cancers
ArticlePrevalence of Germline Variants in a Large Cohort of JapanesePatients with Pheochromocytoma and/or Paraganglioma
Masato Yonamine 1 , Koichiro Wasano 2 , Yuichi Aita 3 , Takehito Sugasawa 1 , Katsutoshi Takahashi 4 ,Yasushi Kawakami 1 , Hitoshi Shimano 3 , Hiroyuki Nishiyama 5 , Hisato Hara 6 , Mitsuhide Naruse 7,8 ,Takahiro Okamoto 9 , Tadashi Matsuda 10 , Shinji Kosugi 11 , Kazuhiko Horiguchi 12 , Akiyo Tanabe 13 ,Atsushi Watanabe 14 , Noriko Kimura 15 , Eijiro Nakamura 16 , Akihiro Sakurai 17 , Kiyoto Shiga 18
and Kazuhiro Takekoshi 1, *
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Citation: Yonamine, M.; Wasano, K.;

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Aita, Y.; Sugasawa, T.; Takahashi, K.;
Kawakami, Y.; Shimano, H.;
Nishiyama, H.; Hara, H.; Naruse, M.;
et al. Prevalence of Germline Variants
in a Large Cohort of Japanese Patients

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with Pheochromocytoma and/or
Paraganglioma. Cancers 2021, 13,114014. https://doi.org/10.3390/
cancers13164014
Academic Editor: Enzo Lalli
Received: 25 July 2021

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Accepted: 4 August 2021
Published: 9 August 2021

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with regard to jurisdictional claims inpublished maps and institutional affiliations.

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*
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Laboratory of Laboratory/Sports Medicine, Division of Clinical Medicine, Faculty of Medicine, Universityof Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Ibaraki, Japan; yonamine.masato.fu@u.tsukuba.ac.jp (M.Y.);
take0716@krf.biglobe.ne.jp (T.S.); y-kawa@md.tsukuba.ac.jp (Y.K.)
Division of Hearing and Balance Research, National Institute of Sensory Organs, National Hospital
Organization Tokyo Medical Center, Meguro 152-8902, Tokyo, Japan; wasano@a5.keio.jp
Department of Endocrinology and Metabolism, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai,
Tsukuba 305-8577, Ibaraki, Japan; yaita@md.tsukuba.ac.jp (Y.A.); hshimano@md.tsukuba.ac.jp (H.S.)
Division of Metabolism, Showa General Hospital, 8-1-1 Hanakoganei, Kodaira 187-8510, Tokyo, Japan;
ktaka-tky@umin.ac.jp
Department of Urology, Faculty of Medicine, University of Tsukuba Hospital, 2-1-1 Amakubo,
Tsukuba 305-8576, Ibaraki, Japan; nishiuro@md.tsukuba.ac.jp
Department of Breast and Endocrine Surgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai,
Tsukuba 305-8577, Ibaraki, Japan; harahisa@md.tsukuba.ac.jp
Institute of Clinical Endocrinology and Metabolism, National Hospital Organization Kyoto Medical Center,
1-1 Fukakusamukaihatacho, Fushimi-ku 612-8555, Kyoto, Japan; m-naruse@takedahp.or.jp
Endocrine Center and Clinical Research Center, Ijinkai Takeda General Hospital, 28-1 Ishidamoriminamicho,
Fushimi-ku 601-1495, Kyoto, Japan
Department of Breast and Endocrine Surgery, Tokyo Women’s Medical University, 8-1 Kawada-cho,Shin-juku-ku 162-8666, Tokyo, Japan; okamoto.takahiro@twmu.ac.jp
Department of Urology and Andrology, Kansai Medical University, 2-5-1 Shin-machi, Hirakata 573-1010,
Osaka, Japan; matsudat@hirakata.kmu.ac.jp
Department of Medical Ethics/Medical Genetics, Kyoto University School of Public Health,
Yoshidakonoecho, Sakyo-ku 606-8501, Kyoto, Japan; kosugi@kuhp.kyoto-u.ac.jp
Division of Endocrinology and Metabolism, Gunma University Graduate School of Medicine,
3-39-15 Showa-machi, Maebashi 371-8511, Gunma, Japan; k-hori@gunma-u.ac.jp
Department of Diabetes, Endocrinology and Metabolism, Center Hospital of the National Center
for Global-Health and Medicine, 1-21-1 Toyama, Shinjuku-ku 162-8855, Tokyo, Japan;
atanabe-endo@umin.ac.jp
Division of Clinical Genetics, Kanazawa University Hospital, 13-1 Takaramachi, Kanazawa 920-8641,
Ishikawa, Japan; aw3703@staff.kanazawa-u.ac.jp
Department of Pathology, National Hospital Organization Hakodate National Hospital, 18-16 Kawahara-cho,
Hakodate 041-8512, Hokkaido, Japan; kimura.noriko.sf@mail.hosp.go.jp
Department of Urology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo City 104-0045, Tokyo, Japan;
einakamu@ncc.go.jp
Department of Medical Genetics and Genomics, Sapporo Medical University School of Medicine, Minami 1-jo
Nishi 17-chome Chuo-ku, Sapporo 060-8556, Hokkaido, Japan; sakurai.akihiro@sapmed.ac.jp
Department of Head and Neck Surgery, Iwate Medical University School of Medicine, 2-1-1 Idaidori,
Yaha-ba-cho, Shiwa-gun 028-3695, Iwate, Japan; kshiga@iwate-med.ac.jp
Correspondence: k-takemd@md.tsukuba.ac.jp; Tel.: +81-29-853-3209

Simple Summary: Pheochromocytoma/paraganglioma (PPGL) has been recognised as one of the mostfrequent inherited tumours with genetic heterogeneity based on studies in Caucasian populations.
Early identification of germline variants is crucial for accurate treatment and follow-up in affectedpatients and relatives. However, there are only a few large cohort studies in Asia and none fromthe Japanese population. In this first comprehensive study of Japanese patients with PPGL, we found
one in four PPGLs with apparently sporadic presentation harboured germline variant in any of the sevensusceptibility genes (MAX, SDHB, SDHC, SDHD, TMEM127, VHL, and RET). SDHB was the mostCancers 2021, 13, 4014. https://doi.org/10.3390/cancers13164014

https://www.mdpi.com/journal/cancers

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frequently mutated gene and was strongly associated with metastatic PPGLs. Our findings emphasise
the importance of genetic testing in determining appropriate treatment and follow-up strategies
for patients and relatives.
Abstract: The high incidence of germline variants in pheochromocytoma and paraganglioma (PPGL)
has been reported mainly in Europe, but not among Japanese populations in Asia. We aimed to
study the prevalence of germline variants in Japanese PPGL patients and the genotype–phenotype
correlation. We examined 370 PPGL probands, including 43 patients with family history and/or
syndromic presentation and 327 patients with apparently sporadic (AS) presentation. Clinical data
and blood samples were collected, and the seven major susceptibility genes (MAX, SDHB, SDHC,
SDHD, TMEM127, VHL, and RET) were tested using Sanger sequencing. Overall, 120/370 (32.4%)
patients had pathogenic or likely pathogenic variants, with 81/327 (24.8%) in AS presentation.
SDHB was the most frequently mutated gene (57, 15.4%), followed by SDHD (27, 7.3%), and VHL(18, 4.9%). The incidence of metastatic PPGL was high in SDHB carriers (21/57, 36.8%). A few
unique recurrent variants (SDHB c.137G>A and SDHB c.470delT) were detected in this Japanesecohort, highlighting ethnic differences. In summary, almost a quarter of patients with apparently
sporadic PPGL in Japan harboured germline variants of the targeted genes. This study reinforces
the recommendation in Western guidelines to perform genetic testing for PPGL and genotype-based
clinical decision-making in the Japanese population.
Keywords: pheochromocytoma; paraganglioma; genetics; germline variants; Japanese; SDHB; SDHD;
VHL

1. Introduction
Pheochromocytoma (PCC) and paraganglioma (PGL) are neuroendocrine tumours
derived from the chromaffin cells in the adrenal medulla and autonomic nervous system
ganglia, respectively. Despite the anatomical distinction, PCC and PGL share a common
pathological basis and genetic background and are collectively referred to as pheochromocytoma/paraganglioma (PPGL) [1,2]. PPGL can secrete catecholamines, the plasma
or urinary metabolites which are essential for biochemical diagnosis [3], while excess
catecholamines can cause cardio- or cerebrovascular complications. All PPGLs have the potential to metastasise to non-chromaffin tissues including bone, lung, liver, and lymph
nodes; thus, the prefix term “benign” was abandoned for these tumours in the 2017 World
Health Organization (WHO) classification of endocrine tumours [4].
PPGL is now considered to be the most frequent inherited tumour with genetic
heterogeneity. Germline variants are present in around 30% of PPGLs [5–8]; more than
20 susceptibility genes have been identified over the last two decades [9,10]. Even in PPGL
with apparently sporadic (AS) presentation (no familial/syndromic [FS] characteristics),
pathogenic variants have been found with a frequency of 11–24% [11–13]. In this context,
current guidelines recommend that germline genetic testing should be considered in all
patients with PPGLs regardless of family history [2,14,15]. Identification of a predisposing
germline variant enables risk assessment of distant metastases in probands and clinicalsurveillance of variant carriers in healthy relatives [1,2,9,16].
The genetic aetiology and genotype-phenotype relationship of PPGL have been studied extensively in Caucasian populations [5,6,11,17–19]. Recently, a large population studyof 719 Chinese and 919 European patients demonstrated broad Sino-European differencesin the genetic landscape and clinical presentation of PPGL [20]. This study suggested
that the genetic background of PPGL and the associated genotype–phenotype relationshipestablished in Caucasian populations may not apply to Asian populations. It is also worth
noting that in the few cohort studies of PPGL in Asia [21–23], the profiles of the mostcommon mutated gene and the recurring SDHB variants vary widely by ethnicity even
within Asia. In several case reports and case series from Japan, characteristic variants with

Cancers 2021, 13, 4014

3 of 15PPGL have been reported [24–28]; however, there are no comprehensive national studies.
We aimed to investigate the prevalence of germline variants in the major susceptibility
genes (MAX, SDHB, SDHC, SDHD, TMEM127, VHL, and RET) in the Japanese population
with PPGL. Furthermore, we evaluated variant classification based on several updated
databases and in silico meta-prediction tools and summarised the clinical and genetic
features of patients with PPGLs in Japan.
2. Results
2.1. Clinical Characteristics of the Study Population
Overall, 370 probands were enrolled in the study (166 males and 204 females; mean
age: 43.3 years; range: 6–83). Table 1 summarises the clinical characteristics for the wholestudy cohort and the FS and AS groups. PCC was present in 153 (41.4%) patients, and 31of these patients had a bilateral PCC. There were 194 (53.0%) patients with extra-adrenal
PGL; 79 (21.4%) had head and neck PGL (HNPGL), of which 6 were bilateral HNPGLs; and116 (31.4%) had abdominal/thoracic PGL (ATPGL), of which 10 were multiple. Twentytwo (5.9%) patients had multifocal tumours, of which 17 had comorbid tumours of PCC
and ATPGL, three had both PCC and HNPGL, and two had both HNPGL and ATPGL.
Metastatic PPGL was observed in 63 (17.0%) patients. A positive FS presentation wasobserved in 43 (11.6%) patients in the entire study cohort. The other 327 (88.4%) patients had an AS presentation. The FS group were diagnosed at a younger age thanthe AS group (36.0 ± 13.9 vs. 44.3 ± 15.8 years, p = 0.001) and more often had bilateral
PCC (25.6% vs. 6.1%), whereas the AS group had a greater proportion of unilateral PCC(35.2% vs. 16.3%).
Table 1. Clinical characteristics of patients with PPGL in the study.
CharacterisicSex (M:F)
Age at diagnosis (years)
Mean ± S.D.
Range
Tumour size (Mean ± S.D.) (cm)Location of tumour
Unilateral PCC
Bilateral PCC
Single HNPGL
Bilateral/Multiple HNPGLSingle ATPGL
Multiple ATPGL
Multifocal (PCC + HNPGL)
Multifocal (PCC + ATPGL)
Multifocal (HNPGL + ATPGL)
Metastatic

Overall(N = 370)

FS Presentation(N = 43, 11.6%)

AS Presentation(N = 327, 88.4%)

p Value(FS vs. AS)

166:204

25:18

141:1860.073

43.3 ± 15.8
6–83
5.4 ± 3.1

36.0 ± 13.9
10–69
4.3 ± 1.6

44.3 ± 15.8
6–83
5.3 ± 3.1

0.001

122 (33.0%)
31 (8.4%)
73 (19.7%)
6 (1.6%)106 (28.6%)
10 (2.7%)
3 (0.8%)17 (4.6%)
2 (0.5%)63 (17.0%)

7 (16.3%)
11 (25.6%)
9 (20.9%)2 (4.7%)8 (18.6%)4 (9.3%)2 (4.7%)5 (11.6%)

115 (35.2%)
20 (6.1%)
64 (19.6%)
4 (1.2%)98 (30.0%)
10 (3.1%)
3 (0.9%)13 (4.0%)58 (17.7%)

0.184<0.001

0.392

FS, familial/syndromic; AS, apparently sporadic; PCC, pheochromocytoma; HNPGL, head and neck paraganglioma; ATPGL, abdominal
and thoracic paraganglioma.

2.2. Classification of Profiled Variants
Of the 370 probands, 63 distinct germline variants were identified in 129 probands,
excluding benign (B) or likely benign (LB) variants (Table 2). We assessed the pathogenicity of these variants according to the American College of Medical Genetics (ACMG)
and the Association for Molecular Pathology (AMP) guidelines [29] (see Materials andMethods). As a result, 24 variants were classified as pathogenic (P), 29 variants as likely
pathogenic (LP), and 9 variants as a variant of uncertain significance (VUS). We found nine
novel variants, which were not previously reported or registered in any disease database.

Cancers 2021, 13, 4014

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Among them, 6/9 variants were classified as pathogenic or likely pathogenic, three variants
remained VUS.
Table 2. List of identified germline variants.
Variant

Gene
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHB
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
SDHD
VHL
VHL
VHL
VHL
VHL
VHL
VHL
VHL

Nucleotide
ChangeAmino Acid
Changec.79C>Tc.137G>A
c.183T>G
c.268C>Tc.470delTc.502C>Tc.641A>G
c.642G>C
c.649C>Tc.725G>A
c.201-2A>C
c.424-2delA #c.424-7_427
delinsC
Exon 1 Del
Exon1 Dup
Promotor andExon1-2 Del
c.1A>Gc.3G>Ac.15G>Ac.57delGc.112C>Tc.196T>C †c.228_239del †c.236T>G †c.242C>Tc.265_279del †c.285_296del †c.317G>A
c.337_340delc.352delc.412G>A
c.315-1G>A
Exon 4 Del
c.191G>C
c.235C>Gc.250G>A
c.250G>C
c.293A>Gc.370A>C †c.371C>Tc.407T>G

p.R27*
p.R46Q
p.Y61*
p.R90*
p.L157*
p.Q168*
p.Q214R
p.Q214H
p.R217C
p.R242H
SSC
SSC
SSC andsmall Indels-

In Silico
Prediction

Disease Database

No.
of
Probands
(FS)

REVEL

HSF

HGMD

1
14 (2)1
2
13 (2)
1
3 (1)
3 (1)
1
4
8
2 (1)

0.911
0.973
0.891
0.988
0.944
-

−32.0%−91.4%

2 (1)

-

1 (1)
1

Population Database
ACMG/
AMP
jMorp
Class
(Japanese)

ClinVargnomAD(Global)gnomAD(East
Asian)

R
R
R
R
R
R
R
R
R
R
NR
NR

P
P/LP
P
P
P
P
US
NR
P/LP
P
LP
NR

1/147,754
1/147,812
NR
2/147,886
NR
NR
NR
NR
1/147,922
1/147,882
1/147,958
NR

1/4946
0/4966
NR
0/4960NR
NR
NR
NR
1/49500/49601/4968
NR

NR
NR
NR
NR
NR
NR
NR
1/16,760
NRNR
4/16,760
NR

LP
P
P
P
P
P
LP
LP
LP
LP
P
P

−75.2%

R

NR

NR

NR

NR

P

-

-

R
R

P
US

NR
NR

NR
NR

NR
NR

P
VUS

-

1

-

-

R

NR

NR

NR

NR

LP

p.M1V
p.M1I
p.W5*
p.L20Cfs*66
p.R38*
p.W66R
p.L77_L80del
p.L79R
p.P81L
p.S89_Y93delp.A96_L99delp.G106D
p.D113Mfs*21
p.D118Mfs*17
p.G138R
SSC
p.R64P
p.R79G
p.V84M
p.V84L
p.Y98C
p.T124P
p.T124I
p.F136C

1
1 (1)
2 (1)
1
1
4
1
1
3 (1)
1
5 (3)
3 (3)
2 (1)
1 (1)
1 (1)
1 (1)
1
1
1
1
1
1 (1)
1 (1)
2 (2)
1

0.734
0.762
0.936
0.968
0.908
0.945
0.978
0.938
0.792
0.758
0.626
0.938
0.88
0.924
0.821

−30.7%
-

R
R
R
R
R
NR
NR
NR
R
NR
NR
R
R
R
NR
NR
R
R
NR
R
R
R
NR
R
R

P
P
NR
P
P
NR
NR
NR
P
NR
NR
NR
P
P
LP
LP
P
P/LP
US
LP/US
P
P
NR
LP
P/US

NR
NR
NR
NR
NR
NR
NR
NR
1/147,924
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
1/147,942
NR
NR
NR
NR

NR
NR
NR
NR
NR
NR
NR
NR
0/4952
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
0/4948
NR
NR
NR
NR

NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR

P
P
P
P
P
LP
VUS
VUS
LP
VUS
LP
LP
P
P
LP
P
P
LP
VUS
LP
LP
LP
LP
LP
LP

Cancers 2021, 13, 4014

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Table 2. Cont.
Variant

Gene

Nucleotide
ChangeAmino Acid
Change

VHL
VHL
VHL
VHL
VHL
VHL
VHL
RET
RET
RET
RET
MAX
MAX
MAX
MAX
MAX
TMEM127
TMEM127
TMEM127
TMEM127
SDHC
SDHC

c.414A>G
c.482G>A
c.496G>Tc.499C>Tc.500G>A
c.524A>Gc.548C>Tc.1891G>T
c.1892A>T
c.1900T>C
c.1901G>A
c.3G>A $c.70_73del †c.97C>Tc.223C>Tc.284T>C
c.116_119delc.119C>Tc.232dupG †c.280C>Tc.43C>Tc.204dupC †p.P138=
p.R161Q
p.V166F
p.R167W
p.R167Q
p.Y175C
p.S183L
p.D631Y
p.D631V
p.C634R
p.C634Y
p.M1I
p.K24Gfs*40
p.R33*
p.R75*
p.L95P
p.I41Rfs*39
p.S40F
p.D78Gfs*30
p.R94W
p.R15*
p.I69Hfs*29

No.
ofProbands
(FS)
4 (4)
1 (1)
1
1 (1)
1 (1)
1 (1)
1
1
1
2
4 (3)
1
1
1
2 (2)
1 (1)
2
1 (1)
1
1
1
1

In Silico
Prediction

Disease Database

Population Database

REVEL HSF HGMDClinVargnomAD(Global)gnomAD(East
Asian)

0.797
0.848
0.868
0.874
0.892
0.620
0.837
0.972
0.917
0.919
0.939
0.715
0.738
-

P
P
P
P
P/US
P/LP
US
P
US
P
P
NR
NR
P
P
US
P
US
NR
US
P
NR

NR
NR
NR
NR
NR
NR
2/147,912
NRNR
2/147,640
NR
NR
NR
NR
NR
NR
3/147,988
NRNR
9/147,980
3/147,874
NR

NR
NR
NR
NR
NR
NR
0/4960NRNR
0/4906
NR
NR
NR
NR
NR
NR
0/4964
NR
NR
0/49600/4964
NR

-

NR
R
R
R
R
R
R
R
NR
R
R
NR
NR
R
R
NR
R
R
NR
R
R
NR

jMorp
(Japanese)
NR
NR
NR
NR
NR
NR
3/16,760
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
1/16,760
NR
NR

ACMG/
AMP
Class
P
LP
LP
LP
LP
LP
VUS
LP
LP
LP
LP
P
LP
P
P
VUS
P
VUS
LP
VUS
P
LP

REVEL, Rare Exome Variant Ensemble Learner, which scores rare missense variants on a scale ranging from 0 to 1 with higher scoresindicating a greater likelihood of that variant being disease-causing, a score above 0.5 was used for supporting pathogenic variants(ACMG/AMP codes; PP3); HSF, Human Splicing Finder, provides information on changes in scores caused by variants in donor andacceptor sites, a reduction of >10% in the predicted score was used as the pathogenic variant; HGMD, Human Gene Mutation Database;
Del, deletion (heterozygous); Dup, duplication (heterozygous); SSC, splice site change; R, registered; NR, not registered; P, pathogenic; LP,likely pathogenic; US, unknown significance; VUS, variant of uncertain significance; * termination codon; † novel variant; # this variant was
described in a previous case report [30]; $ this variant was described in a previous cohort [31].

2.3. Frequency of Germline Variants
In our cohort of 370 probands, 120 subjects were found to harbour P/LP variants, thus
the prevalence rate of germline variants was 32.4% (Figure 1A). The most common variants
were SDHB detected in 57 probands (accounting for 47.5% of P/LP variants detected),
SDHD in 27 probands (22.5%), VHL in 18 probands (15.0%), RET in 8 probands (6.7%),
MAX in 5 probands (4.2%), TMEM127 in 3 probands (2.5%), and SDHC in 2 probands(1.7%). Among the 327 AS presentations, 81 probands had P/LP variants, with a prevalenceof the germline variant of 24.8% (Figure 1B). Compared to the AS presentation, the FS
presentation had a higher percentage of SDHD (30.2% vs. 4.3%) and VHL (27.9% vs. 1.8%)
variants (Table S1). Almost half (29/63, 46.0%) of the probands who developed metastatic
PPGL carried a P/LP germline variant (Figure 1C). Metastatic PPGL were mostly by SDHB
variant (21/29, 72.4%), followed by SDHD, RET, VHL, and MAX.

Cancers 2021, 13, 4014

6/10 (60.0%) cases of multiple ATPGL were variant negative (VUS was excluded).
Table S2 shows the age-based frequencies of the germline variants detected at thediagnosis. The distribution of the number of patients in each age group showed a symmetrical distribution with a peak at 31–50 years. While almost all VHL variants (15/18,
83.3%) were diagnosed before the age of 40, SDHB/SDHD variant positive patients hada6 of 15
wider age distribution including in older patients. Of the 61 patients diagnosed with
PPGL even after the age of 60, 25% (15/61) were found to harbour P/LP variants.

Figure 1. Prevalence and overview of mutated genes by presentation or tumour locations. P/LP, pathogenic/likely
Figure 1. Prevalence and overview of mutated genes by presentation or tumour locations. P/LP, pathogenic/likely pathopathogenic variants; VUS, variant of uncertain significance; B/LB, benign/likely benign variants; PCC, pheochromocytoma;
genic variants; VUS, variant of uncertain significance; B/LB, benign/likely benign variants; PCC, pheochromocytoma;
HNPGL,
head andand neck
neckparaganglioma;
paraganglioma;ATPGL,ATPGL,abdominal
abdominalandandthoracic
thoracicparaganglioma.
paraganglioma.(A)(A)
Prevalenceandoverview
HNPGL, head
Prevalenceandoverviewofofgermlinevariants
theoverallPPGL
PPGLprobands
probands(B)(B)PrevalencePrevalenceandandoverview
overviewof
ofgermline
germline variantsvariants inin apparently
apparently sporadic
germlinevariantsinin
theoverallsporadicpresentations
presentations (C)(C)PrevalencePrevalenceandandoverview
overviewofofgermline
germlinevariantsvariantsininthe
theMetastatic
MetastaticPPGL
PPGL(D)(D)PrevalencePrevalenceofofP/LP
P/LP variantsvariants
by tumourtumour location
location (VUS
(VUS waswas excluded
excluded fromfrom analysis).
analysis)by

The frequency
of germline
variants
accordingto tumour location is shown in Figure 1D
2.4. Clinical
Characteristicsof Probands
with
P/LP Variants(see Table S3 for details). Among the 119 unilateral PCC patients, 11 (9.2%) had the germline
Probands with a P/LP variant were younger at the age of diagnosis than the variant
variants in either 5 genes (SDHB: n = 2, SDHD: 1, VHL: 3, RET: 3, MAX: 2). In contrast,
negative group (38.2. ± 15.2 vs. 46.0 ± 15.6 years, p < 0.001; Table 3). The variant-negative
the variant rate was remarkably high in bilateral PCC (20/29, 69.0%), with VHL (10/20,
group had a significantly greater proportion of unilateral PCC compared to the P/LP pos50.0%) being the most frequently mutated gene. In 77 HNPGL patients, 51.9% (40/77)
itive group (108/241 (44.8%) vs. 11/120 (9.2%), p < 0.00278). In contrast, the ratio of bilateralof them had germline variants. The most frequently mutated genes were SDHD (22/40,
PCC to single HNPGL was significantly higher in the P/LP variant-positive group (20/120
55.0%) and SDHB (17/40, 42.5%), with one case of SDHC variants. Thirty-three per cent(16.7%) vs. 9/241 (3.7%), p < 0.00278). The P/LP variant group were more likely to developof the ATPGL (37/115) patients had germline variants. The majority of these variants weremetastatic PPGL than the variant negative group (24.2% vs. 13.4%, p = 0.029).
in the SDHB (34/37, 91.9%) gene, with one case each of SDHD, VHL, and SDHC variants
also detected. In 21 patients with multifocal PPGL, 57.1% (12/21) of the patients had
2.5. Genetic and Clinical Characteristics by Specific Susceptibility Genes
germline variants; mutated genes including VHL (4/12), SDHB (3/12), SDHD (3/12), MAX
2.5.1. SDHB
Variants (1/12). On the other hand, 9/21 (42.9%) cases of multifocal PPGL,(1/12),and TMEM127
11/28Fifty-seven(39.3%) casesof bilateral
PCC, 1/6 probands(16.7%) cases
bilateral/multiple
SDHB
variant-positive
hadof15
distinct variantsHNPGL,
classifiedand
as
6/10
cases
multiple4,ATPGL
werevariant:variant2,negative(VUS was
P/LP (60.0%)(missense:
5, ofnonsense:
splice site
small deletion:
1, excluded).
deletion-insertion
Table
shows theborder:
age-basedfrequenciesof thegermlinevariants
detectedduplication
at the diagacrossthe S2
intron/exon
1, large
deletions:2; Table2). A
heterozygous
nosis. The distribution of the number of patients in each age group showed a symmetrical
distribution with a peak at 31–50 years. While almost all VHL variants (15/18, 83.3%) werediagnosed before the age of 40, SDHB/SDHD variant positive patients had a wider age
distribution including in older patients. Of the 61 patients diagnosed with PPGL even after
the age of 60, 25% (15/61) were found to harbour P/LP variants.

Cancers 2021, 13, 4014

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2.4. Clinical Characteristics of Probands with P/LP Variants
Probands with a P/LP variant were younger at the age of diagnosis than the variant
negative group (38.2. ± 15.2 vs. 46.0 ± 15.6 years, p < 0.001; Table 3). The variant-negative
group had a significantly greater proportion of unilateral PCC compared to the P/LP positive
group (108/241 (44.8%) vs. 11/120 (9.2%), p < 0.00278). In contrast, the ratio of bilateral PCC
to single HNPGL was significantly higher in the P/LP variant-positive group (20/120 (16.7%)
vs. 9/241 (3.7%), p < 0.00278). The P/LP variant group were more likely to develop metastatic
PPGL than the variant negative group (24.2% vs. 13.4%, p = 0.029).
Table 3. Clinical phenotype based on the seven genotypes (excluding VUS).
VariantNegative(N = 241)

P/LPPositive(N = 120)

p Value #SDHB(N = 57)

SDHD(N = 27)

VHL(N = 18)

RET(N = 8)MAX(N = 5)

TMEM127(N = 3)SDHC(N = 2)Sex (M:F)
Familial
presentation
Syndromic
presentation
Age at diagnosis(years)102:139

59:61

0.228

23:34

18:9

10:8

4:4

1:4

3:0

0:2

2

38

9

13

11

3

2

0

0

-

5

-

-

3

2

-

-

Mean ± S.D.

46.0 ± 15.6

38.2 ± 15.2

42.1 ± 15.2

39.0 ± 21.1

50.3 ± 10.3

Range
Tumour size (cm)(Mean ± S.D.)
Locationof tumour
Unilateral PCC
Bilateral PCC
Single HNPGL
Bilateral HNPGLSingle ATPGL
Multiple ATPGL
PCC + HNPGL
PCC + ATPGL
HNPGL + ATPGL

6–83

10–74

37.2 ±
14.5 †
12–74

25–68

13–69

39–64

43–46

5.3 ± 3.1

4.9 ± 2.6

108
9
36
1
72
6
2
7
-

11 *
20 *
35 *
5
33
4
1
9
2

32 (13.4%)

29 (24.2%)

Characteristic

Metastatic<0.001

23–65

27.1 ±
13.8 †
10–64

5.5 ± 2.9

3.4 ± 1.2

5.2 ± 1.9

7.1 ± 2.8

4.6 ± 3.9

3.0 ± 0.5

5.4 ± 1.4

2
1
17
30
4
3
21
(36.8%) ‡

1
18
4
1
1
2

3
10
1
4
-

3
5
-

2
2
1
-

2
1
-

1
1
-

3 (11.1%)

1 (5.6%)

3 (37.5%)

1 (20.0%)--

44.6 ± 12.0

44.5 ± 1.5<0.001

0.029

VUS, variant of uncertain significance; P/LP, pathogenic/likely pathogenic variants; PCC, pheochromocytoma; HNPGL, head and neckparaganglioma; ATPGL, abdominal and thoracic paraganglioma; # p value for the comparison between variant-negative and P/LP-positive
group; * analysis performed between variant-negative and P/LP-positive group, p value was significant (p < 0.00278 after Bonferroni
correction) between each tumour location by post hoc tests for the chi-square independence test; † analysis performed between SDHB,
SDHD, VHL, and variant-negative group. Mean value was significantly different SDHB or VHL vs. variant-negative group by Kruskal–
Wallis tests; ‡ analysis performed between SDHB, SDHD, VHL, and variant-negative group. p value was significant (p < 0.00625 after
Bonferroni correction) vs. variant-negative group by post hoc tests for the chi-square independence test.

2.5. Genetic and Clinical Characteristics by Specific Susceptibility Genes
2.5.1. SDHB Variants
Fifty-seven SDHB variant-positive probands had 15 distinct variants classified as P/LP
(missense: 5, nonsense: 4, splice site variant: 2, small deletion: 1, deletion-insertion acrossthe intron/exon border: 1, large deletions: 2; Table 2). A heterozygous duplication of exon
1 in single probands was classified as VUS. The missense variant c.137G>A (p.Arg46Gln)
and the frameshift deletion c.470delT (p.Leu157Ter) were the two most frequent variants
occurring in 14/57 (24.6%) probands and 13/57 (22.8%) probands, respectively. Most
SDHB variant-positive patients belonged to the AS presentation (48/57, 84.2%; Table 3).
Of the 57 patients, 54 (94.7%) had PGL (single HNPGL: 17, single ATPGL: 30, multiple
ATPGL: 4, multifocal of PCC/ATPGL: 3), and only 3 (5.3%) patients had PCC. The SDHB
variants group had a significantly greater proportion of metastatic PPGL compared with avariant negative group (14.3% vs. 35.8%, p < 0.00625 after Bonferroni correction).
We also investigated associations between SDHB variant type (truncating or missense)and patient phenotype (Table S3). There were no significant differences in age at diagnosis,
tumour size, or frequency of metastatic PPGL between the truncating and missense variants.

Cancers 2021, 13, 4014

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We only noticed that truncated variants of the SDHB gene tended to show high frequencies
of HNPGL (14/33, 42.4%) as well as ATPGL (17/33, 51.5%).
2.5.2. SDHD Variants
We identified 14 distinct P/LP variants and three VUS in the SDHD gene (Table 2).
Interestingly, three deletion variants of 10–15 bases were found in exon 3 of the SDHD gene,among which, c.285_296del was found in several families with distant origins. We found
13/27 (48.1%) SDHD variant carriers with a family history (Table S1). Among them, nine
had a family history of PPGL on the paternal side, the remaining four had a brother/sisteror son/daughter with PPGL, and none had a family history on the maternal side. The majority of probands with SDHD variants presented with HNPGL or HNPGL combined
multifocal tumours (25/27 patients, 92.6%). Eleven per cent (3/27) of patients with SDHD
variants were metastatic forms, comparable to those in the variants negative group (13.4%,
32/241). There were no significant differences in age at diagnosis, tumour size, or frequencyof metastatic PPGL between the truncating (n = 9) and missense variants (n = 13) (Table S3).
2.5.3. VHL Variants
The P/LP variants of VHL in 18 probands, consisted of 12 missense and a deleterious
synonymous variant (c.414A>G, p.Pro138Pro). The p.Pro138Pro has been reported toconfer PCC susceptibility by promoting exon 2 skipping and consequently repressing
the expression of the full-length VHL transcript [32]. The three probands with syndromicpresentations had hemangioblastoma, pancreatic cysts, and pancreatic endocrine tumours,
respectively. The mean age of VHL variant-positive probands was 27.1 ± 13.8 (range: 10–64)
years. Patients with VHL variants were younger than those in the variant negative group(Table 3). The tumours were bilateral PCC in 10 patients (55.6%), and four (22.2%) had
the multifocal disease (PCC with ATPGL). Only one case showed distant metastasis.
2.5.4. Minor Variants Genes
The four RET missense variants in eight probands were located at the hot-spot codons
631 and 634 in exon 11. Of the five patients with FS presentations, three had a family history
of PPGL, and two had prior medullary thyroid carcinoma. The tumours with RET patientswere always adrenal and often bilateral (5/8, 62.5%). Three of the eight patients had been
diagnosed with metastatic PCC. Five distinct MAX variants, four TMEM127 variants, andtwo SDHC variants were detected (including 3 VUS; See Table 2). Bilateral PCC was often
observed as a phenotype of the variants in MAX or TMEM127 genes. Of the two patientswith the SDHC variant, one had multiple HNPGLs, the other had a single ATPGL.
3. Discussion
The present study revealed five major findings. First, in previously unstudied Japanesepatients with PPGL, we comprehensively profiled the P/LP germline variants in 32.4%of the total and 24.8% of the AS presentations. Second, heritable PPGL could not be
ruled out even at an older age of diagnosis (60–70 years), and the prevalence of germline
variants was high (32.2–67.8%) in all tumour locations except unilateral PCC (9.2%). Third,
as in the previous reports in European populations, the most frequently mutated gene
was SDHB (47.5%). However, several SDHB variants common in the probands of distinct
Japanese families differed from those in other races. Fourth, the incidence of metastatic
PPGL in P/LP variant carriers was high (24.2%), especially in SDHB carriers (36.8%).
Finally, we described nine novel variants, six of which were classified as P/LP.
The overall frequency of germline variants in our study cohort (32.4%) is consistent
with that in the reported European cohorts (27.4–32.9%) [5–7] and with recent reports
in Asians (32.6–34.1%) [22,23,31]. The prevalence of variants in AS presentations vary
widely (11.0–36.6%) [6,11,12,18,21–23] depending on the definition of “sporadic” andthe number of genes investigated. Applying the simple criterion of non-familial and nonsyndromic presentation as AS presentation, we found a 24.8% frequency of germline vari-Cancers 2021, 13, 4014

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ants in anyof the seven major susceptibility genes (MAX, SDHB, SDHC, SDHD, TMEM127,
VHL, and RET). Our findings also established that even patients with PPGL diagnosed over
the age of 60 may harbour germline variants such as SDHB and SDHD genes (Table S2).
It should be noted that false-negative family history in patients with PPGL can occur due
to patients’ lack of awareness of their relatives’ medical history, the presence of multiple
genes with low penetrance in hereditary PPGL [33], and the possibility of transmission
by maternal imprinting, which is characteristic of SDHD-related PPGL [34]. Nevertheless,the present study performed in the one of the scanty large cohorts in Asia shows that morethan one in four PPGL patients had a germline variant, supporting the recommendation
for genetic testing in all patients with PPGLs, regardless of age at presentation and family
history [2]. Early detection of predisposing germline variants is an important step to detect
potentially variant carriers in relatives, as well as the potential for improved outcomesthrough surveillance of SDHB and VHL variant carriers [35].
Our cohort confirms the high prevalence of heritability in all tumour locations except
unilateral PCC (Figure 1). Of note, bilateral PCC (69.0%) and multifocal PPGL (57.1%) had
the strongest association with the presence of a germline variant. These prevalence data
are in line with almost all major studies showing that 56.3–90.0% of patients with bilateral
PCC and 68.8–85.7% patients with multifocal PPGL have a germline variant [6,18,19,22,23].
In these strongly suspected hereditary bilateral PCC or multifocal PPGL, the most commonly mutated gene was VHL, consistent with the priority set by the genetic testing decision algorithm [6,23]. Conversely, unilateral PCC was characterized by a 9.2% frequency
of variants, notably lower than that in other tumour locations. From a cost-effectiveness perspective, the value of genetic testing in patients with unilateral PCC lacking symptomaticor metastatic features and without positive family history has not been established [14].
However, in a seminal study, Sbardella et al. showed the usefulness of routine genetic
screening with multi-gene panels in PCC patients with genetic heterogeneity [36]. Furthermore, NGS has been recently validated to reduce the processing time and cost compared toconventional Sanger sequencing for each exon.
The detailed breakdown of the genes found to be mutated in our study was uniquecompared to the non-Japanese cohort studies. Our study showed that SDHB was the most
mutated gene (47.5% of patients with positive variant and 15.4% of all cases studied),followed by SDHD (22.5%, 7.3% of all). While a recent study has suggested a Sino-European
difference in the frequency of SDHB variants with a lower frequency in East Asian thanin Caucasian populations [20], there are other reports which suggest that SDHB is the mostcommon variant in Asia [21,22]. These inconsistent results might be attributed to both
the differences in criteria for patient selection and the geographic origins of the studies.
The present study has the advantage of having a relatively higher number of patients withfunctional or non-functional HNPGL (79 patients, 21.4% of all PPGL) than other Asiancohort studies (9–39 patients, 2.9–38.6%) [21–23]. We found 22/77 (28.6%) of the subjects
with HNPGL had SDHD variants, and 17/77 (220.1%) had SDHB variants (excluding VUS,
see Figure 1, Table S3). These results confirmed previous reports of a high prevalenceof SDHD variants in HNPGL [37,38] and showed that SDHB variants were present at almost
comparable frequency. Notably, the truncating variants of the SDHB gene showed a highfrequency of presentation of HNPGL as well as ATPGL (Table S4). Further extensive cohort
studies and molecular genetics research are required to clarify the association between
HNPGL and truncated variants of SDHB.
In our cohorts, SDHB variants were the most frequently associated variants with
distant metastasis occurring in 21/63 (33.3%; Figure 1C). Furthermore, the SDHB variant
group showed a significantly higher percentage of metastatic PPGL than the variantnegative group (Table 3). These results have been depicted across almost major studies
with SDHB variants associated with an increased risk of distant metastasis [5,39–41].
Of note, there are several recurrent variants among the 16 distinct SDHB variants in thisstudy. c.137G>A was the most frequent variant (14/59, 23.7%), followed by c.470delT,
which was the second most frequent (13/59, 22.0%; Table 2). In a large UK cohort reported

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in 2018, SDHB intragenic variants were detected in 237 probands, of which c.137G>A
was found in 22 cases (9.3%), and this variant was the second most frequent variant
in SDHB [17]. In the most recent study in the Chinese population, c.137G>A was foundin 2/46 (4.3%) of the SDHB variant-positive patients, whereas c.136C>T, the most recurrent
SDHB variant in China (6/46, 13.0%), was not found in our Japanese PPGL population [22].
Inversely, c.470delT, which was reported as a novel variant associated with metastatic PGLin Japan in 2009 [28], has not been profiled in any other recent cohort studies. Although
haplotype analysis is required for conclusive determination, a founder effect is highly
suspected for c.470delT because this variant is found only in a limited ethnic population.
The accumulation and sharing of the phenotypical knowledge (such as the frequencyof metastasis and tumour localization) of recurrent variants in each population may lead tothe development of variant-specific personalised disease-risk management.
The detection of vast numbers of genetic variants with the recent evolution of sequencing technology in cancer testing has highlighted the importance of standardizing
the interpretation and classification of variants among laboratories. Internationally recognised guidelines have been reported by the ACMG and the AMP [29], providing a five-tierclassification system based on the combination of multiple lines of evidence with variablerank. In silico prediction of pathogenicity is one of the evidence categories recommended
by the ACMG/AMP guidelines. Recently, several in silico meta-prediction tools havebeen developed based on the analysis of multiple individual scores. Among them, Rare
Exome Variant Ensemble Learner (REVEL) has been confirmed to be an excellent predictive
tool for assessing the pathogenicity of missense variants [42–44]. We used this reliable
in silico tool and the latest disease and population databases to facilitate the identification of disease-causing variants. We also profiled nine VUS, including novel variants.
Although VUS is excluded from the analysis of the relationship between genotype andphenotype, it is necessary to repeatedly follow the latest database because the class maychange by the re-evaluation of VUS by PPGL experts [45].
The present study is the first comprehensive study profiling the prevalence of germline
variants in Japanese subjects with PPGL. However, it is essential to acknowledge the study’s
limitations. First, due to financial constraints, we could analyse only seven genes using
the Sanger sequencing technique. Therefore, it remains possible to carry another minor
susceptibility gene, especially in variant-negative multiple PPGLs. However, these sevengenes are reported to account for the majority of the germline variants in PPGL [9,45] andexhaust the list of inherited PPGL genes for which secondary findings are required to bereported in the latest ACMG statement (with the exception of the extremely rare SDHAF2
gene) [46]. Second, this study has the potential for selection bias, thereby falsely increasing
the frequencies of germline variants. However, this bias is minimised by the fact that
our cohort included more than 50% of subjects with only isolated unilateral benign PCC
or ATPGL. Third, we were not able to mention the relationship between the catecholamine
profile or SDHB-negative immunohistochemistry and the variant status. This was due
to variations in the ability to investigate PPGL systematically among the facilities which
provided the samples. Finally, the variant classification to interpret pathogenicity is incomplete because we were not able to perform genetic tests on both parents in all subjects,
thereby preventing the determination of the de novo nature of the annotated variants.
However, we were able to enhance the accuracy of pathogenicity assessment by reviewing
the allele frequencies in multiple population databases, up-to-date disease databases, andutilizing in silico prediction tools.
4. Materials and Methods
4.1. Patients
The study subjects included Japanese probands clinically and pathologically diagnosed
with PPGL referred to the University of Tsukuba Hospital seeking genetic testing during
the February 2007–March 2020 period. Genetic testing was performed on patients older
than 16 years of age for ethical reasons, although patients diagnosed before the age of 16

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years were included. Blood samples and clinical information, including sex, age at diagnosis,
tumour location, and extra-paraganglionic metastases, were collected. The study was conducted in accordance with the Declaration of Helsinki and Ethical Guidelines for Human
Genome/Gene Analysis Research of Japan. Written informed consent was obtained from all
patients. We offered genetic counselling before and after the genetic test, as appropriate.
FS (familial/syndromic) presentation was characterised by the presence of clinicalfeatures of multiple endocrine neoplasia type 2 (MEN2) or Von Hippel–Lindau (VHL)
disease in the proband or their family members (syndromic) or history of PPGL in the family members (familial), or in combination. The absence of FS features was considered to
be AS (apparently sporadic) presentation. Multifocal PPGL was defined as the coexistence of adrenal PCC and PGL or the presence of PGL across multiple areas of the headand neck and abdomen/thorax. Metastatic PPGL was defined by the presence of extraparaganglionic metastases, including in the lung, liver, bone, and lymph nodes.
4.2. Genetic Analysis
Genomic DNA samples were extracted from 10 mL of ethylenediaminetetraacetic acid
(EDTA)-treated peripheral blood samples using the Nucleosopin Blood Mini Kit (MACHEREY–NAGEL GmbH & Co. KG, Düren, Germany) according to the manufacturer’s instructions.
The following seven genes were analysed: MAX (NM_002382.5), SDHB (NM_003000.3), SDHC
(NM_003001.5), SDHD (NM_003002.4), TMEM127 (NM_017849.4), VHL (NM_000551.3), andexons 10, 11 and 13–16 of the RET (NM_020630.4) proto-oncogene. A priority order was used
for genetic analysis according to previous recommendations [5,6]. For instance, VHL and
RET genes were analysed with priority for bilateral PCC, SDHB gene for retroperitoneumPGL or metastatic PCC/PGL, and SDHD gene for head and neck PGL. When a pathogenic
variant was found in one of these genes, no further testing was performed in the remaining
genes. After performing PCR using gel electrophoresis for each primer pair, Sanger sequencing was outsourced to a commercial service provider (Eurofins Genomics, Ota-ku, Tokyo,
Japan) to detect variants, and the results were analysed at our department. The primers
used for the PCR amplification are listed in Table S5. When no P/LP variant was foundby the Sanger sequencing, all exons of the SDHB, SDHC, and SDHD gene were reanalysedusing multiplex ligation-dependent probe amplification (MLPA) to examine copy number
variation. The MLPA assay was carried out by a commercial service provider (FALCO Biosystems Ltd., Kumiyama, Kyoto, Japan). The sequence results were analysed using Sequence
Scanner Software v2.0 (Thermo Fisher Scientific, Waltham, MA, USA) and CLC Sequence
Viewer 8.0 software (QIAGEN, Aarhus C, Denmark).
4.3. Variant Classification
ACMG/AMP guidelines were used to classify variant pathogenicity [29]. The detectedvariations were assessed for pathogenic potential using the following in silico tools: Rare
Exome Variant Ensemble Learner (REVEL) (https://sites.google.com/site/revelgenomics/
downloads, accessed on 21 May 2021), and Human Splicing Finder(https://www.genomnis.com/access-hsf, accessed on 21 May 2021). REVEL is a recently
developed in silico variant meta-predictor, which scores rare missense variants on a scaleranging from 0 to 1, with higher scores indicating a greater likelihood of being a diseasecausing variant [44]. While REVEL does not suggest a strict threshold for variant categorisation, a score above 0.5 was used for supporting pathogenic variants (ACMG/AMP
codes; PP3) with reference to the previously reported criteria [47]. Human Splicing Finder
provides information on changes in scores caused by splice site variants in donor andacceptor sites. A reduction of >10% in the predicted score was used as the pathogenic
variant in accordance with the original article [48]. Reported interpretations for known
variants were obtained through the disease databases such as Human Gene Mutation
Database (HGMD) (accessed on 20 May 2021) (http://www.hgmd.cf.ac.uk/ac/index.php;
accessed on 20 May 2021) and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/; accessedon 20 May 2021). In addition, genome aggregation database (gnomAD v3.1.1 (non-cancer);Cancers 2021, 13, 4014

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https://gnomad.broadinstitute.org/, accessed on 10 June 2021) and Japanese Multi Omics
Reference Panel (jMorp; Genome variation 8.3K JPN (v20200831); https://jmorp.megabank.
tohoku.ac.jp/202102/variants, accessed on 10 June 2021) were used as the population
database for the estimation of mutant allele frequency (MAF). Only annotated variants with
MAF < 0.01 in the gnomAD v3.1.1 (non-cancer) database was retained. All variants absent,
or extremely rare, (MAF ≤ 0.00002) in both gnomAD and jMorp were encoded as PM2
in ACMG/AMP. Frameshift, nonsense, deletion of exon(s), and canonical splicing-sitechange were grouped as protein-truncating variants (Table S4).
4.4. Statistical Analysis
All data were analysed using the SPSS Statistics Version 26 software (IBM Japan Ltd.,
Chuo-ku, Tokyo, Japan). Data are reported as mean ± S.D., actual numbers, or percentages.
Categorical variables were presented as frequency counts and percentages. Comparisonof categorical data was performed using the chi-squared test or Fisher’s exact test as appropriate. For data with normal distributions, between-group differences were analysed using
the Student’s t-test or one-way analysis of variance (ANOVA). For statistical comparisonof nonnormally distributed data, Kruskal–Wallis tests were used. In all statistical tests, twosided testing was used, and a p value of less than 0.05 was considered statistically significant.
For multiple comparisons, Bonferroni’s correction was used to adjust the critical p-value.
5. Conclusions
In this first large-scale examination of the Japanese PPGL cohort, almost a quarterof patients with apparently sporadic PPGL harboured germline variants. This study
reinforces the recommendation in Western guidelines to perform genetic testing for PPGLand genotype-based clinical decision-making in the Japanese population.
Supplementary Materials: The following are available online at https://www.mdpi.com/article/10.3390/cancers13164014/s1, Table S1: Frequency of germline variants according to the presentation;
Table S2: Frequency of germline variant according to the age at diagnosis; Table S3: Comparisonof clinical characteristics based on the presence of germline variants and tumour site in probands with
PPGL; Table S4: Comparison of clinical characteristic between truncating vs. missense variants in SDHB
and SDHD variant-positive probands; Table S5: Primers used for the PCR amplification of genes.
Author Contributions: Conceptualization, K.T. (Kazuhiro Takekoshi); methodology, M.Y., Y.A., T.S.
and K.T. (Kazuhiro Takekoshi); formal analysis, M.Y., K.W. and Y.A.; investigation, M.Y.; resources,
K.T. (Katsutoshi Takahashi), H.S., H.N., M.N., T.O., T.M., S.K., K.H., A.T., A.W., N.K., E.N., A.S., K.S.
and K.T. (Kazuhiro Takekoshi); data curation, M.Y. and Y.A.; writing—original draft preparation,
M.Y.; writing—review and editing, K.W., T.S., K.T. (Katsutoshi Takahashi), M.N., A.W., N.K. and K.T.
(Kazuhiro Takekoshi); visualization, M.Y.; supervision, K.W. and Y.K.; project administration, T.S.,
Y.K. and K.T. (Kazuhiro Takekoshi); funding acquisition, K.T. (Kazuhiro Takekoshi), M.N., H.H., Y.K.
and E.N. All authors have read and agreed to the published version of the manuscript.
Funding: This work was supported in part by Grants-in-Aid from Japan Society for the Promotionof Science (JSPS KAKENHI Grant Numbers 201128060B to M.N.,21591168 to K. Takekoshi, 23591889 to
H.H., 25460671 to Y.K., 16K08961 to Y.K., and 17H04328 to E.N.). The funders had no role in the study
design, data collection and analysis, decision to publish, or the preparation of the manuscript.
Institutional Review Board Statement: The study was conducted according to the guidelinesof the Declaration of Helsinki and approved by the Medical Ethics Committee (approval #119,
date of approval: 5 February 2007) and the Institutional Review Board of the University of Tsukuba
Hospital (approval #H28–134, date of approval: 29 September 2019).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The authors confirm that the datasets analysed during the current
study are available from the corresponding author upon reasonable request.
Acknowledgments: We are grateful to all the patients who participated and the collaborating researchfacilities for providing samples from all over Japan. We would like to thank Sumiko Niisato andCancers 2021, 13, 4014

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Seiko Ono for their technical support. We would also like to thank Masaya Hoshino for help withvariant classification.
Conflicts of Interest: The authors declare no conflict of interest.

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