Chumak et al. Journal of Neuroinflammation
https://doi.org/10.1186/s12974-024-03191-8(2024) 21:199

Journal of Neuroinflammation

Open Access

RESEARCH

Maternal n-3 enriched diet reprograms
the offspring neurovascular transcriptome
and blunts inflammation induced
by endotoxin in the neonate
Tetyana Chumak1*†, Amandine Jullienne2†, C. Joakim Ek1, Maryam Ardalan1, Pernilla Svedin1, Ryan Quan2,
Arjang Salehi2, Sirus Salari2, Andre Obenaus2, Zinaida S Vexler3 and Carina Mallard1
Abstract
Infection during the perinatal period can adversely affect brain development, predispose infants to ischemic
stroke and have lifelong consequences. We previously demonstrated that diet enriched in n-3 polyunsaturated
fatty acids (n-3 PUFA) transforms brain lipid composition in the offspring and protects the neonatal brain fromstroke, in part by blunting injurious immune responses. Critical to the interface between the brain and systemic
circulation is the vasculature, endothelial cells in particular, that support brain homeostasis and provide a barrier tosystemic infection. Here, we examined whether maternal PUFA-enriched diets exert reprograming of endothelial
cell signalling in postnatal day 9 mice after modeling aspects of infection using LPS. Transcriptome analysis was
performed on microvessels isolated from brains of pups from dams maintained on 3 different maternal dietsfrom gestation day 1: standard, n-3 enriched or n-6 enriched diets. Depending on the diet, in endothelial cells
LPS produced distinct regulation of pathways related to immune response, cell cycle, extracellular matrix, andangiogenesis. N-3 PUFA diet enabled higher immune reactivity in brain vasculature, while preventing imbalanceof cell cycle regulation and extracellular matrix cascades that accompanied inflammatory response in standard
diet. Cytokine analysis revealed a blunted LPS response in blood and brain of offspring from dams on n-3 enriched
diet. Analysis of cerebral vasculature in offspring in vivo revealed no differences in vessel density. However, vessel
complexity was decreased in response to LPS at 72 h in standard and n-6 diets. Thus, LPS modulates specifictranscriptomic changes in brain vessels of offspring rather than major structural vessel characteristics during earlylife. N-3 PUFA-enriched maternal diet in part prevents an imbalance in homeostatic processes, alters inflammation
and ultimately mitigates changes to the complexity of surface vessel networks that result from infection.
Importantly, maternal diet may presage offspring neurovascular outcomes later in life.
Keywords Neuroinflammation, Neonatal, Maternal diet, PUFA, Brain vessel transcriptomics, Brain angioarchitecture†

Tetyana Chumak and Amandine Jullienne contributed equally tothis work.
*Correspondence:
Tetyana Chumak
tetyana.chumak@gu.se
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The
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in this article, unless otherwise stated in a credit line to the data.

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Graphical Abstract

Introduction
Perinatal infection can impair neurodevelopment being
associated with motor and cognitive abnormalities in
infants [1] and predispose infants to stroke. Pathogenesis and timeline differ in neonatal and adult stroke due,among other things, to differences in blood-brain barrier(BBB) response [2, 3]. The BBB makes up a unique semipermeable interface between the systemic circulation andbrain parenchyma. Endothelial cells, a major componentof the BBB, ensure the delivery of oxygen and nutrientsand enable crosstalk between blood and brain [4]. The
brain vasculature continues to develop and refine itself
during the postnatal period in synergy with the overall
neurodevelopment and neuroplasticity [5]. Proper function of brain endothelial cells is crucial for brain development, as their genetic abnormality can cause long-term
neurovascular and behavioural alterations [6]. Endothelial cells function also as conditional immune cells
expressing pattern recognition and cytokine receptors,presenting antigens and releasing cytokines in response
to immune stimulation [7].
Long-chain polyunsaturated fatty acids (PUFAs) are
critical components of brain cell membranes. Both n-3
and n-6 long-chain PUFAs are highly enriched in thebrain and are mainly represented by docosahexaenoic

acid (DHA, 22:6 n-3) and arachidonic acid (AA, 20:4n-6) respectively. High n-3 PUFA maternal status has
beneficial effect on pregnancy duration, fetal brain development and eases neurovascular complications of premature birth [8–12]. PUFA content in the cell membranes
not only modulates mechanistic membrane properties
but also defines the nature of surrounding environment:
bioactive lipid derivatives of PUFAs are thought to contribute to creation of a pro- (n-6) or anti- (n-3) inflammatory milieu. Modulatory effects of n-3 PUFAs on immune
function of various immune cells such as macrophages
or microglia have been studied [13]. We previously
demonstrated that diet enriched in n-3 PUFA transforms brain lipid composition in the offspring and protects the neonatal brain from stroke, in part by blunting
injurious immune responses [14]. However, how PUFAs
affect the functions of brain endothelial cells in responseto an inflammatory stimulus in the neonatal period is
unknown.
In the current study, we aimed to characterize thecerebral endothelial transcriptome under physiological conditions (unperturbed mice) and following endotoxin (LPS) administration. Furthermore, we evaluatedimpact of different maternal PUFA diets on LPS-inducedchanges of endothelial RNA transcripts, systemic andChumak et al. Journal of Neuroinflammation(2024) 21:199

cerebral inflammation, and angioarchitecture in theoffspring.

Methods
Animals

Three- to 6-week-old C57BL/6J mice were purchasedfrom Charles River Laboratories (Sulzfeld, Germany) andhoused at the Laboratory for Experimental Biomedicine(University of Gothenburg, Gothenburg, Sweden), or
purchased from Jackson Laboratories (USA) and housed
at the Gillespie Neuroscience Research Facility vivarium(University of California, Irvine). Mice were provided
with nesting material, shelters and ad libitum access tofood and water.
Diet and treatment

Breeding cages were randomly assigned to one of theexperimental isocaloric diets (AIN-93G, BioServ): standard (Stand, BioServ #S7628), n-3 long chain (LC)-PUFA
enriched (n-3, BioServ #S7630; soybean oil replaced with
Menhaden Fish oil) or n-6 LC-PUFA supplemented (n-6,
BioServ #S7629; based on corn oil). The detailed composition of the diets is presented in our previous publication[14]. The day of birth was defined as postnatal day (P) 0.
At P9, pups received a single intraperitoneal injection of
lipopolysaccharide (LPS from E. coli O55:B5, 1 mg/kg,
Cat# 423, List labs) or equivalent volume of saline. The
dams remained on the experimental diet until offspringsacrifice (P10-P12). To allocate pups to particular experimental groups (LPS or saline), randomization in matchedpairs was performed based on sex and weight of animals[15]. Number of animals in each group are shown in
Suppl. Table 1.
Microvessel isolation and RNA sequencing

Microvessels were isolated from mouse brains at 24 hfollowing LPS/saline treatment. Brains from three pups
were pooled together to obtain one sample. Animals were
gently perfused with cold 0.9% saline, cerebellum andolfactory bulbs were removed, and the remaining brain
hemispheres were transferred to a Petri dish with cold
Ringers-Hepes (RH) buffer kept on ice, where meninges
were carefully removed. Brain tissue was then homogenized in RH solution containing 1% albumin using a
7 mL Dounce homogeniser with one gentle stroke. Allfollowing steps were conducted in a cold room using cold
solutions. The homogenate was centrifuged at 500 g for
10 min and supernatant removed. The pellet was thoroughly mixed with 7 mL of 17.5% 70 kDa dextran solution by alternative aspiration/expulsion and centrifugedat 3000 g for 40 min. The supernatant was removed, andpellet resuspended in 1% albumin RH solution. The solution was then filtrated drop-by-drop through a 100 μm
mesh, and microvessels collected on a 20 μm mesh. The

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vessels were resuspended in RH containing 0.1% albumin and spun at 500 g to form a microvessel pellet which
was frozen at -80 °C. Total RNA was extracted using themiRNeasy Micro Kit as per the guidelines from the manufacturer. RNA amount was determined through qubit
analysis (Invitrogen). Preparation of RNA library andtranscriptome sequencing was carried out by Novogene
Co., LTD (Cambridge, UK). Stranded RNA sequencing
with sequencing depth 60 M pair-end reads (2*250) was
performed.
Read alignment and gene expression quantification

FastQC (version 0.11.2) was used for quality control of
FASTQ format files and trimming of the adapter content
and quality trimming was performed using TrimGalore(version 0.4.0) tool, a wrapper around Cutadapt (version
1.9) [16]. Trimmed reads were mapped to the Mus-musculus mm10 genome using STAR (version 2.5.2b) andquantification of reads mapping to each gene was performed using FeatureCounts (version 1.6.4) [17, 18]. Listof annotated genes was downloaded from Ensembl (version 83) Mus-musculus GRCm38 [19].
Differential gene expression analysis and bioinformatics

Differential expression analysis was performed using
DESeq2 v1.32.0 from Bioconductor [20]. For pairwise
comparisons, we compared diets using standard diet asbaseline and then LPS vs. saline controls for each diet.
Pathway analysis was done through the Qiagen Ingenuity Pathways Analysis (IPA) (QIAGEN Inc., https://digitalinsights.qiagen.com/IPA) using genes with differential expression for each diet. During pathway analysis
and visualization of the results using IPA, closely related
pathway terms were omitted.
REACTOME browser was used to functionally annotate the genes regulated by LPS across diets [21, 22]. For
this, lists of differentially expressed genes were analysed
independently for each diet and the result of this overrepresentation analysis was graphically expressed in
REACTOME maps. These maps highlight (in yellow) the
biological processes regulated by LPS within each diet.
To explore the data, perform Principal component
analysis (PCA) and generate heatmaps, we used Qlucore Omics Explorer (Qlucore AB, Lund, Sweden). For
PCA plots, the lists of genes annotated to immune system (1292 genes), cell cycle (593) and the extracellularmatrix (ECM) organisation (280) were extracted from the
REACTOME website and used as input.
Volcano plots were generated using GraphPad Prism
version 10.0.3 (GraphPad Software, Boston, Massachusetts USA, www.graphpad.com).

Chumak et al. Journal of Neuroinflammation(2024) 21:199

Cytokine multiplex assays

At P10 (24 h after injection) or P12 (72 h after injection) the pups were deeply anesthetized via intraperitoneal administration of pentobarbital (Cat#338327, APL),
blood was collected through heart puncture, mixed with
5 µL of 100 mM ethylenediaminetetraacetic acid (EDTA,
ED2P, Sigma-Aldrich) and centrifuged to obtain bloodplasma for further analysis. Pups were then transcardially perfused with 0.9% saline and the brain hemispheres
were collected. Flash frozen plasma samples and brain
hemispheres were stored at -80 °C until further processing. Cytokine/chemokine levels were measured using
Bio-Plex Pro Mouse Cytokine Standard 31-Plex kit (Cat#12,009,159, BioRad) on a Bio-Plex 200 analyser as per the
manufacturer’s guidelines. Some of this data (control animals) have previously been published [14]. However, notethat all the experiments were performed in a matchedpairs manner as outlined above.
Since cytokine levels at baseline could be affected bydiet [14], to assess the cytokine response to LPS andcompare it between the diets, for each diet we calculated
the reaction to LPS using the following formula: Reaction
to LPS, pg/mL = cytokine concentration, pg/mL (LPS) mean cytokine concentration, pg/mL (saline).
Obtained values were then compared between different
diet groups.
Vessel painting

Imaging and analysis of vessel painted brains was performed as previously described [23]. Mice were injected
intraperitoneally with sodium nitroprusside (75 mg/kg) and heparin (20 mg/kg) 5 min before an intraperitoneal injection of ketamine/xylazine (90/10 mg/kg). Vessel painting was performed by injecting a solution of
1,1’-Dioctadecyl-3,3,3’,3’-Tetramethylindocarbocyanine
Perchlorate or DiI (Cat# D282, Invitrogen, 0.3 mg/mL
in phosphate buffer saline (PBS) containing 4% dextrose,
total volume of 250 µL) into the left ventricle of the heart,
followed by a 10 mL PBS flush and a 20 mL 4% paraformaldehyde (PFA) perfusion, using a peristaltic pump
(5 mL/min). Brains were extracted, post-fixed in 4% PFA
for 24 h, washed, and stored at 4 °C in PBS until imaging. Well-labelled brains were imaged axially using a fluorescence microscope (Keyence BZX810, Keyence Corp.,
Japan) with a 2x magnification. This allows for high resolution pictures and visualization up to 1 mm into the cortex. Images were analysed for axial brain area, vessel andbranching density, and vessel length using the Angiotool
software [24]. Vascular complexity was analysed using
the ImageJ plugin “FracLac” [25].
Statistical analyses

Statistical analysis and visualization of cytokine and vessel characteristic data were performed using GraphPad

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Prism version 10.0.3. Outliers in the cytokine analysis
were removed using the ROUT method based on the
False Discovery Rate and identification of the outliers
from nonlinear regression. All vessel painting data were
subjected to statistical interquartile range testing for
identification of outliers. Normality of the data distribution was checked using Q-Q plot of the data. Homogeneity of variance was tested using Brown-Forsythe test.
Two-way ANOVA was used to test the main effects ofdiet and LPS treatment on cytokine levels in blood andbrain, and on vessel characteristics. For cytokine levels,
Tukey’s multiple comparison test was used to assess differences between diets in the LPS-treated groups only,
since the analysis on saline-treated pups has been previously reported [14]. Cytokine reaction to LPS was compared between the diet groups using one-way ANOVA
with Fisher’s LSD post-hoc test for data with normal
distribution and equal variances, Welch’s ANOVA with
Unpaired t with Welch’s correction post-hoc test whengroups had unequal variances, and Kruskal-Wallis test
followed by uncorrected Dunn’s post hoc test when data
had not normal distribution. For vessel characteristics,
Tukey’s multiple comparison test was used to assess
differences between groups and Sidak’s multiple comparison test was used to assess differences between timepoints among each group. Differences were considered
statistically significant at p < 0.05. To analyse pup weight
data, unpaired t test was used to compare two groups or
Welch’s ANOVA with Dunnett’s post-hoc test to compare three groups of animals. Data for normalized countsof brain cell markers and vessel characteristics are presented as median with quartiles and at 10–90th percentile, horizontal bar in graphs for cytokine reaction to LPS
represents median value. Violin plots are used for the pup
weight change and brain area data. Graphs also include
individual data points. Principal component analysis(PCA) and heatmaps were generated using Qlucore Software (Lund, Sweden).

Results
LPS-induced deficits in body weight gain persist longer inpups from dams fed n-6 diet

LPS did not result in pup mortality in any of the diets
but significantly decreased weight gain in pups acrossall diets at 24 h compared to saline controls (Suppl.
Figure 1 A). At 72 h after LPS treatment only pups fed
n-6 diet exhibited significant deficiency in weight gain
(Suppl. Figure 1B). Consistent with our previous observations [14], diet did not affect the pregnancy progress or number of pups born per litter but weight of thepups from the dams fed n-3 diet was 9% higher than theweight of the pups from the dams on the other two dietsat P9, the time of LPS injection (Stand.: 4.16 ± 0.53, n-3:
4.51 ± 0.57, n-6: 4.08 ± 0.4 g; p = 0.003, Welch’s ANOVA,

Chumak et al. Journal of Neuroinflammation(2024) 21:199

Suppl. Figure 1 C). Axial brain area was derived from theAngiotool analysis and revealed no differences between
saline and LPS-treated groups at 24 h (Suppl. Figure 1D)
or 72 h (Suppl. Figure 1E).
Brain vessel isolation procedure leads to highly enriched
population of endothelial cells and pericytes

We first assessed purity of the isolated vessels using
the normalized counts (transcripts per million) of various brain cell markers for endothelial cells, pericytes,
astrocytes, microglia, neurons and oligodendrocytes, assummarised in Fig. 1A. Transcripts for brain endothelialassociated proteins such as Cldn-5, Glut1 and Abcb1/pgp, showed the highest number of counts among thecell markers. The second highest counts were found forthe pericyte-associated transcripts, such as Pdgfrb andCspg4/Ng2, but with an average of 5-fold lower counts
than the endothelia-associated genes. Forty- fifty-foldlower counts were observed for astrocyte-, microglia-,
oligodendrocyte- and neuron-associated transcripts.
Thus, the utilized isolation procedure led to a highly
enriched population of endothelial cells with associatedpericytes.
LPS affects brain microvasculature transcriptome in a dietdependent mannerStandard diet

Analysis of gene transcripts in brain microvessels aftersaline or LPS injection in pups from the dams fed standard diet revealed 791 differentially expressed genes(DEGs). Utilizing IPA, we generated a list of top 20
canonical pathways sorted based on overrepresentation
p-value using all DEGs (Fig. 1B). Most of the highest
overrepresented pathways were related to innate immunity and inflammation with the majority showing significant positive activation score (z-score > + 2) including
neutrophil extracellular trap (+ 5.38), macrophage classical activation (+ 3.71), neuroinflammation (+ 3.4), pathogen induced cytokine storm (+ 3.18), pyroptosis (+ 3.3)
(Fig. 1B, Suppl. Table 2). No activity pattern was predicted for antigen presentation, granulocyte and agranulocyte adhesion and diapedesis signalling pathways(Fig. 1B, Suppl. Table 2).
To gain deeper insight and explore the biological processes that are activated or inhibited in brain microvessels after LPS injection in standard diet group, we also
examined the biological functions generated by IPA. In
Fig. 1C the top 20 positively and negatively regulated
biological processes are listed sorted by z-score. Amongthe top positive z-scores, many are related to cell death(necrosis: +4.8; cell death of immune cells: +4.0; apoptosis of tumour cell lines: +3.5) and inflammatory response,
particularly associated with the interaction of circulating immune cells with the vessel wall (cell movement:

Page 5 of 17+3.5; migration: +3,6; adhesion: +4.5 and binding: +4.3 ofblood cells etc.; Fig. 1C, Suppl. Table 2). The top negative
z-score functions were related to pathogen survival (virallife cycle: -3.5; replication of virus: -1.9, etc.), host cell
survival (cell survival: -2.6 and viability: -1.8;), division(M phase: -2.42; alignment of chromosomes: -2.55; repair
of DNA: -3.24; cytokinesis: -2.95; cell cycle progression:-2.12) and proliferation (cell proliferation: -3.5 and development: -1.76 of tumour cell lines; Fig. 1C, Suppl. Table2). Thus, in brain microvessels of LPS-treated mice fromdams fed a standard diet, upregulation of inflammatory
response genes was accompanied by activation of cell
death and downregulation of cell proliferation pathways.
PUFA diets

Comparisons of gene expression under physiologicalconditions showed no differences between diets, whereas
LPS modulated gene expression in microvessels in dietspecific ways, as shown on a Venn diagram (Fig. 2A), a
heatmap of normalized counts of all DEGs (Fig. 2B) andon volcano plots (Fig. 2C). In the Venn diagram andthe heatmap, we combined all genes regulated by LPS(DEGs) within each diet (1214 genes in total). The total
number of genes regulated by LPS was lower in PUFA
diet groups than in mice on standard diet (742 in n-3 and677 in n-6). Out of all DEGs, 379 were common between
all three diets, and 325 were regulated by LPS exclusively
in the standard diet group (Fig. 2A). Brain microvessels from n-3 and n-6 diets exhibited a higher numberof overlapping DEGs (151) compared to the standard
diet (53 in n-3 and 34 in n-6), which suggests a similar
response to LPS. There was a lower proportion of downregulated genes in the n-3 (12% of DEGs) and n-6 (10%)
diets compared to the standard diet (39%).
Heatmap shows an overall more prominent upregulation of genes by LPS in the n-3 diet group, but more
pronounced downregulation of some genes in the standard diet pups (Fig. 2B). Upregulated genes (labelledin volcano plot) are consistent across all diets with the
majority associated with the immune system function(Fig. 2C). Several of the most downregulated microvessel mRNAs from pups on the standard diet were related
to the ECM (Lum, Adamts16) and collagen production(Col1a1, Col1a2, Col3a2, Col18a). The Col18a1 gene andsome ECM genes (Pxdn, Fbln2, Fbln5) were also downregulated in n-6 diet group. Among these, peroxidasin(Pxdn) and fabulin-5 (Fbln5) have previously been shown
to be involved in angiogenesis [26, 27]. The most downregulated transcripts in n-3 diet included several cell proliferation genes (H1f0, Gkn3, Odc1), but no ECM-related
genes.
The REACTOME browser was used to functionallyannotate and further compare the genes regulated by LPS
across diets. In the REACTOME map for standard diet

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Fig. 1 LPS leads to upregulation of inflammatory pathways while downregulating cell division and proliferation pathways in brain microvessels of offspring on standard diet. (A) Normalised counts of markers for endothelial cells (Cldn-5, CD31, Glut1, Abcb1/p-gp, Ocln, Zo-1), astrocytes (Gfap, Aldh1h1,
S100b, Aqp4), pericytes (CD13, Desmin, Pdgfrb, Cspg4/Ng2), neurons (NeuN), oligodendrocytes (Olig-2), and microglia (Iba1, CD11b). (B) Top 20 canonicalpathways regulated by LPS in standard diet group sorted based on overrepresentation p-value. The colours represent levels of the activation z-score: blue
indicates downregulated and orange- upregulated pathway, pathways for which the direction of change is not possible to predict are shown in grey.
(C) Top 20 up- and downregulated by LPS biological functions in brain microvessels in standard diet group sorted based on the z-score. Positive z-scoreindicates activation (red), negative z-score indicates inhibition (blue) of the biological function

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Fig. 2 The most significantly upregulated genes in brain microvessels after LPS are related to inflammation in all diets, while ECM genes are among
the most significantly downregulated genes in standard and n-6 diets only. (A) Venn diagram of all genes regulated by LPS (adjusted p < 0.05) withineach diet. (B) Heatmap of normalized counts of all genes regulated by LPS across all diets (1214 genes in total) sorted using hierarchical clustering. Eachcolumn refers to one microvessel sample and each row shows level of a specific gene. Numbers of transcripts for each gene were normalized over all
samples using z-score normalization and is shown using a colour scheme based on z-score distribution from − 2 to 2. (C) Scatter plot (Volcano plot) of
p-value (y-axis) versus difference of means (x-axis) of all genes within each diet. Significantly regulated genes are coloured blue (downregulated) or red(upregulated). Note the higher number of downregulated genes in the standard diet than in the n-3 or n-6 diets. Genes with high magnitude of change
and low p-value have been highlighted

in Fig. 3A, the three main categories identified above arehighlighted (in yellow): immune system (innate-, adaptive-immunity and cytokine production), mitotic cell
cycle (M phase etc.) and extracellular matrix organisation(ECM proteoglycans, collagen formation and degradation, and syndecan interactions). To a lesser extent, cell
death and hemostasis categories were also identified. In
contrast, following LPS, only immune system genes werestrongly identified in n-3-fed animals, whereas n-6 dietexhibited a high overrepresentation of immune system,

along with a minor representation of ECM genes, but nooverrepresentation of cell cycle-related genes. The lists ofpathways enriched by LPS across diets are presented in
the Suppl. Table 3.
To explore directionality of LPS-induced gene changes
within biological processes identified by REACTOME,
we utilised variable PCA plots (Fig. 3B). The vast majorityof genes associated with the immune system were upregulated in all diets; however, in n-3 and n-6 diets the percentage of downregulated immune genes was lower than

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Fig. 3 Functional annotation of genes validated stronger ECM gene response in standard and n-6 diet, additionally highlighting downregulation of cell
cycle pathways only in standard diet. (A) Graphical pathway maps from overrepresentation analysis of all genes regulated by LPS within each diet createdusing the Reactome browser (adjusted p < 0.05; DeSeq). Yellow represents specific enrichment. Enrichment of pathways annotated to immune system(innate- and adaptive-immune system as well as cytokine response) is present in all three diets. Note high annotation to cell cycle and extracellular matrix(ECM) organisation pathways in the standard diet. The n-3 and n-6 diet show no enrichment of cell cycle pathways and n-3 diet shows least enrichment of
ECM pathways. (B) PCA plots of individual genes annotated to immune system (upper panel), cell cycle (middle panel), and ECM (lower panel) regulated
by LPS within each diet. Variables are colour-coded according to distance between them rendering upregulated genes red and downregulated genes
blue. Numbers of regulated genes are stated in upper right corner out of all analysed genes for each process (in brackets)in the standard diet group (Fig. 3B, upper panel). Complementing these findings, IPA analysis showed higher
immune response (z-scores) in PUFA-supplemented
diets (Suppl. Table 3). PUFA diets showed less regulationof cell cycle genes as well as less inhibition of these genes
compared to the standard diet (Fig. 3, middle panel).
IPA analysis concurred showing negative z-scores forcell division and proliferation only in standard diet whilemost of these biological functions were not overrepresented in PUFA diets (Suppl. Table 3). In addition, LPS
activated cell death mechanisms in all diets while differently affecting expression of cell survival and viability
genes: negatively in standard diet and positively in PUFAsupplemented diets. PCA plots showed predominant
inhibition of ECM genes in standard and n-6 diets, aneffect not present in n-3 diet (Fig. 3, lower panel). Overall, the number of genes regulated in all these functions(immune system, cell cycle and ECM organisation) werehighest in the standard diet and lowest in the n-3 dietgroup. Thus, PUFA-supplemented diets diminished theeffect of LPS on immune system and cell survival genes,
while only n-3 diet reverted the LPS-triggered downregulation of ECM genes in standard diet.
Changes in cell survival, proliferation and impaired
ECM function can result in BBB malfunction and alteredangiogenesis [28, 29]. However, we found very few celljunction genes that were regulated by LPS across all dietssuggesting preserved BBB function (Suppl. Figure 2). In
contrast, fewer angiogenic genes were downregulated
in the n-3 diet compared to n-6 and standard diets. IPA
analysis showed activation of angiogenesis in the n-3 diet(+ 2.25) while z-scores for n-6 (+ 1.70) and standard diet(+ 0.45) did not reach significance (z-score > 2; Suppl.
Table 2).
N-3 diet diminishes and n-6 diet aggravates offspring
plasma cytokine response to LPS

Differences in inflammatory signalling in brain microvessels in standard diet compared to PUFA-supplemented
diet groups prompted us to examine the extent of systemic inflammatory changes on protein level in pups
from dams fed different diets. See Fig. 4A, Supplemental
Fig. 3A and Supplemental Tables 4, 5 for cytokine levelsin blood of pups from different groups and the results ofstatistical analysis.

Two-way ANOVA analysis showed a significant main
effect of diet on the plasma levels of 4 cytokines at 24 hand 2 cytokines at 72 h after LPS injection (Suppl. Tables
4, 5). Among them, Tukey’s post-hoc test showed higher
post-LPS plasma level of CXCL12 24 h after LPS treatment in pups from dams fed n-6 diets compared to thestandard diet group (Suppl. Table 4).
At 24 h after injection, significant main effect of LPS
treatment on the level of 21 inflammatory cytokines/chemokines was found (Suppl. Table 4). Levels of 11 cytokines were higher and 10 cytokines were lower in plasmaof LPS-treated animals compared to saline controls suggesting the ongoing process of resolution of systemic
inflammation at this time point (Fig. 4A, upper panel;
Suppl. Table 4). For these 21 cytokines we calculated thereaction to LPS and found differences (one-way ANOVAor Kruskal-Wallis) in cytokine response to LPS between
the diets for CXCL13 (p = 0.019), CXCL5 (p < 0.001),
CCL11 (p = 0.034), CXCL11 (p = 0.043), CCL17 (p = 0.02),
TNFα (p < 0.001), INFγ (p = 0.048) and IL6 (p = 0.035), seeFig. 4B. The reaction to LPS in the n-3 diet group wasoften downregulated compared to other diets consistent
with a stronger anti-inflammatory response (Fig. 4B).
In contrast, in the n-6 group, the response to LPS, wasmostly less downregulated compared to standard and/or
n-3 diet (Fig. 4B).
At 72 h after LPS injection, significant main effect oftreatment on cytokine levels in plasma was found for
9 cytokines with the majority [8] being lower in LPSexposed group compared to saline controls (Suppl. Figure 3 A, upper panel, Suppl. Table 5). Reaction to LPS
was different between the diets (one-way ANOVAor Kruskal-Wallis test) for CCL24 (p = 0.038), IL4(p = 0.0007), CCL7 (p = 0.034), CCL20 (p = 0.035), CCL17(p < 0.0001), TNFα (p = 0.009), CCL22 (p < 0.0001), andCCL19 (p = 0.002). For most of these cytokines, the levelsin the n-6 diet group were the farthest from the baseline
levels compared to standard and/or n-3 diets.
Taken together, analysis of systemic cytokine response
suggests inflammatory response in blood plasma 24 hafter LPS injection in all diets, with strongest anti-inflammatory effect 24 h and fastest restoration of the cytokine
balance by 72 h after initiation of inflammation in n-3
diet. The opposite dynamics was found in n-6 diet.

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Fig. 4 PUFA diets modulate cytokine levels in offspring blood and brain 24 h after LPS injection. (A) Heatmap of cytokine levels analysed in blood plasma
and brain of offspring from dams fed the standard, the n-3 or the n-6 enriched diet and injected with saline or LPS at P9. Each column refers to one animaland each row shows levels of a specific cytokine. Each cytokine level was normalized over all samples using Z-score normalization and is shown using acolour scheme based on Z-score distribution from − 2 to 2. Cytokines regulated by LPS (based on two-way ANOVA results) are highlighted with the frame.
(B, C) Graphs showing the reaction to LPS in plasma (B) or brain (C). Zero level indicates no difference between the level of the cytokine in LPS sample
and the mean level of the cytokine among the saline samples. Only graphs with significant differences between diet groups are presented. P values
presented on the graphs show results of the post-hoc test. One-way ANOVA with Fisher’s LSD (B: CXCL13, TNFα; C: CCL5), Welch’s ANOVA with Unpaired t
with Welch’s correction (C: CCL4) and Kruskal-Wallis with uncorrected Dunn’s (B: CXCL5, CCL17, CXCL11, CCL11, INFγ, IL6) post-hoc tests

PUFA-supplemented diets decrease post-LPS cytokine
levels in the offspring brain

Surface cerebrovascular network is unaffected by diet orby LPSTo examine neuroinflammation after systemic LPS injection, we analysed the levels of inflammatory cytokines inthe brain tissue at 24 and 72 h (Fig. 4A, lower panel). As
we have previously reported, most brain cytokines andchemokines basal levels were lower in n-3 and n-6 dietpups at P10 (24 h) compared to standard diet [14].
A significant main effect of diet was found on the levelof 26 cytokines at 24 h and 16 cytokines at 72 h after LPS
injection (Suppl. Tables 6 and 7). Post-hoc test showedthat all 26 cytokines regulated at 24 h, except CXCL10,
were lower in n-3 diet pups than in standard diet group.
Among them, levels of 10 cytokines were lower also in
n-6 diet compared to standard diet. At 72 h after LPS
injection, the level of 7 cytokines was lower in the brainsof LPS-treated pups from n-6 diet fed dams compared tothe standard diet group.
A significant main effect of LPS treatment was observed
for the levels of 16 cytokines in the brain 24 h after injection (Suppl. Table 6). For all of them except CX3CL1, thelevels in the LPS-treated group were higher than those in
the control group suggesting ongoing neuroinflammationin contrast to plasma (Fig. 4A, lower panel; Suppl. Table
7). Results from one-way ANOVA showed differences inreaction to LPS between diets for CCL4 (p = 0.005) and
CCL5 (p = 0.043), with the lowest reaction to LPS in n-3
diet (Fig. 4C).
Two-way ANOVA analysis showed that LPS treatment
resulted in regulation of 7 brain cytokines at 72 h (Suppl.
Figure 3 A, lower panel). Levels of 4 cytokines were elevated and levels of 3 were decreased after LPS (Suppl.
Table 7, Suppl. Figure 3 A, lower panel) in all diet groups
suggesting resolution of inflammation in progress.
Among them, the CCL22 reaction to LPS in the n-3 andn-6 diet (p < 0.0001, one-way ANOVA) and the CCL11
reaction to LPS in the n-3 diet (p = 0.0289, Kruskal-Wallistest) were lower compared to standard diet, see Suppl.
Figure 3 C.
Thus, a strong cytokine response was triggered in the
neonatal brain at 24 h after LPS injection but it declined
by 72 h. For some cytokines, this response was suppressed in the brains of pups from n-3 diet group.

Considering the notable downregulation of genes associated with the cell cycle and ECM in the standard diet,coupled with the upregulated angiogenesis in the n-3
diet, we tested if diets affect brain angioarchitecture following LPS exposure. We first assessed axial brain vessel
effects of diet on saline-treated animals at both 24 and72 h post-treatment (Fig. 5A) by injecting fluorescentdye (DiI) and examining DiI-labelled vessels using the
Angiotool software. We found no effect of the diet on
vessel density, branching density, average and total vessel length in saline or LPS-treated mice 24–72 h after
treatment (Fig. 5A-E and F-I). LPS exposure when compared to saline treatment did not result in any significant
changes in vessel features at 24 h (Fig. 5B-E) nor 72 h
(Fig. 5F-I).
Analysis of the fractal geometry was used to evaluate
the vessel network. Using the FracLac plugin in ImageJ,
each vessel is assigned a local fractal dimension (LFD)
value. A decreased LFD value is associated with lower
complexity of the vessels. Distribution graphs of LFDs areshown in Fig. 6A, D and G. Skewness, which is a measureof the symmetry of the distribution, represents the complexity of the vessels. Skewness (complexity) is decreased
when the peak of the distribution curve is shifted to theleft. Kurtosis shows how tailed the distribution is, witha lower kurtosis value being associated with a decreased
number of vessels. Our analysis showed a global decreasein vessel complexity (leftward shift of distribution curves,
decreased skewness values) at 72 h (dotted lines) compared to 24 h (solid lines) in all groups. Skewness showeda significant time effect in the standard diet (p = 0.023,
two-way ANOVA, Fig. 6B), n-6 diet (p = 0.012, twoway ANOVA, Fig. 6H) but not in the n-3 diet (p = 0.058,
two-way ANOVA, Fig. 6H). Skewness was significantly
decreased in the LPS group in the standard and n-6
diets between 24 h and 72 h (Sidak’s test: p = 0.012 andp = 0.037, Fig. 6B and H). This was not significant in
the n-3 diet (Sidak’s test: p = 0.098, Fig. 6E). Kurtosis of
the LFD curves, which represents the number of vessels, showed a significant effect of time in the n-6 group(p = 0.030, two-way ANOVA, Fig. 6I), but not in the n-3
group (p = 0.081, two-way ANOVA, Fig. 6F) or the standard diet (p = 0.161, two-way ANOVA, Fig. 6C). There
were no significant effects of treatment for skewness orChumak et al. Journal of Neuroinflammation(2024) 21:199

Page 12 of 17

Fig. 5 Morphological vessel characteristics are not affected by diet or treatment. (A) Left: Vessel painting image of one hemisphere from mice of thethree diet groups treated with saline injection at 72 h. Right: Angiotool result images showing vessels in red and branching points in blue. Vessel density,
branching density, average and total vessel length are not significantly affected by the diet nor by treatment at 24 h (B-E) or 72 h (F-I)

kurtosis in any of the diets. The primary finding was adecreased axial vascular complexity with brain maturation as illustrated in Fig. 6J.

Discussion
We have demonstrated that early-life inflammation following systemic LPS administration in mice at P9 led toa shift in brain microvessel transcriptomics towards a
proinflammatory and cell death phenotype at P10 in all
diets with higher immune reactivity in PUFA-supplemented diets. Concurrently downregulation of cell proliferation and ECM genes triggered by LPS in standard

diet group was diminished (n-6) or absent (n-3) in PUFA
supplemented diets. While pups from n-3 and n-6 PUFA
enriched diets showed the same directionality of LPStriggered changes in brain vessel transcriptomics, thesediets had opposing effects on systemic inflammation
where n-3 diet led to faster resolution of inflammationand normalization of cytokine levels and n-6 diet had
the opposite effect. At the same time, PUFA diets lowered the levels of cytokines in the brain rather than their
response to inflammatory stimulation. However, whenanalysing the vessel network on the axial surface, neither
diet nor LPS treatment affected the vessel morphology

Chumak et al. Journal of Neuroinflammation(2024) 21:199

Page 13 of 17

Fig. 6 Vessel network complexity is decreased with time but not affected by diet. Vessel network complexity analysis of the axial surface of the brain,
based on the distribution of the local fractal dimension of vessels. Results are shown for the standard (A-C), n-3 (D-F), and n-6 (G-I) diets. LFD curves areshown at 24 and 72 h for both saline and LPS conditions (A, D, G). Skewness values of the LFD curves (B, E, H) represent the complexity of the vessel
network. Kurtosis values represent the number of vessels (C, F, I). Representation of different complexity levels are shown in (J)and characteristics such as vessel density, branching density and vessel length.
Endotoxin-induced systemic inflammation severely
modulated transcriptomics of neonatal brain vasculature,primarily upregulating pathways related to inflammation and innate immune system regulation. The immune
role of endothelial cells has gained increasing attention inrecent years, including their role in central nervous system inflammation [7, 30]. Like macrophages, endothelial
cells can secrete cytokines [31, 32], perform phagocytosis [33], present antigens [34–36], and sense pathogenand damage-associated molecular patterns [36–38].
Additionally, endothelial cells interact with blood and/or tissue-resident innate immune cells, modulating theirimmune functions [39, 40]. Interestingly, we found that
supplementation of the diet with PUFA, independent onwhether they belong to n-3 or n-6 class, led to increased
immune reaction in brain microvasculature following
LPS. Our data showed higher prevalence of upregulationof immune system related genes over downregulation andhigher activation scores for cytokine storm, inflammatory pathways and pathways related to blood cell migration, adhesion and binding in both PUFA-supplemented
diets compared to the standard diet (Fig. 1B; Table 2).

Increased reactive state of brain microvessels after LPS
injection in animals fed the n-3 diet was not reflected in
the cytokine profiles of blood or brain. On the contrary,
blood cytokine response to LPS was often the lowest in
n-3 diet and the highest in n-6 diet. In brain, lower LPSstimulated cytokine levels in PUFA-supplemented diets
could be partially explained by the lower basal levels ofcytokines reported previously [14]. This discrepancy
between the highly upregulated inflammatory signallingin brain microvessels and the low inflammatory status inblood and brain in n-3 diet group may suggest that endothelial cells are not the primary source of cytokines contributing to systemic circulation and brain tissue. It may
also depend on the fact that some innate immunity functions are deficient in neonates compared to adults [41].
Our findings often showed same directionality of theeffects of PUFA-supplementation independent on prevalence of either n-3 or n-6 fatty acids in the diet. While
traditionally n-3 PUFAs were believed to possess antiinflammatory properties and n-6 PUFAs were considered to be purely pro-inflammatory, this concept has
undergone modifications in recent years [42–44]. For
example, cell culture studies show that both n-3 and n-6
PUFAs can attenuate the baseline release of cytokines

Chumak et al. Journal of Neuroinflammation(2024) 21:199

or promote/decrease the release of pro-inflammatory
cytokines, or supress expression of adhesion moleculeand coagulation factors after inflammatory stimulation[45–47]. A recent study by Hellstrom et al. reports association of higher DHA blood levels with lower severityof retinopathy of prematurity only when the level of AA
in blood is sufficiently high [48]. These and our findings
suggest that the nature of PUFA action on inflammation and neurovasculature during development are more
complex than previously thought, at least after infection.
LPS-induced endothelial activation can be accompanied by cell death via apoptosis, necroptosis and pyroptosis [49–52]. We also observed upregulation of thesecell death pathways after LPS in the brain microvessels of
the pups, independent of diet. Endothelial cell death has
been shown to elevate permeability of the BBB in vitro
and in vivo [53, 54]. Studies of the effect of LPS on the
BBB in neonates have shown mixed outcomes whichappear to be due to differences in dosing, number ofadministrations, species and age of animals and sourcesof LPS. Stolp et al. [55] showed an age dependent leakageof albumin only localized to white matter regions within
24-hours after 1 mg/kg LPS in neonatal rats, with lessleakage at P8 than P0, while no leakage was observed inolder animals. This dose of LPS resulted in around 40%
mortality in the neonatal rat with no mortality at later
developmental ages. Other studies showed BBB leakage
in neonatal rats and mice after repeated dosing of LPS(0.2-3 mg/kg) often accompanied with mortality increasing with higher doses [56, 57]. Our earlier study using
a single dose of 0.3 mg/kg LPS showed no BBB leakage[58]. Overall, this shows that LPS administered to neonates can open the BBB, however, it also shows that an
LPS dose which shows a marked inflammatory responsein blood does not necessarily leads to a compromised
BBB. On the background of these studies and given that
we see little regulation of tight junction-associated genes
in the cerebral vessels, it appears likely that our LPS injection has little effect on the BBB permeability although wecannot rule out that it does have some localized regional
effects.
Endothelial cell death can prevent angiogenesis [59].
Angiogenesis is active in the postnatal brain, expanding the capillary network and reaching stabilization by
P15-P25 when proliferation rates of endothelial cells
and pericytes decline [5]. Consequently, cell death pathways activated by LPS in brain microvessels of animals
fed the standard diet, together with altered cell proliferation pathways, may result in brain vascularization
deficits that would be prevented in animals fed PUFAsupplemented diets. In addition, changed ECM gene
expression observed in LPS-treated standard and n-6
diet groups can impact angiogenesis [60]. Furthermore,
overrepresentation analysis showed upregulation ofPage 14 of 17

angiogenic signalling in the brain microvessels of animals
fed n-3 PUFA diet. LPS and inflammation are known toaffect angiogenesis [61, 62]. For example, microvascular density in the brain is increased in neurological disorders conditioned by chronic neuroinflammation suchas Alzheimer’s disease and multiple sclerosis [63, 64].
Proinflammatory cytokines such as IL1β, IL6 and TNFα
promote endothelial cell proliferation and stimulate
angiogenesis [65]. We recently found higher vascularization in the hippocampus of pups 7 days after LPS exposure [66]. A single LPS injection at P4 was also shownto increase retinal vascularization as soon as 48 h later,
eventually resulting in lack of vascularization at P21 [67].
Similarly, prolonged exposure of prematurely born sheep
to LPS resulted in decreased vessel density and neurovascular remodelling in the cerebral cortex and white matter[68].
At the same time, there is evidence suggesting that
PUFAs can modulate angiogenesis in vitro [69, 70]. N-3
PUFA diet has been shown to increase the number ofproliferating endothelial cells, length and number of vessels after stroke in aged mice [71]. In a recent neonatal
mouse study, we showed that n-3 PUFA-supplemented
maternal diet decreased brain injury size in a modelof neonatal stroke, suggesting a beneficial role in postischemic inflammation and neuroprotection, while positive effects on neurovascular recovery were not studied
and cannot be excluded [14]. To our knowledge, no otherstudies have assessed the effects of PUFA-supplemented
maternal diet in the young or adult offspring in terms of
cerebral vascular remodelling. However, some groups
have shown beneficial effects of PUFA diet in rodents
in stroke studies. A 4-week PUFA-enriched diet in adultmice prior to ischemic stroke onset led to better histological, motor and neurological outcomes [72]. A single
dose of DHA injected to adult rats one to four hours after
ischemic stroke also showed beneficial effects including
decreased lesion volume and behavioural improvement[73, 74]. Finally, using transgenic mice overproducing
n-3 PUFAs, Wang and colleagues showed a beneficial
effect of n-3 PUFAs after transient ischemic stroke withimproved revascularization and angiogenesis [75].
In terms of vascularization deficits, our vessel painting results did not show any significant effects on vesselor branching density due to LPS treatment. Effects of
LPS on signalling pathways might take longer than 72 h
to reveal changes in the brain vasculature, which would
explain why we did not see any major angioarchitecture
differences between diets and treatments.
While we focused on the vascular effects in the offspring of dams fed n-3 enriched or deficient (n-6-supplemented) PUFA diets, deficiency of maternal diet in n-3
PUFAs can affect microglial and oligodendrocyte homeostasis during postnatal brain development even without

Chumak et al. Journal of Neuroinflammation(2024) 21:199

LPS challenge, as was demonstrated by altered microglial function and enhanced phagocytosis of synapses by
microglial cells in P21 mice [76] and by disrupted oligodendrocyte maturation and myelin integrity [77].
Our study has some limitations: as mentioned above,
we only examined effects of diets and LPS up to 72 h after
treatment. The study would also benefit from the cytokine level analysis at the shorter time points to describe
the early stages of inflammation. While we focused onmouse pups, we believe it would also be interesting tostudy effects at later time points in young adults andadults. It is known that maternal diet during foetal development has life-long lasting effects on offspring [78, 79].
It should also be noted that the cytokine and gene assays
were performed on whole cerebrum purified microvessels while the vessel painting experiments only assessedthe vascular network on the axial cortical surface. Hence,
we are not comparing the exact same population of
microvessels. However, we expect the systemic effects of
LPS to affect all brain vessels in a similar way.

Conclusion
The current study shows that PUFAs content in maternal
diet can modulate not only the inflammatory response
but also functional response of offspring brain vasculature to neonatal inflammation and thus might contribute to long-term neurodevelopmental consequences. At
that, our results challenge commonly accepted notion of
opposing biological effects of PUFAs from n-3 and n-6
classes, at least in the neonatal infection-related model,
and highlight the importance of maternal diet during
pregnancy and lactation.
Abbreviations
AA	Arachidonic Acid
ANOVA	Analysis of Variance
BBB	Blood-Brain Barrier
DEG	Differentially Expressed Gene
DHA	Docosahexaenoic Acid
ECM	Extracellular Matrix
IPA	Ingenuity Pathways AnalysiskDa	Kilodalton
LC	Long Chain
LFD	Local Fractal Dimension
LPS	Lipopolysaccharide
LSD	Least Significant DifferencemRNA	Messenger-RNAP	Postnatal Day
PCA	Principal Component Analysis
PUFA	Polyunsaturated Fatty Acids
RH	Ringers-Hepes
RNA	Ribonucleic Acid

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12974-024-03191-8.
Supplementary Material 1

Page 15 of 17

Acknowledgements
We thank Novogene Co., LTD (Cambridge, UK) for performing the sequencing
and Katarine Tuvé (Genomics and Bioinformatics Core Facility platforms at
the Sahlgrenska Academy, University of Gothenburg) for performing theread alignment and expression quantification of the sequencing raw data.
We acknowledge Kajsa Groustra (Experimental Biomedicine, Sahlgrenska
Academy, University of Gothenburg) for help with mouse breeding andfeeding the diets and Anna-Lena Leverin (Institute of Neuroscience andPhysiology, Centre of Perinatal Medicine and Health, Sahlgrenska Academy,
University of Gothenburg) for technical support. We thank Mary Hamer andKara Wendel (Department of Pediatrics, University of California Irvine, Irvine
CA, USA) for help with mouse breeding and perfusion for the vessel painting
experiments. Graphical abstract was created using BioRender.com.
Author contributions
T.C. and A.J. contributed equally. T.C., A.J., C.M., C.J.E., A.O. and Z.S.V.
conceptualized the study, designed experiments and wrote the manuscript.
T.C., A.J., M.A., C.J.E., P.S., R.Q., A.S. and S.S. performed animal studies, laboratory
experiments, data processing and analysis. All authors contributed to datainterpretation and critical revision of the manuscript.
Funding
The work was supported by National Institute of Health (R01 HL139685, ZSV,CM, AO), Swedish Research Council (VR-2017-01409; VR 2021 − 01872, CM),
Public Health Service at the Sahlgrenska University Hospital (ALFGBG-966107
to CM), The Swedish Brain Foundation (FO2022-0110 to CM) and Åhlen
Foundation (CM), the Mary von Sydows, born Wijk, Foundation (6119, TC),
Crown Princess Lovisa’s Association for Children’s Healthcare (2020 − 00561,
TC), The Wilhelm and Martina Lundgren’s Science Foundation (2019-3266,
2020–3591, 2021–3856, 2022–4089, TC), Åke Wiberg’s Foundation (M22-0189,
TC), the Infant Foundation (TC), Magnus Bergvall Foundation (2022 − 408, TC)
and Lundbeck foundation (R322-2019-2721, MA).
Open access funding provided by University of Gothenburg.
Data availability
The datasets used and/or analysed during the current study are available fromthe corresponding author on request.

Declarations
Ethical approval
All experiments were performed in accordance with ethical protocols
approved by the Gothenburg Animal Ethics Committee (no. 32/2016 and663/2018) and by the University of California Irvine Institutional Animal Careand Use Committee (no. 18–127).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
Institute of Neuroscience and Physiology, Centre of Perinatal Medicine
and Health, Sahlgrenska Academy, University of Gothenburg, Box 432,
Gothenburg 405 30, Sweden
2
Department of Pediatrics, University of California Irvine, Irvine, CA, USA
3
Department of Neurology, UCSF, San Francisco, CA, USA
Received: 27 February 2024 / Accepted: 30 July 2024

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