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. Author manuscript; available in PMC: 2021 Aug 4.
Published before final editing as: Psychiatry Res Neuroimaging. 2020 Feb 4;297:111043. doi: 10.1016/j.pscychresns.2020.111043

Hippocampus and cognitive domain deficits in treatment-resistant schizophrenia: A comparison with matched treatment-responsive patients and healthy controls

Junchao Huang a, Yu Zhu a, Fengmei Fan a, Song Chen a, Yuan Hong b, Yimin Cui c, Xingguang Luo d, Shuping Tan a, Zhiren Wang a, Lan Shang a, Ying Yuan e, Jianxin Zhang a, Fude Yang a, Chiang-Shan R Li d, Laura M Rowland f, Peter Kochunov f, Fengyu Zhang g, L Elliot Hong f, Yunlong Tan a,*
PMCID: PMC7490244  NIHMSID: NIHMS1626014  PMID: 32062167

Abstract

Some patients with schizophrenia do not respond to pharmacotherapy. More severe cognitive dysfunctions have been associated with treatment-resistant schizophrenia (TRS). This study examines cognitive functions and hippocampal volumes in 43 patients with TRS and compared them to 43 treatment-responsive patients (NTRS), matched on age, sex and education, as well as 53 healthy controls (HC). The results showed that there were significant deficits in all domains of cognition and hippocampal volumes in TRS as compared to HC group. However, TRS specific deficits, as indicated by comparisons with matched NTRS, were limited to poorer performance in working memory (p = 0.003) and smaller total hippocampal volume (p = 0.01). Logistic regression analysis showed that working memory deficits [OR 0.94 (95% CI 0.89 - 0.98), p = 0.005] and smaller hippocampal volume [OR 0.89 (95% CI 0.81 - 0.97), p = 0.01], but not their interactions (p = 0.68), contributed to higher risk of treatment resistance. The findings suggest that treatment-resistance to currently available antipsychotic medications may not be due to global cognitive deficits in these patients, but be associated with specific deficits in working memory and hippocampus deficits in the subgroup of schizophrenia.

Keywords: Schizophrenia, Treatment-resistant, Cognition, MRI, Hippocampus

Introduction

Approximately one-third of patients with schizophrenia respond poorly to pharmacotherapy and are considered as treatment-resistant schizophrenia (TRS) (Strassnig and Harvey, 2014, Suzuki et al., 2011), which has been regarded as an important subtype of schizophrenia and development of more effective treatment is urgently needed for this group of patients (Castro and Elkis, 2007, Howes et al., 2017). Identifying key brain and cognitive deficit biomarkers associated with TRS would be important to support this effort.

Accumulating evidence suggested differences between patients with TRS and patients who were treatment responders (NTRS) in brain structures (Molina et al., 2008) and cognitive functions (Demjaha et al., 2014), although the findings were inconsistent. Neuroimaging studies suggested that there were more severely reduced cerebral gray matter volume and cortical thickness in TRS compared to NTRS (Mouchlianitis et al., 2016). However, a recent systematic review did not confirm that there were significant differences in cortical gray matter between TRS and NTRS (Nakajima et al., 2015). A study on large sample size (van Erp et al., 2016) reported that the hippocampus had the most severe volume reductions among all the subcortical regions in schizophrenics as compared to healthy controls (HC). So, the first aim of this study was to examine whether gray matter deficits might be associated with treatment resistance by focusing on the hippocampus.

Previous studies showed that patients with TRS had smaller total hippocampal volume compared with HC (Maller et al., 2012), and clozapine treatment might improve hippocampal volume in TRS (Molina et al., 2003). However, without a direct comparison with NTRS, it remained unclear if the differences in TRS vs. HC reflected primarily the diagnosis of schizophrenia rather than treatment refractoriness. So, we examined whether TRS is related to deceased hippocampal volume by comparing TRS patients to NTRS.

The hippocampus was critical to cognitive functions (Arlt et al., 2013) as it involved in working memory(Zhang et al., 2013) and spatial and temporal memory (Eichenbaum, 2014). It was shown that the hippocampus was associated with cognitive dysfunctions in schizophrenia (Bahner and Meyer-Lindenberg, 2017) . In schizophrenia, cognitive impairments were considered as a core feature of the illness (Green and Nuechterlein, 1999) that usually showed limited response to antipsychotics (Keefe and Fenton, 2007). However, few studies systematically focused on identifying specific cognitive deficits in TRS, and the results were inconsistent. Compared to patients with NTRS, TRS patients had significantly poorer performances on verbal abilities, memory, learning (de Bartolomeis et al., 2013, Joober et al., 2002) and attention (Sanchez et al., 2010), lower processing speed, verbal fluency, cognitive flexibility and executive function (Frydecka et al., 2016), and no significant differences in the Stroop task (Vanes et al., 2018). A number of methodological issues, including low statistical power and variable cognitive task battery designs, might contribute to the discrepancy. Notably, none of these studies employed the MATRICS Consensus Cognitive Battery (MCCB), the “gold standard” battery for cognitive assessment in schizophrenia (Smelror et al., 2018). So, the second aim of this study was to compare TRS vs. NTRS across cognitive domains using MCCB to identify cognitive domain(s). And the third aim of the study was to examine whether the identified cognitive deficits contributed to TRS and NTRS if any of domains could be identified to be more impaired in TRS as compared to NTRS. In addition, investigating the interactive effect between cognitive deficits and hippocampal reduction to TRS and NTRS was another aim of interest.

Materials and Methods

Participants

Patients who met the diagnostic criteria of schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders Forth Edition (DSM-IV) given by The Structured Clinical Interview for DSM (SCID) were enrolled from the inpatient of the Beijing Huilongguan Hospital from 2017 to 2018. Patients with NTRS were matched to the TRS group on age-, sex-, and education. TRS was defined based on published consensus guidelines (Howes et al., 2017): (1) criteria of little response to treatment were met that little response to at least 2 different antipsychotic medications with a dose of chlorpromazine (CPZ) equivalent at least 600 mg per day for at least 6 weeks; (2) Brief Psychiatric Rating Scale (BPRS) total score was greater than or equal to 45 during the current assessment, and Clinical Global Impression - severity of illness (CGI - SI) scale score was greater than or equal to 4 during the current assessment. NTRS was defined by a clinical history with periods of good clinical response to antipsychotics as measured by CGI-SI scale less than 3 for at least 12 weeks. We also assessed the number of hospitalizations, age of onset, and duration of illness for all patients. HC were recruited from local communities. Candidates were excluded if they had a history of any other Axis I disorders, a history of head trauma, current or previous substance (except nicotine) dependence or alcoholism, or systemic including neurological diseases. All participants gave written informed consents according to the Helsinki Declaration and a research protocol approved by the Ethics Committee of the Beijing Huilongguan Hospital.

Clinical evaluation

Psychopathology was evaluated using the Positive and Negative Syndrome Scale (PANSS) (He and Zhang, 1997), the Brief Psychiatric Rating Scale (BPRS) (Li et al., 2014a) and the Clinical Global Impression-severity of illness (CGI-SI) (Li et al., 2014b) by one of three attending psychiatrists, and the interrater intra-class correlation coefficient (ICC) of the raters was above 0.80. As BPRS and CGI-SI were used as the entry criteria for group definition, they were not used as dependent variables in this study; and the positive, negative, general psychopathological symptoms sub-scores and total score of the PANSS were used for clinical assessment. An MRI scan and assessment of cognitive function were scheduled within one week for each participant. CPZ equivalent dose of antipsychotics was calculated for each patient (Andreasen et al., 2010, Gardner et al., 2010). Detailed medication information was summarized in Table S1.

Neurocognitive assessment

Cognitive function was assessed with the MCCB validated Chinese version (Kern et al., 2008, Nuechterlein et al., 2008, Zou YZ, 2009), which consists of speed of processing, attention and vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition, as well as a composite score. The composite score was derived by equal weighting of the seven MCCB domain scores.

MRI protocol and data process

Brain structural MRI data was acquired using a Siemens Prisma 3.0T MRI scanner with 64-channel head coil located at the Beijing Huilongguan Hospital Magnetic Resonance Scanner Center. Foam pads were used to minimize head motions. Parameters for structural MRI were acquired covering the whole brain with sagittal 3D-magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence: echo time (TE) = 2.98 ms, inversion time (TI) = 1100 ms, repetition time (TR) = 2530 ms, flip angle (FA) = 7º, field of view (FOV) = 256mm × 224 mm, matrix size = 256 × 224, thickness/gap = 1/0 mm.

Following the ENIGMA protocol (http://enigma.ini.usc.edu/), hippocampal volumes were obtained with FreeSurfer (Fischl, 2012, Fischl et al., 2002) (http://surfer.nmr.mgh.harvard.edu). Intracranial volume (ICV) was obtained for differences in head sizes. Similar to the ENIGMA protocol, a two-step quality control was performed: (1) hippocampus segmentation images were visually inspected by overlaying their segmentations on the anatomical images; (2) outliers (5 standard deviations) of hippocampus were excluded. No subject was excluded under the later rule. The total hippocampus volume was obtained by sum of both hemispheres.

There were 3 participants in TRS group missing their MRI scans due to incompliance caused by symptoms, while 3 participants in NTRS group declined the MRI screening. However, these 6 patients completed the MCCB and clinical evaluations.

Statistical analysis

General linear model (GLM) was used to compare the differences in hippocampal volumes and MCCB measures. The analysis was performed to report overall group comparisons among TRS, NTRS and HC while controlling for age, sex, and education duration. If the finding was significant, it was followed by a priori analysis on the comparison between TRS and NTRS while controlling for age, sex, education duration, age of illness onset and CPZ equivalent dose. Bonferroni corrections were applied to group comparisons of hippocampal volume (p < 0.05/3 = 0.017 for left, right, and total volume) and of MCCB (p < 0.05/8 = 0.006) in evaluating statistical significance. After identifying the measures with significant difference measurements between TRS and NTRS groups, they were further explored using binary logistic analyses to estimate their independent and interactive effects to the risk of TRS.

Results

Cognitive functions

Demographic variables were frequency-matched among the three groups (Table 1). The psychopathological symptoms and CGI-SI scores were more severe in TRS group than those in NTRS group (Table 1). After adjusting for age, sex, and education, all cognitive domains were significantly different among TRS, NTRS and HC groups (F = 11.20 to 47.40, p = 3.3×10−5 to 4.7×10−16). However, only working memory deficit was significantly more severe in TRS than in NTRS (p = 0.003) after Bonferroni correction for eight MCCB measures (p < 0.05/8 = 0.006) (Table 2).

Table 1.

Demographic and clinical characteristics.

TRS (n = 43) NTRS (n = 43) HC (n = 53) F or χ2 (p Value )
across three groups (TRS vs. HC) (NTRS vs. HC) (TRS vs. NTRS)
Sex (M/F) 28/15 28/15 27/26 2.74(0.25) 1.95(0.16) 1.95(0.16) 0(1.00)
Age (years) 48..5± 8.9 46.5±10.6 44.8±9.4 1.71(0.18) 2.79(0.10) 1.36(0.25) 0.15(0.70)
Education (years) 12.1± 2.7 12.3± 3.0 12.3±2.3 0.02(0.95) 0.35(0.56) 0.03(0.86) 0.12(0.73)
Age of onset (years) 22.7 ±5.7 25.1±6.7 NA NA NA NA 3.07(0.08)
Duration of illness (years) 25.3±9.7 22.1±12.0 NA NA NA NA 1.84(0.18)
CPZ equivalent dose (mg/d) 745.9±227.4 470.6±217.9 NA NA NA NA 32.86(1.5 × 10−7)
PANSS
 Positive sub-scores 23.4±4.3 10.95±3.9 NA NA NA NA 196.76(1.0 × 10−23)
 Negative sub-scores 23.4±7.2 14.8±5.3 NA NA NA NA 42.41(5.2 × 10−9)
 General sub-scores 38.4±8.3 23.7±3.6 NA NA NA NA 113.66(2.8 × 10−17)
 Total scores 85.1±12.6 49.1±10.8 NA NA NA NA 202.29(4.4 × 10−24)
BPRS 54.1±7.1 29.5±7.0 NA NA NA NA 260.60(1.8 × 10−27)
CGI-SI 5.8±0.8 2.4±0.5 NA NA NA NA 525.00(6.9 × 10−38)

CPZ: Chlorpromazine; PANSS: Positive and negative syndrome scale; BPRS: Brief psychiatric rating scale; CGI-SI: Clinical global impression-severity of illness; TRS: treatment-resistant schizophrenia; NTRS: treatment-responsive schizophrenia; HC: Healthy controls.

Table 2.

Cognitive functions and hippocampal volumes.

TRS (n = 43) NTRS (n = 43) HC (n = 53) F or χ2 (p Value)
across three groups (TRS vs. HC) (NTRS vs. HC) (TRS vs. NTRS)
MCCB
 Processing speed 43.4 ± 7.8 45.7 ± 10.4 56.7 ±8.6 34.76(8.1 × 10−13) 66.27(3.0 × 10−12) 30.99(3.03 × 10−7) 1.30(0.20)
 Attention/vigilance 45.2 ± 9.8 46.0 ± 9.6 57.3 ± 8.3 29.77(2.6 × 10−11) 39.17(1.5 × 10−8) 37.23(3.10 × 10−8) 0.35(0.60)
 Working memory 41.2 ± 13.2 47.5 ± 10.0 57.5 ± 7.7 36.70(2.1 × 10−13) 54.48(9.8 × 10−11) 28.28(8.55 × 10−7) 9.31(0.003)
 Verbal learning 44.9 ± 11.4 50.6 ± 11.3 58.0 ± 8.3 23.15(2.4 × 10−9) 40.37(1.0 × 10−9) 12.12(0.001) 7.66(0.007)
 Visual learning 42.7± 10.6 46.2 ± 11.9 53.0 ± 8.6 12.93(7.5 × 10−6) 23.25(6.2 × 10−6) 9.23(0.003) 2.32(0.10)
 Reasoning and problem solving 44.9 ± 11.4 50.6 ± 11.3  58.0 ± 8.3 42.09(7.2 × 10−15) 73.46(4.0 × 10−13) 40.23(1.08 × 10−8) 2.00(0.20)
 Social cognition 42.7± 10.6 46.2 ± 11.9 53.0 ± 8.6  11.20(3.3 × 10−5)  19.45(3.0 × 10−5)  8.81(0.004)  2.49(0.10)
 Composite score 40.4± 9.7 45.4±10.6 57.8±7.9 47.40(4.7 × 10−16) 92.75(2.9 × 10−15) 42.28(5.4 × 10−9) 5.12(0.03)
 Intracranial volume (×106mm3) 1.44±0.13 1.47±0.12 1.46±0.09 0.94 (0.39) 0.96(0.39) 0.44(0.51) 1.51(0.22)
Hippocampal volume(×103mm3)
Total 6.37±0.65 6.75±0.56 6.91±0.50 11.47(2.6 × 10−5) 19.66(2.8 × 10−5) 2.17(0.14) 6.30(0.01)
 Left 3.13± 0.30 3.32± 0.28 3.40±0.23 11.46(2.7 × 10−5) 21.24(1.4 × 10−5) 2.00(0.16) 6.05(0.02)
 Right 3.24±0.38 3.43±0.29 3.51±0.28 9.72(1.2 × 10−4) 15.36(1.8 × 10−4) 2.07(0.15) 5.43(0.02)

Hippocampus volumes were available in 40 of the 43 TRS, 40 of the 43 NTRS, and all 53 HC. F (p Value) of cognitive function and hippocampus volume in three groups, TRS vs. HC and NTRS vs. HC were controlling for sex, age, years of education; F (p Value) (TRS vs. NTRS) of cognitive function and hippocampus volume were added age of illness onset and CPZ equivalent dose as covariate in addition. TRS: treatment-resistant schizophrenia; NTRS: treatment-responsive schizophrenia; HC: Healthy controls.

Hippocampal volume differences

The three groups were significantly different in the total (F = 11.47, p = 2.6×10−5), left (F = 11.46, p = 2.7×10−5) and right (F = 9.72, p = 1.2×10−4) hippocampal volumes after controlling for age, sex and education (Table 2). Compared to the HC, TRS patients had significant reductions in total, left and right hippocampal volumes (all p’s < 0.001). In contrast, these hippocampal measures were not significantly different between NTRS and HC (p = 0.10 to 0.12; all p’s > 0.05/3 = 0.017). TRS showed significantly reduction in total hippocampal volumes compared to NTRS after controlling for age, sex, education duration, age of illness onset and CPZ equivalent dose (p = 0.01). Left and right hippocampal volumes individually did not show significant differences between TRS and NTRS (both p’s = 0.02).

Predicting treatment resistance occurrence

Logistic regression was performed to further examine the total hippocampal volume, working memory and their potential interaction effects on treatment resistance. The reduced total hippocampal volume [OR (95% CI: 0.89 (0.81, 0.97), p = 0.01] and lower score of working memory [OR (95% CI: 0.94 (0.89, 0.98), p = 0.005] were significantly associated with higher risk of TRS compared to NTRS controlling for age, sex, education, age of illness onset and CPZ equivalent dose. However, there were no additional significant interactions between hippocampal volume and working memory in predicting treatment resistance (Table 3), suggesting largely independent contributions to treatment resistance.

Table 3.

Odds ratios of working memory and hippocampal volume on treatment resistance.

95% C.I. for OR
Estimate Standard Error p Value Odds Ratio Lower Upper
Hippocampal volume −0.12 0.05 0.01 0.89 0.81 0.97
Working memory −0.07 0.02 0.005 0.94 0.89 0.98
Hippocampal volume × working memory −0.002 0.005 0.68 NA NA NA

Adjusted for sex, age, duration of education, age of illness onset and CPZ equivalent dose.

Discussion

The findings of this study showed that only working memory was significantly associated with TRS compared to NTRS. Furthermore, TRS has significantly smaller volume of hippocampus compared to NTRS and HC, but there were no significant differences between NTRS and HC. Therefore, worse performance of working memory and smaller hippocampal volume might be associated with higher risk of treatment resistance,but working memory deficit and hippocampal reduction contributed to TRS and NTRS independently.

Some studies examined cognitive deficits in TRS as compared to NTRS, although the findings were inconsistent (de Bartolomeis et al., 2013, Frydecka et al., 2016, Joober et al., 2002, Sanchez et al., 2010, Vanes et al., 2018). The study of Frydecka et al. showed lower scores of processing speed, verbal fluency, cognitive flexibility and executive functions in TRS compared to NTRS. However, the definition for TRS yielded no significant differences in symptom severity between TRS and NTRS (Frydecka et al., 2016), which might suggest that the inclusion criteria for defining TRS vs. NTRS maybe unusual. The studies that did not control for age, sex and duration of illness showed TRS had worse performance on attention (Sanchez et al., 2010) or verbal memory and learning (Joober et al., 2002) compared to NTRS. In our study, TRS and NTRS patients were enrolled with a much stricter inclusion as consensus criteria; age, sex, education and duration of illness were matched as closely as possible, and comprehensive assessments of cognition were performed by MCCB. De Bartolomeis et al. reported TRS performed worse verbal memory score than NTRS, which also illustrated in our study before Bonferroni corrections (p = 0.007) (de Bartolomeis et al., 2013). One of the possible reasons was that the relatively small sample sizes decreased the statistic power. One study showed there were no significant differences between TRS (n=22) and NTRS (n=21) in the Strop task (Vanes et al., 2018). The inconsistency in several methodological choices might contribute to the discrepancy of the findings.

Accumulating evidence suggested hippocampal volume loss was the most severe across all subcortical structures (van Erp et al., 2016) and similar findings had been found in first-episode schizophrenia (Kalmady et al., 2017). A longitudinal study found patients with a first-episode psychosis that later developed to schizophrenia in a one year follow-up had markedly smaller left hippocampal volume compared to participants who did not progress to schizophrenia (Sauras et al., 2017). Although previous studies revealed that TRS patients had reduced hippocampal volume compared to HC, but the study did not compare TRS to NTRS patients (Maller et al., 2012). Our findings demonstrated that reduced hippocampal volumes in TRS were present even when compared to NTRS patients who were frequency-matched on age, sex, education, and illness duration, which suggested that reduced hippocampal volume in TRS might be associated with a risk for schizophrenia.

Cognitive deficit and reduced hippocampal volume in TRS patients might reflect a chronic course. However, NTRS showed no significant reduction in hippocampal volume compared to HC, despite duration of illness similar to TRS, which might be due to the response to antipsychotics. Animal studies found increased neurogenesis in the hippocampus by administration of several psychotropic medications (Chikama et al., 2017, Gottschling et al., 2016, Nasrallah et al., 2010).

The hippocampus is known to be important in cognitive performances (O’Neill et al., 2013, Zhang et al., 2013), especially working memory functions (Foster and Knierim, 2012, Sanderson and Bannerman, 2012), but the present study indicated that working memory deficit and hippocampus volume reduction independently contribute to the risk of treatment resistance. However, interactive effect between working memory and hippocampal volume on TRS attracted very little attention. Independent contributions of working memory and hippocampus to TRS suggested that the lack of correlation in such chronic patients may possibly because the hippocampal structures might be impaired to the extent that it gradually loses its effect on cognition, especially in TRS.

Limitations of the study should be considered. The TRS and NTRS groups enrolled were all inpatients, and long term hospitalizations might underlie cognitive and function decline (Harvey et al., 2013). This study did not examine sub-regions of the hippocampus or other brain areas, which might provide additional anatomic specificity on gray matter involvement in TRS. TRS and NTRS had different levels of exposure to antipsychotic medications which might also skew the findings. Specifically, TRS were more likely to be exposed to a higher dose, multiple medications, and clozapine than NTRS. Our analysis partially addressed this by covarying out CPZ equivalent dose; although CPZ captured only recent dosage of medications and did not necessarily account for all the medication exposure differences between the two groups. Longitudinal studies are necessary for differentiating some of these potential confounds.

Conclusions

Our study suggested that TRS was not associated with pan-domain deficits in cognition, but was more specifically linked to impaired working memory compared with NTRS. Hippocampus volume was also significantly associated with TRS although working memory deficit and smaller hippocampal volume appeared to independently contribute to TRS without significant interaction. Our study expanded the literature in understanding the features of cognitive impairment and the changes of brain structure in TRS, which aimed to identify the underlying mechanism and the associated biomarkers for TRS, an effort that would eventually support the crucial clinical work in developing more effective treatment for schizophrenia.

Supplementary Material

Supplemental tables

Acknowledgments

Supports were received from National Natural Science Foundation of China (81771452, 81761128021) and NIH R01MH112180 and R01MH116948.

Footnotes

Conflict of interest

The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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