Metabolomics in Schizophrenia and Major Depressive Disorder

Abstract

Defining pathophenotype, a systems level consequence of a disease genotype, together with environmental and stochastic influences, is an arduous task in psychiatry. It is also an appealing goal, given growing need for appreciation of brain disorders biological complexity, aspiration for diagnostic tests development and ambition to identify novel drug targets. Here, we focus on the Schizophrenia and Major Depressive Disorder and highlight recent advances in metabolomics research. As a systems biology tool, metabolomics holds a promise to take part in elucidating interactions between genes and environment, in complex behavioral traits and psychopathology risk translational research.

Full text

REVIEW
Metabolomics in Schizophrenia and Major Depressive Disorder
Iva Petrovchich
2, *
, Alexandra Sosinsky
3, *
, Anish Konde
4, *
, Abigail Archibald
5
, David Henderson
6
, Mirjana Maletic-Savatic
7
,
Snezana Milanovic (✉)
1
1
Massachusetts General Hospital, Department of Psychiatry, MGH Clinical Trials Network Institute, MGH Division of Global Psychiatry,
MGH Depression Clinical and Research Program, Boston, MA 02114, USA
2
School of Nursing, University of California San Francisco (UCSF), San Francisco, CA 94143, USA
3
Massachusetts General Hospital, Department of Psychiatry, MGH Center for Women’s Mental Health, Boston, MA 02114, USA
4
Louisiana State University Health Science Center, Department of Internal Medicine, Lafayette, LA 70112, USA
5
Massachusetts General Hospital, Department of Psychiatry, MGH Depression Clinical and Research Program, Boston, MA 02114, USA
6
Boston Medical Center, Department of Psychiatry, Boston, MA 02118, USA
7
Baylor College of Medicine, Neurology Research Institute, Houston, TX77030, USA
© Higher Education Press and Springer-Verlag Berlin Heidelberg 2016
Abstract Defining pathophenotype, a systems level consequence of a disease genotype, together with environmental
and stochastic influences, is an arduous task in psychiatry. It is also an appealing goal, given growing need for
appreciation of brain disorders biological complexity, aspiration for diagnostic tests development and ambition to
identify novel drug targets. Here, we focus on the Schizophrenia and Major Depressive Disorder and highlight recent
advances in metabolomics research. As a systems biology tool, metabolomics holds a promise to take part in elucidating
interactions between genes and environment, in complex behavioral traits and psychopathology risk translational
research.
Keywords Schizophrenia, Major Depressive Disorder, omics, metabolomics, systems biology
Introduction
A major component of psychiatric illness risk is polygenic:
heritability that arises from many genetic loci having a “small
effect.”Polygenicity and rare large-effect genetic loci are at
the core of complex quest to elucidate under print of
psychiatric disorders. Given the limited biological insight
obtained through Genome Wide Association Studies
(GWAS), the focus of genetic research has shifted to
exploring major effect-size contributions (rare copy variants
and whole exome sequencing), improving phenotype defini-
tion, and attempts to connect various genetic risks to brain
mechanisms. In parallel, advances in the bioinformatics,
multivariate statistics, and the high-throughput analytical
approaches utilized for processing of microarray data have
paved the way for further development of the systems biology
“panomic”view of the organism, which will be necessary for
the successful “unlocking”of psychiatric disorders. However,
integration of so called “omics”sciences (genomics, tran-
scriptomics, proteomics, metabolomics) is a formidable task,
as it aims to capture the cross-talk between different levels of
molecular organization, represented by individual ‘omics’
sciences. Nevertheless, the implications of such development
are very significant, not only for the further advances of our
knowledge of molecular mechanisms, but also for psychiatric
practice, which lacks specific diagnostic, prognostic, and
therapeutic biomarkers in a wide range of diseases.
Metabolites are the final product of interactions between
gene expression, protein expression, and the cellular
environment. Metabolome presents a state regulated by
interactions between genes and environment, and possibly
genotype and phenotype. As such, it has the potential to be an
informative target for genetic studies of intermediate
phenotypes in brain disorders and help illustrate their
heterogeneity.
Schizophrenia
Schizophrenia is a severe complex mental disorder character-
ized by psychotic symptoms such as hallucinations, delu-
Received March 16, 2016; accepted April 15, 2016
Correspondence: Snezana Milanovic
E-mail: SMILANOVIC@mgh.harvard.edu
*These authors contributed equally to this work.
Front. Biol. 2016, 11(3): 222–231
DOI 10.1007/s11515-016-1400-8

sions, and deficits in executive function (Whitfield-Gabrieli et
al., 2009; Milanovic et al., 2011). It affects 0.5%–1%of the
world population. Similar to other psychiatric disorders,
diagnosis of schizophrenia is based on patient’s and family’s
reports and thus subjective clinical evaluation. The under-
lying molecular mechanisms of schizophrenia are poorly
understood (Yao et al., 2010; He et al., 2012). Symptomatic
onset is in early adulthood- factors such as environment, drug
abuse, and childhood trauma play important roles, as well as
common genetic variations and rare variants. Estimated
heritability is 0.80. Although initial genetic studies demon-
strated increased risk of de novo mutations, larger sample
sizes failed to replicate these data. So far, identification of the
individual risk genes using Whole Exome Sequencing has
had no significant yield. A variation in the Major Histocom-
patibility Complex locus was shown to have a strong
association with schizophrenia at the population level. A
follow up study (Sekar et al., 2016) identified complement
complex alleles playing the role in synapse elimination during
postnatal development. This finding is consistent with
reported excessive loss of gray matter and synapses in
schizophrenia. In spite of high heritability, clinical hetero-
geneity remains a major limitation in schizophrenia genetic
research. Schizophrenia is not one disease entity, but instead a
cluster of clinical symptoms. Identical genomic causation is
probably shared only by subsets of schizophrenia patients
(Yao et al., 2010; Hosak, 2013). The actual schizophrenia risk
will likely be governed by a combination of alleles of small
effect size, rare alleles, copy number variations, and
epigenetic effects. Complex relationship between genotype
and phenotype leading to different clinical presentations in
patient sub-cohorts has to be tested, from the genetic variation
level to the underlying biologic etiology.
Using downstream products of gene expression, “omics”
methods (transcriptomics, proteomics and metabolomics)
facilitate the search for plausible disease risk pathways
(Allen et al., 2011; Arnold et al., 2015; Botas et al., 2015). A
recent metabolomics study (He et al., 2012) demonstrated
differences in the amino acid and lipid metabolism in
medicated and non-medicated schizophrenia patients when
compared to the control group. Subsequent network analysis
of these potentially relevant metabolites and known schizo-
phrenia risk genes identified glutamine and arginine signaling
pathways as possible risk factors. Another study (Orešičet al.,
2011) raised a possibility that there are at least two different
schizophrenia related risk pathways, glucoregulatory and
proline metabolism.
Amino acids
In addition to glutamine and arginine metabolism, amino
acids altered in plasma or cerebrospinal liquid of schizo-
phrenia patients are also involved in nitrogen compound
biosynthetic processes. Removal of the α-amino group is the
first step in amino acid catabolism, a process essential for the
energy production. Removed nitrogen can be excreted as urea
or incorporated into other compounds during the anabolic
processes. Amonia and asparatate are two sources of urea
nitrogen provided by transamination and oxidative deamina-
tion.
Arginine is the essential element in the urea cycle. It is
produced by various tissues, but hydrolyzed into urea and
ornithine exclusively by the liver. Decreased arginine found
in schizophrenia could indicate an increase in ammonia and/
or nitric oxide (NO) metabolism. Monoamines are one of the
sources of ammonia. In the brain, monoamines serve as
hormones or neurotransmitters. Altered cerebrospinal fluid
monoamine turnover rates and ratios were implicated in
genetics of psychosis and schizophrenia (Andreou et al.,
2014; Luykx et al., 2014). NO is CNS neurotransmitter. It is
also involved in the storage, uptake, and release of other
neurotransmitters and oxidative stress. Arginine is one of
three substrates for NO synthesis. It is plausible that an
increase in arginine consumption may be related to aberrant
nitric oxide metabolism in schizophrenia (Yanik et al., 2003;
Bernstein et al., 2005; He et al., 2012; Weber et al., 2014)
Data on tryptophan (Trp) metabolites in schizophrenia are
inconsistent, possibly due to patient cohort characteristics
(first episode vs chronic illness) or the source of biologic
sample (blood or cerebrospinal fluid). Trp is metabolized to 5-
hydroxytryptamine (5-HT or serotonine) by tryptophan
hydrolase (TH) and aromatic amino acid decarboxylase
(AAD) in the serotonin pathway. 5-HT is further metabolized
to melatonin, which possesses anti-oxidant activity (Reiter et
al., 2008). Changes in Trp could reflect a compensatory
mechanism due to increased oxidative stress in schizophrenia.
Work in the first episode patients (Yao et al., 2010) revealed
increased conversion of serotonin to N-acetylserotonin,
possibly driving a drop in serum tryptophan levels. Reduction
in tryptophan serum availability was also detected in
treatment naïve patients (Manowitz et al., 1973; Xuan et al.,
2011). In contrast, medicated schizophrenia cohorts demon-
strate either increase (Fukushima et al., 2014) or decrease
(Manowitz et al., 1973) in Trp and decrease in 5-
hydroxyindoleacetic acid (5HIAA) level in plasma (Fukush-
ima et al., 2014) or cerebrospinal fluid (Ashcroft et al., 1966).
Earlier investigations suggest that hyperserotonemia may
play an etiological role in some forms of schizophrenia
(Garelis et al., 1975; Jackman et al., 1983; Stahl et al., 1983).
Trp is metabolized to Kyn by tryptophan 2,3-dioxygenase or
indoleamine 2,3-dioxygenase in the Kyn pathway (Olney and
Farber, 1995; Schwarcz et al., 2001; Fukushima et al., 2014).
The kynurenine pathway produces neurotoxic (3-hydroxy-
kynurenine and quinolinic acid) and neuro-inhibitory
(kynurenic acid) compounds. At high concentrations,
kynurenic acid is a competitive antagonist of the glycine
site of N-methyl-D-asparate (NMDA) receptors (Stone, 1993)
and a noncompetitive antagonist of the α-7-nicotinic
acetylcholine receptor at a low concentration (Hilmas et al.,
Iva Petrovchich et al. 223

2001; Alkondon et al., 2004). Thus, increased levels of
kynurenic acid may be associated with a spatial working
memory dysfunction (Alkondon et al., 2004) though NMDA
receptor action. Schwarcz et al. (2001) have shown increased
cortical levels of kynurenic acid in schizophrenia, which may
be related to cognitive impairment. (Yao et al., 2010).
Increases in kynurenic acid levels were also reported in the
post-mortem brain tissue (Schwarcz et al., 2001) or
cerebrospinal fluids (Erhardt et al., 2001) from schizophrenia
patients. However, patient’s serum kynurenic acid levels
remained unaltered, indicating that increased kynurenic acid
levels might occur only locally in the brain (Fukushima et al.,
2014).
Glutamine is a precursor of g-GluCys. Lower concentra-
tion of glutamine was detected in plasma and elevated
glutamate in serum and cortex of patients (He et al., 2012;
Fukushima et al., 2014). Interestingly, amonia obtained by
removal of alpha amino acid amino group is combined with
glutamate to form glutamine, which is transported to the liver
to be catabolized to glutamate and ammonia. Additionally,
glutamine is an important building block for purine and
pirimidine synthesis. The glutamate/glutamine hypothesis of
schizophrenia and associated brain metabolic abnormalities in
patients and their first degree relatives is well documented
(Tandon et al., 2013). A single-nucleotide polymorphism
(SNP) in glutamine-dependent carbamoyl-phosphate
synthase enzyme involved in glutamine hydrolysis is possibly
linked to schizophrenia
,
(Stone et al., 2007; He et al., 2012;
Fukushima et al., 2014). As evidenced by genetic studies, a
broader metabolic abnormality might exist in schizophrenia.
Comorbid type 2 diabetes mellitus, cardiac autonomic
dysregulation, and numerous autoimmune disorders have
the strongest familiar predisposition in schizophrenia (Fer-
entinos and Dikeos, 2012).
Serum glutamate (Glu) is elevated in all psychoses
compared to controls. Glutamate is a precursor of ammonia
and aspartate nitrogen in the urea cycle. Consequently,
glutamate-related metabolic abnormalities may reflect a
common, amino-acid pathway abnormality, across different
psychoses types (Cherlyn et al., 2010). Serum Glu level is
reported to be elevated in treatment resistant schizophrenia, in
concert with other amino acid abnormalities, which further
supports amino-acid pathway aberrance in schizophrenia
(Tortorella et al., 2001).
Upregulation of serum proline was reported in schizo-
phrenia. There is evidence that polymorphisms in the
PRODH gene encoding proline oxidase are associated with
schizophrenia risk (Liu et al., 2002; Kempf et al., 2008) and
that the related hyperprolinemia is negatively associated with
cognitive performance (Orešičet al., 2011).
Low concentrations of histidine in whole blood and high
levels in cerebrospinal fluid were identified in schizophrenic
patients (He et al., 2012). Histidine is the histamine precursor.
Histamine is an ubiquitous neurotransmitter but also a
chemical messenger modulating allergic and inflammatory
reactions (He et al., 2012), postulate that downregulation of
TCF4, a transcription factor crucially involved in fetal brain
development, could probably release its inhibition on
histidine decarboxylase, leading to accelerated histidine
decarboxylation in schizophrenia (Prell et al., 1995; Fernán-
dez-Novoa and Cacabelos, 2001; He et al., 2012).
Ornithine is another amino acid implicated in schizo-
phrenia, due to low plasma levels found in patients. Urea is a
major disposal product derived of amino acids amino groups.
Ornithine is synthetized in the cytoplasm of liver cells and
transported to mitochondria, where it participates in the final
stages of urea formation. Increased plasma ornithine implies
suppression in the ornithine decarboxylation process (Mid-
dleton et al., 2002; He et al., 2012) as a possible aberrant
mechanism in schizophrenia patients. Arginine, glutamine,
histidine, and ornithine metabolic pathways were associated
with schizophrenia genetic susceptibility, based on metabo-
lomic data and schizophrenia risk genes molecular network
analyses (He et al., 2012).
Lipids, fatty acids and amino acids
associated with phospholipid synthesis
Decreased phosphatidylcholines (PC ae C38:6) in the plasma
of schizophrenia patients (He et al., 2012) could imply
aberrations in choline metabolism, immune-related signaling,
or neurotrophin signaling. Choline is a precursor and
metabolite of the neurotransmitter acetylcholine and an
essential component of neuronal membrane phospholipids.
Phosphatidylcholine serves as substrate for phosphatidylser-
ine synthesis, a major phospholipid located in the inner
neuronal membrane. An increase in phospholipase A2
activity in schizophrenia (Gattaz et al., 1987; Gattaz et al.,
1990) could implicate acceleration in the breakdown of
membrane phospholipids in schizophrenia. Alternatively, an
increase in phosphatidylcholine demand would lead to its
depletion. The increase in phosphatidylcholine synthesis is a
common feature of neuronal differentiation, with nerve
growth factor directly modulating this process through
immediate early genes and the ERK 1/2 pathway (Paoletti
et al., 2011). Outlined findings are consistent with demon-
strated cell membrane abnormalities associated with dis-
ordered phospholipids composition and metabolism (He et
al., 2012).
Saturated triglycerides, small-molecular clusters contain-
ing branched chain amino acids, phenylalanine and tyrosine,
and proline, glutamic (Fukushima et al., 2014), lactic and
pyruvic acids were increased in schizophrenia serum samples,
suggesting possible relevance between glucoregulatory path-
ways, proline metabolism, and schizophrenia (He et al.,
2012). A global metabolomic analysis approach coupled with
the network analysis identified the lipid cluster LC9,
containing saturated and longer chain triglycerides, as the
strongest link to schizophrenia (Orešičet al., 2011). In this
study, schizophrenia patients were also insulin resistant with
224 Metabolomics in Schizophrenia and Major Depressive Disorder

elevated fasting serum insulin levels, which calls for a
replication study prodrome or first episode schizophrenia
patients. A separate lipidomic study (Kotronen et al., 2009)
revealed that the lipids found in LC9 are associated with
insulin resistance. Together, these findings imply that
schizophrenia, independent of antipsychotic medication and
metabolic co-morbidity, is characterized by insulin resistance,
enhanced hepatic very low density lipoprotein production,
(Kotronen and Yki-Järvinen, 2008) and thus elevated serum
concentrations of specific triglycerides (Orešičet al., 2011).
Consequently, it is not surprising that fatty acids and ketone
bodies were found to be significantly elevated in both the
serum and urine sample of the patients, as demonstrated by
metabolic profiling (Yang et al., 2013). These metabolic
findings could be interpreted as upregulated fatty acid
catabolism as a result of insufficient brain of glucose supply
(Orešičet al., 2011; He et al., 2012).
Liver mitochondria have a capacity to convert acetyl CoA
derived from fatty acid oxygenation into ketone bodies,
including 3-hydroxybutyrate. Ketone bodies are used by
peripheral tissue as an energy source. Data imply there might
be a subset of schizophrenia patients characterized by
downregulated fatty acid metabolism, including a decrease
in 3-hydroxybutyrate (Yang et al., 2013; Fukushima et al.,
2014). 3-hydroxybutyrate also plays a role as the inhibitor of
class I histone deacetylases (HDACs). Consequently, a
decrease in 3-hydroxybutyrate would downregulate histone
acetylation and change DNA transcription, potentially
leaving the cell more vulnerable to the oxidative stress
(Bitanihirwe and Woo, 2011; Shimazu et al., 2013).
Decreases in linoleic and arachidonic acids (Ramos-Loyo
et al., 2013; Fukushima et al., 2014) were identified in some
schizophrenia patients. Linoleic acid (LA) is a precursor of w
arachidonic acid (AA) and αlinoleic acid, which is
metabolized to w-3 fatty acids, essential in growth and
development. Arachidonic acid belongs to long-chain poly-
unsaturated fatty acids (LCPUFA), with roles in neuronal
development and neurodegeneration. LCPUFA deficiency is
associated with schizophrenia and attention deficit hyper-
activity disorder (ADHD). In biological fluids, LA and AA
are bound to fatty acid binding protein (FABP), which
governs the sequesteration of circulating PUFAs. Increase in
tissue expression of FABP is closely associated with the
etiology of schizophrenia (Maekawa et al., 2011), high-
lighting one of the possible biological mechanisms poten-
tially responsible for decrease in LA and AA found in
schizophrenia.
Glutathione (GSH) can chemically detoxify hydrogen
peroxide (H
2
O
2
). H
2
O
2
is a by-product of anaerobic
metabolism, with the potential to cause serious damage to
DNA, proteins, or unsaturated lipids which can lead to cell
death. Decreases in the GSH level of some schizophrenia
patients (Raffa et al., 2009; Fukushima et al., 2014) indicate
schizophrenia–consistent with the notion of free radical–
mediated neurotoxicity in schizophrenia (Yao et al., 2010). g-
glutamylcysteine (g-GluCys) is a precursor of an endogenous
antioxidant, glutathione (GSH), produced from Glu and Cys
by glutamatecysteine ligase (GCL). Interstingly, GCL activity
is a rate-limiting enzyme for GSH synthesis, and genetic
polymorphisms in GCL significantly modulate schizophrenia
risk (Gysin et al., 2007; Nichenametla et al., 2008; Fukushima
et al., 2014).
Serine is a substrate for phosphatidylserine synthesis,
required for the membrane production. Interestingly, while
low levels of serine are found in the peripheral blood of
schizophrenia subjects (Hashimoto et al., 2003; Fukushima et
al., 2014), the prefrontal cortex is reported to have high level
of phosphatidylserine (Wood and Holderman, 2015). Conse-
quently, a dysfunction of oligodendrocyte glycosynapses in
the schizophrenia brain could be implicated in peripheral D-
serine depletion. D-serine is also a co-agonist of the glycine
site of the NMDA receptor. The glutamate hypothesis of
schizophrenia etiology suggests that endogenous D-serine is a
crucial factor related to the hypofunction of the N-methyl-D-
aspartate (NMDA) receptor (Schell et al., 1997; Hashimoto et
al., 2003). Interestingly, genetic studies identify D-amino acid
oxidase (DAO), a molecule highly expressed in the brain
where it oxidizes d-serine, as a possible schizophrenia risk
(Chumakov et al., 2002; Madeira et al., 2008).
Glucose and lactate
Schizophrenic patients have higher baseline serum levels of
glucose and lactate (Xuan et al., 2011). Linkage studies in
schizophrenia highlight the possible importance of genes
related to glycolysis (Stone et al., 2004). Lactate is a final
product of the anaerobic glycolysis in the cells. It signals
disordered energy homeostasis: lactate correlates with obesity
and type 2 diabetes and modulates diastolic blood pressure.
Importantly, stem cell proliferation is ensured through the
anabolic state of glycolysis. In contrast, differentiation to
adult cells is governed by mitochondrial oxidative metabo-
lism. High levels of lactate decrease neurogenesis in animal
models, likely through excessive inflammatory response
(Inoue et al., 2015). Similarly, schizophrenia metabolic shift
favoring an increase in lactate level could lead to neuronal
loss.
Major Depressive Disorder
Major Depressive Disorder is a common psychiatric illness. It
is estimated that 10%–15%of people will experience Major
Depressive Disorder during their lifetime. Depression is
predicted to become the second most common world health
problem by 2020. It has relatively low heritability (~0.4) and
is clinically heterogeneous. Treatment success is highly
variable; less than 50%of patients respond to any given
Iva Petrovchich et al. 225

antidepressant. Such poor response reflects our lack of
knowledge of depression biomarkers and their poor clinical
characterization. Genetic loci identified by biologic candidate
gene studies were not supported by genome-wide studies
(GWAS). Failure to identify loci associated with depression
from large-scale unbiased GWAS is in part due to a need for a
bigger sample size (75 000–100 000) in order to reach
comparable power to identify risk loci as has been done in
schizophrenia genome-wide studies (Smoller, 2016). Lack of
homogeneity in clinical cohorts is an additional significant
challenge.
Research on gene-environment interactions (GE) is
growing: there is a strong correlation between stressful life
events and depression risk calling for quantification of the
stress diathesis model. The allostatic load (AL) is an
interdisciplinary approach aimed at quantifying chronic stress
in relation to various life pathologies. Allostatic load
encompasses the definition of stress as a multidimensional
model. Integral parts of this model are genetic and epigenetic
factors, early adversities that shape brain development, and
hypothalamo-pituitary-adrenal axis responses. These factors
include moderation or mediation by environmental toxins,
distinctions among socioeconomic status, sex, gonadal
hormones and their effects on the brain, and endocrine,
metabolic and immune systems. Consistent with AL hypoth-
esis, data indicate that while some Major Depressive Disorder
patients have immune related dysfunctions leading to
depression, others have energy metabolism impairment,
which could be a gate to a disorder (Martins-de-Souza,
2014). Metabolomic analysis findings might improve strati-
fication of heterogeneous Major Depressive Disorder cohorts
and facilitate G E studies. Currently, stratification is based
on so called depressive subtypes (by sex, recurrent depression
or recurrent vs. early-onset).
Fatty acid and lipid metabolism
β-oxidation is the major fatty acids catabolic pathway, taking
place in mitochondia. Carnitine is a molecule essential for the
“carnitine shuffle,”a process during which a long chain fatty
acyl group is transported across the inner mitochondrial
membrane. Recent metabolomics analysis (Liu et al., 2015)
identified decrease in various plasma acyl carnitine molecules
(carnitine C10:1, carnitine C10:2, carnitine C14:2, carnitine
C14:3, carnitine C6:0, carnitine C8:0, carnitine C8:1,
carnitine C10:0, carnitine C12:1, carnitine C3:0) as possible
Major Depressive Disorder biomarker set. Consistent with
this finding, there is evidence that Acetyl-l-carnitine may be
effective in depression, as adjunct treatment in Major
Depressive Disorder or monotherapy in Disthymia (Wang et
al., 2014).
Decreased stearic amide and palmitic amide (Liu et al.,
2015) levels were reported in plasma of some Major
Depressive Disorder patients. Palmitic acid has 16 carbons
(16:0) and stearic 18 (18:0). In animal models, palmitic acid
induces anxiety like behaviors (Moon et al., 2014). Interest-
ingly, running, which has anxiolytic effect in animal models,
decreases palmitic acid concentration in the cortex (Santos-
Soto et al., 2013). Palmitic acid was shown to reduces
neuronal progenitor cells proliferation (Park et al., 2011)
while, stearic acid seems to have neuroprotective effects
(Wang et al., 2006).
A variety of lysophospholipids, monoglycerophospholi-
pids, and phosphatidylethanolamines (Liu et al., 2015) were
reported as increased in plasma of Major Depressive Disorder
patients (16:1 sn-1, LPC 16:1 sn-2, LPE 16:0 sn-1, LPE 16:0
sn-2, LPE 16:1 sn-1, LPE 18:1 sn-2, LPE 22:5 sn-1, LPC 16:0
sn-2d, LPC 18:1 sn-1, LPC 18:1 sn-2, LPC 20:1 sn-2, LPC
22:4 sn-1, LPC 22:4 sn-2, LPC P-16:0, LPE 16:1 sn-2, LPE
20:3 sn-2, LPE 22:5 sn-2, LPE 18:0 sn-1, LPE 18:0 sn-2, LPE
18:2 sn-1, LPE 18:2 sn-2, LPE 20:3 sn-1, PC 32:0, PC 32:1,
PC O 36:2, PE 34:2, PE 36:4, PE O 36:6, PE O 34:3, PE O
36:5, PE O 38:7), accompanied with a concomitant decrease
in the free fatty acids (FFA 16:2d). Lysophospholipids,
monoglycerophospholipids, and phosphatidylethanolamines
participate in fuel and energy storage, cell signaling, and
ensuring membrane integrity and stability. On the cellular
level, the lysophospholipatidic acid receptor modulates
survival and apoptosis and serves as a novel cell survival
and apoptotic factor (Santin et al., 2009). Antidepressant
treatment was shown to increase the release of lysopho-
spholipids in the cortex of mice (Lee et al., 2009).
Decreased plasma levels of lithocholic, deoxycholic,
glycodesoxycholic, glycoursodeoxycholic and taurocheno-
deoxycholic acid (Liu et al., 2015) suggest possible
dysregulation of the bile acid metabolism in Major Depres-
sive Disorder. Glycoursodeoxycholic and taurochenodeoxy-
cholic acid were shown to have neuroprotective roles (Vaz et
al., 2015; Nunes et al., 2012).
Amino acid and glucose metabolites
Serum glutamate (Glu) and asparate levels are elevated in
Major Depressive Disorder compared to controls (Liu et al.,
2015). As outlined in Schizophrenia section, glutamate is a
precursor of ammonia and aspartate nitrogen in the urea
cycle, which occurs exclusively in the liver, and changes in its
concentration imply amino-acid pathway abnormality. Serum
increases in glutamate and aspartate levels could also reflect a
global dysfunction in NMDA receptor function. Ketamine is
an NMDA antagonist, blocking glutamate neuronal actions.
Rapid antidepressant actions of ketamine underscore clinical
applicability of the glutamate Major Depressive Disorder
hypothesis for at least a subpopulation of patients.
Higher levels of alanine, taurine, citrate, formate, glycine,
isobutyrate, and nicotinate were identified in the urine of
226 Metabolomics in Schizophrenia and Major Depressive Disorder

medication naïve, first episode Major Depressive Disorder
patients (Zheng et al., 2013). Alanine is a key gluconeogen-
esis amino acid. High levels of alanine in combination with
low brain glucose might imply inefficient gluconeogenesis
process. Taurine is a major constituent of bile. In addition to
bile acid conjugation, taurine fosters proliferation of human
neural stem/progenitor neural cells during fetal brain devel-
opment (Hernández-Benítez et al., 2013). Citrate could be
viewed as a high energy signal. It enables the transfer of
acetate units from mitochondria to cytosol, initiating de novo
fatty acid synthesis. Increases in citrate, in conjunction with
high levels of alanine and low glucose, highlights possible
gluconeogenesis inefficiency and a shift in the metabolic
balance toward fatty acid synthesis. Deceased levels of
plasma glucose, lactate, and pyruvate (Zheng et al., 2012)
further support putative imbalance between glycolysis and
gluconeogenesis energy cycles in Major Depressive Disorder.
In addition to being building blocks for proteins, amino
acids are precursors of nitrogen-containing molecules with
important biochemical functions: hormones, neurotransmit-
ters, pyrines, and pyrimidines. The serotonergic system is one
of the key neurotransmitter systems implicated in Major
Depressive Disorder pathophysiology. Seratonin production
is highly dependent on plasma tryptophan utilization. A
decrease in tryptophan levels directly affects the brain
serotonergic system, and metabolomics data reaffirm the
tryptophan depletion hypothesis of depression (Moreno et al.,
2010; Martins-de-Souza, 2014; Liu et al., 2015). Tyrosine is a
building block for cateholamines, dopamine, norepinephrine,
and epinephrine. A decrease in tyrosine (Martins-de-Souza,
2014; Liu et al., 2015) could imply increased conversion to
cateholamines or deficit in protein catabolism. Cerebrospinal
fluid shows reductions in metabolites associated with
tryptophan and tyrosine pathways in remitted depression
(Kaddurah-Daouk et al., 2012). Tryptophan, tyrosine and
methionine pathways might reveal differences between
remitted and non-remitted Major Depressive Disorder sub-
jects (Kaddurah-Daouk et al., 2012).
The tricarboxylic acid (TCA) cycle (also known as the
Krebs cycle) presents the final pathway for the oxidative
catabolism of carbohydrates, amino acids, and fatty acids.
Depressed patients’urine (Zheng et al., 2013) was shown to
have a decrease in the molecules feeding into the TCA cycle
(glucose and piruvate) and an increase in TCA cycle
associated metabolites (α-ketoglutarate, succinate, malonate,
methylmalonate, and succinyl-CoA). This finding confirms
the postulated compromise of glucose metabolism and a shift
toward fatty acid and/or amino acid catatabolism with the aim
of meeting cell energetic and anabolic needs.
Decreases (Liu et al., 2015) or increases (Woo et al., 2015)
in methionine were reported in the plasma of Major
Depressive Disorder patients. Methionine derivative is S-
adenosyl methionine (SAM), a molecule fundamental to
DNA methylation (Cantoni et al., 1989; Kaddurah-Daouk et
al., 2012).
Other metabolites and pathways
Serotonin, dopamine, and norepinephrine metabolites (5-
hydroxyindoleacetic acid [5-HIAA], and homovanillic acid
[HVA]) were decreased in CSF of patients with melancholic
depression (Asberg et al., 1984) implying altered serotonine
and dopamine brain function, consistent with monoaminergis
hypothesis of depression.
Decreased N-methylnicotinamide (NMNA) (Zheng et al.,
2013). N-methylnicotinamide is a metabolite of niacin (or
nicotinamide) and a decrease in urine concentration could
imply niacin deficiency. Biologicaly active coenzyme forms
are nicotinamid adenine dinucleotide (NAD
+
) and its
phosphorylated form, NADP
+
. Both molecules serve as
coenzymes in oxidation-reduction reactions, which could be
compromised in depression.
Conclusion
The “Omics”systems biology approach opens a new venue
for the quest to identify diagnostic and treatment outcome
biomarkers in psychiatry. Unbiased genome-wide studies and
pathway analysis hold a promise to identify reproducible
disease-risk gene associations. Complex challenges persist,
such as disease heterogeneity, polygenicity, and low pene-
trance of most genetic variants, to name a few. “Omics”tools
have a potential to facilitate defining intermediate disease
phenotypes (Maletic-Savatic et al., 2008; Vingara et al., 2013;
Peterson et al., 2013). Additionally, “in vivo”or “in vitro”
metabolomics may provide valuable insight about GE
interactions.
Recently, genetics studies discovered a possible role of
mobile DNA transposomes in the brain cellular heterogeneity
(Singer et al., 2010; Evrony et al., 2015). DNA transposomes
are transposable autonomous elements, scattered throughout
the genome and inherited from one generation to the next.
These DNA elements are active and capable of “jumping”
during neuronal differentiation, altering individual cell
transcriptome and metabolome profiles and thereby modulat-
ing functional output through G E interactions. The human
hippocampus has an astonishing 13.7 somatic insertions per
neuron (Upton et al., 2015). Bundo et al. (2014) found that
transposomes may play a role in psychiatric diseases-
increases in the copy numbers were evident in cortical
neurons of schizophrenia patients and had a positive trend in
mood disorders. Moreover, induced pluripitent cell-derived
neurons from patients with schizophrenia with 22q11 deletion
also had an increase in transposome copy numbers. Human
brain somatic transposition was shown to influence the
biosynthesis of more than 250 metabolites (Arbusán, 2012),
including those linked to schizophrenia.
Hippocampal and/or cortical neuronal mosaicism may be
evolutionary imprinted to ensure genomic diversity and
greater adaptability to the environment (Glinsky, 2015). It
Iva Petrovchich et al. 227

could also pose a psychiatric risk and contribute to disease
heterogeneity. It is in this context that “in vivo”(brain) and “in
vitro”(blood) metabolomics profiling in patient populations
could help elucidate G x E interactions and offer an additional
tool set for much needed biomarker discovery.
Acknowledgements
This work was supported by Brain and Behavior Research Foundation
2012 Young Investigator Award (19722) to Dr. S. Milanovic.
Compliance with ethics guidelines
Iva Petrovchich, Alexandra Sosinsky, Anish Konde4, Abigail Archibald,
David Henderson, Mirjana Maletic-Savatic and Snezana Milanovic
declare that they have no conflict of interest. This manuscript is a review
article and does not involve a research protocol requiring approval by the
relevant institutional review board or ethics committee.
References
Abrusán G (2012). Somatic transposition in the brain has the potential to
influence the biosynthesis of metabolites involved in Parkinson’s
disease and schizophrenia. Biol Direct, 7(1): 41
Alkondon M, Pereira E F, Yu P, Arruda E Z, Almeida L E, Guidetti P,
Fawcett W P, Sapko M T, Randall W R, Schwarcz R, Tagle D A,
Albuquerque E X (2004). Targeted deletion of the kynurenine
aminotransferase ii gene reveals a critical role of endogenous
kynurenic acid in the regulation of synaptic transmission via α7
nicotinic receptors in the hippocampus. J Neurosci, 24(19): 4635–
4648
Allen G I, Maletić-SavatićM (2011). Sparse non-negative generalized
PCA with applications to metabolomics. Bioinformatics, 27 (21):
3029–3035
Andreou D, Söderman E, Axelsson T, Sedvall G C, Terenius L, Agartz I,
Jönsson E G (2014). Polymorphisms in genes implicated in
dopamine, serotonin and noradrenalin metabolism suggest associa-
tion with cerebrospinal fluid monoamine metabolite concentrations in
psychosis. Behav Brain Funct, 10(1): 26
Appleton K M, Rogers P J, Ness A R (2008). Is there a role for n-3 long-
chain polyunsaturated fatty acids in the regulation of mood and
behaviour? A review of the evidence to date from epidemiological
studies, clinical studies and intervention trials. Nutr Res Rev, 21(1):
13–41
Arai M, Yuzawa H, Nohara I, Ohnishi T, Obata N, Iwayama Y, Haga S,
Toyota T, Ujike H, Arai M, Ichikawa T, Nishida A, Tanaka Y,
Furukawa A, Aikawa Y, Kuroda O, Niizato K, Izawa R, Nakamura
K, Mori N, Matsuzawa D, Hashimoto K, Iyo M, Sora I, Matsushita
M, Okazaki Y, Yoshikawa T, Miyata T, Itokawa M (2010). Enhanced
carbonyl stress in a subpopulation of schizophrenia. Arch Gen
Psychiatry, 67(6): 589–597
Arnold J M, Choi W T, Sreekumar A, Maletić-SavatićM(2015).
Analytical strategies for studying stem cell metabolism, Front Biol,
10 (2): 141–153
Asberg M, Bertilsson L, Mårtensson B, Scalia-Tomba G P, Thorén P,
Träskman-Bendz L (1984). CSF monoamine metabolites in mel-
ancholia. ActaPsychiatrScand, 69(3): 201–219
Ashcroft G W, Crawford T B, Eccleston D, Sharman D F, MacDougall E
J, Stanton J B, Binns J K (1966). 5-hydroxyindole compounds in the
cerebrospinal fluid of patients with psychiatric or neurological
diseases. Lancet, 2(7472): 1049–1052
Bernstein H G, Bogerts B, Keilhoff G (2005). The many faces of nitric
oxide in schizophrenia. A review. Schizophr Res, 78(1): 69–86
Bitanihirwe B K, Woo T U (2011). Oxidative stress in schizophrenia: an
integrated approach. NeurosciBiobehav Rev, 35(3): 878–893
Botas A, Campbell H M,Han X , Maletic-Savatic M(2015). Metabo-
lomics of neurodegenerative diseases, Int Rev Neurobiol, 122: 53–80
Bowers M BJr (1973). 5-Hydroxyindoleacetic acid (5HIAA) and
homovanillic acid (HVA) following probenecid in acute psychotic
patients treated with phenothiazines. Psychopharmacologia, 28(4):
309–318
Bundo M, Toyoshima M, Okada Y, Akamatsu W, Ueda J, Nemoto-
Miyauchi T, Sunaga F, Toritsuka M, Ikawa D, Kakita A, Kato M,
Kasai K, Kishimoto T, Nawa H, Okano H, Yoshikawa T, Kato T,
Iwamoto K (2014). Increased l1 retrotransposition in the neuronal
genome in schizophrenia. Neuron, 81(2): 306–313
Cantoni G L, Mudd S H, Andreoli V (1989). Affective disorders and S-
adenosylmethionine: a new hypothesis. Trends Neurosci, 12(9):
319–324
Capuron L, Neurauter G, Musselman D L, Lawson D H, Nemeroff C B,
Fuchs D, Miller A H (2003). Interferon-alpha-induced changes in
tryptophan metabolism. relationship to depression and paroxetine
treatment. Biol Psychiatry, 54(9): 906–914
Cherlyn S Y, Woon P S, Liu J J, Ong W Y, Tsai G C, Sim K (2010).
Genetic association studies of glutamate, GABA and related genes in
schizophrenia and bipolar disorder: a decade of advance. Neurosci
Biobehav Rev, 34(6): 958–977
Chumakov I, Blumenfeld M, Guerassimenko O, Cavarec L, Palicio M,
Abderrahim H, Bougueleret L, Barry C, Tanaka H, La Rosa P, Puech
A, Tahri N, Cohen-Akenine A, Delabrosse S, Lissarrague S, Picard F
P, Maurice K, Essioux L, Millasseau P, Grel P, Debailleul V, Simon
A M, Caterina D, Dufaure I, Malekzadeh K, Belova M, Luan J J,
Bouillot M, Sambucy J L, Primas G, Saumier M, Boubkiri N, Martin-
Saumier S, Nasroune M, Peixoto H, Delaye A, Pinchot V, Bastucci
M, Guillou S, Chevillon M, Sainz-Fuertes R, Meguenni S, Aurich-
Costa J, Cherif D, Gimalac A, Van Duijn C, Gauvreau D, Ouellette G,
Fortier I, Raelson J, Sherbatich T, Riazanskaia N, Rogaev E,
Raeymaekers P, Aerssens J, Konings F, Luyten W, Macciardi F,
Sham P C, Straub R E, Weinberger D R, Cohen N, Cohen D (2002).
Genetic and physiological data implicating the new human gene G72
and the gene for D-amino acid oxidase in schizophrenia. Proc Natl
Acad Sci U S A, 99(21): 13675–13680
Craft S, Watson G S (2004). Insulin and neurodegenerative disease:
shared and specificmechanisms. Lancet Neurol, 3(3): 169–178
Domino E F, Krause R R (1974). Free and bound serum tryptophan in
drug-free normal controls and chronic schizophrenic patients. Biol
Psychiatry, 8(3): 265–279
Erhardt S, Blennow K, Nordin C, Skogh E, Lindström L H, Engberg G
(2001). Kynurenic acid levels are elevated in the cerebrospinal fluid
of patients with schizophrenia. Neurosci Lett, 313(1-2): 96–98
Evrony G D, Lee E, Mehta B K, Benjamini Y, Johnson R M, Cai X,
Yang L, Haseley P, Lehmann H S, Park P J, Walsh C A (2015). Cell
lineage analysis in human brain using endogenous retroelements.
228 Metabolomics in Schizophrenia and Major Depressive Disorder

Neuron, 85(1): 49–59
Ferentinos P, Dikeos D (2012). Genetic correlates of medical
comorbidity associated with schizophrenia and treatment with
antipsychotics. Curr Opin Psychiatry, 25(5): 381–390
Fernández-Novoa L, Cacabelos R (2001). Histamine function in brain
disorders. Behav Brain Res, 124(2): 213–233
Fukushima T, Iizuka H, Yokota A, Suzuki T, Ohno C, Kono Y,
Nishikiori M, Seki A, Ichiba H, Watanabe Y, Hongo S, Utsunomiya
M, Nakatani M, Sadamoto K, Yoshio T (2014). Quantitative analyses
of schizophrenia-associated metabolites in serum: serum D-lactate
levels are negatively correlated with gamma-glutamylcysteine in
medicated schizophrenia patients. PLoS One, 9(7): e101652
Garelis E, Gillin J C, Wyatt R J, Neff N (1975). Elevated blood serotonin
concentration in unmedicated chronic schizophrenic patients. Am J
Psychiatry, 132(2): 184–186
Gattaz W F, Brunner J, Schmitt A, Maras A (1994). Accelerated
breakdown of membrane phospholipids in schizophrenia—implica-
tions for the hypofrontality hypothesis. Fortschr Neurol Psychiatr, 62
(12): 489–496
Gattaz W F, Hübner C V, Nevalainen T J, Thuren T, Kinnunen P K
(1990). Increased serum phospholipase A2 activity in schizophrenia:
a replication study. Biol Psychiatry, 28(6): 495–501
Gattaz W F, Köllisch M, Thuren T, Virtanen J A, Kinnunen P K J (1987).
Increased plasma phospholipase-A2 activity in schizophrenic
patients: reduction after neuroleptic therapy. Biol Psychiatry, 22
(4): 421–426
Gillin J C, Kaplan J A, Wyatt R J (1976). Clinical effects of tryptophan in
chronic schizophrenic patients. Biol Psychiatry, 11(5): 635–639
Glinsky G V (2015). Transposable elements and DNA methylation
create in embryonic stem cells human-specific regulatory sequences
associated with distal enhancers and noncoding RNAs. Genome Biol
Evol, 7(6): 1432–1454
Gysin R, Kraftsik R, Sandell J, Bovet P, Chappuis C, Conus P, Deppen
P, Preisig M, Ruiz V, Steullet P, Tosic M, Werge T, Cuénod M, Do K
Q (2007). Impaired glutathione synthesis in schizophrenia: con-
vergent genetic and functional evidence. Proc Natl Acad Sci U S A,
104(42): 16621–16626
Hashimoto K, Fukushima T, Shimizu E, Komatsu N, Watanabe H,
Shinoda N, Nakazato M, Kumakiri C, Okada S, Hasegawa H, Imai K,
Iyo M (2003). Decreased serum levels of D-serine in patients with
schizophrenia: evidence in support of the N-methyl-D-aspartate
receptor hypofunction hypothesis of schizophrenia. Arch Gen
Psychiatry, 60(6): 572–576
Hashimoto K, Shimizu E, Iyo M (2005). Dysfunction of glia-neuron
communication in pathophysiology of schizophrenia. Curr Psychia-
try Rev, 1(2): 151–163
He Y, Yu Z, Giegling I, Xie L, Hartmann A M, Prehn C, Adamski J,
Kahn R, Li Y, Illig T, Wang-Sattler R, Rujescu D (2012).
Schizophrenia shows a unique metabolomics signature in plasma.
Transl Psychiatry, 2(8): e149
Hernández-Benítez R, Vangipuram S D, Ramos-Mandujano G, Lyman
W D, Pasantes-Morales H (2013). Taurine enhances the growth of
neural precursors derived from fetal human brain and promotes
neuronal specification. Dev Neurosci, 35(1): 40–49
Hilmas C, Pereira E F, Alkondon M, Rassoulpour A, Schwarcz R,
Albuquerque E X (2001). The brain metabolite kynurenic acid
inhibits α7 nicotinic receptor activity and increases non-α7 nicotinic
receptor expression: physiopathological implications. J Neurosci, 21
(19): 7463–7473
Hosak L (2013). New findings in the genetics of schizophrenia. World J
Psychiatry, 3(3): 57–61
Inoue K, Okamoto M, Shibato J, Lee M C, Matsui T, Rakwal R, Soya H
(2015). Long-term mild, rather than intense, exercise enhances adult
hippocampal neurogenesis and greatly changes the transcriptomic
profile of the hippocampus. PLoS One, 10(6): e0128720
Iwayama Y, Hattori E, Maekawa M, Yamada K, Toyota T, Ohnishi T,
Iwata Y, Tsuchiya K J, Sugihara G, Kikuchi M, Hashimoto K, Iyo M,
Inada T, Kunugi H, Ozaki N, Iwata N, Nanko S, Iwamoto K, Okazaki
Y, Kato T, Yoshikawa T (2010). Association analyses between brain-
expressed fatty-acid binding protein (FABP) genes and schizophrenia
and bipolar disorder. Am J Med Genet B Neuropsychiatr Genet,
153B(2): 484–493
Jackman H, Luchins D, Meltzer H Y (1983). Platelet serotonin levels in
schizophrenia: relationship to race and psychopathology. Biol
Psychiatry, 18(8): 887–902
Joseph M H, Owen F, Baker H F, Bourne R C (1977). Platelet serotonin
concentration and monoamine oxidase activity in unmedicated
chronic schizophrenic and in schizoaffective patients. Psychol
Med, 7(1): 159–162
Kaddurah-Daouk R, Yuan P, Boyle S H, Matson W, Wang Z, Zeng Z B,
Zhu H, Dougherty G G, Yao J K, Chen G, Guitart X, Carlson P J,
Neumeister A, Zarate C, Krishnan R R, Manji H K, Drevets W
(2012). Cerebrospinal fluid metabolome in mood disorders-remission
state has a unique metabolic profile. Sci Rep, 2(667): 667
Kempf L, Nicodemus K K, Kolachana B, Vakkalanka R, Verchinski B A,
Egan M F, Straub R E, Mattay V A, Callicott J H, Weinberger D R,
Meyer-Lindenberg A (2008). Functional polymorphisms in PRODH
are associated with risk and protection for schizophrenia and fronto-
striatal structure and function. PLoS Genet, 4(11): e1000252
Kolakowska T, Molyneux S G (1987). Platelet serotonin concentration
in schizophrenic patients. Am J Psychiatry, 144(2): 232–234
Kotronen A, Velagapudi V R, Yetukuri L, Westerbacka J, Bergholm R,
Ekroos K, Makkonen J, Taskinen M R, Oresic M, Yki-Järvinen H
(2009). Serum saturated fatty acids containing triacylglycerols are
better markers of insulin resistance than total serum triacylglycerol
concentrations. Diabetologia, 52(4): 684–690
Kotronen A, Yki-Järvinen H (2008). Fatty liver: a novel component of
the metabolic syndrome. Arterioscler Thromb Vasc Biol, 28(1): 27–
38
Lee L H, Shui G, Farooqui A A, Wenk M R, Tan C H, Ong W Y (2009).
Lipidomic analyses of the mouse brain after antidepressant treatment:
evidence for endogenous release of long-chain fatty acids? Int J
Neuropsychopharmacol, 12(7): 953–964
Liu H, Heath S C, Sobin C, Roos J L, Galke B L, Blundell M L, Lenane
M, Robertson B, Wijsman E M, Rapoport J L, Gogos J A,
Karayiorgou M (2002). Genetic variation at the 22q11 PRODH2/
DGCR6 locus presents an unusual pattern and increases suscept-
ibility to schizophrenia. Proc Natl Acad Sci U S A, 99(6): 3717–
3722
Liu X, Zheng P, Zhao X, Zhang Y, Hu C, Li J, Zhao J, Zhou J, Xie P, Xu
G (2015). Discovery and validation of plasma biomarkers for major
depressive disorder classification based on liquid chromatography-
mass spectrometry. J Proteome Res, 14(5): 2322–2330
Luykx J J, Bakker S C, Lentjes E, Neeleman M, Strengman E, Mentink
Iva Petrovchich et al. 229

L, DeYoung J, de Jong S, Sul J H, Eskin E, van Eijk K, van Setten J,
Buizer-Voskamp J E, Cantor R M, Lu A, van Amerongen M, van
Dongen E P, Keijzers P, Kappen T, Borgdorff P, Bruins P, Derks E
M, Kahn R S, Ophoff R A (2014). Genome-wide association study of
monoamine metabolite levels in human cerebrospinal fluid. Mol
Psychiatry, 19(2): 228–234
Madeira C, Freitas M E, Vargas-Lopes C, Wolosker H, Panizzutti R
(2008). Increased brain D-amino acid oxidase (DAAO) activity in
schizophrenia. Schizophr Res, 101(1-3): 76–83
Maekawa M, Owada Y, Yoshikawa T (2011). Role of polyunsaturated
fatty acids and fatty acid binding protein in the pathogenesis of
schizophrenia. Curr Pharm Des, 17(2): 168–175
Maletić-SavatićM, Vingara L K, Manganas L N, Li Y, Zhang S, Sierra
A, Hazel R, Smith D, Wagshul M E, Henn F, Krupp L, Enikolopov
G, Benveniste H, DjurićP M, Pelczer I (2008). Metabolomics of
neural progenitor cells: a novel approach to biomarker discovery.
Cold Spring Harb Symp Quant Biol, 73:389–401
Manowitz P, Gilmour D G, Racevskis J (1973). Low plasma tryptophan
levels in recently hospitalized schizophrenics. Biol Psychiatry, 6(2):
109–118
Martins-de-Souza D (2014). Proteomics, metabolomics, and protein
interactomics in the characterization of the molecular features of
major depressive disorder. Dialogues Clin Neurosci, 16(1): 63–73
Middleton F A, Mirnics K, Pierri J N, Lewis D A, Levitt P (2002). Gene
expression profiling reveals alterations of specific metabolic path-
ways in schizophrenia. J Neurosci, 22(7): 2718–2729
Milanovic S M, Thermenos H W, Goldstein J M, Brown A, Gabrieli S
W, Makris N, Tsuang M T, Buka S L, Seidman L J(2011). Medial
prefrontal cortical activation during working memory differentiates
schizophrenia and bipolar psychotic patients: a pilot fMRI study.
Schizophr Res, 129(2-3): 208–210
Moon M L, Joesting J J, Lawson M A, Chiu G S, Blevins N A, Kwakwa
K A, Freund G G (2014). The saturated fatty acid, palmitic acid,
induces anxiety-like behavior in mice. Metabolism, 63(9): 1131–
1140
Moreno F A, Parkinson D, Palmer C, Castro W L, Misiaszek J, El
Khoury A, Mathé A A, Wright R, Delgado P L (2010). CSF
neurochemicals during tryptophan depletion in individuals with
remitted depression and healthy controls. Eur Neuropsychopharma-
col, 20(1): 18–24
Mück-Seler D, JakovljevićM, DeanovićZ (1988). Time course of
schizophrenia and platelet 5-HT level. Biol Psychiatry, 23(3): 243–
251
Nichenametla S N, Ellison I, Calcagnotto A, Lazarus P, Muscat J E,
Richie J P Jr (2008). Functional significance of the GAG
trinucleotide-repeat polymorphism in the gene for the catalytic
subunit of gamma-glutamylcysteine ligase. Free Radic Biol Med, 45
(5): 645–650
Nunes A F, Amaral J D, Lo A C, Fonseca M B, Viana R J, Callaerts-
Vegh Z, D’Hooge R, Rodrigues C M (2012). TUDCA, a bile acid,
attenuates amyloid precursor protein processing and amyloid-β
deposition in APP/PS1 mice. Mol Neurobiol, 45(3): 440–454
Olney J W, Farber N B (1995). Glutamate receptor dysfunction and
schizophrenia. Arch Gen Psychiatry, 52(12): 998–1007
OrešičM, Tang J, Seppänen-Laakso T, Mattila I, Saarni S E, Saarni S I,
Lönnqvist J, Sysi-Aho M, Hyötyläinen T, Perälä J, Suvisaari J
(2011). Metabolome in schizophrenia and other psychotic disorders:
a general population-based study. Genome Med, 3(3): 19
Paoletti L, Elena C, Domizi P, Banchio C (2011). Role of
phosphatidylcholine during neuronal differentiation. IUBMB Life,
63(9): 714–720
Park H R, Kim J Y, Park K Y, Lee J (2011). Lipotoxicity of palmitic
Acid on neural progenitor cells and hippocampal neurogenesis.
Toxicol Res, 27(2): 103–110
Payne I R, Walsh E M, Whittenburg E J (1974). Relationship of dietary
tryptophan and niacin to tryptophan metabolism in schizophrenics
and nonschizophrenics. Am J Clin Nutr, 27(6): 565–571
Peterson C, Vannucci M, KarakasC, Choi W, Ma L, Maletic-Savatic M
(2013). Inferring metabolic networks using the Bayesian adaptive
graphical lasso with informative priors. Stat Interface, 6(4): 547–558
Prell G D, Green J P, Kaufmann C A, Khandelwal J K, Morrishow A M,
Kirch D G, Linnoila M, Wyatt R J (1995). Histamine metabolites in
cerebrospinal fluid of patients with chronic schizophrenia: their
relationships to levels of other aminergic transmitters and ratings of
symptoms. Schizophr Res, 14(2): 93–104
Raffa M, Mechri A, Othman L B, Fendri C, Gaha L, Kerkeni A (2009).
Decreased glutathione levels and antioxidant enzyme activities in
untreated and treated schizophrenic patients. Prog Neuropsycho-
pharmacol Biol Psychiatry, 33(7): 1178–1183
Ramos-Loyo J, Medina-Hernández V, Estarrón-Espinosa M, Canales-
Aguirre A, Gómez-Pinedo U, Cerdán-Sánchez L F (2013). Sex
differences in lipid peroxidation and fatty acid levels in recent onset
schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry, 44:
154–161
Reiter R J, Tan D X, Jou M J, Korkmaz A, Manchester L C, Paredes S D
(2008). Biogenic amines in the reduction of oxidative stress:
melatonin and its metabolites. Neuro Endocrinol Lett, 29(4): 391–
398
Santin L J, Bilbao A, Pedraza C, Matas-Rico E, López-Barroso D,
Castilla-Ortega E, Sánchez-López J, Riquelme R, Varela-Nieto I, de
la Villa P, Suardíaz M, Chun J, De Fonseca F R, Estivill-Torrús G
(2009). Behavioral phenotype of maLPA1-null mice: increased
anxiety-like behavior and spatial memory deficits. Genes Brain
Behav, 8(8): 772–784
Santos-Soto I J, Chorna N, Carballeira N M, Vélez-Bartolomei J G,
Méndez-Merced A T, Chornyy A P, Peña de Ortiz S (2013).
Voluntary running in young adult mice reduces anxiety-like behavior
and increases the accumulation of bioactive lipids in the cerebral
cortex. PLoS One, 8(12): e81459
Schell M J, Brady R O Jr, Molliver M E, Snyder S H (1997). D-serine as
a neuromodulator: regional and developmental localizations in rat
brain glia resemble NMDA receptors. J Neurosci, 17(5): 1604–1615
Schwarcz R, Rassoulpour A, Wu H Q, Medoff D, Tamminga C A,
Roberts R C (2001). Increased cortical kynurenate content in
schizophrenia. Biol Psychiatry, 50(7): 521–530
Sekar A, Bialas A R, de Rivera H, Davis A, Hammond T R, Kamitaki N,
Tooley K, Presumey J, Baum M, Van Doren V, Genovese G, Rose S
A, Handsaker R E, Daly M J, Carroll M C, Stevens B, McCarroll S A,
and the Schizophrenia Working Group of the Psychiatric Genomics
Consortium (2016). Schizophrenia risk from complex variation of
complement component 4. Nature, 530(7589): 177–183
Shimazu T, Hirschey M D, Newman J, He W, Shirakawa K, Le Moan N,
Grueter C A, Lim H, Saunders L R, Stevens R D, Newgard C B,
Farese R VJr, de Cabo R, Ulrich S, Akassoglou K, Verdin E (2013).
230 Metabolomics in Schizophrenia and Major Depressive Disorder

Suppression of oxidative stress by β-hydroxybutyrate, an endogen-
ous histone deacetylase inhibitor. Science, 339(6116): 211–214
Singer T, McConnell M J, Marchetto M C, Coufal N G, Gage F H
(2010). LINE-1 retrotransposons: mediators of somatic variation in
neuronal genomes? Trends Neurosci, 33(8): 345–354
Smith Q R (2000). Transport of glutamate and other amino acids at the
blood-brain barrier. J Nutr, 130(4SSuppl): 1016S–1022S
Smoller J W (2016). The genetics of stress-related disorders: PTSD,
depression, and anxiety disorders. Neuropsychopharmacology, 41
(1): 297–319
Stahl S M, Woo D J, Mefford I N, Berger P A, Ciaranello R D (1983).
Hyperserotonemia and platelet serotonin uptake and release in
schizophrenia and affective disorders. Am J Psychiatry, 140(1): 26–
30
Steffens D C, Jiang W, Krishnan K R, Karoly E D, Mitchell M W,
O’Connor C M, Kaddurah-Daouk R (2010). Metabolomic differ-
ences in heart failure patients with and without major depression. J
Geriatr Psychiatry Neurol, 23(2): 138–146
Stone J M, Morrison P D, Pilowsky L S (2007). Glutamate and dopamine
dysregulation in schizophrenia—a synthesis and selective review. J
Psychopharmacol, 21(4): 440–452
Stone T W (1993). Neuropharmacology of quinolinic and kynurenic
acids. Pharmacol Rev, 45(3): 309–379
Stone W S, Faraone S V, Su J, Tarbox S I, Van Eerdewegh P, Tsuang M
T (2004). Evidence for linkage between regulatory enzymes in
glycolysis and schizophrenia in a multiplex sample. Am J Med Genet
B Neuropsychiatr Genet, 127B(1): 5–10
Tandon N, Bolo N R, Sanghavi K, Mathew I T, Francis A N, Stanley J A,
Keshavan M S (2013). Brain metabolite alterations in young adults at
familial high risk for schizophrenia using proton magnetic resonance
spectroscopy. Schizophr Res, 148(1-3): 59–66
Tortorella A, Monteleone P, Fabrazzo M, Viggiano A, De Luca L, Maj
M (2001). Plasma concentrations of amino acids in chronic
schizophrenics treated with clozapine. Neuropsychobiology, 44(4):
167–171
UptonK r,GerhardtD J, Jesuadian J S, Richardson S R, Sánchez-Luque F
J, Bodea G O, Ewing A D, Salvador-PalomequeC,van der Knaap M
S, Brennan P M, Vanderver A, Faulkner G J(2015). Ubiquitous L1
mosaicism in hippocampal neurons. Cell, 161(2): 228–239
Vaz A R, Cunha C, Gomes C, Schmucki N, Barbosa M, Brites D (2015).
Glycoursodeoxycholic acid reduces matrix metalloproteinase-9 and
caspase-9 activation in a cellular model of superoxide dismutase-1
neurodegeneration. Mol Neurobiol, 51(3): 864–877
Vingara L K, Yu H J,Wagshul M E , Serafin D,Christodoulou C , Pelczer
I, Krupp L B, Maletić-SavatićM(2013). Metabolomic approach to
human brain spectroscopy identifies associations between clinical
features and the frontal lobe metabolome in multiple sclerosis.
Neuroimage, 82: 586–594
Wang S M, Han C, Lee S J, Patkar A A, Masand P S, Pae C U (2014). A
review of current evidence for acetyl-l-carnitine in the treatment of
depression. J Psychiatr Res, 53: 30–37
Wang Z J, Li G M, Tang W L, Yin M (2006). Neuroprotective effects of
stearic acid against toxicity of oxygen/glucose deprivation or
glutamate on rat cortical or hippocampal slices. Acta Pharmacol
Sin, 27(2): 145–150
Weber H, Klamer D, Freudenberg F, Kittel-Schneider S, Rivero O,
Scholz C J, Volkert J, Kopf J, Heupel J, Herterich S, Adolfsson R,
Alttoa A, Post A, Grußendorf H, Kramer A, Gessner A, Schmidt B,
Hempel S, Jacob C P, Sanjuán J, Moltó M D, Lesch K P, Freitag C M,
Kent L, Reif A (2014). The genetic contribution of the NO system at
the glutamatergic post-synapse to schizophrenia: further evidence
and meta-analysis. Eur Neuropsychopharmacol, 24(1): 65–85
Whitfield-Gabrieli S, Thermenos H W, Milanovic S, Tsuang M T,
Faraone S V, McCarley R W, Shenton M E, Green A I, Nieto-
Castanon A, LaViolette P, Wojcik J, Gabrieli J D, Seidman L J
(2009). Hyperactivity and hyperconnectivity of the default network
in schizophrenia and in first-degree relatives of persons with
schizophrenia. Proc Natl Acad Sci U S A. 106(4): 1279–1284
Wichers M C, Koek G H, Robaeys G, Verkerk R, Scharpé S, Maes M
(2005). IDO and interferon-alpha-induced depressive symptoms: a
shift in hypothesis from tryptophan depletion to neurotoxicity. Mol
Psychiatry, 10(6): 538–544
Woo H I, Chun M R, Yang J S, Lim S W, Kim M J, Kim S W, Myung W
J, Kim D K, Lee S Y (2015). Plasma amino acid profiling in major
depressive disorder treated with selective serotonin reuptake
inhibitors. CNS Neurosci Ther, 21(5): 417–424
Wood P L (2014). Accumulation of N-acylphosphatidylserines and N-
acylserines in the frontal cortex in schizophrenia. Neurotransmitter
(Houst), 1(1): e263
Wood P L, Holderman N R (2015). Dysfunctional glycosynapses in
schizophrenia: disease and regional specificity. Schizophr Res, 166
(1-3): 235–237
Wyatt R J, Vaughan T, Galanter M, Kaplan J, Green R (1972).
Behavioral changes of chronic schizophrenic patients given L-5-
hydroxytryptophan. Science, 177(4054): 1124–1126
Xuan J, Pan G, Qiu Y, Yang L, Su M, Liu Y, Chen J, Feng G, Fang Y, Jia
W, Xing Q, He L (2011). Metabolomic profiling to identify potential
serum biomarkers for schizophrenia and risperidone action. J
Proteome Res, 10(12): 5433–5443
Yang J, Chen T, Sun L, Zhao Z, Qi X, Zhou K, Cao Y, Wang X, Qiu Y,
Su M, Zhao A, Wang P, Yang P, Wu J, Feng G, He L, Jia W, Wan C
(2013). Potential metabolite markers of schizophrenia. Mol
Psychiatry, 18(1): 67–78
Yanik M, Vural H, Kocyigit A, Tutkun H, Zoroglu S S, Herken H, Savaş
H A, Köylü A, Akyol O (2003). Is the arginine-nitric oxide pathway
involved in the pathogenesis of schizophrenia? Neuropsychobiology,
47(2): 61–65
Yao J K, Dougherty G GJr, Reddy R D, Keshavan M S, Montrose D M,
Matson W R, Rozen S, Krishnan R R, McEvoy J, Kaddurah-Daouk R
(2010). Altered interactions of tryptophan metabolites in first-episode
neuroleptic-naive patients with schizophrenia. Mol Psychiatry, 15
(9): 938–953
Yao J K, Reddy R (2011). Oxidative stress in schizophrenia:
pathogenetic and therapeutic implications. Antioxid Redox Signal,
15(7): 1999–2002
Zheng P, Gao H C, Li Q, Shao W H, Zhang M L, Cheng K, Yang Y, Fan
S H, Chen L, Fang L, Xie P (2012). Plasma metabonomics as a novel
diagnostic approach for major depressive disorder. J Proteome Res,
11(3): 1741–1748
Zheng P, Wang Y, Chen L, Yang D, Meng H, Zhou D, Zhong J, Lei Y,
Melgiri N D, Xie P (2013). Identification and validation of urinary
metabolite biomarkers for major depressive disorder. Mol Cell
Proteomics, 12(1): 207–214
Iva Petrovchich et al. 231