C LI NI CA L
RE SE AR CH
A RT IC LE
Raquel G. Martins,1,2,3* Luı́s G. Gonçalves,4* Nuno Cunha,5
and Maria Jo~
ao Bugalho6,7
1
Endocrinology Department, Portuguese Oncology Institute of Coimbra, 3000-075 Coimbra, Portugal;
Medical Psychology Unit, Department of Clinical Neurosciences and Mental Health, Faculty of Medicine,
University of Oporto, 4200-072 Porto, Portugal; 3Research Centre, Portuguese Oncology Institute of Oporto,
4200-072 Porto, Portugal; 4ITQB NOVA, Instituto de Tecnologia Quı́mica e Biológica António Xavier,
Universidade Nova de Lisboa, 2780-157 Oeiras, Portugal; 5Clinical Laboratory Department, Portuguese
Oncology Institute of Coimbra, 3000-075 Coimbra, Portugal; 6Endocrinology, Diabetes and Metabolism
Department, CHULN-Hospital Santa Maria, 1649-035 Lisbon, Portugal; and 7Faculty of Medicine, University
of Lisbon, 1649-004 Lisbon, Portugal
2
ORCiD numbers: 0000-0003-2786-3650 (R. G. Martins).
Context: Metabolomic studies of pheochromocytoma and paraganglioma tissue showed a correlation between metabolomic profile and presence of SDHx mutations, especially a pronounced
increase of succinate.
Objective: To compare the metabolomic profile of 24-hour urine samples of SDHx mutation carriers
with tumors (affected mutation carriers), without tumors (asymptomatic mutation carriers), and
patients with sporadic pheochromocytomas and paragangliomas.
Methods: Proton nuclear magnetic resonance spectroscopic profiling of urine samples and
metabolomic analysis using pairwise comparisons were complemented by metabolite set enrichment analysis to identify meaningful patterns.
Results: The urine of the affected SDHx carriers showed substantially lower levels of seven metabolites than the urine of asymptomatic mutation carriers (including, succinate and N-acetylaspartate). The urine of patients with SDHx-associated tumors presented substantially higher levels of
three metabolites compared with the urine of patients without mutation; the metabolite set
enrichment analysis identified gluconeogenesis, pyruvate, and aspartate metabolism as the
pathways that most probably explained the differences found. N-acetylaspartate was the only
metabolite the urinary levels of which were significantly different between the three groups.
Conclusions: The metabolomic urine profile of the SDHx mutation carriers with tumors is different
from that of asymptomatic carriers and from that of patients with sporadic neoplasms. Differences
are likely to reflect the altered mitochondria energy production and pseudohypoxia signature of
these tumors. The urinary levels of N-acetylaspartate and succinate contrast with those reported in
tumor tissue, suggesting a defective washout process of oncometabolites in association with tumorigenesis. The role of N-acetylaspartate as a tumor marker for these tumors merits further
investigation. (J Clin Endocrinol Metab 104: 5467–5477, 2019)
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in USA
Copyright © 2019 Endocrine Society
Received 11 May 2019. Accepted 17 July 2019.
First Published Online 23 July 2019
doi: 10.1210/jc.2019-01101
*R.G.M. and L.G.G. are co-first authors.
Abbreviations: CoA, coenzyme A; GIST, gastrointestinal stromal tumors; 1H, proton;
MSEA, metabolite set enrichment analysis; NMR, nuclear magnetic resonance; PPGL,
pheochromocytomas and paragangliomas.
J Clin Endocrinol Metab, November 2019, 104(11):5467–5477
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Metabolomic Urine Profile: Searching for New
Biomarkers of SDHx-Associated Pheochromocytomas
and Paragangliomas
5468
Martins et al
SDHx-Associated Tumors: Urine Metabolomics
T
substrate and the metabolite of succinate dehydrogenase. In
vivo metabolomic analysis of SDHx-related tumors using
proton (1H) magnetic resonance spectroscopy was also able
to identify a succinate peak in the majority of SDHx mutation carriers (17, 18). Metabolomic analysis of random
blood and/or urine samples showed elevated plasma succinate in one SDHB mutation carrier and in two of five
SDHD mutation carriers. Increased urine succinate was
observed in fewer participants, but it is not clear whether
these individuals were SDHx mutation carriers (19). A role
for succinate as serum biomarker in SDHx-mutated PPGL
individuals was observed in another study (20).
The metabolomic profile of urine samples from patients
with PPGL was not performed. However, it has shown
clinical utility in the identification of new biomarkers in
other pathologies (21, 22). The study of biofluids using high
resolution 1H nuclear magnetic resonance (NMR) spectroscopic profiling provides a global quantitative description
of a wide number of endogenous metabolites (23). Because it
enables a global evaluation of the intermediaries of several
metabolic pathways, it might allow the highlight of those
altered in a given pathological condition. Describing the
metabolomic profile of SDHx patients’ biofluids might be
helpful in the identification of targets for the future development of new biomarkers for PPGL. To this end, this study
aims to evaluate the metabolomic profile of patients with
PPGL and SDHx mutations in 24-hour urine samples, in
comparison with unaffected SDHx mutation carriers and
with patients with sporadic PPGL.
Materials and Methods
Study population
The study was conducted in the three Portuguese oncology
institutes (Coimbra, Lisbon, and Oporto) that follow patients
with neoplasias nationwide. The sample included 76 patients:
68 SDHx mutation carriers (55 SDHB, 12 SDHD, and 1
SDHC) and 8 individuals SDHx wild-type. Only carriers of
known pathogenic mutations (identified through Sanger sequencing or next generation sequencing, and multiplex ligationdependent probe amplification for deletion detection) were
included. Coexistence of polymorphisms cannot be excluded.
Individuals with SDHx variants of unknown significance were
not eligible. Patients with questionable imaging examinations
were also excluded from the analysis. Among the SDHx mutation carriers, 26 presented associated tumors (25 PPGL and 1
GIST) at the time of the 24-hour urine collection, 9 of whom
had metastatic disease. The remaining SDHx mutation carriers
were unaffected or were previously treated for PPGL or GIST
but remained without evidence of disease at the time of urine
collection; they were classified as asymptomatic mutation
carriers. Among the individuals without mutation, all presented
PPGL at the time of urine collection (Table 1). Participation was
voluntary and data anonymity was ensured. The study received
approval from the ethics committees of all three hospitals. All
patients gave written informed consent.
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he pheochromocytomas and paragangliomas (PPGL)
are neuroendocrine tumors with origin in the sympathetic and parasympathetic paraganglia from the autonomic nervous system. At least 40% of these rare
neoplasias are associated with germline mutations (1) and
this is considered as the tumor for which the contribution
of genetics is the strongest (2). Among the described
mutations, those of the genes coding for succinate dehydrogenase are the most frequent (3). They are broadly
called SDHx mutations. Succinate dehydrogenase is a
hetero-tetrameric mitochondrial enzyme complex that
plays a pivotal role in cellular metabolism. It is involved in
the citric acid cycle and in the mitochondrial electron
transportation chain from the oxidative phosphorylation
as complex II (4). Since 2000, several mutations in the
genes that encode the four subunits (SDHD, SDHB,
SDHC, and SDHA) or the factor needed for their activation (SDHAF2) have been described in association with
the development of PPGL (5–10). The mutation penetrance is not complete and varies according to the identified mutation (11). Thus, a variable number of the
mutation carriers develop the associated illness, which can
include pheochromocytomas or paragangliomas in the
head and neck, thorax, abdomen or pelvis, and less frequently, gastrointestinal stromal tumors (GIST), renal cell
carcinomas, and pituitary adenomas. Medical complications arising from these neoplasias derive from the effect of
tumor mass and/or the hypersecretion of catecholamines
by pheochromocytomas or functioning paragangliomas.
A presymptomatic screening of the patients’ relatives
who are also carriers of the SDHx mutation is recommended with the expectation of establishing an early
diagnosis of the disease, which in turn, improves prognosis. Currently, the follow-up of asymptomatic carriers
is based on the measurement of catecholamine metabolites (i.e., metanephrines) in blood or in 24-hour urine
samples in addition to serial imaging examinations.
However, the analytical studies do not allow the diagnosis of nonfunctioning tumors and imaging studies
are time-consuming, relatively expensive (because of the
need for cervical, thoracic, abdominal, and pelvic examinations), and lack accuracy for small tumors. These
difficulties indicate the need to find new tumor markers
that enable early diagnosis.
Previous metabolomic studies conducted in PPGL tumor tissue showed a correlation between metabolomic
profile and the presence of SDHx mutations (12–16). The
profile includes mainly higher succinate and lower fumarate levels in PPGL associated with SDHx mutations,
but also differences in other metabolites such as cisaconitate and isocitrate. The succinate and fumarate that
are intermediates in the citric acid cycle are, respectively, the
J Clin Endocrinol Metab, November 2019, 104(11):5467–5477
doi: 10.1210/jc.2019-01101
Table 1.
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Participants’ Characteristics
Variables
SDHx Wild-Type
(N 5 8)
41.6 6 15.9
61.3 6 12.7
34 (50.0)
34 (50.0)
3 (37.5)
5 (62.5)
Age (y), mean 6 SD
Sex, n (%)
Female
Male
Type of mutation, n (%)
SDHB
SDHC
SDHD
State at time of urine collection, n (%)
Unaffected
With nonmetastatic tumor
With metastatic tumor
Type of tumor’s hormonal secretion, n (%)
Nonfunctioning
Adrenergic
Noradrenergic
Dopaminergic
Unknown
Metanephrines measurement
Participants were instructed to fast for at least 8 hours,
follow a diet low in catecholamine-containing products, and
cease interfering medicines on the days before the blood collection. The blood samples were collected in the various hospitals
after at least 30 minutes of supine rest, through a venipuncture
technique into K3-EDTA and serum-separating tubes. All samples were collected and placed on ice, immediately centrifuged,
aliquoted, and stored at 280°C before analyses. At the central
laboratory, an online solid-phase extraction was performed
using the fully automated Symbiosis™ system (Spark Holland,
Emmen, Netherlands), coupled with high-performance liquid
chromatography tandem quadrupole mass spectrometric detection (XLC-MS/MS, Waters XEVO TQ-MS, Waters Corp.,
Milford, MA), to measure metanephrine, normetanephrine, and
3-methoxytiramine in plasma samples. Tumors were classified as
functioning if amines excretion was at least 1.5 times the upper
limit of the normal range.
NMR acquisition
Participants were instructed how to collect a 24-hour urine
sample properly. After reception, samples were locally frozen
at a temperature of 280°C. Before NMR analysis, the urine
samples were thawed at room temperature and then centrifuged
for 10 minutes at 12 000g. Then, 60 mL of a 1.5 M potassium
dihydrogen phosphate buffer (pH 7.4) in deuterated water
with 2.9 mM 3-(trimethylsilyl)propionic-2,2,3,3-d4 and 0.05%
sodium azide were added to 540 mL of urine and transferred to
5 mm NMR tubes. The spectra were acquired on a Bruker
Avance II1 800 MHz (Bruker Biospin, Wissembourg, France)
spectrometer equipped with a 5 mm TXI-Z H/C/N/-D probe
(Bruker Biospin). All 1D 1H were acquired at 300 K using a
noesygppr1d pulse program (128 scans; relaxation delay of 4 s;
mixing time of 10 ms; spectral width of 16025.641 Hz; size of
free induction decay was 128k points). For all the samples a
JH,H-resolved (2 scans, 100 points in F1 and 8192 points in F2,
relaxation delay of 2 s, spectral width of 78.113 Hz in F1 and
13368.984 in F2) was acquired to aid compound identification.
55 (80.9)
1 (1.5)
12 (17.6)
42 (61.8)
17 (25.0)
9 (13.2)
0
8 (100)
0
11 (42.3)
0 (0)
7 (26.9)
7 (26.9)
1 (3.8)
4 (50.0)
3 (37.5)
1 (12.5)
0
0
The spectra acquisition and processing was performed with
Bruker TopSpin 3.2 (Bruker Biospin). All free induction decays
were multiplied by an exponential function, followed by Fourier
transformation. Spectra were manually phased, and baseline
corrected. Chemical shifts were adjusted according to the
chemical shift of trimethylsilylpropanoic acid at 0.00 ppm that
was used as concentration reference. The metabolites present in
the spectra were identified and quantified recurring to Chenomx NMR suite 8.12 (Chenomx, Edmonton, Alberta,
Canada). All the metabolites were confirmed through recourse to two-dimensional NMR spectra. Samples that
revealed the presence of blood or infection were discarded
from the analysis.
Statistical analysis
In the metabolomic analysis, 58 metabolites that were
present in most of the samples were considered. The metabolite
concentrations that exceed 4 times the interquartile range were
discarded from the analysis. Pairwise comparisons were conducted using the Wilcoxon rank-sum test to look for significant
differences (P , 0.05) between the groups of samples. Correction for multiple testing was performed using the BenjaminiHochberg procedure.
Metabolite set enrichment analysis
The metabolite set enrichment analysis (MSEA) was performed to identify biologically meaningful patterns in the
metabolite levels present in urine (www.metaboanalyst.ca) (24,
25). Urine metabolite concentrations was used as input data and
the enrichment analysis was performed in the metabolic
pathway associated set library.
Results
In the urine 1H-NMR spectra it was possible to identify
and quantify 58 metabolites that were present in most of
the samples. Because urine is a complex biofluid that is
composed by the excreted metabolites of the body, many
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SDHx Mutation Carriers
(N 5 68)
Mean
(mM)
1359.94
360.7
180.49
178.1
158.44
99.31
86.03
80.35
50.45
48.29
46.22
44.74
33.83
32.91
27.11
26.3
25.62
24.02
24.01
23.04
21.24
18.16
17.26
15.35
15.23
14.47
14.41
14.12
12.61
11.49
10.21
10.17
10.15
10.11
9.15
8.55
8.45
7.91
7.85
Creatinine
Citrate
Glycine
Hippurate
Taurine
Creatine
Trimethylamine N-oxide
N-Phenylacetylglycine
Acetate
Dimethylamine
Malonate
Formate
Alanine
3-Indoxylsulfate
Glucose
Glucuronate
Xylose
cis-Aconitate
Lactate
Threonine
Galactose
Allantoin
4-Hydroxyphenylacetate
Fucose
O-Phosphocholine
Methanol
Betaine
Tyrosine
3-Hydroxyisobutyrate
Xanthine
3-Aminoisobutyrate
Trigonelline
Sucrose
1,6-Anhydro-b-D-glucose
Succinate
Imidazole
2-Furoylglycine
Dimethyl sulfone
Tartrate
1214.4
324.6
119
154.4
147
65
54.8
66.4
9.6
45.5
39.9
36.6
30.2
30.1
25.2
23.5
23.3
23.9
18.9
18
17
16.6
13.5
14
11.9
13.7
11.7
12.3
10.6
7.8
7.4
6.6
7
5.2
6.7
6.7
7.4
8.2
3
Median
(mM)
708.68
234.33
155.41
131.09
107.97
103.26
104.74
54.71
79.7
20.27
25.35
41.2
19.98
18.31
13.22
18.3
15.76
10.04
17.51
19.29
17.11
10.31
12.14
7.86
13.33
10.6
10.59
9.43
6.39
10.99
8.57
9.8
9.9
12.02
7.7
6.75
6.71
3.24
8.83
SD
(mM)
1068.22
250.08
121.75
163.73
116.3
99.7
69.1
74.7
32.77
45.25
45.34
36.94
26.43
26.57
27.9
23.37
24.5
20.75
26.6
15.47
22.08
17.18
14.38
13.98
11.13
10.25
11.24
10.01
11.44
5.35
10.83
8.43
11.37
7.28
5.93
7.78
4.94
6.44
5.59
Mean
(mM)
942
206.9
112.6
113.5
108.8
19.6
45.2
57.6
6
38.8
40.2
32.4
23.4
22.8
25.2
19.6
19.2
20
16.8
12.8
20.5
15.5
14.5
10.8
7.4
5.1
10.4
10
8.9
4.5
6.2
8
6.4
4.2
3.4
6.2
4.4
6
2.8
Median
(mM)
SD
(mM)
519.31
160.5
70.31
148.56
63.21
145.85
60.16
49.29
57.7
34.74
26.9
23.77
14.96
12.93
12.95
13.48
21.23
8.99
29.63
10.9
11.53
9.47
7.51
9.8
10.36
14.27
6.46
6.04
8.44
2.85
10.91
5.3
9.46
9.62
6.15
6.44
3.19
3.32
6.46
SDHx Tumors (T)
1359.94
360.7
180.49
178.1
158.44
99.31
86.03
80.35
50.45
48.29
46.22
44.74
33.83
32.91
27.11
26.3
25.62
24.02
24.01
23.04
21.24
18.16
17.26
15.35
15.23
14.47
14.41
14.12
12.61
11.49
10.21
10.17
10.15
10.11
9.15
8.55
8.45
7.91
7.85
Mean
(mM)
660.8
156.2
84.3
130.1
91.7
25.9
49.8
90.7
10.5
29.9
29.5
28
23.5
25.1
16.6
18.6
33.6
15.3
7.1
10
13
15.6
10.9
9.1
7.6
5.2
11.1
8.4
6
5
7.8
8.3
4.6
5.1
2.8
2.9
2.6
5
5.2
Median
(mM)
SD
(mM)
314.86
100.47
45.77
76.31
201.85
145.46
193.03
32.95
53.73
24.02
20.31
21.68
11.01
13.97
13.66
14.62
22.46
5.45
6.53
9.55
9.88
6.16
4.07
6.25
10.37
10.75
13.84
3.87
4.44
1.78
5.68
8.37
8.6
5.41
3.78
3.21
3.38
2.56
11.57
Sporadic PPGL (S)
0.027
0.023
0.008
0.034
0.014
0.022
0.005
0.009
0.008
0.011
A vs S
P Value
(Continued)
0.044
T vs S
P Value
SDHx-Associated Tumors: Urine Metabolomics
0.020
0.021
A vs T
P Value
Martins et al
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Metabolite
SDHx Asymptomatics (A)
Table 2. Comprehensive List of the 58 Quantified Metabolite Concentrations for the SDHx Mutation Carriers Without Evidence of Disease (SDHx
Carriers), the SDHx Mutation Carriers With Related Tumors (SDHx Tumors), and the Patients With Sporadic PPGL (Sporadic PPGL)
5470
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5
5.6
6
6.2
5.3
5.9
3
5.5
5.6
3.8
4.9
4
4
3.9
3.6
3
2.8
1.6
1
0.5
4.79
4.79
4.28
3.53
3.17
2.06
1.47
0.7
Median
(mM)
7.54
7.35
6.91
6.87
6.75
6.66
6.5
6.26
6.01
5.61
5.53
4.84
Mean
(mM)
2.69
3.14
3.06
2.38
1.37
1.16
1.38
0.57
7.2
4.41
4.25
3.72
5.99
3.45
6.7
3.07
3.09
4.14
3.2
2.37
SD
(mM)
3.8
3.85
3.99
3.05
2.52
2.21
1.21
0.74
4.7
8.6
4.87
7.39
5.8
5.99
6.44
5.32
5.63
4.75
4.7
5.43
Mean
(mM)
2.9
3.4
2.1
2.7
2
1.6
0.9
0.6
3.6
7.8
4
6.7
3.6
5.7
3.4
3.6
4.2
3.6
3.6
4.3
Median
(mM)
SDHx Tumors (T)
2.44
1.79
3.92
1.89
1.31
1.78
0.85
0.5
3.71
6.07
2.92
4.63
6.43
2.95
6.83
4.14
4.04
4.11
3.26
3.55
SD
(mM)
4.79
4.79
4.28
3.53
3.17
2.06
1.47
0.7
7.54
7.35
6.91
6.87
6.75
6.66
6.5
6.26
6.01
5.61
5.53
4.84
Mean
(mM)
3.3
2.9
2.9
2.9
1.7
1.6
0.8
0.6
2.9
5.9
3.6
3.2
3.4
4
1.8
2.5
3.8
2.1
2.9
2.5
Median
(mM)
Sporadic PPGL (S)
3.9
2.29
2.71
1.6
0.59
0.7
0.6
0.3
1.87
4.92
4.28
3.42
1.45
2.22
0.84
1.7
2.06
1.75
2.86
3.56
SD
(mM)
0.036
0.026
A vs T
P Value
0.011
0.015
0.001
0.041
0.017
0.047
A vs S
P Value
0.016
0.042
T vs S
P Value
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The P values for observed statistically significant differences are presented.
Ascorbate
N-Acetylglucosamine
Choline
3-Hydroxyisovalerate
Creatine phosphate
2-Hydroxyisobutyrate
Benzoate
N-Acetylaspartate
N,N-Dimethylglycine
O-Acetylcholine
Maltose
4-Hydroxy3-methoxymandelate
3-Hydroxy-3-methylglutarate
Carnitine
trans-Aconitate
Valine
5-Hydroxyindole-3-acetate
Acetone
Trimethylamine
Fumarate
Metabolite
SDHx Asymptomatics (A)
Table 2. Comprehensive List of the 58 Quantified Metabolite Concentrations for the SDHx Mutation Carriers Without Evidence of Disease (SDHx
Carriers), the SDHx Mutation Carriers With Related Tumors (SDHx Tumors), and the Patients With Sporadic PPGL (Sporadic PPGL) (Continued)
doi: 10.1210/jc.2019-01101
5471
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SDHx-Associated Tumors: Urine Metabolomics
samples show unique metabolites that can be the result
of therapeutics, food additives, etc., that were not considered in our analysis. A comprehensive list of assignments is provided in Table 2.
J Clin Endocrinol Metab, November 2019, 104(11):5467–5477
Affected SDHx carriers vs asymptomatic SDHx
carriers vs patients with sporadic PPGL
The metabolomic urinary profile of SDHx carriers with
associated tumors was compared with that of asymptomatic
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Figure 1. Metabolites in urine that registered statistically significant different concentrations between asymptomatic SDHx mutation carriers
(asymptomatic), SDHx carriers with associated tumors (SDHx tumor), and individuals with sporadic PPGL (sporadic). P . 0.05 (ns); *P # 0.05;
**P # 0.01. ns, not significant.
doi: 10.1210/jc.2019-01101
5473
0.036). The MSEA analysis indicated that the pathways that
are most influenced by the development of tumors in the
SDHx mutation carriers are those related to catecholamine
biosynthesis, tryptophan, and lipid metabolism (Fig. 2A).
Restricting the analysis to individuals with tumors, the
urine of patients with SDHx mutations presented higher
Figure 2. MSEA of urine showing the differentially affected metabolic pathways of (A) SDHx mutation carriers with related tumors compared
with SDHx mutation carriers without evidence of disease; (B) SDHx mutation carriers with related tumors compared with patients with sporadic
PPGL; (C) SDHx mutation carriers without evidence of disease compared with patients with sporadic PPGL; and (D) PPGL patients with SDHB vs
SDHD mutations.
Downloaded from https://academic.oup.com/jcem/article-abstract/104/11/5467/5536622 by Endocrine Society Member Access 3 user on 17 October 2019
carriers and of patients with sporadic PPGL (Fig. 1; Table 2).
Compared with asymptomatic SDHx carriers, the urine
of affected carriers showed substantially lower levels of
xanthine (P 5 0.008), methanol (P 5 0.020), citrate
(P 5 0.021), succinate (P 5 0.023), choline (P 5 0.026),
2-furoyglycine (P 5 0.027), and N-acetylaspartate (P 5
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Martins et al
SDHx-Associated Tumors: Urine Metabolomics
Other analyses
When metastatic tumors were compared with nonmetastatic PPGL in patients with SDHx mutations, only one
difference emerged. Specifically, methanol levels were lower
in the urine of patients with tumors who developed
metastases (4.38 6 3.18 mM vs 13.36 616.83 mM,
P 5 0.02).
The type of SDHx mutation also influenced the metabolites present in the urine. Specifically, patients with
PPGL associated with the SDHD mutation had increased
levels of dimethyl sulfone (P 5 0.039) and formate (P 5
0.035) compared with affected SDHB mutation carriers
(Fig. 3A). The MSEA indicated differences in gluconeogenesis, Warburg effect, citric acid cycle, and transfer
of acetyl groups into mitochondria between carriers of
SDHD and SDHB mutation (Fig. 2D).
When we compared the urine of patients with functioning vs nonfunctioning PPGL, the only metabolite
that showed a difference was dimethylglycine (P 5
0.027), an amino acid derivative produced in the
metabolization of choline into glycine. Its concentrations
were lower in the urine of patients with functioning
Figure 3. Metabolites in urine with a substantial concentration difference (P , 0.05) between (A) affected individuals with SDHB and SDHD
mutation; (B) patients with functioning tumors (Func) and nonfunctioning tumors (no Func), regardless of the existence or not of mutation.
P . 0.05 (ns); *P # 0.05; **P # 0.01. ns, not significant.
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levels of N-acetylaspartate (P 5 0.016), 3-hydroxyisovalerate (P 5 0.042), and lactate (P 5 0.044) than the
urine of individuals with sporadic PPGL (Fig. 1). The
metabolite differences indicated that gluconeogenesis, pyruvate metabolism, ammonia recycling, porphyrin, and aspartate metabolism are differentially affected in patients with
SDHx-associated neoplasias, relative to sporadic PPGL patients (Fig. 2B).
Comparative analysis of urine from asymptomatic
SDHx mutation carriers and from patients with sporadic
PPGL revealed lower levels of a number of metabolites in
the latter (Fig. 1): N-acetylaspartate (P 5 0.001), cisaconitate (P 5 0.005), creatinine (P 5 0.008), lactate
(P 5 0.009), citrate (P 5 0.011), 5-hydroxyindole-3acetate (P 5 0.011), 3-hydroxyisobutyrate (P 5 0.014),
O-acetylcholine (P 5 0.015), 3-hydroxyisovalerate (P 5
0.017), xanthine (P 5 0.022), imidazole (P 5 0.034), 2hydroxyisobutyrate (P 5 0.041), and ascorbate (P 5
0.047). The metabolite differences could result from
alterations in mitochondria pathways, such as acetyl
groups transference, glucose metabolism, and citric acid
cycle (Fig. 2C).
J Clin Endocrinol Metab, November 2019, 104(11):5467–5477
doi: 10.1210/jc.2019-01101
Discussion
Our results indicate that the metabolomic urine profile of
SDHx mutation carriers with associated tumors is different from that of asymptomatic carriers. Seven metabolites presented lower levels in the former than in the
latter carriers. These findings, and the MSEA, suggest
the presence of alterations in the pathways related to the
PPGL catecholamine biosynthesis. Unlike the metabolomic profile of tumoral tissue, in which the oncometabolite succinate characteristically presents high levels
(13–16), in the urine, its levels were lower for SDHx
mutation carriers with associated tumors than for SDHx
asymptomatic carriers. The increased retention and accumulation of succinate in tumor cells, and its role as an
oncometabolite (26), might be associated with its deficient elimination and low excretion in urine. Larger
studies measuring this metabolite in plasma can help to
clarify these findings and to establish the relevance of
succinate as a tumor marker for this disease. Similar to
succinate, the citrate levels were lower in SDHx carriers
with associated tumors than in asymptomatic mutation
carriers. Citrate is also a metabolite of the citric acid
cycle, and this finding is consistent with the changes
observed in tumor tissue, in which citrate levels in SDHxassociated tumors were lower than in sporadic tumors
(15). Other metabolites were also different in affected
vs asymptomatic carriers. Patients with tumors always
presented lower levels of such metabolites, suggesting a
washout problem in association with tumorigenesis.
Reinforcing this hypothesis, all the statistically significant
differences between patients with disease (sporadic or
associated with SDHx) and asymptomatic SDHx carriers
showed lower levels in the former group.
The metabolomic urinary profile of patients with
SDHx-associated and sporadic PPGL was also different.
Lactate levels, for example, were higher in patients with
SDHx-related tumors than in patients with sporadic
5475
PPGL. This finding underscores the preference for anaerobic pathways, in line with the known pseudohypoxia
signature of these tumors (27). The fact that lactate levels
were also higher in asymptomatic SDHx mutation carriers than in patients with sporadic tumors provides
support for the occurrence of pseudohypoxia even in
unaffected SDHx mutation carriers. The MSEA analysis
suggested that gluconeogenesis, pyruvate metabolism,
ammonia recycling, porphyrin, and aspartate metabolism most probably explain the differences found between SDHx-associated and sporadic PPGL patients.
Gluconeogenesis, the process of generating glucose from
carbon substrates (as pyruvate) other than carbohydrates, has shown to be upregulated in cancer (28).
Lussey-Lepoutre et al. (29) previously demonstrated that
SDH-mutated tumors presented altered metabolism of
pyruvate, which is the glycolytic entry point into the citric
acid cycle. The alteration consisted of an increased
production of aspartate, which worked as an alternative
pathway enabling the truncated citric acid cycle to
continue and upon which the cells become dependent for
proliferation and survival.
Synthesized from aspartate and acetyl-coenzyme A
(CoA; an intermediary of the citric acid cycle, derived
from pyruvate) (30), N-acetylaspartate was the only
metabolite the urinary levels of which registered differences among the three groups analyzed. The lowest
levels were observed in patients with sporadic PPGL
followed by intermediate levels observed in individuals
with SDHx-associated tumors; the highest levels corresponded to SDHx asymptomatic carriers. These results
concerning urinary levels of N-acetylaspartate contrast,
once again, with those reported in previous studies using
tumor tissue, which documented lower N-acetylaspartate
levels in SDHx tumors, compared with sporadic tumors
(12). N-acetylaspartate has been classically associated
with central nervous system disturbances (30). Our study
reinforces its relevance also for this disease of peripheral
nervous system, as recently suggested (12). Its synthesis in
mitochondria depends on respiratory chain and oxidative phosphorylation (31), and a strong positive correlation was shown between N-acetylaspartate content and
ATP/ADP/AMP contents in PPGL (12). In a recent review
about this metabolite, the authors hypothesized that
N-acetylaspartate might complement citrate, delivering
acetyl-CoA to the cytosol (30). Our findings support the
relation of this metabolite with the development of
neoplasms associated with SDHx mutations. Future
studies based, for example, on plasma analysis, are
needed for a better understanding of the present findings
and for the establishment of the potential utility of Nacetylaspartate as a biomarker. Ammonia recycling is
another pathway highlighted in MSEA that enables
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PPGL. Interestingly, the levels of vanillylmandelic acid
(also known as 4-hydroxy-3-methoxymandelate), a
product of the catecholamine catabolism, were higher
(P 5 0.022) in the urine of patients with functioning
PPGL (Fig. 3B). The MSEA indicated that one of the
pathways that was altered in the functioning PPGL was
catecholamines biosynthesis, but phospholipid synthesis,
citric acid cycle, and tyrosine metabolism were also
altered.
Analysis by type of hormonal secretion (nonfunctioning, adrenergic, noradrenergic, dopaminergic) did
not show differences in metabolites concentrations. This
can be explained by the reduced number of samples of
each type.
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Martins et al
SDHx-Associated Tumors: Urine Metabolomics
Acknowledgments
The authors would like to thank all the clinicians from the
involved hospitals who contributed to this study, allowing
access to the patients (Helder Sim~
oes, Maria Jo~
ao Matos,
Isabel Torres, Valeriano Leite, Fernando Rodrigues, Manuel R.
Teixeira); all those who contributed to sample collection and
storage (Celeste Fontoura, Nuno Gonçalves, Susana Prazeres);
Professor Irene Carvalho who proofread the manuscript; and
the study participants for their contribution to this research.
The NMR data were acquired at CERMAX (Centro de
Ressonância Magnética António Xavier).
Financial Support: R.G.M. received a Dr. Rocha Alves
research grant from the Núcleo Regional do Centro da Liga
Portuguesa Contra o Cancro. L.G.G. had a post-doc grant,
SFRH/BPD/111100/2015, awarded by FCT - “Fundaç~
ao para a
Ciência e a Tecnologia.” The use of NMR facility was funded
by project LISBOA-01-0145-FEDER-007660 (Microbiologia
Molecular, Estrutural e Celular), by FEDER through COMPETE2020 - POCI and by national funds through FCT“Fundaç~
ao para a Ciência e a Tecnologia.”
Additional Information
Correspondence and Reprint Requests: Raquel G. Martins,
MD, MsC, Departamento de Neurociências Clı́nicas e Saúde
Mental/Unidade de Psicologia Médica, Faculdade de Medicina
da Universidade do Porto, Al. Prof. Hernâni Monteiro, 4200-319
Porto, Portugal. E-mail: martins.raquel@hotmail.com.
Disclosure Summary: The authors have nothing to
disclose.
Data Availability: The datasets generated during and/or
analyzed during the current study are not publicly available but
are available from the corresponding author on reasonable
request.
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