ISSN 0006-2979, Biochemistry (Moscow), 2024, Vol. 89, No. 2, pp. 377-391 © Pleiades Publishing, Ltd., 2024.
377
REVIEW
Developing Peripheral Biochemical Biomarkers
of Brain Disorders: Insights from Zebrafish Models
Nikita P. Ilyin
1,a
, Elena V. Petersen
2,b
, Tatyana O. Kolesnikova
3,c
*,
Konstantin A. Demin
1,2,4,5,d
*, Sergey L. Khatsko
6,e
, Kirill V. Apuhtin
7,8,f
,
and Allan V. Kalueff
1,4,6,7,g
*
1
Institute of Translational Biomedicine, St. Petersburg State University, 199034 St.Petersburg, Russia
2
Moscow Institute of Physics and Technology, 115184 Moscow, Russia
3
Neuroscience Program, Sirius University of Science and Technology, 354340 Sochi, Russia
4
Institute of Experimental Medicine, Almazov National Medical Research Centre,
Ministry of Healthcare of the Russian Federation, 197341 St.Petersburg, Russia
5
Laboratory of Preclinical Bioscreening, Granov Russian Research Center of Radiology and Surgical Technologies,
Ministry of Healthcare of the Russian Federation, 197758 Pesochny, Russia
6
Ural Federal University, 620002 Ekaterinburg, Russia
7
Laboratory of Biopsychiatry, Scientific Research Institute of Neurosciences and Medicine,
630117 Novosibirsk, Russia
8
Neuroscience Division, Sirius University of Science and Technology, 354340 Sirius Federal Territory, Russia
a
e-mail: nik.ilyn.98@gmail.com 
b
e-mail: petersen.ev@mipt.ru 
c
e-mail: kolesnikova.to@talantiuspeh.ru
d
e-mail: k.demin@spbu.ru 
e
e-mail: sergey.khatsko@urfu.ru 
f
e-mail: kirillapuhtin@mail.ru
g
e-mail: avkalueff@gmail.com
Received August 22, 2023
Revised January 9, 2024
Accepted February 13, 2024
AbstractHigh prevalence of human brain disorders necessitates development of the reliable peripheral bio-
markers as diagnostic and disease-monitoring tools. In addition to clinical studies, animal models markedly ad-
vance studying of non-brain abnormalities associated with brain pathogenesis. The zebrafish (Danio rerio) is be-
coming increasingly popular as an animal model organism in translational neuroscience. These fish share some
practical advantages over mammalian models together with high genetic homology and evolutionarily conserved
biochemical and neurobehavioral phenotypes, thus enabling large-scale modeling of human brain diseases. Here,
we review mounting evidence on peripheral biomarkers of brain disorders in zebrafish models, focusing on al-
tered biochemistry (lipids, carbohydrates, proteins, and other non-signal molecules, as well as metabolic reactions
and activity of enzymes). Collectively, these data strongly support the utility of zebrafish (from a systems biology
standpoint) to study peripheral manifestations of brain disorders, as well as highlight potential applications ofbio-
chemical biomarkers in zebrafish models to biomarker-based drug discovery and development.
DOI: 10.1134/S0006297924020160
Keywords: zebrafish, brain disorders, biomarker, peripheral, neurodegeneration, stress, epilepsy
* To whom correspondence should be addressed.
INTRODUCTION
Central nervous system (CNS) disorders, such as
neurodegenerative (Alzheimer’s and Parkinson’s) and
affective (depression and anxiety) diseases, are com-
plex, wide-spread, and treatment-resistant, and they
contribute significantly to the global public health
costs [1, 2]. The lack of objective evidence-based ap-
proaches, especially for early diagnostics of these
disorders, underlies the growing interest to studying
biomarkers of the CNS pathogenesis, including be-
havioral, morphological, and molecular responses.
ILYIN et al.378
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
Abbreviations: ATP,adenosine triphosphate; CNS,central nervous system; EEG,electroencephalography; GABA,γ-amino-
butyric acid; NPC,Niemann–Pick typeC; PLP,pyridoxal 5′-phosphate; PLPBP, PLP-binding protein; PNPO,pyridoxamine
5′-phosphate oxidase.
In addition to molecular biomarkers in the brain,
pathological biochemical changes also occur peripher-
ally, necessitating identification of novel biochemical
biomarkers of CNS disorders [3, 4].
Studying clinical biomarkers in vivo is often hin-
dered by impossibility of measuring pathological
markers directly in the brain tissue using invasive
methods. Thus, using pathological biomarkers from
peripheral samples, such as blood or skin, becomes
more relevant [3, 5]. Validity of this approach is based
on the fact that various signs of central pathology can
be successfully measured in peripheral tissues. For ex-
ample, while this is particularly common for the dis-
eases associated with neuroendocrine deficits or with
damaged blood-brain barrier (BBB) [6], peripheral bio-
markers can originate in the periphery, reflecting sys-
temic nature of CNS pathogenesis [7, 8].
In addition to the established clinical biomarkers,
there are also animal models, especially rodents, wide-
ly used to study CNS pathogenesis and biomarker val-
idation [9-11]. Because collecting brain tissue is not a
problem in animals, their peripheral biomarkers as-
sociated with central neuropathology are relatively
understudied. However, validity of the peripheral bio-
markers in animals would be markedly reinforced by
showing that they reproduce the signs of peripheral
dysregulations observed in clinical studies, e.g., endo-
crine hyperactivation in animal models of depression
[11, 12]. Moreover, animal models of CNS diseases can
help not only to identify peripheral biomarkers among
those already discovered in patients, but also to search
for novel biomarkers not yet identified previously [13].
Thus, studying non-brain abnormalities in animal mod-
els of CNS pathologies helps elucidate their pathophys-
iological mechanisms, providing novel insights into a
complex ‘systems biology’ nature of these disorders,
eventually facilitating translational research and de-
velopment of novel therapies [14, 15].
Addressing this problem further, here we re-
view mounting evidence on peripheral biomarkers
of brain disorders, focusing on altered biochemistry
(lipids, carbohydrates, proteins, and other non-sig-
nal molecules, as well as metabolic reactions and ac-
tivity of enzymes), in a novel model organism, the
zebrafish (Danio rerio). Zebrafish is becoming one of
the most important model species in biomedicine, in-
cluding neuroscience[16-20]. The idea for the present
paper originated from the invited talk on this topic,
given bythe senior co-author in May 2022, and subse-
quent discussion, at Professor Vladimir P. Skulachev’s
seminar at Belozersky Institute of Physico-Chemi-
cal Biology in Lomonosov Moscow State University.
Thispaper is dedicated to the memory of academician
V. P. Skulachev (1935-2023), a brilliant scientist, a re-
spected scholar, and a great colleague.
ZEBRAFISH MODELS
AND BIOMARKERS OF CNS DISORDERS
A common problem of using animal biomarkers
in biomedical research is their ambiguous interpreta-
tion and often somewhat unclear validity [21]. For ex-
ample, this problem is particularly inherent in transla-
tional neuroscience since various animal models may
have their own, acquired through natural evolution,
unique characteristics [22]. Thus, one of the strategies
for a more accurate and comprehensive modeling of
CNS pathobiology is to expand the number of model
objects (beyond the traditionally used rodents), there-
by utilizing a wider spectrum of animals from various
taxa [22-24]. A small teleost fish, the zebrafish, has re-
cently emergedas a novel powerful model organism in
translational neuroscience [25, 26]. This fish possesses
several key advantages over other model organisms
(e.g., rodents), providing a reasonable compromise
between the system complexity and practical sim-
plicity [27], and also enabling a large-scale modeling
of “core”, evolutionary conserved aspects of complex
brain disorders [28, 29]. Table 1 summarizes both ad-
vantages and limitations of zebrafish models in bio-
medical research (also see further).
Multiple zebrafish models of brain disorders have
also been developed (Tables 2 and 3), based on targeting
a wide range of their CNS biomarkers. For example,
similarly to rodent studies, zebrafish models of Parkin-
son’s disease utilize reduced brain levels of dopamine
and tyrosine hydroxylase (the main enzyme of dopa-
mine biosynthesis) as markers of dopaminergic neu-
ronal loss [43, 44]. Likewise, in the zebrafish models
of pentylenetetrazol (PTZ)-induced epilepsy, the brain
gene expression level of c-fos is often used as a bio-
marker of overall neuronal activity [45, 46]. Another
example involves biomarkers of neuroinflammation
observed in various zebrafish models of traumatic
brain injury [47, 48]. While multiple other (e.g., endo-
crine, genomic, and proteomic) peripheral biomarkers
of CNS disorders have already been developed as well,
here we focus on purely biochemical biomarkers, in-
cluding lipids, non-signaling proteins, carbohydrates,
amino acids and their derivatives that can be easily
analyzed in peripheral samples. Accordingly, descrip-
tion of the peripheral genomic (mutations and genet-
ic polymorphism), transcriptomic (genes expression
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BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
Table 1. Brief summary of selected major advantages and limitations of utilizing zebrafish models in translational
biomedicine and neuroscience
Advantages References
Low cost of maintenance [30]
Rapid development [25]
Highly tractable genome [31]
High percent of genetic homology to humans [32]
Ease of pharmacological manipulations [30]
Ease of genetic manipulations [33]
Potential for high-throughput drug screening [34]
Limitations
Evolutionary remoteness from humans, contributing to some existing genetic, biochemical,
and physiological differences
[35, 36]
Certain neuroanatomical differences from mammals (e.g., lack of neocortex and midbrain
dopaminergic neurons)
[16, 37, 38]
Some of the genes exist in two copies compared to one copy in mammals
(due to the teleost-specific whole-genome duplication event)
[39]
Limited availability of the genetically characterized inbred and outbred strains compared
to rodent models
[26, 40]
Superior neuroregenertative potential (vs. mammals) that complicates modeling
neurodegenerative disorders
[41]
Lack of certain complex behaviors characteristic of mammals (e.g., parental care) [42]
Table 2. Selected examples of zebrafish models of human
brain disorders and their CNS biomarkers
Models References
Parkinson’s disease
↓ Tyrosine hydroxylase [43]
↓ Dopamine [44]
Epilepsy
c-fos expression [45, 46]
↓ γ-Aminobutyric acid (GABA) [49]
Stress-related (affective) disorders
↓ Glucocorticoid receptor expression [50]
↓ Serotonin [51]
levels), and endocrine (hormones, cytokines) biomark-
ers was beyond the scope of the present study.
PERIPHERAL BIOCHEMICAL BIOMARKERS
OF ZEBRAFISH CNS PATHOGENESIS
Stress-related disorders. Stress is a key risk fac-
tor in pathogenesis of multiple CNS diseases, including
anxiety and depression – the two most common and
widespread brain maladies [76-78]. There are many ze-
brafish models based both on acute [79-82] and chron-
ic stress exposure [50, 83-89] that recapitulate the signs
of central and peripheral dysregulation characteristic
of stress-related pathologies in humans. While cortisol
is widely accepted as a peripheral biomarker of stress
level in zebrafish [90-92], metabolomic analyses may
also accurately assess the overall physiological stress
response of an organism [52].
Indeed, fish subjected to acute netting stress and
two different behavioral tests demonstrated changes
ILYIN et al.380
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
Table 3. Zebrafish models of human brain disorders and their peripheral biochemical biomarkers
Models, biomarkers Responses References
Stress-related disorders
Alanine, taurine, adenosine, creatine, lactate, acetate, leucine/isoleucine,
and histidine
[52]
HADHB, hspa8, hspa5, actb1, mych4, atp2a1, zgc:86709, and zgc:86725 proteins [53]
Heart proteins of glucose metabolism, gluconeogenesis,
the ubiquitin–proteasome system and peroxisomal proliferator-activated
receptor signaling
rate of synthesis [54]
Niemann–Pick type C disease (NPC)
Unesterified cholesterol [55-59]
Phospholipids and sphingolipids
altered
whole-body levels
[60]
Epilepsy (metabolic biomarkers)
Glycolysis rate and mitochondrial respiration rate [61-63]
Basal respiration, maximal respiration, mitochondrial respiration,
proton leaks, and ATP-linked respiration rates
[64]
Glucose level [61]
B6-responsive epilepsies
Pyridoxal and pyridoxal 5′-phosphate [65-68]
Pyridoxine-dependent epilepsy
Piperideine-6-carboxylate, aminoadipate semialdehyde, pipecolic acid [67, 68]
The Krebs cycle metabolites (citrate, malate, fumarate, isocitrate, lactate) [69]
γ-Aminobutyric acid (GABA) pathway metabolites (γ-hydroxybutyrate,
glutamine, glutamate, total GABA, succinic semialdehyde)
[69]
Activity of electron transport chain enzymes [69]
Pyridoxamine 5′-phosphate oxidase (PNPO) deficiency
Pyridoxamine 5′-phosphate, pyridoxine 5′-phosphate [65]
Glycine, glutamate and GABA [65]
Lysine, arginine, tryptophan, methionine, phenylalanine, and threonine [65]
Pyridoxal 5′-Phosphate (PLP)-Binding Protein (PLPBP) deficiency
Lysine, threonine, asparagine, glutamate, glutamine, proline, alanine,
α-aminobutyric acid, GABA
[66]
Methionine, cystathionine, isoleucine, tyrosine, β-alanine, phenylalanine,
aminoisobutyric acid, tryptophan
[66]
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BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
Table 3 (cont.)
Models, biomarkers Responses References
Parkinson’s disease
Dehydrogenase-dependent resazurin metabolism [70]
Maximal mitochondrial respiration [71]
Parkin, pink1, and dj-1 protein content [72]
Lipid peroxidation [73, 74]
Glutathione [73, 75]
Superoxide dismutase activity [73, 74]
Glutathione-S-transferase and catalase activity [73, 74]
in the whole-body quantitative content of a number of
metabolites (e.g., alanine, taurine, adenosine, creatine,
lactate, acetate, leucine/isoleucine, and histidine). Im-
portantly, content of some metabolites seemed to be
influenced not only by the netting stress exposure
per se, but also by behavioral testing procedures
which themselves are well-established stressors– indi-
cating the sensitivity of metabolomic characterization
to biochemical alterations induced by altered envi-
ronment [52]. Another proteomic study has demon-
strated that chronic stress (electric shock) upregulates
the whole-body content of several zebrafish proteins
(e.g., HADHB, hspa8, hspa5, actb1, mych4, atp2a1,
zgc:86709, and zgc:86725) regardless of stress predict-
ability [53]. Besides the heat shock proteins, these pro-
tein biomarkers include enzymes, cation transporters,
cytoskeleton proteins, increased level of which may be
considered to play a role in counteracting conditions
associated with elevated fear/anxiety levels.
Moreover, in addition to CNS, cardiovascular sys-
tem is also highly susceptible to the destructive effects
of stress [93, 94]. Proteomic analyses in the chronic
unpredictable stress (CUS) zebrafish model revealed
changes caused by stress in the zebrafish hearts [95].
For example, the observed anxiety-like behavioral
phenotype was accompanied by significantly altered
synthesis rates of several heart proteins involved in
such processes as glycolysis, gluconeogenesis, and hy-
poxia response. Notably, even acute low-level stress af-
fects zebrafish heart proteome, causing decrease in the
rates of degradation of cardiac muscle proteins [54].
Niemann–Pick type C disease. The Niemann–Pick
type C disease (NPC) is a severe autosomal recessive
disease caused by mutations in the NPC1 and NPC2
genes that result in abnormal lysosomal trafficking of
cholesterol and some other lipids [96-98]. This disease
is characterized by a wide range of progressive neu-
rological symptoms including neurodegeneration [99,
100]. Recently, several genetic zebrafish models of NPC
have been successfully developed targeting both NPC1
[55, 56, 59] and NPC2 [57,  58] orthologs of the respec-
tive human genes. Besides the characteristic NPC-like
neurological symptoms and visceral organs damage,
these fish models recapitulate the key biochemical
hallmark of the disease – intracellular accumulation
of unesterified cholesterol. Importantly, free cholester-
ol accumulates in the cells of almost all body tissues
of zebrafish and its presence can be determined by
simple staining techniques [55, 56, 59]. Treatment of
larval zebrafish with 2HPβCD (a drug effective in clin-
ical trials) significantly reduces the cholesterol-posi-
tive staining in neuromast cells [59]. Collectively, this
supports utility of unesterified cholesterol as a suit-
able biomarker of NPC in zebrafish, potentially appli-
cable for high-throughput drug screening. However,
cholesterol is not the only lipid dysregulated in NPC;
altered whole-body distribution of several sphingo-
lipids and phospholipids in the npc1
–/–
zebrafish has
been revealed in a recent study using elaborated 3D
MALDI mass spectrometry imaging (MALDI-MSI) spec-
trometry imaging [60]. Thus, unique lipid biosignatures
for different organs could shed light on the nature of
multifaceted pathological manifestations of NPC.
Epilepsy. Epilepsy is a group of severely debili-
tating neurological disorders characterized by sponta-
neous and recurrent seizures. Zebrafish is becoming
increasingly popular as an alternative model organism
in epilepsy research, with multiple pharmacological
(using proconvulsant drugs) and genetic (based on epi-
lepsy-causing mutations) models of epilepsy in zebraf-
ish being developed (for comprehensive review see
[101]). While most of these models employ behavioral
(seizure-like behavior) and electroencephalographic
(EEG) biomarkers, some studies indicate systemic bio-
ILYIN et al.382
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
chemical/bioenergetic dysregulation that accompanies
the observed epilepsy phenotype.
Indeed, the use of biochemical biomarkers is com-
mon in zebrafish models of B6-responsive epilepsies
a group of rare genetic disorders, characterized by
severe neonatal seizures that can be alleviated by vi-
tamin B6 [66, 102, 103]. For example, aldh7a1
–/–
zebraf-
ish larvae represent the first animal model of pyridox-
ine-dependent epilepsy, as they readily recapitulate the
main biochemical markers of this disorder: accumula-
tion of piperideine-6-carboxylate, aminoadipate semi-
aldehyde (lysine catabolism metabolites, the substrates
of ALDH7a1 enzyme) and reduced levels of B6 vitam-
ers– pyridoxal(PL), pyridoxal 5′-phosphate (PLP), and
pyridoxamine 5′-phosphate (PMP) [67, 68]. Additionally,
these fish exhibit an approximately twice lower sys-
temic levels of γ-aminobutyric acid (GABA) [67]. While
B6 deficiency in the pyridoxine-dependent epilepsy is
known to be caused by chemical complexation of PLP
with piperideine-6-carboxylate [104], the proposed ex-
planation of reduced GABA levels suggests impaired ac-
tivity of PLP-dependent glutamate decarboxylase – the
key enzyme of GABA biosynthesis [67]. A broad spec-
trum of biochemical dysregulations in aldh7a1
–/–
ze-
brafish likely involves reduced levels of tricarboxylic
acid (Krebs) cycle metabolites, GABA pathway metab-
olites, and activity of the electron transport chain en-
zymes [69].
Biochemical biomarkers have also been extensively
characterized in the zebrafish model of pyridoxamine
5′-phosphate oxidase (PNPO) deficiency – a B6-respon-
sive epilepsy caused by mutation in the gene encoding
the PLP biosynthesis enzyme [105]. The UPLC-MS/MS
analyses of extracts of homogenized bodies of pnpo
–/–
zebrafish reveal the accumulation of pyridoxamine
5′-phosphate, pyridoxine 5′-phosphate (substrates of
PNPO), and reduced levels of pyridoxal 5′-phosphate
and pyridoxal (PNPO downstream products) [65].
Moreover, the pnpo
–/–
zebrafish display reduced levels
of glycine, glutamate, and GABA, and elevated levels
of several essential amino acids (lysine, arginine, tryp-
tophan, methionine, phenylalanine, and threonine),
suggesting impaired activity of the PLP-dependent en-
zymes involved in their metabolism [65]. In contrast,
the PLP treatment normalizes aberrant behavior of
pnpo
–/–
zebrafish, increases fish survival, and restores
the levels of glycine, glutamate, and GABA, although
accumulation of pyridoxamine (PM), PMP and essen-
tial amino acids persisted [65, 106].
The PLP-binding protein (PLPBP) deficiency is an-
other B6-responsive epileptic disorder that has been
successfully modeled in zebrafish. The exact function
of PLPBP and etiology of this recently described disor-
der remain unclear [107]. Similarly to human patients,
plpbp
–/–
zebrafish mutants display reduced systemic
concentrations of PLP, pyridoxal, lysine, threonine,
asparagine, glutamate, glutamine, proline, alanine,
α-aminobutyric acid, GABA, and increased concentra-
tions of methionine, cystathionine, isoleucine, tyro-
sine, β-alanine, phenylalanine, aminoisobutyric acid,
and tryptophan [66]. Overall, zebrafish genetic models
of B6-responsive epilepsies display a wide range of bio-
chemical alterations, most of which can be explained
by impaired activity of the B6-dependent enzymes.
These biochemical markers support the ability of these
models to accurately recapitulate human diseases and
can serve as easily accessible tools for the model val-
idation. Moreover, these findings provide valuable in-
sights into pathophysiology of the B6-responsive epi-
lepsies, corroborating, for example, low GABA levels
as a possible mechanism of epileptogenesis.
Mounting evidence supports the link between hu-
man epilepsy and multiple metabolic defects, including
changes in glucose metabolism, mitochondrial respira-
tion, and glycolysis [108, 109]. Metabolism is also dys-
regulated in the zebrafish models of epilepsy [61-64].
For example, in a zebrafish model of Dravet syndrome
(epilepsy caused by mutations in the sodium NaV
channel), typical behavioral and EEG changes are ac-
companied by the decreased rates of mitochondrial
respiration and glycolysis, measured as oxygen con-
sumption rate and extracellular acidification rate, re-
spectively [63]. Further analyses reveal downregulated
glycolytic enzymes and unaltered activity of the elec-
tron transport chain enzymes, suggesting the causal
role of glycolysis dysregulation in this CNS pathogene-
sis [63]. Reduced glycolysis and mitochondrial respira-
tion have also been reported in the zebrafish epilepsy
model caused by STXBP1 deficiency [62], representing
a simple non-invasive metabolism-based approach
that can be used for real-time monitoring epilepsy and
drug responses in zebrafish.
Such strategies may also be useful for uncovering
novel anti-seizure drugs [110], for instance, identifying
vorinostat (a histone deacetylase inhibitor) as a po-
tential anti-seizure compound based on its ability to
restore metabolic parameters (e.g., basal respiration,
maximal respiration, mitochondrial respiration, proton
leaks, and ATP-linked respiration) in both pharmaco-
logical (pentylenetetrazol-induced) and genetic (kcna1-
morpholino-induced knockdown) zebrafish models of
epilepsy [64]. The efficacy of vorinostat as an antie-
pileptic agent has been further validated in mice us-
ing behavioral and EEG markers [64]. Metabolic-based
small molecule screening has also been successful in
the zebrafish model of the Dravet syndrome discussed
above, since PK11195 (a compound known to enhance
gluconeogenesis) normalizes behavior and restores hy-
pometabolic phenotype of mutant zebrafish, correcting
hypoglycemia and reduced rates of mitochondrial res-
piration and glycolysis [61]. In addition to emphasiz-
ing the value of peripheral metabolic biomarkers for
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BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
specific CNS disorders, these findings support the use
of the energy-producing pathways as novel therapeu-
tic targets for the treatment of brain disorders.
Parkinson’s disease. Mitochondrial dysfunctions
and oxidative stress are strongly implicated in the
Parkinson’s disease pathogenesis [111,  112], a highly
prevalent and severely debilitating progressive neu-
rodegenerative disorder. Some drugs that directly in-
terfere with mitochondrial function can induce Par-
kinsonism in both humans and animals [113-115].
Likewise, zebrafish exposed to mitochondrial dehy-
drogenase inhibitors, such as rotenone, 1-methyl- 4-
phenyl-1,2,3,6-tetrahydropyridine (MPTP), 1-methyl-
4- phenylpyridinium (MPP
+
), 6-hydroxidopamine and
paraquat, develop motor deficits, loss of dopaminergic
neurons, and γ-synuclein aggregation, providing good
pharmacological models of Parkinson’s disease [116].
Altered mitochondrial function and redox status in
these models are reflected in various biochemical bio-
markers that can be reliably measured in whole-body
zebrafish samples.
For example, MPTP induces mitochondrial dys-
function in zebrafish, as reflected by decreased activ-
ity of mitochondrial complexI and downregulation of
mitochondrial proteins parkin, DJ-1, and PINK1 [72].
These proteins are crucial for mitochondrial homeo-
stasis and oxidative stress protection, and their dys-
function is associated with familial cases of Parkin-
son’s disease [117]. Interestingly, melatonin treatment
restores both proteins content and complexI activity,
as well as normalizes larvae behavior, supporting its
therapeutic potential for Parkinson’s disease [72]. The
whole-larvae mitochondrial bioenergetics is also af-
fected in the paraquat- [71] and MPP
+
-induced zebraf-
ish models of Parkinson’s disease [70].
Furthermore, the neurotoxin-exposed zebrafish
present classical biomarkers of oxidative stress, such
as increased lipid peroxidation and decreased gluta-
thione level [73-75], including altered activity of the
enzymes participating in the oxidative stress response,
such as catalase [74, 118], glutathione-S-transferase [73,
74, 118], and superoxide dismutase [73,  74]. Notably,
oxidative stress biomarkers are specifically altered in
the intestines and brains of the rotenone-exposed ze-
brafish [73, 74]. Given some evidence of the causal role
of gastrointestinal dysfunction in Parkinson’s disease
[119, 120], the rotenone-exposed zebrafish may rep-
resent an interesting model to study oxidative stress
related gut-brain interactions relevant to Parkinson
pathogenesis [74].
DISCUSSION
As animal models continue to facilitate studying
mechanisms of complex brain disorders and drug dis-
covery, the zebrafish is rapidly becoming a valuable
model object in the translational neuroscience and
probing a growing number of CNS diseases. These fish
share some practical advantages over mammalian
models together with conserved biochemical and neu-
robehavioral features. Overall, like in humans, CNS
pathogenesis in zebrafish is associated with the dis-
ease-specific biochemical changes, impacting concen-
trations of lipids, carbohydrates, proteins, and other
non-signal molecules, as well as enzymes activities
and rates of metabolic reactions. Importantly, the
signs of biochemical dysregulation can be detected
not only specifically in the brain, but also in peripher-
al tissues and whole bodies of zebrafish. This, togeth-
er with the use of elaborated analytic methods (e.g.,
high performance liquid chromatography-mass spec-
trometry [HPLC-MS]), facilitates biomarker detection
process by making it less time- and labor-consuming.
As discussed above, this strategy has been applied to
a diverse group of zebrafish models of CNS diseases
(e.g., stress-related affective disorders, NPC, epilepsy,
Parkinson’s disease), where the non-brain biochem-
ical biomarkers are used for three major purpos-
es (Table 3).
Firstly, they can be used for the validation of a
particular model, provided that the observed biochem-
ical changes parallel those seen in the clinic. This case
is common in the models of CNS diseases with clearly
established biochemical profile, where, for example,
increased levels of lysine catabolites serve as reliable
biomarkers of pyridoxine-dependent epilepsy in ze-
brafish [67, 68]. Another application is drug screening,
where the reversal of the impaired biochemical pro-
file provides a clear indication of drug effectiveness.
Several studies, as mentioned above, show sensitivity
of zebrafish biochemical biomarkers to pharmacolog-
ical interventions [59, 61, 65, 73, 106], thus promoting
the biomarker-based high-throughput drug screening
in zebrafish. Indeed, at least one compound identified
in zebrafish by its ability to restore metabolic aberra-
tions in epilepsy, vorinostat, now undergoes clinical
trials [64, 121]. Finally, zebrafish may serve as a useful
low-cost platform for the development of biomarkers
that provide new insights into the pathophysiology of
CNS diseases, such as the developed zebrafish 3D maps
of lipid distribution in NPC [60] and profiling amino
acid dysregulation in the models of B6-responsive epi-
lepsies [65, 66,  69].
PROBLEMS, LIMITATIONS,
AND FUTURE RESEARCH
Although focused on peripheral biomarkers, only
few studies have actually investigated the samples of
peripheral tissues without brain tissue, rather than
ILYIN et al.384
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
using whole-body samples. As such, it is not always
clear whether the described biomarkers are actually
of peripheral, central, or rather of “systemic” nature.
A major advantage of the whole-body approach is that
it is fast and does not require tissue dissection, hence,
markedly facilitating rapid biomarkers determination.
This is particularly relevant for the experiments with
small-sized larval and embryonic zebrafish. For exam-
ple, in the zebrafish model of the Dravet syndrome, the
low glucose levels clearly correlate with seizure-like
behavior, thus serving as likely biomarkers of drug re-
sponsiveness as well [61]. At the same time, because
such analyses are performed on the pooled homoge-
nized bodies of zebrafish larvae, it is unclear wheth-
er hypoglycemia is due to the increased brain energy
demands or peripheral glucose depletion. On the one
hand, practically speaking, it is not always necessary to
know the exact origin of the biomarker, if it fulfills its
purpose. On the other hand, further studies may need
to use more specific techniques for tissue collection, re-
vealing the exact origin for each biomarker used.
Studying biomarkers in animal models also has
another benefit – the possibility of finding artifacts
specific to the animal model(s), rather than to the mod-
eled disease itself. In the present context, this can be
attributed to distinct biochemical features of zebrafish
(from those seen in mammals), differences in the ap-
plied experimental manipulations that may only mimic
certain, but not all, etiological factors of ‘real’ human
CNS diseases. For example, in the stress-evoked me-
tabolomic responses, the observed biochemical bio-
markers may reflect zebrafish response to specific
experimental conditions (e.g., stressors) rather than
universal reaction to stress per se [52]. Likewise, vari-
ous oxidative stress biomarkers found in the intestines
of zebrafish exposed to rotenone [73, 74]– a compound
known to induce oxidative stress – can simply con-
firm the peripheral activity of the applied neurotoxin,
rather than inform us on Parkinson’s pathogenesis.
To overcome this problem, one strategy can be to test
such findings using different animal models, also in-
creasing the range of disease-inducing factors (i.e.,
combining pharmacological, genetic, and environmen-
tal manipulations) and employing a wider range of
model organisms, aiming at a greater generality of a
model. Translational relevance of the specific disease
biomarker in question can then be more reliably estab-
lished based on how it integrates into the existing com-
plex pathophysiological picture of the modeled disease.
Finally, the zebrafish as a model organism has
some other, species-specific limitations (Table 1) that
may become critical for CNS disease modeling. Forin-
stance, the zebrafish possesses several neuroanatom-
ical features (e.g., the lack of neocortex) that, albeit
characteristic of all lower vertebrates [16], can hin-
der direct translation of zebrafish disease phenotypes
into humans [122]. Another example is the lack of
midbrain dopaminergic neurons in zebrafish, which
is particularly pertinent when modeling Parkinson’s
disease. In humans, Parkinson’s disease is character-
ized by degeneration of dopaminergic neurons in the
substantia nigra and ventral tegmental area situated
in the midbrain [123, 124]. However, in the zebrafish
models, it is the diencephalic populations that are
primarily affected [113, 125,  126]. While some studies
propose that dopaminergic neurons in the dienceph-
alon of zebrafish may serve as functional analogs of
the human midbrain neuronal populations, this ques-
tion is debated [38, 127,  128]. Thus, while behavioral
and physiological phenotypes observed in zebrafish
models of Parkinson’s disease resemble those in mam-
mals, the degree to which the findings from zebraf-
ish studies can be extrapolated to humans remains
uncertain.
Furthermore, due to additional round of genome
duplication that occurred in the teleost fishes millions
of years ago, zebrafish have more copies of many or-
thologous human genes, including those implicated
into CNS diseases [129, 130]. This, in turn, may com-
plicate such research in zebrafish, including devel-
opment of the genetic knock-out models and inter-
pretation of the results of pharmacological studies.
Furthermore, while zebrafish is perfectly suitable for
administration of water-soluble drugs (through water
immersion), some compounds are water insoluble and
may necessitate the use of organic solvents or injec-
tions, thus increasing the number of factors influenc-
ing the experiment [131]. Lastly, being a relatively new
model object in neuroscience, zebrafish lack some con-
venient features of the traditionally utilized rodents,
such as the availability of multiple fully characterized
inbred strains or behavioral tools [26, 132]. Although
many zebrafish behavioral paradigms have been suc-
cessfully adopted from rodent models [83, 133-135],
some complex behaviors (e.g., fine motor coordina-
tion or parental care) cannot be assessed in zebrafish
experiments despite being highly relevant to many
CNS disorders.
CONCLUSION
Brain disorders often have pathological manifesta-
tions occurring peripherally or at the whole-organism
level, which strongly supports the use of peripheral
biomarkers for diagnostic and therapeutic purposes.
Zebrafish models are becoming an important tool in
the field of translational neuroscience [16, 136], also
providing useful models of human CNS pathologies,
where reliable biochemical changes can be detected ei-
ther in samples of peripheral tissues or whole-bodies.
Zebrafish models often demonstrate similar pattern of
BIOCHEMICAL MARKERS OF BRAIN DISORDERS IN ZEBRAFISH 385
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
biochemical dysregulation to those observed in clin-
ical studies, supporting the developing utility of ze-
brafish to study peripheral biochemical biomarkers of
brain disorders, and their value for the mechanistical-
ly-driven, target-based discovery of novel therapies.
Contributions. A.V.K. conceived and supervised
the study; N.P.I., T.O.K., and S.L.Kh. analyzed the data
and discussed findings with input from all authors;
N.P.I. and K.A.D. wrote the manuscript; E.V.P. and A.V.K.
edited the manuscript.
Funding. The work was financially supported by
the St. Petersburg State University budgetary funds
(Project ID 94030626). A.V.K. and T.O.K. are support-
ed by the Sirius University of Science and Technology
budgetary funds (Project ID NRB-RND-2116).
Ethics declarations. This work does not contain
any studies involving human and animal subjects.
The authors of this work declare that they have no
conflicts of interest.
REFERENCES
1. Feigin, V. L., Nichols, E., Alam, T., Bannick, M. S.,
Beghi,E., Blake,N., and Ellenbogen, R.G. (2019) Glob-
al, regional, and national burden of neurological dis-
orders, 1990-2016: a systematic analysis for the Glob-
al Burden of Disease Study 2016, Lancet Neurol., 18,
459-480, doi:10.1016/S1474-4422(18)30499-X.
2. Vigo,D., Thornicroft,G., and Atun,R. (2016) Estimat-
ing the true global burden of mental illness, Lancet
Psychiatry, 3, 171-178, doi: 10.1016/S2215-0366(15)
00505-2.
3. Hayashi-Takagi, A., Vawter, M. P., and Iwamoto, K.
(2014) Peripheral biomarkers revisited: integrative
profiling of peripheral samples for psychiatric re-
search, Biol. Psychiatry, 75, 920-928, doi: 10.1016/
j.biopsych.2013.09.035.
4. Htike, T. T., Mishra, S., Kumar, S., Padmanabhan, P.,
and Gulyás, B. (2019) Peripheral biomarkers for
early detection of Alzheimers and Parkinson’s dis-
eases, Mol. Neurobiol., 56, 2256-2277, doi: 10.1007/
s12035-018-1151-4.
5. Tomasik,J., Han, S.Y.S., Barton-Owen,G., Mirea, D.M.,
Martin-Key, N. A., Rustogi, N., Lago, S.G., Olmert, T.,
Cooper, J.D., and Ozcan,S. (2021) A machine learning
algorithm to differentiate bipolar disorder from ma-
jor depressive disorder using an online mental health
questionnaire and blood biomarker data, Translat.
Psychiatry, 11, 41, doi:10.1038/s41398-020-01181-x.
6. Chmielewska, N., Szyndler, J., Makowska, K., Woj-
tyna, D., Maciejak,P., and Płaźnik, A. (2018) Looking
for novel, brain-derived, peripheral biomarkers of
neurological disorders, Neurol. Neurochirurg. Polska,
52, 318-325, doi:10.1016/j.pjnns.2018.02.002.
7. Lopresti, A. L., Maker, G. L., Hood, S. D., and Drum-
mond, P.D. (2014) A review of peripheral biomarkers
in major depression: the potential of inflammatory
and oxidative stress biomarkers, Progr. Neuro Psycho-
pharmacol. Biol. Psychiatry, 48, 102-111, doi:10.1016/
j.pnpbp.2013.09.017.
8. Porter, F.D., Scherrer, D.E., Lanier, M.H., Langmade,
S.J., Molugu,V., Gale, S.E., and Fu,R. (2010) Cholester-
ol oxidation products are sensitive and specific blood-
based biomarkers for Niemann-Pick C1 disease, Sci.
Translat. Med., 2, 56ra81, doi: 10.1126/scitranslmed.
3001417.
9. Birmpili,D., Charmarke Askar,I., Bigaut,K., and Bag-
nard,D. (2022) The translatability of multiple sclero-
sis animal models for biomarkers discovery and their
clinical use, Int. J. Mol. Sci., 23, 11532, doi: 10.3390/
ijms231911532.
10. McGonigle, P. (2014) Animal models of CNS disor-
ders, Biochem. Pharmacol., 87, 140-149, doi: 10.1016/
j.bcp.2013.06.016.
11. Murtazina, A. R., Bondarenko, N. S., Pronina, T. S.,
Chandran, K. I., Bogdanov, V. V., Dilmukhametova,
L.K., and Ugrumov, M.V. (2021) A comparative analy-
sis of CSF and the blood levels of monoamines as neu-
rohormones in rats during ontogenesis, Acta Naturae,
13, 89-97, doi:10.32607/actanaturae.11516.
12. Carboni, L. (2013) Peripheral biomarkers in animal
models of major depressive disorder, Dis. Markers, 35,
33-41, doi:10.1155/2013/284543.
13. Ugrumov,M. (2020) Development of early diagnosis of
Parkinson’s disease: illusion or reality?, CNS Neurosci.
Ther., 26, 997-1009, doi:10.1111/cns.13429.
14. Sabbagh, J.J., Kinney, J.W., and Cummings, J.L. (2013)
Animal systems in the development of treatments for
Alzheimers disease: challenges, methods, and impli-
cations, Neurobiol. Aging,
34, 169-183, doi: 10.1016/
j.neurobiolaging.2012.02.027.
15. Ugrumov, M. (2023) Preclinical diagnosis of Par-
kinson’s disease: upgraded and new approaches,
Parkinsonism Rel. Disord., doi: 10.1016/j.parkreldis.
2023.105547.
16. Costa, F. V., Zabegalov, K. N., Kolesnikova, T. O., de
Abreu, M. S., Kotova, M. M., Petersen, E. V., and
Kalueff, A. V. (2023) Experimental models of human
cortical malformations: from mammals to ‘acorti-
cal’ zebrafish, Neurosci. Biobehav. Rev., 155, 105429,
doi:10.1016/j.neubiorev.2023.105429.
17. De Abreu, M. S., Demin, K. A., Kotova, M. M., Mir-
zaei,F., Shariff,S., Kantawala,B., Zakharchenko, K.V.,
Kolesnikova, T. O., Dilbaryan, K., and Grigoryan, A.
(2023) Developing novel experimental models of
m-TORopathic epilepsy and related neuropathologies:
translational insights from zebrafish, Int. J. Mol. Sci.,
24, 1530, doi:10.3390/ijms24021530.
18. Krotova, N. A., Lakstygal, A. M., Taranov, A. S., Ilyin,
N.P., Bytov, M.V., Volgin, A.D., Amstislavskaya, T.G.,
ILYIN et al.386
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
Demin, K.A., and Kaluev, A. V. (2019) Zebrafish as a
new prospective model in translational neurobiology,
Russ. J.Physiol., 105, 1417-1435.
19. Maslov, G.O., Zabegalov, K.N., Demin, K.A., Kolesniko-
va, T.O., Kositsyn, Y.M., de Abreu, M.S., Petersen, E.V.,
and Kalueff, A.V. (2023) Towards experimental mod-
els of delirium utilizing zebrafish, Behav. Brain Res.,
453, 114607, doi:10.1016/j.bbr.2023.114607.
20. Zabegalov, K. N., Costa, F., Viktorova, Y. A., Maslov,
G.O., Kolesnikova, T.O., Gerasimova, E.V., Grinevich,
V.P., Budygin, E.A., and Kalueff, A.V. (2023) Behavioral
profile of adult zebrafish acutely exposed to a selective
dopamine uptake inhibitor, GBR 12909, J.Psychophar-
macol., 37, 601-609, doi:10.1177/02698811231166463.
21. Wendler,A., and Wehling,M. (2010) The translatability
of animal models for clinical development: biomark-
ers and disease models, Curr. Opin. Pharmacol., 10,
601-606, doi:10.1016/j.coph.2010.05.009.
22. Manger, P., Cort, J., Ebrahim, N., Goodman, A., Hen-
ning,J., Karolia,M., and Strkalj,G. (2008) Is 21st centu-
ry neuroscience too focussed on the rat/mouse model
of brain function and dysfunction?, Front. Neuroanat.,
2, 5, doi:10.3389/neuro.05.005.2008.
23. Burne,T., Scott,E., van Swinderen,B., Hilliard,M., Re-
inhard, J., Claudianos, C., and McGrath, J. (2011) Big
ideas for small brains: what can psychiatry learn from
worms, flies, bees and fish?, Mol. Psychiatry, 16, 7-16,
doi:10.1038/mp.2010.35.
24. Kalueff, A., Wheaton, M., and Murphy, D. (2007)
What’s wrong with my mouse model?: Advances and
strategies in animal modeling of anxiety and depres-
sion, Behav. Brain Res., 179, 1-18, doi: 10.1016/j.bbr.
2007.01.023.
25. Kalueff, A. V., Echevarria, D. J., and Stewart, A. M.
(2014) Gaining translational momentum: more zebraf-
ish models for neuroscience research, Prog. Neuropsy-
chopharmacol. Biol. Psychiatry, 55, 1-6, doi: 10.1016/
j.pnpbp.2014.01.022.
26. Stewart, A. M., Braubach, O., Spitsbergen, J., Ger-
lai,R., and Kalueff, A.V. (2014) Zebrafish models for
translational neuroscience research: from tank to
bedside, Trends Neurosci., 37, 264-278, doi: 10.1016/
j.tins.2014.02.011.
27. Gerlai, R. (2020) Evolutionary conservation, transla-
tional relevance and cognitive function: the future
of zebrafish in behavioral neuroscience, Neurosci.
Biobehav. Rev., 116, 426-435, doi: 10.1016/j.neubiorev.
2020.07.009.
28. Fontana, B. D., Mezzomo, N. J., Kalueff, A. V., and
Rosemberg, D.B. (2018) The developing utility of ze-
brafish models of neurological and neuropsychiatric
disorders: a critical review, Exp. Neurol., 299, 157-171,
doi:10.1016/j.expneurol.2017.10.004.
29. Meshalkina, D. A., Kysil, E. V., Warnick, J. E., De-
min, K. A., and Kalueff, A. V. (2017) Adult zebrafish
in CNS disease modeling: a tank that’s half-full, not
half-empty, and still filling, Lab. Animal, 46, 378-387,
doi:10.1038/laban.1345.
30. Kalueff, A.V., Stewart, A.M., and Gerlai,R. (2014) Ze-
brafish as an emerging model for studying complex
brain disorders, Trends Pharmacol. Sci., 35
, 63-75,
doi:10.1016/j.tips.2013.12.002.
31. Woods, I.G., Kelly, P.D., Chu,F., Ngo-Hazelett,P., Yan,
Y.L., Huang,H., and Talbot, W.S. (2000) A comparative
map of the zebrafish genome, Genome Res., 10, 1903-
1914, doi:10.1101/gr.164600.
32. Howe, K., Clark, M. D., Torroja, C. F., Torrance, J.,
Berthelot,C., Muffato,M., and Matthews,L. (2013) The
zebrafish reference genome sequence and its rela-
tionship to the human genome, Nature, 496, 498-503,
doi:10.1038/nature12111.
33. Varshney, G.K., Sood,R., and Burgess, S.M. (2015) Un-
derstanding and editing the zebrafish genome, Adv.
Genet., 92, 1-52, doi:10.1016/bs.adgen.2015.09.002.
34. Lessman, C. A. (2011) The developing zebrafish (Da-
nio rerio): A vertebrate model for high-throughput
screening of chemical libraries, Birth Defects Res.
Part C Embryo Today Rev., 93, 268-280, doi: 10.1002/
bdrc.20212.
35. Postlethwait, J.H. (2007) The zebrafish genome in con-
text: Ohnologs gone missing, J.Exp. Zool. B Mol. Dev.
Evol., 308, 563-577, doi:10.1002/jez.b.21137.
36. Bayés,À., Collins, M.O., Reig-Viader,R., Gou,G., Gould-
ing,D., Izquierdo,A., Choudhary, J.S., Emes, R.D., and
Grant, S.G. (2017) Evolution of complexity in the ze-
brafish synapse proteome, Nat. Commun., 8, 14613,
doi:10.1038/ncomms14613.
37. Butler, A. B. (2000) Topography and topology of the
teleost telencephalon: A paradox resolved, Neurosci.
Lett., 293, 95-98, doi:10.1016/S0304-3940(00)01497-X.
38. Du, Y., Guo,Q., Shan,M., Wu,Y., Huang, S., Zhao, H.,
Hong,H., Yang,M., Yang,X., and Ren,L. (2016) Spatial
and temporal distribution of dopaminergic neurons
during development in zebrafish, Front. Neuroanat.,
10, 115, doi:10.3389/fnana.2016.00115.
39. Glasauer, S.M., and Neuhauss, S. C. (2014) Whole-ge-
nome duplication in teleost fishes and its evolutionary
consequences, Mol. Genet. Genomics, 289, 1045-1060,
doi:10.1007/s00438-014-0889-2.
40. Sison, M., Cawker, J., Buske, C., and Gerlai, R. (2006)
Fishing for genes influencing vertebrate behavior:
Zebrafish making headway, Lab Animal, 35, 33-39,
doi:10.1038/laban0506-33.
41. Zambusi, A., and Ninkovic, J. (2020) Regeneration of
the central nervous system-principles from brain re-
generation in adult zebrafish, World J. Stem Cells, 12,
8, doi:10.4252/wjsc.v12.i1.8.
42. Facciol, A., and Gerlai, R. (2020) Zebrafish shoaling,
its behavioral and neurobiological mechanisms, and
its alteration by embryonic alcohol exposure: a re-
view, Front. Behav. Neurosci., 14, 572175, doi:10.3389/
fnbeh.2020.572175.
BIOCHEMICAL MARKERS OF BRAIN DISORDERS IN ZEBRAFISH 387
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
43. Edson, A. J., Hushagen, H. A., Frøyset, A. K., Elda, I.,
Khan, E.A., Di Stefano,A., and Fladmark, K.E. (2019)
Dysregulation in the brain protein profile of zebrafish
lacking the Parkinson’s disease-related protein DJ-1,
Mol. Neurobiol., 56, 8306-8322, doi: 10.1007/s12035-
019-01667-w.
44. Wang, Y., Liu, W., Yang, J., Wang, F., Sima, Y., Zhong,
Z. M., and Liu, C. F. (2017) Parkinson’s disease-like
motor and non-motor symptoms in rotenone-treated
zebrafish, Neurotoxicology, 58, 103-109, doi: 10.1016/
j.neuro.2016.11.006.
45. Baraban, S. C., Taylor, M., Castro, P., and Baier, H.
(2005) Pentylenetetrazole induced changes in ze-
brafish behavior, neural activity and c-fos expres-
sion, Neuroscience, 131, 759-768, doi: 10.1016/
j.neuroscience.2004.11.031.
46. Wong, K., Stewart, A., Gilder, T., Wu, N., Frank, K.,
Gaikwad,S., and Chang,K. (2010) Modeling seizure-re-
lated behavioral and endocrine phenotypes in adult
zebrafish, Brain Res., 1348, 209-215, doi: 10.1016/
j.brainres.2010.06.012.
47. Gan,D., Wu,S., Chen,B., and Zhang,J. (2020) Applica-
tion of the zebrafish traumatic brain injury model in
assessing cerebral inflammation, Zebrafish, 17, 73-82,
doi:10.1089/zeb.2019.1793.
48. Ilyin, N.P., Galstyan, D.S., Demin, K.A., and Kalueff,
A. V. (2023) Behavioral, genomic and neurochemical
deficits evoked by neurotrauma in adult zebrafish
(Danio rerio), Russ. J.Physiol., 109, 1-19.
49. Leclercq,K., Afrikanova,T., Langlois,M., De Prins,A.,
Buenafe, O. E., Rospo, C. C., and Smolders, I. (2015)
Cross-species pharmacological characterization of the
allylglycine seizure model in mice and larval zebraf-
ish, Epilepsy Behav., 45, 53-63, doi: 10.1016/j.yebeh.
2015.03.019.
50. Piato, Â.L., Capiotti, K.M., Tamborski, A.R., Oses, J.P.,
Barcellos, L.J., Bogo, M.R., and Bonan, C.D. (2011) Un-
predictable chronic stress model in zebrafish (Danio
rerio): behavioral and physiological responses, Progr.
Neuro Psychopharmacol. Biol. Psychiatry, 35, 561-567,
doi:10.1016/j.pnpbp.2010.12.018.
51. Shams,S., Chatterjee,D., and Gerlai,R. (2015) Chronic
social isolation affects thigmotaxis and whole-brain
serotonin levels in adult zebrafish, Behav. Brain Res.,
292, 283-287, doi:10.1016/j.bbr.2015.05.061.
52. Mushtaq, M.Y., Marçal, R.M., Champagne, D.L., Van
Der Kooy,F., Verpoorte,R., and Choi, Y.H. (2014) Effect
of acute stresses on zebra fish (Danio rerio) metabo-
lome measured by NMR-based metabolomics, Planta
Medica, 80, 1227-1233, doi:10.1055/s-0034-1382878.
53. Magdeldin,S., Blaser, R.E., Yamamoto,T., and Yates Iii,
J.R. (2015) Behavioral and proteomic analysis of stress
response in zebrafish (Danio rerio), J. Proteome Res.,
14, 943-952, doi:10.1021/pr500998e.
54. Geary, B., Magee, K., Cash, P., Husi, H., Young, I. S.,
Whitfield, P. D., and Doherty, M. K. (2019) Acute
stress alters the rates of degradation of cardiac mus-
cle proteins,
J.Proteomics, 191, 124-130, doi:10.1016/
j.jprot.2018.03.015.
55. Lin,Y., Cai,X., Wang,G., Ouyang,G., and Cao,H. (2018)
Model construction of Niemann-Pick type C disease
in zebrafish, Biol. Chem., 399, 903-910, doi: 10.1515/
hsz-2018-0118.
56. Louwette,S., Régal,L., Wittevrongel,C., Thys,C., Van-
deweeghde, G., Decuyper, E., and Jaeken, J. (2013)
NPC1 defect results in abnormal platelet formation
and function: studies in Niemann–Pick disease type C1
patients and zebrafish, Human Mol. Genet., 22, 61-73,
doi:10.1093/hmg/dds401.
57. Majewski, L., Adamek-Urbanska, D., Wasilewska, I.,
and Kuznicki, J. (2021) npc2-deficient zebrafish re-
produce neurological and inflammatory symptoms
of Niemann-Pick type C disease, Front. Cell. Neurosci.,
15, 131, doi:10.3389/fncel.2021.647860.
58. Tseng, W. C., Johnson Escauriza, A. J., Tsai-Morris,
C.H., Feldman,B., Dale, R. K., Wassif, C. A., and Por-
ter, F. D. (2021) The role of Niemann–Pick type C2 in
zebrafish embryonic development, Development, 148,
dev194258, doi:10.1242/dev.194258.
59. Tseng, W. C., Loeb, H. E., Pei, W., Tsai-Morris, C. H.,
Xu, L., Cluzeau, C. V., and Pavan, W. J. (2018) Model-
ing Niemann-Pick disease type C1 in zebrafish: a ro-
bust platform for in vivo screening of candidate thera-
peutic compounds, Dis. Model. Mech., 11, dmm034165,
doi:10.1242/dmm.034165.
60. Liang, X., Cao,S., Xie,P., Hu,X., Lin, Y., and Liang, J.
(2021) Three-dimensional imaging of whole-body
zebrafish revealed lipid disorders associated with
Niemann–Pick disease type C1, Anal. Chem., 93, 8178-
8187, doi:10.1021/acs.analchem.1c00196.
61. Banerji,R., Huynh,C., Figueroa,F., Dinday, M.T., Bara-
ban, S.C., and Patel,M. (2021) Enhancing glucose me-
tabolism via gluconeogenesis is therapeutic in a ze-
brafish model of Dravet syndrome, Brain Commun., 3,
fcab004, doi:10.1093/braincomms/fcab004.
62. Grone, B. P., Marchese, M., Hamling, K. R., Kumar,
M. G., Krasniak, C. S., Sicca, F., and Baraban, S. C.
(2016) Epilepsy, behavioral abnormalities, and phys-
iological comorbidities in syntaxin-binding protein1
(STXBP1) mutant zebrafish, PLoS One, 11, e0151148,
doi:10.1371/journal.pone.0151148.
63. Kumar, M.G., Rowley,S., Fulton,R., Dinday, M.T., Bara-
ban, S.C., and Patel,M. (2016) Altered glycolysis and
mitochondrial respiration in a zebrafish model of
Dravet syndrome, ENeuro, 3, ENEURO.0008-16.2016,
doi:10.1523/ENEURO.0008-16.2016.
64. Ibhazehiebo, K., Gavrilovici, C., de la Hoz, C. L., Ma,
S. C., Rehak, R., Kaushik, G., and Kim, D. Y. (2018) A
novel metabolism-based phenotypic drug discovery
platform in zebrafish uncovers HDACs 1 and 3 as a po-
tential combined anti-seizure drug target, Brain, 141,
744-761, doi:10.1093/brain/awx364.
ILYIN et al.388
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
65. Ciapaite,J., Albersen,M., Savelberg, S.M., Bosma,M.,
Tessadori, F., Gerrits, J., and Zwartkruis, F. J. (2020)
Pyridox(am)ine 5′-phosphate oxidase (PNPO) deficien-
cy in zebrafish results in fatal seizures and metabol-
ic aberrations, Biochim. Biophys. Acta, 1866, 165607,
doi:10.1016/j.bbadis.2019.165607.
66. Johnstone, D.L., Al-Shekaili, H.H., Tarailo-Graovac,M.,
Wolf, N.I., Ivy, A.S., Demarest,S., and Kernohan, K.D.
(2019) PLPHP deficiency: clinical, genetic, biochem-
ical, and mechanistic insights, Brain, 142, 542-559,
doi:10.1093/brain/awy346.
67. Pena, I. A., Roussel,Y., Daniel, K., Mongeon,K., John-
stone,D., Weinschutz Mendes,H., and Chakraborty,P.
(2017) Pyridoxine-dependent epilepsy in zebrafish
caused by Aldh7a1 deficiency, Genetics, 207, 1501-
1518, doi:10.1534/genetics.117.300137.
68. Zabinyakov, N., Bullivant, G., Cao, F., Fernandez Oje-
da,M., Jia, Z.P., Wen, X.Y., and Mercimek-Andrews,S.
(2017) Characterization of the first knock-out aldh7a1
zebrafish model for pyridoxine-dependent epilepsy
using CRISPR-Cas9 technology, PLoS One, 12, e0186645,
doi:10.1371/journal.pone.0186645.
69. Minenkova, A., Jansen, E. E., Cameron, J., Barto, R.,
Hurd, T., MacNeil, L., and Mercimek-Andrews, S.
(2021) Is impaired energy production a novel insight
into the pathogenesis of pyridoxine-dependent epilep-
sy due to biallelic variants in ALDH7A1?, PLoS One,
16, e0257073, doi:10.1371/journal.pone.0257073.
70. Pinho, B. R., Reis, S. D., Guedes-Dias, P., Leitão-Ro-
cha, A., Quintas, C., Valentão, P., and Oliveira, J. M.
(2016) Pharmacological modulation of HDAC1 and
HDAC6 in vivo in a zebrafish model: therapeutic im-
plications for Parkinson’s disease, Pharmacol. Res.,
103, 328-339, doi:10.1016/j.phrs.2015.11.024.
71. Wang, X.H., Souders Ii, C.L., Zhao, Y.H., and Martyni-
uk, C.J. (2018) Paraquat affects mitochondrial bioen-
ergetics, dopamine system expression, and locomotor
activity in zebrafish (Danio rerio), Chemosphere, 191,
106-117, doi:10.1016/j.chemosphere.2017.10.032.
72. Díaz-Casado, M.E., Lima,E., García, J.A., Doerrier,C.,
Aranda, P., Sayed, R. K., and Acuña-Castroviejo, D.
(2016) Melatonin rescues zebrafish embryos from
the parkinsonian phenotype restoring the parkin/
PINK 1/DJ-1/MUL 1 network, J.Pineal Res., 61, 96-107,
doi:10.1111/jpi.12332.
73. Cansız,D., Ünal,İ., Üstündağ, Ü.V., Alturfan, A.A., Alti-
noz, M. A., Elmacı, İ., and Emekli-Alturfan, E. (2021)
Caprylic acid ameliorates rotenone induced inflam-
mation and oxidative stress in the gut-brain axis in
Zebrafish, Mol. Biol. Rep., 48, 5259-5273, doi:10.1007/
s11033-021-06532-5.
74. Ünal,İ., Üstündağ, Ü.V., Ateş, P.S., Eğilmezer,G., Altur-
fan, A.A., Yiğitbaşı,T., and Emekli-Alturfan,E. (2019)
Rotenone impairs oxidant/antioxidant balance both
in brain and intestines in zebrafish, Int. J. Neurosci.,
129, 363-368, doi:10.1080/00207454.2018.1538141.
75. Nellore, J., and Nandita, P. (2015) Paraquat exposure
induces behavioral deficits in larval zebrafish during
the window of dopamine neurogenesis, Toxicol. Rep.,
2, 950-956, doi:10.1016/j.toxrep.2015.06.007.
76. McEwen, B. S. (2004) Protection and damage from
acute and chronic stress: allostasis and allostatic
overload and relevance to the pathophysiology of
psychiatric disorders, Ann. NY Acad. Sci., 1032, 1-7,
doi:10.1196/annals.1314.001.
77. Melchior, M., Caspi, A., Milne, B. J., Danese, A., Poul-
ton, R., and Moffitt, T. E. (2007) Work stress precipi-
tates depression and anxiety in young, working wom-
en and men, Psychol. Med., 37
, 1119, doi: 10.1017/
S0033291707000414.
78. Slavich, G.M., and Irwin, M.R. (2014) From stress to
inflammation and major depressive disorder: a so-
cial signal transduction theory of depression, Psychol.
Bull., 140, 774, doi:10.1037/a0035302.
79. De Abreu, M. S., Koakoski, G., Ferreira, D., Oliveira,
T.A., da Rosa, J.G.S., Gusso,D., and Barcellos, L.J.G.
(2014) Diazepam and fluoxetine decrease the stress re-
sponse in zebrafish, PLoS One, 9, e103232, doi:10.1371/
journal.pone.0103232.
80. Gaikwad, S., Stewart, A., Hart, P., Wong, K., Piet, V.,
Cachat, J., and Kalueff, A. V. (2011) Acute stress dis-
rupts performance of zebrafish in the cued and spa-
tial memory tests: the utility of fish models to study
stress–memory interplay, Behav. Processes, 87, 224-
230, doi:10.1016/j.beproc.2011.04.004.
81. Giacomini, A.C.V., Abreu, M.S., Giacomini, L.V., Sieb-
el, A.M., Zimerman, F.F., Rambo, C.L., and Barcellos,
L.J. (2016) Fluoxetine and diazepam acutely modulate
stress induced-behavior, Behav. Brain Res., 296, 301-
310, doi:10.1016/j.bbr.2015.09.027.
82. Mocelin,R., Herrmann, A.P., Marcon,M., Rambo, C.L.,
Rohden, A., Bevilaqua, F., and Barcellos, L. J. (2015)
N-acetylcysteine prevents stress-induced anxiety be-
havior in zebrafish, Pharmacol. Biochem. Behav., 139,
121-126, doi:10.1016/j.pbb.2015.08.006.
83. Demin, K. A., Lakstygal, A. M., Chernysh, M. V., Kro-
tova, N.A., Taranov, A.S., Ilyin, N.P., and Mor, M.S.
(2020) The zebrafish tail immobilization (ZTI) test
as a new tool to assess stress-related behavior and
a potential screen for drugs affecting despair-like
states, J.Neurosci. Methods, 337, 108637, doi:10.1016/
j.jneumeth.2020.108637.
84. Fulcher,N., Tran,S., Shams,S., Chatterjee,D., and Ger-
lai,R. (2017) Neurochemical and behavioral respons-
es to unpredictable chronic mild stress following de-
velopmental isolation: the zebrafish as a model for
major depression, Zebrafish, 14, 23-34, doi: 10.1089/
zeb.2016.1295.
85. Marcon,M., Herrmann, A.P., Mocelin,R., Rambo, C.L.,
Koakoski,G., Abreu, M.S., and Zanatta,L. (2016) Pre-
vention of unpredictable chronic stress-related phe-
nomena in zebrafish exposed to bromazepam, flu-
BIOCHEMICAL MARKERS OF BRAIN DISORDERS IN ZEBRAFISH 389
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
oxetine and nortriptyline, Psychopharmacology, 233,
3815-3824, doi:10.1007/s00213-016-4408-5.
86. Mocelin, R., Marcon, M., D’ambros, S., Mattos, J., Sa-
chett,A., Siebel, A.M., and Piato,A. (2019) N-Acetylcys-
teine reverses anxiety and oxidative damage induced
by unpredictable chronic stress in zebrafish, Mol. Neu-
robiol., 56, 1188-1195, doi:10.1007/s12035-018-1165-y.
87. Rambo, C. L., Mocelin, R., Marcon, M., Villanova, D.,
Koakoski,G., de Abreu, M.S., and Bonan, C.D. (2017)
Gender differences in aggression and cortisol lev-
els in zebrafish subjected to unpredictable chron-
ic stress, Physiol. Behav., 171, 50-54, doi: 10.1016/
j.physbeh.2016.12.032.
88. Song,C., Liu, B.P., Zhang, Y.P., Peng,Z., Wang,J., Col-
lier, A.D., and Rex, C.S. (2018) Modeling consequences
of prolonged strong unpredictable stress in zebrafish:
Complex effects on behavior and physiology, Progr.
Neuro Psychopharmacol. Biol. Psychiatry, 81, 384-394,
doi:10.1016/j.pnpbp.2017.08.021.
89. Demin, K. A., Lakstygal, A. M., Krotova, N. A.,
Masharsky, A., Tagawa,N., Chernysh, M.V., and Der-
zhavina, K.A. (2020) Understanding complex dynam-
ics of behavioral, neurochemical and transcriptomic
changes induced by prolonged chronic unpredictable
stress in zebrafish, Sci. Rep., 10, 1-20, doi: 10.1038/
s41598-020-75855-3.
90. Canavello, P. R., Cachat, J. M., Beeson, E. C., Laffoon,
A. L., Grimes, C., Haymore, W. A., and Elkhayat, S. I.
(2011) Measuring endocrine (cortisol) responses of
zebrafish to stress, in Zebrafish Neurobehavioral Pro-
tocols, Springer, pp.135-142, doi:10.1007/978-1-60761-
953-6_11.
91. Egan, R.J., Bergner, C.L., Hart, P.C., Cachat, J.M., Ca-
navello, P.R., Elegante, M.F., and Tien, D.H. (2009) Un-
derstanding behavioral and physiological phenotypes
of stress and anxiety in zebrafish, Behav. Brain Res.,
205, 38-44, doi:10.1016/j.bbr.2009.06.022.
92. Ramsay, J.M., Feist, G.W., Varga, Z.M., Westerfield,M.,
Kent, M.L., and Schreck, C.B. (2009) Whole-body corti-
sol response of zebrafish to acute net handling stress,
Aquaculture, 297, 157-162, doi: 10.1016/j.aquaculture.
2009.08.035.
93. Cohen, B.E., Edmondson,D., and Kronish, I.M. (2015)
State of the art review: depression, stress, anxiety, and
cardiovascular disease, Am. J. Hypertens., 28, 1295-
1302, doi:10.1093/ajh/hpv047.
94. Golbidi, S., Frisbee, J. C., and Laher, I. (2015) Chron-
ic stress impacts the cardiovascular system: ani-
mal models and clinical outcomes, Am. J. Physiol.
Heart Circ. Physiol., 308, H1476-H1498, doi: 10.1152/
ajpheart.00859.2014.
95. Geary, B. (2016) Determining the Rates of Protein Syn-
thesis in the Zebrafish Heart in Response to Chronic Un-
predictable Stress, Doctoral Thesis.
96. Cologna, S. M., and Rosenhouse-Dantsker, A. (2019)
Insights into the molecular mechanisms of choles-
terol binding to the NPC1 and NPC2 proteins, Adv.
Exp. Med. Biol., 1135, 139-160, doi:10.1007/978-3-030-
14265-0_8.
97. Vanier, M.T. (2010) Niemann-Pick disease type C, Or-
phanet J. Rare Dis., 5, 1-18, doi:10.1186/1750-1172-5-16.
98. Vanier, M.T., and Millat,G. (2004) Structure and func-
tion of the NPC2 protein,
Biochim. Biophys. Acta, 1685,
14-21, doi:10.1016/j.bbalip.2004.08.007.
99. Patterson, M. C., Hendriksz, C. J., Walterfang, M.,
Sedel, F., Vanier, M. T., Wijburg, F., and NP-C Guide-
lines Working Group (2012) Recommendations for the
diagnosis and management of Niemann–Pick disease
type C: an update, Mol. Genet. Metab., 106, 330-344,
doi:10.1016/j.ymgme.2012.03.012.
100. Patterson, M.C., Mengel,E., Wijburg, F.A., Muller,A.,
Schwierin,B., Drevon,H., and Pineda,M. (2013) Dis-
ease and patient characteristics in NP-C patients:
findings from an international disease registry,
Orphanet J. Rare Dis., 8, 1-10, doi: 10.1186/1750-
1172-8-12.
101. Gawel, K., Langlois, M., Martins, T., van der Ent, W.,
Tiraboschi,E., Jacmin, M., and Esguerra, C. V. (2020)
Seizing the moment: Zebrafish epilepsy models,
Neurosci. Biobehav. Rev., 116, 1-20, doi: 10.1016/
j.neubiorev.2020.06.010.
102. Mills, P. B., Footitt, E. J., Mills, K. A., Tuschl, K.,
Aylett,S., Varadkar,S., and Baxter,P. (2010) Genotyp-
ic and phenotypic spectrum of pyridoxine-dependent
epilepsy (ALDH7A1 deficiency), Brain, 133, 2148-2159,
doi:10.1093/brain/awq143.
103. Pearl, P.L., Hyland,K., Chiles,J., McGavin, C.L., Yu,Y.,
and Taylor, D. (2012) Partial pyridoxine respon-
siveness in PNPO deficiency, JIMD Rep., 9, 139-142,
doi:10.1007/8904_2012_194.
104. Mills, P.B., Struys,E., Jakobs,C., Plecko,B., Baxter,P.,
Baumgartner,M., and Uhlenberg,B. (2006) Mutations
in antiquitin in individuals with pyridoxine-depen-
dent seizures, Nat. Med., 12, 307-309, doi: 10.1038/
nm1366.
105. Khayat, M., Korman, S.H., Frankel,P., Weintraub,Z.,
Hershckowitz,S., Sheffer, V.F., and Falik-Zaccai, T. C.
(2008) PNPO deficiency: an under diagnosed inborn
error of pyridoxine metabolism, Mol. Genet. Metab.,
94, 431-434, doi:10.1016/j.ymgme.2008.04.008.
106. Chen, P. Y., Tu, H. C., Schirch, V., Safo, M. K., and Fu,
T.F. (2019) Pyridoxamine supplementation effectively
reverses the abnormal phenotypes of zebrafish lar-
vae with PNPO deficiency, Front. Pharmacol., 10, 1086,
doi:10.3389/fphar.2019.01086.
107. Tremiño, L., Forcada-Nadal, A., and Rubio, V. (2018)
Insight into vitamin B6-dependent epilepsy due to
PLPBP (previously PROSC) missense mutations, Hum.
Mutat., 39, 1002-1013, doi:10.1002/humu.23540.
108. Patel, M. (2018) A metabolic paradigm for epilepsy,
Epilepsy Curr., 18, 318-322, doi: 10.5698/1535-7597.
18.5.318.
ILYIN et al.390
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
109. Pearson-Smith, J. N., and Patel, M. (2017) Metabol-
ic dysfunction and oxidative stress in epilepsy, Int. J.
Mol. Sci., 18, 2365, doi:10.3390/ijms18112365.
110. Ibhazehiebo,K., Rho, J.M., and Kurrasch, D.M. (2020)
Metabolism-based drug discovery in zebrafish: An
emerging strategy to uncover new anti-seizure ther-
apies, Neuropharmacology, 167, 107988, doi: 10.1016/
j.neuropharm.2020.107988.
111. Dias,V., Junn,E., and Mouradian, M.M. (2013) The role
of oxidative stress in Parkinson’s disease, J. Parkin-
son’s Dis., 3, 461-491, doi:10.3233/JPD-130230.
112. Park, J.S., Davis, R.L., and Sue, C.M. (2018) Mitochon-
drial dysfunction in Parkinson’s disease: new mecha-
nistic insights and therapeutic perspectives, Curr. Neu-
rol. Neurosci. Rep., 18, 1-11, doi: 10.1007/s11910-018-
0829-3.
113. Bretaud, S., Lee, S., and Guo, S. (2004) Sensitivity of
zebrafish to environmental toxins implicated in Par-
kinson’s disease, Neurotoxicol. Teratol., 26, 857-864,
doi:10.1016/j.ntt.2004.06.014.
114. Inden,M., Kitamura,Y., Abe,M., Tamaki,A., Takata,K.,
and Taniguchi,T. (2011) Parkinsonian rotenone mouse
model: reevaluation of long-term administration of
rotenone in C57BL/6 mice, Biol. Pharmaceut. Bull., 34,
92-96, doi:10.1248/bpb.34.92.
115. Langston,J., Forno,L., Tetrud,J., Reeves,A., Kaplan,J.,
and Karluk, D. (1999) Evidence of active nerve cell
degeneration in the substantia nigra of humans
years after 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyri-
dine exposure, Ann. Neurol., 46, 598-605, doi:10.1002/
1531-8249(199910)46:4<598::AID-ANA7>3.0.CO;2-F.
116. Vaz, R. L., Outeiro, T. F., and Ferreira, J. J. (2018) Ze-
brafish as an animal model for drug discovery in
Parkinson’s disease and other movement disorders: a
systematic review, Front. Neurol., 9, 347, doi:10.3389/
fneur.2018.00347.
117. Trempe, J.F., and Fon, E.A. (2013) Structure and func-
tion of Parkin, PINK1, and DJ-1, the three musketeers
of neuroprotection, Front. Neurol., 4, 38, doi:10.3389/
fneur.2013.00038.
118. Melo, K.M., Oliveira,R., Grisolia, C.K., Domingues,I.,
Pieczarka, J.C., de Souza Filho,J., and Nagamachi, C.Y.
(2015) Short-term exposure to low doses of rotenone
induces developmental, biochemical, behavioral, and
histological changes in fish, Environ. Sci. Pollut. Res.,
22, 13926-13938, doi:10.1007/s11356-015-4596-2.
119. Fasano, A., Visanji, N. P., Liu, L. W., Lang, A. E., and
Pfeiffer, R. F. (2015) Gastrointestinal dysfunction
in Parkinson’s disease, Lancet Neurol., 14, 625-639,
doi:10.1016/S1474-4422(15)00007-1.
120. Harsanyiova,J., Buday,T., and Kralova Trancikova,A.
(2020) Parkinson’s disease and the gut: future per-
spectives for early diagnosis, Front. Neurosci., 14, 626,
doi:10.3389/fnins.2020.00626.
121. Kurrasch, D. (2018) A Phase II Pilot Clinical Trial Test-
ing the Safety and Efficacy of Vorinostat in Pediatric
Patients with Medically Intractable Epilepsy,
Alberta
Health Services.
122. Panula, P., Chen, Y. C., Priyadarshini, M., Kudo, H.,
Semenova, S., Sundvik, M., and Sallinen, V. (2010)
The comparative neuroanatomy and neurochemis-
try of zebrafish CNS systems of relevance to human
neuropsychiatric diseases, Neurobiol. Dis., 40, 46-57,
doi:10.1016/j.nbd.2010.05.010.
123. Alberico, S. L., Cassell, M. D., and Narayanan, N. S.
(2015) The vulnerable ventral tegmental area in Par-
kinson’s disease, Basal Ganglia, 5, 51-55, doi:10.1016/
j.baga.2015.06.001.
124. Trist, B. G., Hare, D.J., and Double, K. L. (2019) Oxi-
dative stress in the aging substantia nigra and the
etiology of Parkinson’s disease, Aging Cell, 18, e13031,
doi:10.1111/acel.13031.
125. Bretaud,S., Allen,C., Ingham, P.W., and Bandmann,O.
(2007) P53-dependent neuronal cell death in a DJ-1-de-
ficient zebrafish model of Parkinson’s disease, J.Neu-
rochem., 100, 1626-1635, doi: 10.1111/j.1471-4159.
2006.04291.x.
126. Flinn, L., Mortiboys, H., Volkmann, K., Köster, R. W.,
Ingham, P.W., and Bandmann,O. (2009) Complex I de-
ficiency and dopaminergic neuronal cell loss in par-
kin-deficient zebrafish (Danio rerio), Brain, 132, 1613-
1623, doi:10.1093/brain/awp108.
127. Rink,E., and Wullimann, M. F. (2001) The teleostean
(zebrafish) dopaminergic system ascending to the sub-
pallium (striatum) is located in the basal diencepha-
lon (posterior tuberculum), Brain Res., 889, 316-330,
doi:10.1016/S0006-8993(00)03174-7.
128. Schweitzer, J., Löhr, H., Filippi, A., and Driever, W.
(2012) Dopaminergic and noradrenergic circuit de-
velopment in zebrafish, Dev. Neurobiol., 72, 256-268,
doi:10.1002/dneu.20911.
129. Alsop,D., and Vijayan,M. (2009) The zebrafish stress
axis: molecular fallout from the teleost-specific ge-
nome duplication event, Gen. Compar. Endocrinol.,
161, 62-66, doi:10.1016/j.ygcen.2008.09.011.
130. Taylor, J.S., Van de Peer,Y., Braasch,I., and Meyer,A.
(2001) Comparative genomics provides evidence for
an ancient genome duplication event in fish, Philos.
Trans. R. Soc. London SerB Biol. Sci., 356, 1661-1679,
doi:10.1098/rstb.2001.0975.
131. Audira, G., Siregar, P., Chen, J. R., Lai, Y. H., Huang,
J.C., and Hsiao, C.D. (2020) Systematical exploration
of the common solvent toxicity at whole organism
level by behavioral phenomics in adult zebrafish,
Environ. Pollut., 266, 115239, doi: 10.1016/j.envpol.
2020.115239.
132. Vaz, R., Hofmeister,W., and Lindstrand,A. (2019) Ze-
brafish models of neurodevelopmental disorders: lim-
itations and benefits of current tools and techniques,
Int.J. Mol. Sci., 20, 1296, doi:10.3390/ijms20061296.
133. Blaser, R., and Gerlai, R. (2006) Behavioral pheno-
typing in zebrafish: comparison of three behavioral
BIOCHEMICAL MARKERS OF BRAIN DISORDERS IN ZEBRAFISH 391
BIOCHEMISTRY (Moscow) Vol. 89 No. 2 2024
quantification methods, Behav. Res. Methods, 38, 456-
469, doi:10.3758/BF03192800.
134. Echevarria, D.J., Hammack, C.M., Pratt, D.W., and Hose-
mann, J.D. (2008) A novel behavioral test battery to as-
sess global drug effects using the zebrafish, Int.J. Com-
par. Psychol., 21, 19-34, doi:10.46867/IJCP.2008.21.01.02.
135. Stewart, A.M., Gaikwad,S., Kyzar,E., and Kalueff, A.V.
(2012) Understanding spatio-temporal strategies of
adult zebrafish exploration in the open field test, Brain
Res., 1451, 44-52, doi:10.1016/j.brainres.2012.02.064.
136. Costa, F. V., Kolesnikova, T. O., Galstyan, D. S., Ilyin,
N. P., de Abreu, M. S., Petersen, E. V., Demin, K. A.,
Yenkoyan, K. B., and Kalueff, A. V. (2023) Current
state of modeling human psychiatric disorders us-
ing zebrafish, Int. J. Mol. Sci., 24, 3187, doi: 10.3390/
ijms24043187.
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