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\begin{document}

\title{Reduced functional connectivity induced by longitudinal alterations of
structure and perfusion may be associated with cognitive impairment in
patients on maintenance hemodialysis}



\author[1]{Wenbo Yang}%
\author[1]{Mingan Li}%
\author[1]{Lijun Song}%
\author[2]{Boyan Xu}%
\author[1]{Qian Chen}%
\author[1]{Zhenghan Yang}%
\author[1]{Wenhu Liu}%
\author[1]{Aihua Zhang}%
\author[1]{Hao Wang}%
\author[3]{Zhenchang Wang}%
\affil[1]{Capital Medical University Affiliated Beijing Friendship Hospital}%
\affil[2]{GE Healthcare}%
\affil[3]{Beijing Friendship Hospital, Capital Medical University}%


\vspace{-1em}



  
  \date{May 19, 2024}


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\selectlanguage{english}
\begin{abstract}
Background: Hemodialysis (HD) leads to cognitive impairment; however,
the pathophysiology of maintenance HD remains unclear. This study aimed
to investigate the longitudinal alterations in gray matter volume (GMV)
and cerebral blood flow (CBF) in patients on follow-up HD compared with
baseline HD, examine the alterations in functional connectivity (FC) by
defining co-changed brain regions as seed points, and investigate the
correlation between the co-changed brain regions and neuropsychological
test scores. Methods: Twenty-seven patients with HD and 30 healthy
controls were enrolled in this study. All participants underwent
high-resolution T1-weighted imaging, arterial spin labeling, and
functional MR imaging to measure GMV, CBF, and FC. The patients on HD
were assessed at baseline and 3 years subsequently. Results: The right
and left medial superior frontal gyrus (SFGmed.L) exhibited
significantly lower GMV and CBF in patients on follow-up HD compared
with patients on baseline HD and lower FC between the SFGmed.L and left
middle temporal gyrus (MTG.L). Decreased FC between the SFGmed.L and
MTG.L was positively correlated with neuropsychological test scores in
the follow-up HD group. Conclusions: Reduced GMV and CBF may result in
decreased FC between the SFGmed.L and MTG.L, which may be associated
with cognitive impairment in patients on maintenance HD. Our findings
provide unique insights into the pathological mechanisms of patients on
maintenance HD with cognitive impairment.%
\end{abstract}%



\sloppy


\textbf{Introduction}

The prevalence of chronic kidney disease (CKD) has increased over the
past few decades, and CKD has become a serious public health problem
worldwide (Ene-Iordache et al., 2016; G. B. D. Chronic Kidney Disease
Collaboration, 2020). When the glomerular filtration rate is \textless{}
15 ml/min/1.73 m\textsuperscript{2}, CKD progresses to end-stage renal
disease (ESRD) (Foley and Collins, 2007). Hemodialysis (HD) is the most
common kidney replacement therapy for patients with ESRD (Romagnani et
al., 2017), but it leads to a range of complications, including
cognitive impairment (Drew et al., 2019), cerebral atrophy (Wang et al.,
2020), cerebrovascular diseases (Jin et al., 2020a), iron deposition
(Wang et al., 2020a), white matter lesions (Chou et al., 2019), and
restless legs syndrome (Wang et al., 2021). Cognitive impairment is
extremely common in patients on HD, with a prevalence of 80\% (Murray et
al., 2006; van Zwieten et al., 2018). However, the pathophysiology of
cognitive impairment in patients on HD remains unclear. Accordingly,
cognitive function may experience abnormal brain changes, such as
atrophic cerebral gray matter, abnormal cerebral blood flow (CBF),
changes in brain activity, and iron deposition. Therefore, identifying
the changes of patients on HD in gray matter volume (GMV), CBF, and
functional connectivity (FC) may help understand neuronal mechanisms in
patients with HD.

Multimodal magnetic resonance imaging (MRI) techniques, such as
voxel-based morphological (VBM) analysis (Jin et al., 2020b; Zhang et
al., 2013), arterial spin labeling (ASL) (Findlay et al., 2019; Jiang et
al., 2016), resting-state functional MRI (rs-fMRI) (Chen et al., 2015;
Jin et al., 2021), diffusion tensor imaging (Zhang et al., 2015), and
quantitative susceptibility mapping (Chai et al., 2015; Hao Wang et al.,
2022), play a critical role in the early diagnosis of cognitive
impairment in patients on HD. Patients on HD exhibit abnormal brain
changes using these techniques. VBM studies have shown that patients on
HD have lower GMV in some brain regions compared with healthy controls
(HCs). For example, Qiu et al. found a significant decrease in GMV in
the bilateral medial orbito-prefrontal, bilateral dorsal lateral
prefrontal, and left middle temporal cortices in patients on HD (Qiu et
al., 2014). Moreover, Jin et al. reported a significant decrease in GMV
in the bilateral rectus, caudate, and temporal gyrus in patients on HD
(Jin et al., 2020b). In a recent ASL study, Jiang et al. found that
patients on HD had lower CBF mainly in the bilateral frontal and
anterior cingulate cortices compared with patients with ESRD who were
not on dialysis (Jiang et al., 2016). Using rs-fMRI, previous
investigators have observed abnormal brain FC in the default mode
network (DMN) of patients on HD (Zheng et al., 2023). As these studies
are cross-sectional, it is impossible to not consider the influence of
individual factors on their results. Therefore, further longitudinal
studies are required to determine the long-term consequences of HD on
brain changes and whether these changes correlate with cognitive
impairment. We hypothesized that long-term HD may lead to changes in
GMV, CBF, and FC in patients on HD.

In the current study, we aimed to (1) clarify the longitudinal
variations of GMV and CBF in patients on HD, (2) define co-changed brain
regions as seed points and illustrate abnormal seed-based FC in patients
on HD, and (3) investigate the correlation between the co-changed brain
regions and neuropsychological test scores.

\textbf{Methods}

All the participants were right-handed and had ESRD caused by
glomerulonephritis or primary hypertensive nephropathy. All the
participants underwent dialysis thrice a week for \textgreater{} 6
months, and each HD session lasted for approximately 4 h. The exclusion
criteria were as follows: (I) participants aged \textless{} 18 years;
(II) participants who received other renal replacement therapies; (III)
participants with a history of diabetic nephropathy; (IV) participants
with a history of brain lesions, including stroke, head trauma,
hemorrhage, infarction, and tumors; (V) participants with a history of
psychiatric disorders; (VI) participants with a history of alcohol abuse
or drug use; and (VII) participants with a history of claustrophobia. This
study was approved by the Medical Ethics Committee of Beijing Friendship
Hospital, Capital Medical University. All participants provided informed
consent, in accordance with the principles of the Declaration of
Helsinki.

Sixty-three patients were recruited into the HD group. Each patient
underwent brain MRI assessment, laboratory examinations, and Montreal
Cognitive Assessment (MoCA) evaluation at baseline, and most of the
patients (34 of 63) underwent a second examination (brain MRI
assessment, laboratory examinations, and MoCA evaluation) after 3 years.
However, seven patients (7 of 34) were excluded because of unqualified
image quality and head motion. Ultimately, 27 patients who met the
inclusion criteria were enrolled in the HD follow-up group. Thirty HCs
were recruited from local communities. Laboratory examinations and MoCA
evaluation were not performed in the HC group. No follow-up examinations
were performed in the HC group. The details of the participants are
presented in Supplementary 1. The demographic data, laboratory
examinations, and neurophysiological tests of all participants are
presented in Table 1.

\emph{Magnetic resonance imaging data acquisition}

A 3.0 Tesla magnetic resonance system (Discovery MR750W, General
Electric, Milwaukee, Wisconsin, USA) with an eight-channel phased array
coil was used to capture images. Before MRI, all participants were
instructed to avoid ingesting any meals or beverages containing
caffeine.

The three-dimensional (3D) brain volume imaging sequence was used to
acquire a structural image with the following parameters: repetition
time (TR) = 8.8 ms, echo time (TE) = 3.5 ms, inversion time = 450 ms,
axial slices = 196, slice thickness = 1 mm, matrix = 256 \selectlanguage{ngerman}× 256, field of
view (FOV) = 240 × 240 mm\textsuperscript{2}, and flip angle (FA) = 15°.

The pseudo-continuous ASL imaging sequence was applied for perfusion
imaging with the following parameters: TR = 4844 ms, TE = 10.5 ms, FOV =
240 × 240 mm\textsuperscript{2}, axial slices = 36, slice thickness = 4
mm, matrix = 128 × 128, labeling time = 2025 ms, post-label delay = 2025
ms, excitations = 3, and spiral-in readout = 512 sample points with 8
arms. The CBF maps were extracted from the original ASL data using an
MRI scanner.

The fMRI maps were collected using the following parameters: TR = 2000
ms, TE = 35 ms, axial slices = 28, slice thickness = 5 mm, time points =
200, matrix = 64 × 64, FOV = 24 × 24 cm\textsuperscript{2}, and FA =
90°.

\emph{VBM data processing}

The Digital Imaging and Communications in Medicine format of the MRI T1
raw image data acquired by the 3D-BRAVO sequence was converted to the
Neuroimaging Informatics Technology Initiative (NIfTI) format.
Subsequently, all attempted images were assessed for quality layer by
layer, and images with large artifacts were rejected. VBM data
processing was performed using the MATLAB-based (R2018b; MathWorks)
Statistical Parametric Mapping software (SPM12) and the SPM12-based
standard pipeline of a computational anatomy toolbox (CAT12). First, the
T1-weighted images were normalized to Montreal Neurological Institute
(MNI) space using the Diffeomorphic Anatomical Registration Through the
Exponentiated Lie (DARTEL) algebra (Ashburner, 2007) to enable the
analysis of group data. After normalizing the T1-weighted images, tissue
probability maps were used to segment gray matter, white matter, and
cerebrospinal fluid tissues. Finally, the GMV images were further
smoothed to reduce spatial noise using a 6 mm × 6 mm × 6-mm full-width
half maximum (FWHM) isotropic Gaussian kernel. The details are presented
in step 1 of Figure 1.

\emph{ASL data processing}

After subtracting the labeled images from the control images, we
generated ASL difference images using a single-compartment model.
Ultimately, the proton density-weighted reference and ASL difference
images produced the CBF images. The CBF maps were converted to NIfTI
format images, all the attempted images were assessed for quality layer
by layer, and images with large artifacts were rejected. Using the
DARTEL technique of the SPM12 software, the CBF maps in the individual
spaces of all participants were individually normalized to the MNI
standard space. After normalization, the quality of the CBF images of
all participants was assessed again, and severely distorted CBF images
were removed for the next step of analysis. All data were standardized
using the mean division method of the Data Processing Assistant for
Resting-State fMRI (DPARSF) advanced edition software package (Yan et
al., 2016) to increase parameter sensitivity. Finally, all standardized
CBF images were spatially smoothed using an isotropic Gaussian kernel
with a 6 mm × 6 mm × 6-mm FWHM to improve the signal-to-noise ratio of
the CBF images. The details are presented in step 2 of Figure 1.

\emph{Functional connectivity processing}

The DPARSF Advanced Edition software package was used to preprocess the
functional imaging data. The first 10 volumes for each participant were
excluded from the acquisition of 200 volumes. We corrected 190 volumes
for temporal differences between the slices. After slice time correction
had been made, head motion was corrected by realignment, and
participants with head motion \textgreater{} 3.0 mm were excluded. A
nuisance regression analysis was performed with the motion parameters
from the Friston-24 model, the white matter, cerebral spinal fluid, and
global signals as covariates. A co-registration step was then performed
between the individual T1 and mean functional images. The acquired T1
images were then segmented and spatially normalized to the MNI space
using the DARTEL algebra technique. The normalized functional images
were filtered using a bandpass filter with a frequency range of
0.01--0.10 Hz. Significantly different regions based on changes in GMV
and CBF were further selected as seed points for FC analyses. Therefore,
we defined the left medial superior frontal gyrus (SFGmed.L) and right
medial superior frontal gyrus (SFGmed.R) as seed points for subsequent
FC analysis. FC maps were derived from the correlation between the mean
time series of the seed points and the time series of the voxels within
the total brain cortices. Fisher's Z transformation was used to ensure
that the data were normally distributed. Spatial smoothing was performed
on the FC maps with a 6 mm × 6 mm × 6-mm FWHM isotropic Gaussian kernel.
The details are presented in step 3 of Figure 1.

\emph{Statistical analyses}

The Statistical Package for the Social Sciences (SPSS) version 26.0
(SPSS Inc., IBM Company, Chicago, IL, United States) and the SPM12
package were used for data analysis. Statistical significance was
defined as P \textless{} 0.05. The Shapiro--Wilk test was used to
determine whether the data were normally distributed. Two independent
sample t-tests were used to assess the differences in age and total
intracranial volume (TIV) between the HD (including baseline and
follow-up HD) and HC groups. Fisher's exact test was used to determine
differences in sex between the HD and HC groups. A paired-samples t-test
was used to demonstrate differences in systolic pressure and hemoglobin,
calcium, phosphorus, parathyroid hormone, and serum ferritin levels
between the baseline and follow-up HD groups. The paired-samples
Wilcoxon test was used to demonstrate differences in diastolic pressure,
creatinine levels, and MoCA scores between the baseline and follow-up HD
groups.

A paired sample t-test was performed to determine the differences in
GMV, CBF, and FC between the follow-up and baseline HD groups using
SPM12. Two independent sample t-tests were performed using SPM12 with
age, sex, and TIV as covariates to determine the differences in GMV,
CBF, and FC between the follow-up and baseline HD and HC groups. When
GMV and CBF were compared between the groups, multiple comparisons were
corrected using a voxel-wise threshold of P \textless{} 0.001 and a
cluster-level false discovery rate (FDR) threshold of P \textless{}
0.05. When FC was compared between groups, multiple comparisons were
corrected using a voxel-wise threshold of P \textless{} 0.001 and a
cluster-level Gaussian random field (GRF) threshold of P \textless{}
0.05. To examine the relationship between MoCA scores and GMV, CBF, and
FC, Pearson's correlation analysis was used for the baseline and
follow-up HD groups.

\textbf{Results}

\emph{Demographics and clinical characteristics}

Table 1 shows the characteristic demographic data of the participants.
Age, TIV, and sex did not differ significantly between the two groups (P
\textgreater{} 0.05). There were significant differences in diastolic
pressure, calcium levels, and parathyroid hormone levels between the
follow-up and baseline HD groups (P = 0.026, 0.004, and 0.001,
respectively). Compared with the baseline HD group, the MoCA scores of
the follow-up HD group were significantly lower (P \textless{} 0.001).

\emph{GMV} \emph{differences among the groups}

A comparison of GMV differences among the groups is shown in Figure 2
and Supplementary 2. Compared with the baseline HD group, the follow-up
HD group exhibited lower GMV in the bilateral medial superior frontal
gyrus (SFGmed) and bilateral dorsolateral superior frontal gyrus
(SFGdor) (P \textless{} 0.05, cluster-level FDR-corrected).

Compared with the HC group, the baseline HD group exhibited lower GMV in
the bilateral SFGmed, bilateral rectus, bilateral putamen, bilateral
anterior cingulate, and bilateral anterior cingulate and paracingulate
gyri (ACG) (P \textless{} 0.05, cluster-level FDR-corrected). Compared
with the HC group, the baseline HD group exhibited higher GMV in the
bilateral thalamus (P \textless{} 0.05, cluster-level FDR-corrected).

Compared with the HC group, the follow-up HD group exhibited lower GMV
in the bilateral SFGmed, bilateral SFGdor, and bilateral median
cingulate and paracingulate gyri (DCG), left middle frontal gyrus (MFG),
and left putamen (P \textless{} 0.05, cluster-level FDR-corrected).
Compared with the HC group, the follow-up HD group exhibited higher GMV
in the left thalamus (P \textless{} 0.05, cluster-level FDR-corrected).

\emph{CBF} \emph{differences among the groups}

A comparison of the differences in CBF between the groups is shown in
Figure 3 and Supplementary 3. Compared with the baseline HD group, the
follow-up HD group exhibited lower CBF in the bilateral SFGmed,
bilateral SFGdor, bilateral middle temporal gyrus (MTG), and left MFG (P
\textless{} 0.05, cluster-level FDR-corrected).

Compared with the HC group, the baseline HD group exhibited lower CBF in
the right insula (P \textless{} 0.05, cluster-level FDR-corrected).
Compared with the HC group, the baseline HD group exhibited higher CBF
in the right thalamus and SFGmed.R (P \textless{} 0.05, cluster-level
FDR-corrected).

Compared with the HC group, the follow-up HD group exhibited lower CBF
in the bilateral SFGmed and right MTG (P \textless{} 0.05, cluster-level
FDR-corrected). Compared with the HC group, the HD group exhibited
higher CBF in the bilateral thalamus (P \textless{} 0.05, cluster-level
FDR-corrected).

\emph{FC differences among the groups}

As part of the present study, the SFGmed.L and SFGmed.R were selected as
seed regions for FC analyses. The results for seed point SFGmed.L are
presented in Figure 4(A) and Supplementary 4. Compared with the baseline
HD group, the follow-up HD group exhibited lower FC with the left MFG
(MTG.L), left parahippocampal gyrus (PHG), and left posterior cingulate
gyrus (PCC) (P \textless{} 0.05, cluster-level GRF-corrected). Compared
with the HC group, the baseline HD group exhibited lower FC with the
MTG.L (P \textless{} 0.05, cluster-level GRF-corrected). Compared with
the HC group, the follow-up HD group exhibited lower FC with the MTG.L,
bilateral PCC, and left hippocampus (P \textless{} 0.05, cluster-level
GRF-corrected).

The results for the seed point SFGmed.R are presented in Figure 4(B) and
Supplementary 5. Compared with the baseline HD group, the follow-up HD
group exhibited lower FC with the MTG.L and right PHG (P \textless{}
0.05, cluster-level GRF-corrected). Compared with the HC group, the
baseline HD group exhibited lower FC with the MTG.L and right PCC (P
\textless{} 0.05, cluster-level GRF-corrected). Compared with the HC
group, the follow-up HD group exhibited lower FC with the MTG.L, right
PCC, right PHG, and right hippocampus (P \textless{} 0.05, cluster-level
GRF-corrected).

\emph{Correlations between MoCA scores and GMV, CBF, and FC in the
baseline and follow-up HD groups}

The decreased GMV in the SFGmed.L was positively correlated with the
MoCA scores in the baseline HD group (\emph{r =} 0.411, P = 0.033). The
decreased FC between the SFGmed.L and MTG.L was positively correlated
with the MoCA scores in the follow-up HD group (\emph{r =} 0.4468, P =
0.014). Correlation analyses based on the GMV of the SFG.L in the
follow-up HD group showed no significant correlation. Correlation
analyses based on the FC of the SFG.L in the baseline HD group showed no
significant correlation. Correlation analyses based on the CBF of the
SFG.L showed no significant correlation. A series of correlation
analyses based on SFGmed.R revealed no significant correlation. The
results of the correlation analysis based on SFGmed.L are shown in
Figure 5.

\textbf{Discussion}

We observed that the patients on baseline HD showed significantly lower
GMV compared with HCs, and some brain regions in the patients on
follow-up HD showed significantly lower GMV compared with the patients
on baseline HD, specifically in the bilateral SFGmed and SFGdor. The
patients on baseline HD showed more subtle abnormalities in CBF compared
with HCs, but some brain regions in the patients on follow-up HD showed
significantly lower CBF, including the bilateral SFGmed, bilateral
SFGdor, and bilateral MTG. The patients on follow-up HD showed decreased
FC between the bilateral SFGmed and MTG.L compared with the patients on
baseline HD.

HD, the most common kidney replacement therapy, can cause brain atrophy.
In our study, the patients on baseline HD demonstrated an extensively
lower GMV compared with HCs. In addition, some brain regions in the
patients on follow-up HD showed significantly lower GMV compared with
the patients on baseline HD, specifically in the bilateral SFGmed and
bilateral SFGdor. We observed a reduction in GMV in the bilateral rectus
of patients on HD at baseline, which is consistent with the findings of
previous studies. Jin et al.\textsuperscript{13} demonstrated that the
GMV of the bilateral rectus, caudate, and temporal gyri decreased in
patients on HD. Compared with the patients on baseline HD, the patients
on follow-up HD had lower GMV in the bilateral SFGmed and bilateral
SFGdor, which is similar but not identical to the results of previous
studies. For example, Wang et al. investigated the longitudinal changes
in GMV in patients on HD and found regionally lower GMV in the bilateral
frontal lobes, bilateral insula, bilateral temporal lobes, bilateral
rolandic operculum, and bilateral caudate in the patients on follow-up
HD compared with the patients on baseline HD (Huiying Wang et al.,
2022). However, the patient duration in our study was longer than that
reported in a previous study. In our study, the bilateral SFGmed,
SFGdor, and insula were located in the prefrontal cortex (PFC). In the
human brain, the PFC is responsible for regulating cognitive progress at
the highest level (Yan and Rein, 2022). Moreover, it plays an essential
role in cognitive functions, including working memory, attention, and
decision-making (Carlén, 2017). In particular, there is a strong
correlation between the SFGmed and the cognitive function (Li et al.,
2013; Liu et al., 2022). According to our study, the decrease in GMV in
the PFC is in line with that observed in previous studies, indicating
that HD may exacerbate deficits in executive function of patients with
ESRD. This may be a neurological mechanism for patients on HD with
cognitive impairment.

HD can also result in abnormal cerebral perfusion. In the present study,
we examined both cross-sectional and longitudinal variations in CBF. In
our study, the baseline HD group showed a more subtle alteration in CBF
compared with the HC group. However, the follow-up group showed a
significantly lower CBF in the PFC compared with the baseline HD group
and higher CBF in the bilateral thalamus compared with the HC group.
This suggests that HD, as an independent factor, is highly likely to
adversely affect CBF. Similar but not identical findings have been
reported in other studies in patients on HD. For example, Liu et al.
found that patients on HD had lower CBF than patients on baseline HD in
the orbitofrontal cortex and hippocampus after 6 months (Li et al.,
2020). In the present study, the regions of longitudinally decreased CBF
are also located in the PFC. A close relationship exists between changes
in the brain volume and CBF (Dai et al., 2009; Prohovnik et al., 2007).
In patients on HD, PFC atrophy and reduced CBF may explain to some
extent the cause of their cognitive impairments.

Alterations in CBF and GMV may have contributed to abnormal brain
activity in patients on HD. In our study, compared with the baseline HD
group, the follow-up HD group exhibited significantly lower FC between
the SFGmed.L with the left PCG, left MTG, and left PHG, exhibiting
significantly decreased FC between the SFGmed.R, bilateral MTG, and
right PHG. Interestingly, these regions are mostly located within the
DMN. In other words, HD may disrupt FC within the DMN through a
potential mechanism. Using the independent component analysis technique,
Ni et al. found that patients with ESRD had lower FC in the DMN compared
with HCs, specifically in the PCC, precuneus, and PFC. There is some
similarity between the results of our cross-sectional study and those of
the study (Ni et al., 2014); however, the differences may be associated
with the differences in technology and grouping. We found that the
patients on baseline HD had lower FC compared with HCs between the
SFGmed.L with the left MTG and left PHG and between the SFGmed.R with
the left MTG and right PCC, suggesting that patients at baseline already
have reduced FC within the DMN (Buckner et al., 2008). Furthermore, HD
may exacerbate this trend by disrupting neuronal connections in
functional networks. In the present study, impaired FC was found in the
prefrontal-PCC circuits of patients on HD, revealing a gradual decrease
in FC in the SFGmed from controls to baseline patients to follow-up
patients with PCC, which is a critical region responsible for
higher-order cognitive control (Ries et al., 2006; Sheth et al., 2012).
The reduced FC between the SFGmed and PHG in patients suggests that the
fronto-limbic network is hypoconnected. In general, the PHG is involved
in episodic memory, including associative memory, source memory, and
memory retrieval (Aminoff et al., 2013). According to a meta-analysis of
functional imaging studies on semantic processing, the SFGmed, MTG, and
PCC are brain regions that are reliably activated by general semantic
processes (Binder et al., 2009; Binder and Desai, 2011). In this study,
we hypothesized that reduced FC between the bilateral SFGmed and MTG.L
may reflect a decline in semantic processing function. Our findings
provide unique insights into the pathological mechanisms of patients on
HD with cognitive impairment.

Structural damage may lead to functional damage in patients on HD. At
baseline, the decreased GMV in the SFGmed.L was positively associated
with MoCA scores, indicating that cognitive impairment is likely to be
the predominant structural impairment in patients on baseline HD. After
3 years, the decreased FC between the SFGmed.L and MTG.L was positively
correlated with MoCA scores, suggesting that functional damage becomes a
more dominant factor resulting in cognitive impairment.

Our study has some limitations. First, the different HD durations
between the patients may have influenced the results. Hence, further
studies are required to determine how the HD duration affects brain
changes and cognitive impairment in patients on HD. Second, the effects
of different ESRD pathologies on the results were not considered. In the
future, we will explore the possible influences of various pathological
types. Third, this study had a small sample size. Therefore, additional
studies with larger sample sizes of patients with ESRD on HD should be
conducted.

\textbf{Conclusion}

HD may cause changes in the GMV and CBF of patients on maintenance HD.
Reduced GMV and CBF may result in decreased FC between the SFGmed.L and
MTG.L, which may be associated with cognitive impairment in patients on
maintenance HD. Our findings provide unique insights into the
pathological mechanisms of patients on maintenance HD with cognitive
impairment.

\textbf{Acknowledgments}

This work was supported by the Beijing Municipal Administration of
Hospitals Clinical Medicine Development of Special Funding Support
(contract grant numbers: ZYLX201824 and ZYLX202101), Beijing Municipal
Administration of Hospital's Mission Plan (contract grant number:
SML20150101), Beijing Scholars Program (contract grant number:{[}2015{]}
160), Beijing Friendship Hospital, Capital Medical University (contract
grant number: seed project YYZZ202129), Training Fund for Open Projects
at Clinical Institutes and Departments of Capital Medical University
(CCMU2022ZKYXY011), and Natural Science Foundation of China (82202099).

\textbf{Disclosure}

The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.

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\textbf{Table}

Table 1. Demographics and neuropsychologic tests of the baseline HD,
follow-up HD, and HC group\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Baseline HD (n = 27)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Follow-up HD (n = 27)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
HC (n = 30)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\emph{P}-value\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Age (years)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
54.2\selectlanguage{ngerman}±9.3\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
57.1\selectlanguage{ngerman}±9.3\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
52.9\selectlanguage{ngerman}±8.0\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.578\textsuperscript{a+} 0.067\textsuperscript{a++}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
TIV(cm\textsuperscript{3})\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1447.2\selectlanguage{ngerman}±125.7\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1443.6\selectlanguage{ngerman}±133.9\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1478.3\selectlanguage{ngerman}±133.9\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.372\textsuperscript{a+}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.326\textsuperscript{a++}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Sex (male/female)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
15/12\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
15/12\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
15/15\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.792\textsuperscript{b}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
HD duration (months)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
91.6\selectlanguage{ngerman}±66.1\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
123.4\selectlanguage{ngerman}±65.7\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
SP (mmHg)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
141.6\selectlanguage{ngerman}±24.6\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
136.0\selectlanguage{ngerman}±22.6\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.258\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
DP (mmHg)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
77 (67, 93)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
71 (62,80)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.026\textsuperscript{d}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Hemoglobin (g/L)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
116.9\selectlanguage{ngerman}±11.5\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
115.8\selectlanguage{ngerman}±10.4\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.654\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Creatinine (\selectlanguage{greek}μ\selectlanguage{english}mol/L)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
901.0 (861.9, 1102.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1034.2 (873.3, 1121.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.248\textsuperscript{d}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Calcium (mmol/L)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.2\selectlanguage{ngerman}±0.2\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
2.3\selectlanguage{ngerman}±0.1\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.004\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Phosphorus (mmol/L)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.9\selectlanguage{ngerman}±0.5\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.8\selectlanguage{ngerman}±0.6\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.469\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
PTH (pg/mL)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
212.6\selectlanguage{ngerman}±147.5\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
299.4\selectlanguage{ngerman}±232.4\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.001\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Serum ferritin (ng/mL)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
196.8\selectlanguage{ngerman}±122.6\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
169.2\selectlanguage{ngerman}±114.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
0.314\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
MoCA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
20.44\selectlanguage{ngerman}±3.32\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
18.00\selectlanguage{ngerman}±2.35\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
NA\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
<0.001\textsuperscript{c}\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

HD, hemodialysis; HC, healthy control; TIV, total intracranial volume;
SP, Systolic pressure; DP, Diastolic pressure; PTH, Parathyroid hormone;
NA, not applicable; MoCA, Montreal Cognitive Assessment.

\textsuperscript{+}Comparison between the baseline HD and HC group

\textsuperscript{++}Comparison between the follow-up HD and HC group

\textsuperscript{a} Two independent sample t-test

\textsuperscript{b} Fisher's exact test

\textsuperscript{c} Paired-samples t-test

\textsuperscript{d} Paired-samples Wilcoxon test

\textbf{Figure legends}

\textbf{Figure 1} Flowchart of the experimental procedure. GMV, gray
matter volume; CBF, cerebral blood flow; FC, functional connectivity;
MoCA, Montreal Cognitive Assessment.

\textbf{Figure 2} GMV alterations among the baseline HD, follow-up HD,
and HC groups. The cold color indicates a significant decrease in GMV
between groups (P \textless{} 0.05, FDR-corrected). The hot color
indicates a significant increase in GMV between groups (P \textless{}
0.05, FDR-corrected).

SFGmed.L, left superior frontal gyrus, medial; SFGmed.R, right superior
frontal gyrus, medial; THA.L, left thalamus; THA.R, right thalamus; HD,
hemodialysis; HC, healthy control; GMV, gray matter volume; FDR, false
discovery rate.

\textbf{Figure 3} CBF alterations among the baseline HD, follow-up HD,
and HC groups. The cold color indicates a significant decrease in CBF
between groups (P \textless{} 0.05, FDR-corrected). The hot color
indicates a significant increase in CBF between groups (P \textless{}
0.05, FDR-corrected).

SFGmed.L, left superior frontal gyrus, medial; SFGmed.R, right superior
frontal gyrus, medial; THA.R, right thalamus; HD, hemodialysis; HC,
healthy control; CBF, cerebral blood flow; FDR, false discovery rate.

\textbf{Figure 4 A} Difference among groups in FC between the SFGmed.L
and the rest of the whole brain. The cold color indicates a significant
decrease in FC between groups (P \textless{} 0.05, GRF-corrected). The
hot color indicates a significant increase in CBF between groups (P
\textless{} 0.05, GRF-corrected). \textbf{B} Difference among groups in
FC between the SFGmed.R and the rest of the whole brain. The cold color
indicates a significant decrease in FC between groups (P \textless{}
0.05, GRF-corrected). The hot color indicates a significant increase in
CBF between groups (P \textless{} 0.05, GRF-corrected).

MTG.L, left middle temporal gyrus; PHG.L, left parahippocampal gyrus;
PHG.R, right parahippocampal gyrus; PCG.L, left posterior cingulate
gyrus; PCG.R, right posterior cingulate gyrus; SFGmed.L, left superior
frontal gyrus, medial; SFGmed.R, right superior frontal gyrus, medial;
HD, hemodialysis; HC, healthy control; FC, functional connectivity; GRF,
Gaussian random field.

\textbf{Figure 5} \textbf{A} Correlation between MoCA scores and
decreased GMV in the SFGmed.L in the baseline HD group (\emph{r} =
0.411, P = 0.033). \textbf{B} Correlation between MoCA scores and
decreased GMV in the SFGmed.L in the follow-up HD group (\emph{r} =
0.350, P = 0.073). \textbf{C} Correlation between MoCA scores and
decreased CBF in the SFGmed.L in the baseline HD group (\emph{r} =
0.044, P = 0.827). \textbf{D} Correlation between MoCA scores and
decreased CBF in the SFGmed.L in the follow-up HD group (\emph{r} =
--0.060, P = 0.765). \textbf{E} Correlation between MoCA scores and
decreased FC in the SFGmed.L-MTG.L in the baseline HD group (\emph{r} =
0.245, P = 0.217). \textbf{F} Correlation between MoCA scores and
decreased FC in the SFGmed.L-MTG.L in the follow-up HD group (\emph{r
=}0.447, P = 0.014).

GMV, gray matter volume; CBF, cerebral blood flow; FC, functional
connectivity; MoCA, Montreal Cognitive Assessment; HD, hemodialysis; HC,
healthy control; SFGmed.L, left superior frontal gyrus, medial; MTG.L,
left middle temporal gyrus.

\textbf{Supplementary 1} Summary of the baseline HD, follow-up HD, and
HC group inclusions and exclusions. HD, hemodialysis; HC, healthy
control; MoCA, Montreal Cognitive Assessment.\selectlanguage{english}
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