Original Article

Yonago Acta medica 2016;59:118–125

Clinical Diagnosis of Mendelian Disorders Using a Comprehensive Gene-Targeted
Panel Test for Next-Generation Sequencing
Tetsuya Okazaki,*† Megumi Murata,‡ Masachika Kai,§ Kaori Adachi,‡ Naoko Nakagawa,†‖Noriko Kasagi,†¶
Wataru Matsumura,*† Yoshihiro Maegaki* and Eiji Nanba†‡‖*Division of Child Neurology, Institute of Neurological Sciences, Tottori University Faculty of Medicine, Yonago 683-8504, Japan, †Division of Clinical Genetics, Tottori University Hospital, Yonago 683-8504, Japan, ‡Division of Functional Genomics, Research Center
for Bioscience and Technology, Tottori University, Yonago 683-8503, Japan, §Division of Technical Department, Tottori University,
Yonago 683-8503, Japan, ‖ Center for Promoting Next-Generation Highly Advanced Medicine, Tottori University Hospital, Yonago 6838504, Japan and ¶ Department of Fundamental Nursing, School of Health Science, Tottori University Faculty of Medicine, Yonago 6838503, Japan

ABSTRACT

Key words

Backgroundcandidate gene analyses; diagnosis
high-throughput DNA sequencing

Corresponding author: Tetsuya Okazaki, MD
t-okazaki@med.tottori-u.ac.jp
Received 2016 February 29
Accepted 2016 March 15
Abbreviations: BAM, binary formats; BWA, Burrows-Wheeler
Aligner; CGH, comparative genomic hybridization; FISH, fluorescence in situ hybridization; HGMD, Human Gene Mutation Database; HGVD, Human Genetic Variation Database; ID, intellectual
disability; NGS, next generation sequencing; WES, whole-exome
sequencing; WGS, whole-genome sequencing

Traditional genetic diagnosis requires the recognition ofcharacteristic patterns of signs or symptoms to guide targeted genetic testing for the confirmation of diagnoses.
Because genetic diagnoses are often difficult, even forexperienced clinicians, the traditional approach for diagnosing patients with suspected genetic disorders is on
the threshold of a paradigm shift due to next-generation
sequencing (NGS). Whole-exome sequencing (WES)
was first used in 2010 to identify causative genes of a
Mendelian disease1 and is rapidly becoming an attractive
tool for diagnostic testing in general medical genetics.
Typical exomes contain more than 30,000 variants
compared with human reference sequences and approximately 10,000 of these represent nonsynonymous aminoacid substitutions, alterations of conserved splice site
residues, or small insertions or deletions.2 Thus, subsequent steps are required to determine the significanceof mutations by identifying benign variants, and genetic
diagnoses using NGS remain challenging.
NGS is performed by sequencing small DNA fragments, and the sequenced “reads” can be 25–100 bps
from one or both ends. The massive capacity of NGS allows sequencing of multiple randomly overlapping DNA
fragments. Therefore, all nucleotides in targeted regions
may be included in many reads, allowing repeated analysis and depth of coverage. Increased depth of coverage
usually improves sequencing accuracy and has a major
influence on the performance of targeted capture for
NGS.3
Although NGS is becoming an important tool for
genetic diagnosis, whole-genome sequencing (WGS)and WES remain expensive, and the volume of information obtained hampers interpretation of the results. Recently, target gene capture sequencing using gene panels
has been applied to genetic diagnoses.2, 4 In particular,
restricted target gene sequencing has high sequencing
accuracy and deep achievable coverage of targeted

Genetic diagnoses provide beneficial information to patients and families. However, traditional
genetic diagnoses are often difficult even for experienced clinicians and require recognition of characteristic
patterns of signs or symptoms to guide targeted genetic
testing for the confirmation of diagnoses. Next-generation sequencing (NGS) is a powerful genetic diagnostic
tool. However, whole-genome and whole-exome sequencing (WES) are expensive, and the interpretation of
results is difficult. Hence, target gene capture sequencingof gene panels has recently been applied to genetic diagnoses. Herein, we demonstrate that targeted sequencing
approaches using gene panel testing are highly efficientfor the diagnosis of Mendelian disorders.
Methods NGS using TruSight one gene panel was
performed in 17 families and 20 patients, and we developed a bioinformatic pipeline at our institution for
detecting mutations.
Results We detected causative mutations in 6 of 17(35%) families. In particular, 11 (65%) families had
syndromic diagnosis and 6 (35%) had no syndromic
diagnosis before NGS testing. The number of positive
diagnoses was 5 of 11 (45%) in the syndromic group andwere 1 of 6 (17%) among patients of the no syndromic
diagnosis group.
Conclusion Diagnostic yields in the present study
were higher than in previous reports of genetic and chromosomal tests and WES. The present comprehensive
gene-targeted panel test is a powerful diagnostic tool for
Mendelian disorders.

118Clinical diagnosis using NGS

genes, giving rise to significant cost saving and feasible
data sets for bioinformatic analyses that are functionallyinterpretable.3 The present study demonstrates that atargeted sequencing approach using gene panel testing ishighly efficient for the diagnosis of Mendelian disorders.

ditionally, we explained that only genes related to thepatient’s present symptoms would be investigated in thisclinical study. Peripheral-blood samples were provided
in all cases, and clinical data were collected from medical records. The study was approved by the ethics committee at the Tottori University (dated September 22,
2014, approval number G152).

SUBJECTS AND METHODS
Subjects

Patients were recruited for targeted gene testing from
October 2014 through September 2015 at the Tottori
University Hospital. Patients were divided into twogroups of syndromic diagnoses and no syndromic diagnoses. The syndromic diagnosis group comprised
patients who received specific diagnoses such as Sotos
syndrome, Joubert syndrome, and Neuro-fibromatosis
type 1. The no syndromic diagnosis group included patients with no specific diagnoses of epilepsy, polydactyly, or intellectual disability (ID), among others (Tables 1
and 2).
Tests were performed after patients were informedof the risks and benefits and provided written informed
consent. Informed written consent was obtained fromadult subjects and parents of children. Each patient was
informed about incidental findings, which were definedas conditions unrelated to the present symptoms. Ad-

Table 1. Clinical Characteristics of 17 families,
20 patients
Cohort (n = 20)
GenderMale
FemaleAge (years old)
0–10
10–20
> 20
Group (n = 17)
Syndromic diagnosis (family: n = 17)
No syndromic diagnosis
Previous exploration
Array CGH
Karyotype
CGH, comparative genomic hybridization.

12
8
13
3
4
11
6
1
12

Table 2. List of all patients in our study
Group Genetic Family history
diagnosis

Sex

Age

Phenotype

F1
F2
F3
F4
F5
F6

M
F
F
M
F
F

1 year 11 months Joubert syndrome
2 years
Epilepsy, Macrocephaly, ID
4 years
Sotos syndrome
6 years
Sotos syndrome
31 years
Nonsyndromic hearing loss
47 years
Neurofibromatosis type 1

S
N
S
S
S
S

AHI1
FGFR3
NSD1
NSD1
WFS1
NF1

F7

F

10 months

S

ND

F8

M

2 years

Hydranencephaly

Genetic testnone
G-bandNSD1 gene, G-band
none
none
FISH
none
FISH
none
none
none
none
SisterG-band(hydranencephaly)none
G-bandID
N
ND
Polydactyly,
Congenital
heart
disease,F9-1 F
3 yearsN
ND
Brother (F9-2)
G-bandCraniosynostosis, ID
F9-2 M
5 years
Hydrocephaly, polydactyly
N
ND
Sister (F9-1)
G-band, Array CGH
F10 M
5 years
Leigh syndrome
S
ND
None
mt-DNA
F11-1 M
6 years
Joint hyperextension, ID
N
ND
Brother (F11-2, 3) none
F11-2 M
9 years
Joint hyperextension, ID
N
ND
Brother (F11-1, 3) none
F11-3 M
12 years
Joint hyperextension, ID
N
ND
Brother (F11-1, 2) none
Nemo gene
F12 M
7 years
Anhidrotic ectodermal dysplasia
S
ND
None
F13 M
7 years
ID
N
ND
None
G-bandF14 M
10 years
Congenital disorders of glycosylation
S
ND
None
G-bandCyclic vomiting, peripheral neuropathy, N
F15 F
13 years
ND
None
G-band, mt-DNA
ID
Arrhythmogenic right ventricular cardioF16 M
42 yearsS
ND
Father and Sisternone
myopathy
Progressive Familial Intrahepatic
F17 F
63 years
S
ND
None
none
Cholestasis
AHI1, abelson helper integration site 1; CGH, comparative genomic hybridization; F, female; FGFR3, fibroblast growth factor receptor
3; FISH, fluorescence in situ hybridization; ID, intellectual disability; M, male; N, non clinical diagnosis group; ND, not detective; NF1,
neurofibromatosis type 1; NSD1, nuclear receptor binding SET domain protein 1; S, syndromic diagnosis group; WFS1, wolframin ER
transmembrane glycoprotein.

119

T. Okazaki et al.

Library preparation and Sequencing

large reference genomes, such as the human genome.
Variant calling and assembly of variant files were performed using standard procedures with software such as
SAMtools, genome analysis toolkit, and picard, which
produce binary formats (BAM) from raw data. Variant filtering was performed using SnpEff and SnpSift
software, which collects variant-specific informationaccording to predicted pathogenicity (putative effects onprotein, conservation scores, splice site predictions, andallelic frequencies in all patients, and in control cohorts
such as the variant databases, Human Genetic Variation
Database (HGVD), GWAS, and dbSNP. The HGVD is
a Japanese mutation database. Additionally, to narrowcandidate variants, we prepared a list of candidate genes
for each symptom and clinical diagnosis (Table 3).
Candidate variants were selected when harboring afrequency that was compatible with the incidence of thedisease and expectedly accounted for less than 1%. Variants with suboptimal quality scores were removed from

Genomic DNA was extracted from peripheral-blood
samples. Targeted resequencing was performed using
TruSight One sequencing panels (Illumina, San Diego,CA), which included 4,813 genes that are associated withknown clinical phenotypes. TruSight one sequencing
panels contain all the reagents required for amplification, amplicon enrichment, and indexing of samples, andprocedures were performed according the manufacturer’s instructions. After constructing the sequence library,a MiSeq next-generation sequencer (Illumina) was used
to sequence 152-bp paired-end reads.
Bioinformatic pipeline and variant ranking

A bioinformatic pipeline was constructed in our institution to detect mutations (Fig. 1). Extracted data were
mapped to a reference genome (GRCh37/hg19) using a
Burrows-Wheeler Aligner (BWA). BWA is a software
package for mapping low-divergent sequences against4813	
  gene	  targeted	
  Sequencing	
  Syndromic	
  diagnosis	  or	
  phenotype

Iden:ﬁed	
  variants

Candidate	
  genes	  sequencing

Frequency	
  <	
  1%	
  

Nonsynonymous?

Yes

Yes

In	
  muta:on	
  data	  base?

No

Yes

Informa:on	
  from	  another	
  reports
No

Yes

Predicted	
  to	
  be	
  pathogenic?
Sanger	  sequencing

Diagnosis

Yes
Candidate	
  muta:onNoNo	
  diagnosis

Fig. 1. Flowchart for bioinformatic analyses.
Targeted resequencing was performed using a TruSight One sequencing panel (Illumina, San Diego, CA), which includes 4,813 genes.
Data were mapped to a reference genome (GRCh37/hg 19), and variant calling using the bioinformatic pipeline was constructed in our facility. Variant filtering was performed using predicted pathogenicities and frequencies according to several mutation databases. Finally, weused the list of candidate genes to narrow candidate variants. In cases of the variant that were predicted to be pathogenic, we detected thevariant as a candidate mutation, and all candidate mutations were validated using Sanger sequencing.

120

Clinical diagnosis using NGS
Table 3. Overview of gene list of our method
Brain malformation
Hereditary hearing
loss

Epilepsy

Hereditary sensory
and autonomic
neuropathy
Intellectual disability

ARFGEF2 ARX DCX EOMES FKRP FKTN FLNA GPR56 LAMC3 LARGE NDE1 OCLN PAFAH1B1
POMGNT1 POMT1 POMT2 PQBP1 RELN SRPX2 TUBA1A TUBA8 TUBB2B TUBB3 VLDLR
ACTG1 BSND CCDC50 CDH23 CHRN CLDN14 COCH COL11A2 DFNA5 DFNB59 DIAPH1 DSPP
ESPN ESRRB EYA4 FAM189A2 GJB2 GJB3 GJB6 GPSM2 GRHL2 GRXCR1 HGF KCNQ4 LHFPL5
LOXHD1 LRTOMT MARVELD2 MIR96 MYH14 MYH9 MYO15A MYO1A MYO3A MYO6 MYO7A
OTOA OTOF P2RX2 PCDH15 POU3F4 POU4F3 PRPS1 PTPRQ RDX SIX1 SLC17A8 SLC26A4SLC26A5 SMPX STRC SYNE4 TECTA TJP2 TMC1 TMIE TMPRSS3 TPRN TRIOBP USH1C WFS1
ALDH7A1 ARFGEF2 ARHGEF9 ARX ATP1A2 ATP2A2 ATP6AP2 ATP6V0A2 ATRX CACNA1ACASK CASR CCDC88C CDKL5 CHRNA2 CHRNA4 CHRNB2 CLCNKA CLCNKB CLN3 CLN5
CLN6 CLN8 CNTNAP2 VPS13B COL18A1 COL4A1 CPT2 CSTB CTSD CUL4B OFD1 DCX DEPDC5 DNAJC5 EFHC1 EMX2 EPM2A FGD1 FGFR3 FKRP FKTN FLNA FOXG1 GABRA1 GABRB3GABRD GABRG2 GPC3 GPR56 GRIA3 GRIN2A HSD17B10 KDM5C KCNA1 KCNJ1 KCNJ10 KCNMA1 KCNQ2 KCNQ3 KCNT1 KCTD7 KIAA1279 LAMA2 LARGE LBR LGI1 MBD5 ME2 MECP2MEF2C MFSD8 MLL2 NHLRC1 NIPBL NOTCH3 NRXN1 OPHN1 PAFAH1B1 PAK3 PANK2 PAX6
PCDH19 PEX7 PHF6 SERPINI1 PIGV PLA2G6 PLP1 PNKP POLG POMGNT1 POMT1 POMT2
PPT1 PQBP1 PRICKLE1 PRICKLE2 PRRT2 RAB39B RAB3GAP1 RAI1 RELN RNASEH2A RNASEH2B RNASEH2C SAMHD1 SCARB2 SCN1A SCN1B SCN2A SCN8A SCN9A SETBP1 SLC25A22
SLC2A1 SLC4A10 SLC9A6 SMC1A SMC3 SMS SNAP29 SPTAN1 SRPX2 STXBP1 SYNGAP1 SYPTBC1D24 TBX1 TCF4 TPP1 TREX1 TSC1 TSC2 TUBA1A TUBA8 TUBB2B UBE3A VPS13A WDR62
ZEB2
ATL1 CCT5 DNMT1 FAM134B HSN2 IKBKAP KIF1A NGFB NTRK1 RAB7 SCN9A SPTLC1SPTLC2 WNK1
ABCC9 ABCD1 ABCD4 ABHD5 ACAD9 ACO2 ACOX1 ACSF3 ACSL4 ACTB ACTG1 ACVR1 ADARADCK3 ADSL AFF2 AGA AGPAT2 AGTR2 AHCY AHI1 AIFM1 AIMP1 AK1 AKT3 ALDH18A1
ALDH3A2 ALG1 ALG12 ALG13 ALG2 ALG3 ALG6 ALG9 AMT ANKH ANKRD11 ANO10 AP1S2
AP3B1 AP4B1 AP4E1 AP4S1 APTX ARFGEF2 ARHGEF6 ARHGEF9 ARID1A ARID1B ARL13B
ARL6 ARX ASB11 ASL ASPA ASPM ASXL1 ATP1A2 ATP2A2 ATP6AP2 ATP6V0A2 ATR ATRXAUH B3GALTL B4GALT1 B4GALT7 BBS1 BBS10 BBS12 BBS2 BBS4 BBS5 BBS7 BBS9 BCKDHABCKDHB BCOR BCS1L BIVMERCC5 BLM BRAF BRWD3 BSCL2 BUB1B C5orf42 CA2 CACNA1CCACNG2 CASK CC2D1A CC2D2A CCBE1 CCDC78 CDH15 CDK5RAP2 CDKL5 CDON CENPJ
CEP135 CEP152 CEP290 CEP41 CHD7 CHKBCPT1B CNTNAP2 COG1 COG7 COG8 COL4A1
COL4A2 COLEC11 COQ2 COX15 CRBN CREBBP CTDP1 CTNNB1 CUL4 CYB5R3 D2HGDH DBT
DCX DDHD2 DDX26B DHCR24 DHCR7 DHFR DHTKD1 DIP2B DKC1 DLD DLG3 DMD DMPKDNAJC19 DNMT3B DOCK8 DPAGT1 DPM1 DPYD DYM DYNC1H1 DYRK1A EFTUD2 EHMT1
EIF2AK3 ELOVL4 EMX2 ENOX2 EP300 EPB41L1 ERCC2 ERCC3 ERCC6 ERLIN2 ESCO2 ETHE1FANCB4 FANCD2 FAM120C FBN1 FGD1 FGFR2 FGFR3 FH FKRP FKTN FLNA FMR1 FOXG1
FOXP1 FRAS1 FTO FTSJ1 FUCA1 GAD1 GALE GALT GAMT GATAD2B GATM GCH1 GCSH
GDI1 GFAP GJC2 GK GLDC GLI3 GNAS GNPAT GNS GPC3 GPHN GPM6B GPR56 GRIA3
GRIK2 GRIN1 GRIN2A GRIN2B GSS GTF2H5 GUCY2F GUSB HAX1 HCCS HCFC1 HDAC4
HDAC8 HESX1 HLCS HOXA1 HPD HPRT1 HRAS HSD17B10 IDS IDUA IER3IP1 IGF1 IKBKG
INPP5E IQSEC2 ISPD JAM3 KANSL1 KAT6B KCNJ11 KCNK9 KCNQ2 KCNT1 KCTD7 KDM5C
KDM6A KIAA1279 KIF11 KIF7 KIRREL3 KLHL13 KMT2D KRAS KRBOX4 L1CAM L2HGDH
LAMA2 LAMC3 LAMP2 LARGE LARP7 LIG4 LRP2 LRPPRC MAGT1 MAN1B1 MANBA MAOA
MAP2K1 MAP2K2 MAT1A MBD5 MCCC1 MCCC2 MCOLN1 MCPH1 MECP2 MED12 MED17
MED23 MEF2C MGAT2 MID1 MKKS MLYCD MMAA MMACHC MMADHC MOCS1 MOCS2
MPDU1 MPLKIP MRPS22 MTR MTRR MUT MVK MYO5A NAA10 NAGA NAGLU NBN NDE1
NDP NDUFA1 NDUFA11 NDUFA12 NDUFS1 NDUFS2 NDUFS3 NDUFS4 NDUFS7 NDUFS8NDUFV1 NEU1 NF1 NHS NIPBL NKX2-1 NLGN3 NLGN4 NLGN4X NLRP3 NPHP1 NRXN1 NSD1NSDHL NSUN2 NTRK1 OCRL OFD1 OPHN1 ORC1 PACS1 PAFAH1B1 PAK3 PANK2 PAX6 PC
PCDH19 PCNT PDHA1 PDSS1 PDSS2 PDZB11 PEPD PEX1 PEX10 PEX11B PEX13 PEX26 PEX5
PEX7 PGK1 PHF6 PHF8 PHGDH PIGN PIGO PIGV PIK3R2 PLCB1 PMM2 PNKP PNP POC1A
POLR3A POLR3B POMGNT1 POMT1 POMT2 PORCN PPOX PQBP1 PRODH PRPS1 PRSS12PTCH1 PTCHD1 PTEN PTPN11 PUS1 PVRL1 PYCR1 RAB18 RAB27A RAB39B RAB3GAP1 RAB3GAP2 RAB40AL RAD21 RAF1 RAI1 RARS2 RELN REPS2 RFT1 RMND1 RNASEH2A RNASEH2B
RNASEH2C ROGDI RPGRIP1L RPS6KA3 SALL1 SATB2 SC5D SCN1A SCN2A SCN8A SCO2 SDHASERAC1 SETBP1 SHH SHOC2 SHROOM4 SIL1 SIX3 SKI SLC12A6 SLC16A2 SLC17A5 SLC25A15
SLC25A22 SLC2A1 SLC35C1 SLC4A4 SLC6A8 SLC9A6 SMAD4 SMARCA2 SMARCA4 SMARCB1SMC1A SMC3 SMCX SMOC1 SMPD1 SMS SNAP29 SOBP SOS1 SOX10 SOX2-OT SOX3 SPRED1
SRCAP SRD5A3 SRPX2 ST3GAL3 STIL STRA6 STXBP1 SUOX SURF1 SYNGAP1 SYP SYN1 SYT14TAT TBC1D24 TBCE TBX22 TCF4 TECR TGFBR1 TGFBR2 THRB TIMM8A TMCO1 TMEM165
TMEM231 TMEM237 TMEM67 TRAPPC9 TREX1 TRPC5 TSC1 TSC2 TSPAN7 TTC8 TUBA1A
TUBB2B TUSC3 UBE2A UBE3A UBR1 UPB1 UPF3B VPS13B WDR62 XPA ZDHHC9 ZEB2 ZIC2
ZNF41 ZNF592 ZNF674 ZNF711 ZNF81

121

T. Okazaki et al.
Leigh syndrome

Progressive familial
intrahepatic cholestasis
Macrocephaly
Skeletal dysplasia

Congenital Disordersof Glycosylation

Joubert syndrome
Hypohydrotic Ectodermal dysplasia
Arrhythmogenic
Right Ventricular
Dysplasia

BCS1L C12orf65 COX10 COX15 EARS2 ECHS1 FARS2 FOXRED1 GFM1 HIBCH LRPPRC MTFMT
MT-ATP6 MT-ND1 MT-ND2 MT-ND3 MT-ND4 MT-ND5 MT-ND6 MT-TK MT-TV MT-TW NDUFA1 NDUFA9 NDUFA10 NDUFA11 NDUFA2 NDUFA4 NDUFAF2 NDUFAF5 NDUFAF6 NDUFS1NDUFS2 NDUFS3 NDUFS4 NDUFS7 NDUFS8 NDUFV1 PET100 PDHA1 PDHB PDSS2 POLG
SCO2 SDHA SDHAF1 SERAC1 SUCLA2 SUCLG1 SURF1 TACO1 TTC19 UQCRQ
ATP8B1 ABCB11 ABCB4 TJP2
ASPA BRAF CA2 CDKN1C CLCN7 D2HGD FGFR3 FMR1 GCDH GFAP GPC3 HEXA HRAS IDSIDUA KRAS L1CAM LRP5 MEK1 MEK2 MLC1 NF1 NSD1 OSTM1 PLEKHM1 PTEN PTPN11
RAF1 SOS1 TCIRG1 TNFSF11 VG5Q
ACAN ACVR1 ADAMTS10 ADAMTSL2 AGPS ALPL ALX4 ANKH ARSE BMPR1B CA2 CASR
CHST3 CLCN7 COL10A1 COL11A1 COL11A2 COL1A1 COL1A2CRTAP COL2A1 COL9A1 COL9A2
COL9A3 COMP CRTAP CTSK CUL7 CXORF5 DDR2 DHCR24 DHPAT DLL3 DLX3 DTDST DYM
DYNC2H1 EBP EFNB EIF2AK3 ESCO2 EVC1 EVC2 EXT1 EXT2 FBN1 FGF10 FGF23 FGF9
FGFR1 FGFR2 FGFR3 FLNA FLNB GDF5 GDF5COMP GJA1 GLI3 GNAS1 HOXA11 HOXD13
HSPG2 IFT80 IHH IKBKG LBR LEMD3 LEPRE LFNG LIFR LMBR1 LMNA LMX1B LRP5 MATN3
MESP2 MGP MMP13 MMP2 MSX2 NEMO NOG NPR2 OSTM1 P63 PAPSS2 PCTN2 PEX7 PHEX
PLOD2 POR PPIB PTHR1 RANKL RECQL4 RMRP ROR2 RUNX2 SALL1 SALL4 SBDS SCYL1BP1
SEDL SHH SHOX SLC34A3 SMARCAL1 SOST SOX9 TBCE TBX15 TBX3 TBX4 TBX5 TBXAS1TCIRG1 TGFB1 TMEM16E TNFRSF11A TNFRSF11B TNFSF11 TP63 TRIP11 TRPS1 TRPV4 TWIST1
WISP3 WNT3 WNT7A ZMPSTE24
ALDH18A1 ALDOB ALG1 ALG11 ALG12 ALG13 ALG2 ALG3 ALG6 ALG8 ALG9 ATP6V0A2
B3GALTL B3GNT1 B4GALT1 BSCL2 CACNA1C CANT1 CDH3 CEP290 CHRNE CHST14 CHSY1
CNTN4 COG1 COG4 COG5 COG6 COG7 COG8 COL1A1 COL1A2 CSF2RA DAG1 DDOST DOLKDPAGT1 DPM1 DPM2 DPM3 EIF2AK3 F13A1 FBN1 FBN2 FGA FGF10 FGFR1 FGG FKRP FKTNG3GALNT2 G6PC3 GARS GDNF GFPT1 GH1 GMPPB GPR143 GPR98 IFNGR1 IFNGR2 IL12B
IL12RB1 ISPD ITGB2 JAM3 LARGE LHCGR LMNA LRP2 LRP5 MBTPS2 MGAT2 MOGS MPDU1
MPI MYOC NEU1 NGLY1 NRXN1 NTRK2 P2RX1 PDE4D PGM1 PIGN PKD1 PKHD1 PMM2
PMP22 POMGNT1 POMGNT2 POMT1 POMT2 PRKAG2 PSAP PYCR1 RELN RET RFT1 RHORNASET2 RPGR SEC23B SERPINA7 SERPINC1 SGK196 SHH SI SIL1 SLC10A2 SLC26A4 SLC35A1
SLC35A2 SLC35C1 SLC4A1 SLC4A11 SLC5A7 SPINK5 SPINT2 SRD5A1 SRD5A3 STAT1 STT3A
STT3B SYNE1 TGFBR1 TMEM15 TMEM165 TMEM5 TSHR TYR VPS45A VWF WFS1
AHI1 ARL13B C5orf42 CC2D2A CEP290 (NPHP6) CEP41 INPP5E KIF7 NPHP1 OFD1 RPGRIP1L
TCTN1 TCTN2 TCTN3 TMEM138 TMEM216 TMEM231 TMEM237 TMEM67 (MKS3)EDA EDAR EDARADD
DSC2 DSG2 DSP JUP PKP2 RYR2 TGFB3 TMEM43

RESULTS

consideration. Remaining variants were compared computationally with the list of reported mutations from the
Human Gene Mutation Database (HGMD). Variants inthis database with minor allele frequencies of less than
1% according to either HGVD were retained. Variants
that are not described in the HGMD, including synonymous variants, intronic variants that were more than 5
bp from exon boundaries (unlikely to affect messenger
RNA splicing), and common variants (minor allele frequency, > 1%) were also discarded.

Patient characteristics

Detailed clinical phenotypes of 17 families and 20 patients are provided in the clinical descriptions of patient
section in Table 2. Subjects that were submitted to theclinical laboratory for targeted gene testing were primarily pediatric patients. Clinical characteristics are presented in Table 1 and include 13 children younger than
10 years (59%), 3 children and adolescents from 10 to 20
years of age (18%), and 4 adults older than 20 years (24%;
Table 1). Office settings of the ordering physicians wereas follows: pediatrics (13 families), cardiology (1 family), and gastroenterology (1 family). A total of 11 (65%)
families had syndromic diagnoses and 6 (35%) families
had no syndromic diagnoses. Samples were available
from both parents for five families. The majority of patients had phenotypes that were related to intellectual

Mutation validation

All candidate mutations were validated by Sanger sequencing, and co-segregation analyses were performed
when possible.

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Clinical diagnosis using NGS
Table 4. Overview of sequencing data of our method
DupliUnRead
Median Mean
Fam- Raw reads mapped mapped cate
> 1x
cover- cover- (%)
ily
reads
reads (%)
age
age
(%)

> 10x
(%)

> 20x
(%)

> 40x
(%)

EXON
EXON
Variant
Variant
EXON
Variant
variant
Variant variant (freq < (freq < (freq < (freq <
0.05)
0.01)
0.05)
0.01)

1

13324086

2602

99.98

3.23

40

43.69

98.73

89.62

76.53

48.74 26423

7080

4057

943

3297

691

2

9625914

1978

99.98

5.74

27

30.86

97.47

83.55

64.3

26.75 24607

7045

3751

927

3048

672

3

12116082

1956

99.98

14.05

36

43.65

97.5

86.14

72.03

44.71 23864

6910

4132

1020

3509

775

4

12164432

3055

99.97

3.17

37

41.06

98.9

89.67

75.27

44.97 27983

7300

3999

950

3339

729

5

9980608

2009

99.98

5.55

28

31.86

97.68

84.48

65.79

28.36 25371

6975

3750

902

3134

680

6

14588198

4130

99.97

3.46

42

46.15

98.41

90.33

78.48

52.48 28846

7241

4553

1053

3826

799

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disabilities (40%), and 13 of 20 patients had received
chromosomal or other genetic tests, such as array comparative genomic hybridization (CGH) and fluorescencein situ hybridization (FISH) analysis.
The median sequence coverage was 27.5, and an averageof 84% of all targeted exons was covered by at least 10
sequence reads (Table 4). Approximately, 15,000–37,000
single-nucleotide variants and small insertion and deletion changes were identified in each patient’s personal
genome by comparison with the current reference haploid human genome sequence (GRCh37/hg 19). Afterremoving low-frequency variants and synonymous
variants, an average of 742 exon variants per sample wasanalyzed for the 20 samples. No cases of detected causative genes showed false positives when confirmed bySanger sequencing.

(17%) of those in the no syndromic diagnosis group. We
detected certainly causative mutations in 6 of 17 (35%)
families, including five families with autosomal dominant diseases and one with autosomal recessive disease.
All five mutations of autosomal dominant diseases were
described in HGMD (Table 5). Due to the absence ofconsent, parental studies were not performed in all five
families, and one autosomal recessive family demonstrated compound heterozygosity of two distinct mutations. Nonetheless, parental studies indicated that patients inherited mutant alleles from each carrier parent,
and both mutations were not present in HGMD. The c.841
G > T mutation causes a stop codon. At the c. 2015 C >T mutation, the prediction of function using Polyphen2
shows probably damaging. Additionally, this mutation
was detected in two cases of Joubert syndrome at ourfacility, and both mutations were confirmed by Sanger
sequencing.

Diagnosis based on target resequencing

DISCUSSION

Positive diagnoses were observed in 5 of 11 (45%) patients of the syndromic diagnosis group and in 1 of 6

Patient characteristics

Sequencing data and false-positive calls for SNVs

Certainly causative mutations were detected in 6 of 17123

T. Okazaki et al.
Table 5. Summary of disease-causing mutations in 6 clinical cases
Age, y Gene

Mutation

References

Inheritance Phenotype

E281X c.841 G > T
In house data, prediction ofAR
Joubert syndrome
T702M c.2105 C > T
function
FGFR3 N540K c.1620 C > A
F2
2
13
AD
Hypochondroplasia
R2117X
NSD1
F3
4
14
AD
Sotos syndromec.6349 C > T
NSD1
F4
6
T2055I c.6164 C > T
15
AD
Sotos syndrome
D797N
WFS1
F5
31
16
AD
Nonsyndromic hearing loss
c.2389 G > A
NF1
F6
47
W2208X c.6623 G > A
17AD
Neurofibromatosis-1
AD, autosomal dominant; AHI1, abelson helper integration site 1; AR, autosomal recessive; FGFR3, fibroblast growth factor receptor 3;
NF1; neurofibromatosis type 1; NSD1, nuclear receptor binding SET domain protein 1; WFS1, wolframin ER transmembrane glycoprotein; y, year(s).
F1

1

AHI1

tests. This patient carried a mutation in the FGFR3 gene,which is associated with hypochondroplasia. Bone dysplasia of this patient was mild and was unnoticed, andclinical diagnosis had been difficult. Thus, informationfrom genetic diagnosis provides benefits for patient andfamilies with genetic disorders and ID.

(35%) families. Among families who received genetic
diagnoses, five in six were syndromically diagnosed
before targeted gene testing. In the cases F2, F3 and F6(Tables 2 and 5), the size of NSD1 and NF1 genes waslarge, and no family history was found. To confirm theabsence of other gene mutations, we used TruSight one
gene panel sequencing instead of Sanger sequencing. In
the case of F1 (Tables 2 and 5), Joubert syndrome has
genetically heterogeneous. Accordingly, 19 genes wereassociated with Joubert syndrome in the OMIM database. Recently, reports of causative genes have increasedin number, and genetic heterogeneity of Mendeliandisorders is more widely understood. Hence, genetic
diagnosis using NGS is more important as a diagnostic
alternate to Sanger sequencing.
In the present study, most cases were children, andonly four cases were adults. ID cases were identified in
6 of 17 families. IDs are common neurodevelopmental
disorders and are reported in 1.5%–2% of children andadolescents.5 Syndromic diagnoses of ID patients are
made according to clinical symptoms but remain difficult even for experienced professional clinicians. However, although most ID disorders lack therapeutic drugs,
understanding of genetic causes can benefit patients andfamilies by providing prognostic information and precluding further unnecessary invasive testing. Moreover,diagnoses often facilitate access to appropriate medical
and supportive care, and family members may benefit
from knowledge of the risks of recurrence counselingand possible prenatal diagnoses.6 In the present study,
physicians performed extensive clinical diagnostic workups on some subjects before ordering gene panel testing,and some of these may have exceeded the time and costof gene panel testing. For example, one patient (F2 inTable 2) had gene panel testing at 2 years of age following evaluation using karyotype analysis, chromosomal
CGH array analysis, and NSD1 single-gene sequencing

Target gene sequencing

Upon applying gene panel testing to genetic diagnosesof 17 families, we observed a molecular diagnostic yieldof 35%, which was higher than the positive rates of other genetic tests, such as karyotype analysis (5%–15%)
and chromosomal microarray analysis (30%).7 A recent
study of diagnostic WES in 250 unselected, consecutive
cases achieved a diagnostic yield of 25%,7 and anotherlarger study of subjects with ID reached a diagnostic
yield of 16%.6 Although comparisons of diagnostic
yields between studies are statistically difficult, the results of the present study show higher rates of definitive
genetic diagnosis than other genetic and chromosomal
tests and WES reports, potentially reflecting testing of
more specific subjects. Accordingly, among 2,000 WES
samples, the molecular diagnosis rate was 36.1% inchildren with specific neurological findings (36.1%).7 In
agreement, the present syndromic diagnostic rate was
45%, whereas that among subjects of the no syndromic
diagnosis group was only 17%.
Genetic diagnosis of patients with certain clinicaldiagnoses and suspected causative genes are limited,
warranting use of disease-restricted targeted gene panel
sequencing, such as cancer panels, hearing loss panels,
and muscular dystrophy panels. Hence, depending on
specialization of facilities, disease-restricted targeted
gene panel sequencing may be sufficient. Conversely,
in facilities with patients carrying various diseases,
multiple-restricted gene panels are required. However,numerous causative genes have been identified for het124

Clinical diagnosis using NGS

erogeneous diseases such as ID. In these cases, a large
number of gene-targeted panels, such as TruSight one
gene panel, may find utility.
Various clinical studies report diagnoses using TruSight one gene panels.9, 10 Accordingly, TruSight one
gene panels target 4813 genes that are potentially associated with known clinical phenotypes. Because genes are
numerous, suspected variants are also numerous, and interpretations of variants remain poorly established. Genetic diagnosis in approximately 35% of our six families
with positive cases was based on disease-related genemutations that were reported in mutation databases andin in-house data. However, most gene mutations that underlie Mendelian disorders remain to be discovered. We
expect that diagnostic rates of gene panel testing will increase with the identification of additional patients who
have mutations in novel candidate genes. Additionally, in
undiagnosed cases, etiological mutations may be locatedin noncoding regions, such as regulatory or deep intronic regions, and copy number variations are currently notdetected by the present gene panel tests.
NGS is used to sequence many randomly overlapping DNA fragments. Moreover, increased depth ofcoverage usually improves sequencing accuracy. In thisstudy, the depth of coverage at 20× was 66% and was
lower than in another report using the Trusight one genepanel.11 Hence, low depth of coverage may influence
sequencing accuracy. Although the necessity for confirmation of Sanger sequencing after NGS has not reachedconsensus, NGS variants with lower coverage of depth
are likely sufficient for confirmation of Sanger sequencing-based diagnoses.12 In this study, we confirmed all
mutations by Sanger sequencing and considered that thisapproach can compensate for the low depth of coverage.
In conclusion, the use of the present gene panel test
to analyze 17 clinical cases yielded diagnoses in 35% ofcases. Hence, large numbers of gene-targeted panel tests
are warranted as diagnostic tests for patients carrying
nonspecific or unusual disease presentations with possible genetic causes and for patients with clinical diagnoses of heterogeneous genetic conditions.

cations of targeted gene capture and next-generation sequencing technologies in studies of human deafness and other genetic disabilities. Hear Res. 2012;288:67-76. PMID: 22269275.
4 Vrijenhoek T, Kraaijeveld K, Elferink M, de Ligt J,
Kranendonk E, Santen G, et al. Next-generation sequencing-based genome diagnostics across clinical genetics centers:
implementation choices and their effects. Eur J Hum Genet.
2015;23:1270. PMID: 26269248.
5 Redin C, Gérard B, Lauer J, Herenger Y, Muller J, Quartier A,
et al. Efficient strategy for the molecular diagnosis of intellectual disability using targeted high-throughput sequencing. J
Med Genet. 2014;51:724-36. PMID: 25167861
6 de Ligt J, Willemsen MH, van Bon BW, Kleefstra T,
Yntema HG, Kroes T, et al. Diagnostic exome sequencing
in persons with severe intellectual disability. N Engl J Med.
2012;367:1921-9. PMID: 23033978.
7 Yang Y, Muzny DM, Reid JG, Bainbridge MN, Willis A,
Ward PA, et al. Clinical whole-exome sequencing for the diagnosis of Mendelian disorders. N Engl J Med. 2013;369:150211. PMID: 24088041.
8 Yang Y, Muzny DM, Xia F, Niu Z, Person R, Ding Y, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312:1870-9. PMID: 25326635.
9 Dello Russo C, Di Giacomo G, Mesoraca A, D’Emidio L,
Iaconianni P, Minutolo E, et al. Next generation sequencing
in the identification of a rare genetic disease from preconceptional couple screening to preimplantation genetic diagnosis. J
Prenat Med. 2014;8:17-24. PMID: 25332755.
10 Kato T, Morisada N, Nagase H, Nishiyama M, Toyoshima D,
Nakagawa T, et al. Somatic mosaicism of a CDKL5 mutation identified by next-generation sequencing. Brain Dev.
2015;37:911-5. PMID: 25819767.
11 Yamamoto T, Igarashi N, Shimojima K, Sangu N, Sakamoto Y,
Shimoji K, et al. Use of targeted next-generation sequencing
for molecular diagnosis of craniosynostosis: identification of
a novel de novo mutation of EFNB1. Congenit Anom (Kyoto).
2015. PMID: 26208246.
12 Baudhuin LM, Lagerstedt SA, Klee EW, Fadra N, Oglesbee D,
Ferber MJ. Confirming Variants in Next-Generation Sequencing Panel Testing by Sanger Sequencing. J Mol Diagn.
2015;17:456-61. PMID: 25960255.
13 Bellus GA, McIntosh I, Smith EA, Aylsworth AS, Kaitila I,
Horton WA, et al. A recurrent mutation in the tyrosine kinasedomain of fibroblast growth factor receptor 3 causes hypochondroplasia. Nat Genet. 1995;10:357-9. PMID: 7670477.
14 Tong TM, Hau EW, Lo IF, Chan DH, Lam ST. Spectrum of
NSD1 gene mutations in southern Chinese patients with Sotos
syndrome. Chin Med J (Engl). 2005;118:1499-506. PMID:
16232326.
15 Duno M, Skovby F, Schwartz M. Leukocyte cDNA analysis
of NSD1 derived from confirmed Sotos syndrome patients.
Ann Hum Genet. 2007;71:713-8. PMID: 17561922.
16 Bai X, Lv H, Zhang F, Liu J, Fan Z, Xu L, et al. Identificationof a novel missense mutation in the WFS1 gene as a cause of
autosomal dominant nonsyndromic sensorineural hearing loss
in all-frequencies. Am J Med Genet A. 2014;164A:3052-60.
PMID: 25250959.
17 va n M i n k ele n R , va n B eve r Y, K r o m o s o e t o J N,
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The authors declare no conflict of interest.

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