by two independent researchers (see Fig. 1 for

a study selection flow chart). In total, ten articles were deemed eligible for inclusion in the systematic review, and six of these studies were suitable for inclusion in the meta-analysis.

The characteristics of the studies identified are summarised in Table 1. Of these, five studies were of patients in their first episode of illness, and five were of patients with chronic

illnesses. SYSTEMATIC REVIEW OF STUDIES INVESTIGATING FREE-WATER IN SCHIZOPHRENIA The reported extracellular FW differences between patients and healthy volunteers are summarised in Table 2.

Of the ten studies, five studies [29,30,31,32,33] did not report a statistically significant difference between groups. This may be due to differences in duration of illness, given that

patients included in those studies were diagnosed with CSZ. The remaining five studies reported significantly higher FW levels in schizophrenia. Although there were insufficient data to

investigate the association between FW values and PANSS subscales, one study [25] reported a secondary analysis revealing patients with positive symptoms (olfactory hallucinations, thought

disorder, pressured speech, and inappropriate affect) had significantly higher FW values relative to patients who were asymptomatic. One other study [32] also showed that total Scale for the

Assessment of Positive Symptoms scores were significantly associated with increased FW values in the right posterior thalamic radiatia and the left sagittal stratum. Focusing on the studies

that included patients with the diagnosis of first episode of psychosis, three studies [24, 34, 35] found differences in FW levels between early onset patients and healthy volunteers. The

only study that did not find a difference [33] used a scanner with a lower magnetic field (1.5 T), which may have reduced the sensitivity to detect differences. META-ANALYSIS OF FREE-WATER

The overall sample in the meta-analysis comprised 614 participants (288 patients with schizophrenia, 326 healthy volunteers). The mean age was 24 years (SD 8.7), and 234 (38.1%) of the

participants were female. The average duration of illness was 36.7 months (SD 41.8) and mean chlorpromazine (CPZ) equivalent antipsychotic dose was 365.2 (SD 343) mg/day, although one study

failed to report any medication equivalents [35]. Whole-brain FW was significantly higher in patients relative to healthy volunteers (Hedge’s _g_ = 0.38, 95% CI 0.07–0.69, _p_ = 0.02) (see

Fig. 2A, B for funnel plot). There were moderate to high levels of between-study inconsistency (_I_2 =  70.32, _p_ < 0.01). However, Egger’s test indicated that there was no evidence of

publication bias (_z_ = 1.50, _p_ > 0.05), and a trim-fill analysis indicated that there were no missing studies. EFFECT OF MODERATORS The magnitude of the effect size of FW values

between patients vs. controls did not significantly vary with age (_z_ = 0.47, _p_ = 0.64), illness duration (_z_ = 0.72, _p_ = 0.47), type of scanner (_z_ = −0.88, _p_ = 0.38), CPZ

equivalent antipsychotic doses (_z_ = −0.13, _p_ = 0.89), or total PANSS score (_z_ = −0.11, _p_ = 0.91). The magnitude of the effect size of FW values between patients vs. controls

significantly varied with sex (z = −2.54, _p_ < 0.05), such that samples with a greater proportion of female patients associated with smaller FW difference in patients relative to

controls. There were insufficient studies to investigate the effect of disease status (FEP vs. CSZ) on FW values. DISCUSSION Our main finding was that FW levels in the white matter are

higher in patients with schizophrenia compared to healthy volunteers. The magnitude of this effect did not vary with variables such as age, illness duration, total PANSS score, CPZ

equivalent antipsychotic drugs, or type of scanner used for data acquisition. However, a greater proportion of females resulted in smaller FW difference in patients relative to controls.

STRENGTHS AND LIMITATIONS Strengths include that this first study to perform meta-analyse of FW measures in schizophrenia includes a moderately large sample size. However, we detected

significant heterogeneity between studies. Our sensitivity analyses identified sex as a potential contributor to this. In addition, five of the six studies included in the meta-analysis

included individuals with the diagnosis of schizoaffective, or schizophreniform disorder, which may have contributed to the heterogeneity in the sample. There was also variability in the

criteria used to match healthy controls with patients, which could contribute to heterogeneity. Nevertheless, all of the studies reported matching between patients and controls for age,

gender, and education. Our findings are in accordance with previous studies highlighting that excessive FW characterises the white-matter pathology in early stages of schizophrenia, and

other processes such as demyelination or axonal degeneration predominate with disease progression [16, 25]. However, since only one out of six studies in our analysis included patients with

the diagnosis of CSZ, we were unable to further characterise the disease progression effect. In regards to possible medication effects, we did not find a relationship with CPZ equivalent

dose, suggesting antipsychotics are not substantially influencing our findings. However, since four studies did not report the number of unmedicated patients in the sample [16, 29, 34, 36],

we were unable to account for this in our meta-analysis. Therefore, differences in the use of medications may have contributed to high levels of heterogeneity across studies [37].

Notwithstanding these potential sources of variability, we used a random effects meta-analysis, which allows for heterogeneity in findings, although this approach underestimates the effect

size relative to fixed effects approaches. Thus, the true effect may be larger than we report here. Another limitation was that there were too few studies to permit meta-analyses in specific

regions. Thus, further studies reporting data on specific brain regions are needed to determine if there are regionally specific effects. IMPLICATIONS FOR UNDERSTANDING THE PATHOPHYSIOLOGY

OF SCHIZOPHRENIA Increased apparent diffusion coefficient, and MD levels [38] have consistently been reported in schizophrenia [10, 39]. Our findings add to this, by indicating that there is

increased extracellular FW in white matter in people with schizophrenia as well. The fractional volume of the extracellular water, relative to the remaining water molecules diffusing in

restricted conditions, is increased in pathological processes known to modify the interstitial extracellular space [40], such as vasogenic oedema [23], and neuroinflammation [41]. Thus, the

increased FW in schizophrenia could be indicative of one or more of these processes, consistent with the hypothesis of immune activation in schizophrenia. It has been hypothesised that the

innate immune system triggers an inflammatory response in the brain in schizophrenia [42], in a process that also involves astrocytes and microglia [19, 20], and leads to synaptic

alterations and disruption of long-range connectivity, both of which have been reported in schizophrenia [43]. Other mechanisms could also contribute to the connection between schizophrenia

and increased white-matter extracellular volume. In particular, a blood-brain barrier disruption has been hypothesised to be consistent with the neuroimaging findings seen in the disorder

[22, 44], and in line with ideas that schizophrenia is a multi-system disorder [45]. When disrupted, abnormal trafficking of cells and molecules between the peripheral blood and the brain

occur, allowing bone marrow-derived immune cells to cross into the nervous system [46], and increasing the extracellular fractional volume [47]. Further work is needed to determine if

inflammatory states or other mechanisms underlie the increased FW in schizophrenia. In particular, studies are needed in first episode patients, ideally combining FW imaging with other

neuroimaging methodologies such as PET measures of markers expressed on immune cells [20, 48,49,50] and including measures of peripheral and central cytokines [19, 51,52,53] in order to

understand how these peripheral and central measures of inflammation are related. It is also important to recognise that extracellular changes in FW could also reflect other biological

factors such as decreased cell density [26]. However, altered cell density is not generally reported in schizophrenia [25]. We did not find that symptom severity moderated findings,

indicating that our FW findings are unrelated to symptoms. Neuroinflammation has been previously hypothesised as contributing to impaired neurocognitive functioning in schizophrenia [19,

54]. Contrarily, a certain degree of acute inflammation is necessary to attain optimal function of the central nervous system [55], and even support healing in cases of brain injury [56].

Given the limited number of studies included in our meta-analysis that reported symptom ratings, this finding warrants further investigation before firm conclusions are drawn. We did not

find a relationship with CPZ equivalent dose, suggesting antipsychotics are not substantially influencing our findings. Critically, studies addressing the effect of antipsychotic treatment

in microglia have shown conflicting results, with some in vitro studies showing a reduction in microglial activation [57], and in vivo studies reporting an increase with olanzapine [58], but

a reduction with risperidone [59]. Thus, further work is needed to comprehend if antipsychotic treatment could have affected our results. We found that patients with schizophrenia show

greater white-matter FW levels relative to healthy volunteers with a moderate effect size. There was significant heterogeneity, which could be partly due to differences in sex between

studies given our finding that studies with more females showed lower elevations in free-water in patients relative to controls. This finding is consistent with previous FW results showing

that female FEP patients exhibit significant increases in FW values compared to female healthy volunteers [35]. However, there is not a consensual explanation for these findings, and future

work examining sex differences in these neuroinflammatory parameters is warranted. We did not investigate differences in FAT in our meta-analysis. Future studies are needed to understand the

magnitude of findings in schizophrenia and implications of this parameter. These findings extend the existing understanding of the extracellular and white-matter changes in schizophrenia

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  PubMed Central  CAS  Google Scholar  Download references FUNDING This study was funded by Medical Research Council-UK (no. MC_U120097115), and Wellcome Trust (no. 094849/Z/10/Z) grants to

ODH and the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. For the purpose of open

access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The views expressed are those of the author(s) and not

necessarily those of the NHS, the NIHR or the Department of Health. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Psychosis Studies Department, Institute of Psychiatry, Psychology and

Neuroscience, King’s College London, London, UK Inês Carreira Figueiredo, Faith Borgan & Oliver D. Howes * Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard

Medical School, Boston, MA, USA Ofer Pasternak * Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK Federico E. Turkheimer *

Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London, UK Oliver D. Howes * H. Lundbeck UK, Ottiliavej 9, 2500, Valby, Denmark Oliver D.

Howes Authors * Inês Carreira Figueiredo View author publications You can also search for this author inPubMed Google Scholar * Faith Borgan View author publications You can also search for

this author inPubMed Google Scholar * Ofer Pasternak View author publications You can also search for this author inPubMed Google Scholar * Federico E. Turkheimer View author publications

You can also search for this author inPubMed Google Scholar * Oliver D. Howes View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS ICF and FB

contributed with the conception and design of the work, acquisition, analysis, and interpretation of data. OP, FET, and ODH revised critically the work for important intellectual content,

and approved the final version to be published. CORRESPONDING AUTHOR Correspondence to Inês Carreira Figueiredo. ETHICS DECLARATIONS COMPETING INTERESTS The authors declared no potential

conflicts of interest with respect to the research, authorship, and/or publication of this article. FB became an employee at COMPASS Pathways plc after the completion of this work. This work

is unrelated to COMPASS Pathways plc. ODH is a part-time employee of H. Lundbeck A/S and has received investigator-initiated research funding from and/or participated in advisory/speaker

meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Heptares, Global Medical Education, Invicro, Janssen, Lundbeck, Neurocrine, Otsuka, Sunovion, Rand,

Recordati, Roche and Viatris/Mylan. Neither ODH or his family have holdings/a financial stake in any pharmaceutical company. ODH has a patent for the use of dopaminergic imaging. ADDITIONAL

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To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Carreira Figueiredo, I., Borgan, F.,

Pasternak, O. _et al._ White-matter free-water diffusion MRI in schizophrenia: a systematic review and meta-analysis. _Neuropsychopharmacol._ 47, 1413–1420 (2022).

https://doi.org/10.1038/s41386-022-01272-x Download citation * Received: 17 September 2021 * Revised: 09 December 2021 * Accepted: 05 January 2022 * Published: 15 January 2022 * Issue Date:

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