# Unravelling the Complexity of Inherited Retinal Dystrophies Molecular Testing: Added Value of Targeted Next-Generation Sequencing

Authors: Isabella Bernardis; Laura Chiesi; Elena Tenedini; Lucia Artuso; Antonio Percesepe; Valentina Artusi; Maria Luisa Simone; Rossella Manfredini; Monica Camparini; Chiara Rinaldi; Antonio Ciardella; Claudio Graziano; Nicole Balducci; Antonia Tranchina; Gian Maria Cavallini; Antonello Pietrangelo; Valeria Marigo; Enrico Tagliafico
Journal: BioMed Research International
 (2016)

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## Abstract

To assess the clinical utility of targeted Next-Generation Sequencing (NGS) for the diagnosis of Inherited Retinal Dystrophies (IRDs), a total of 109 subjects were enrolled in the study, including 88 IRD affected probands and 21 healthy relatives. Clinical diagnoses included Retinitis Pigmentosa (RP), Leber Congenital Amaurosis (LCA), Stargardt Disease (STGD), Best Macular Dystrophy (BMD), Usher Syndrome (USH), and other IRDs with undefined clinical diagnosis. Participants underwent a complete ophthalmologic examination followed by genetic counseling. A custom AmpliSeq™ panel of 72 IRD-related genes was designed for the analysis and tested using Ion semiconductor Next-Generation Sequencing (NGS). Potential disease-causing mutations were identified in 59.1% of probands, comprising mutations in 16 genes. The highest diagnostic yields were achieved for BMD, LCA, USH, and STGD patients, whereas RP confirmed its high genetic heterogeneity. Causative mutations were identified in 17.6% of probands with undefined diagnosis. Revision of the initial diagnosis was performed for 9.6% of genetically diagnosed patients. This study demonstrates that NGS represents a comprehensive cost-effective approach for IRDs molecular diagnosis. The identification of the genetic alterations underlying the phenotype enabled the clinicians to achieve a more accurate diagnosis. The results emphasize the importance of molecular diagnosis coupled with clinic information to unravel the extensive phenotypic heterogeneity of these diseases.


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## Body

## 1. Introduction

Inherited Retinal Dystrophies (IRDs) are a heterogeneous group of eye disorders characterized by rod and/or cone photoreceptor cells degeneration, which include Retinitis Pigmentosa (RP), Leber Congenital Amaurosis (LCA), Stargardt Disease (STGD), Best Macular Dystrophy (BMD), and syndromic forms such as Usher Syndrome (USH). The overall prevalence of these disorders is ~1 in 4,000 individuals for RP, ~1 in 90,000 individuals for LCA and USH, ~1 in 5,000–10,000 individuals for STGD, and 1/5000–1/67000 for BMD (http://www.orpha.net). Classification of IRDs considers the principal site of retinal dysfunction (rod, cone, retinal pigment epithelium, or inner retina), the mode of inheritance, the underlying gene defect, typical age of onset, rate of progression, and association with systemic syndromes. The genetic bases of IRDs are highly heterogeneous, with almost 150 genes currently known [RetNet, https://sph.uth.edu/retnet/] and a wide clinical and genetic overlap among the different disorders, with high phenotypic variability and genes associated with more than one phenotype. The inheritance of these diseases is also complex, with autosomal dominant (AD), autosomal recessive (AR), X-linked (XL), and even digenic patterns [1]. The extensive clinical and genetic heterogeneity in IRD, along with the variable age of onset, the incomplete penetrance, and unclear inheritance, hamper clinical diagnosis.Recently, Next-Generation Sequencing (NGS) has been used for the genetic diagnosis of retinal diseases [2–6] and has been reported as a cost-effective approach [7, 8] with a wide range of reported mutation detection rates related to differences in number of genes analyzed, NGS platform, and cohort size but above all composition of the study case phenotypes. We therefore present a multidisciplinary approach coupled with a comprehensive NGS amplicon-based strategy to explore IRD genetic complexity and evaluate genotype-phenotype correlations.


## 2. Patients and Methods

This study was approved by the ethics committee (Comitato Etico di Modena, Modena, Italy). The procedures followed were in accordance with the Helsinki Declaration of 1975, as revised in 2000, and samples were obtained after patients had provided written informed consent.A total of 109 samples were collected, including 88 IRDs affected probands with unknown molecular diagnosis and 21 healthy family members (Table1). Subjects were recruited at the Medical Genetics Unit of the University Hospital of Modena (70 samples), at the Medical Genetics Unit of Parma University Hospital (15 samples) and Medical Genetics Unit of Policlinico Sant’Orsola Malpighi, Bologna (24 samples). All subjects underwent a complete ophthalmologic examination (visual acuity, anterior segment and fundus examination, spectral domain-optical coherence tomography, electroretinogram, and/or electrooculogram) followed by genetic counseling. When indicated fundus autofluorescence imaging and visual field were also performed. Clinical information for the patients with identified pathogenic mutations is shown in Supplementary Table  1 (in Supplementary Material available online at http://dx.doi.org/10.1155/2016/6341870). Clinical diagnoses of participating subjects included RP, USH (hearing impairment + RP), LCA, STGD, BMD, and IRDs not otherwise specified or with imprecisely defined clinical diagnosis. Four control patients with known molecular diagnosis were used to validate our method.Table 1
Patients cohort.
Clinical diagnosis
Number of cases
Healthy relatives
Familiar Cases (number of families)
Presumed inheritance in family
Sex
Age at genetic counseling
Sporadic
AD
AR
XL
M
F
Range
Median
BMD
4
2 (1)
4
1
3
12–65
58
LCA
5
5
1
4
2
3
5–85
9
STGD
14
6 (3)
14
5
9
8–59
28
RP
45
12
9 (4)
14
6
20
5
25
20
2–73
47.5
USH
3
3
2
1
33–53
51
nd IRD
17
4
6 (2)
6
6
5
13
4
2–62
35
Total
88
21
23 (10)
21
16
46
5
48
40
2–85
37
BMD: Best Macular Dystrophy; LCA: Leber Congenital Amaurosis; STGD: Stargardt disease; RP: Retinitis Pigmentosa; USH: Usher syndrome; nd IRD: inherited retinal degeneration not otherwise specified without precisely defined diagnosis; AD: autosomal dominant; AR: autosomal recessive; XL: X-linked; M: male; F: female.


### 2.1. AmpliSeq Panel Design and Ion Torrent™ PGM™ Library Preparation and Sequencing

The Ion AmpliSeq technology (Life Technologies Ltd., Paisley, UK) was used to design a panel of 72 genes (Supplementary Table  2) associated with the following IRD forms: RP, LCA, STGD, BMD, and USH [RetNet,https://sph.uth.edu/retnet/]. The Ion AmpliSeq Designer tool (https://www.ampliseq.com/browse.action) generated an optimized primers design encompassing the coding DNA sequence of the selected genes, for a total of 1.649 amplicons divided into two pools to optimize coverage and multiplex PCR conditions. Libraries were prepared using the Ion AmpliSeq Library Kit 2.0 starting from 15 ng of gDNA/pool according to manufacturer’s recommendations. Template preparation was performed using an Ion OneTouch™ 2 System following the latest version of the manufacturer’s manuals. The template positive Ion Sphere Particles (ISPs+) were sequenced on an Ion Torrent Personal Genome Machine® (PGM) System (Life Technologies Ltd., Paisley, UK) using the Ion 318™ Chip kit v2 following the Ion PGM Sequencing 200 Kit v2 manual.


### 2.2. Sanger Sequencing

Sanger sequencing was performed to validateCNGB1 c.875-5_891dup mutation (identified with an anomalous distribution of NGS reads attributable to amplification problems due to the insertion itself located at the end of the target region) and to sequenceRPGRORF15 partially uncovered by the NGS panel. Primers for PCR and sequencing are shown in Supplementary Table  3. The following conditions were used: a 50 μL PCR reaction containing 100 ng of DNA, 100 pmol of forward and reverse primers, 5 μL of buffer, and 0.5 μL of Taq Expand High Fidelity™ DNA Polymerase (Roche). PCR amplification (see Supplementary Table  3) was performed using a Gene Amp PCR System 9700 (Applied Biosystems, California, USA). The resultant amplicons were purified using High Pure PCR Product Purification Kit (Roche). Additional primers forRPGR sequencing were used. The sequencing reactions were performed with BigDye Terminator v1.0 (Life Technologies) and run on ABI PRISM® 3130XL Genetic Analyzer (Life Technologies). Due to sequence composition and technical difficulties, part ofRPGR ORF15 (~250 bp, chrX: 38145343–38145593) could not be accurately sequenced with Sanger sequencing.


### 2.3. Data Analysis

Samples were processed using the Ion Torrent Suite™ (TS) Software for raw data processing and sequence alignment to the human genome reference sequence hg19. The TS Variant Caller was used for the detection of germline variants that were subsequently analyzed using the following optimized filtering and annotation pipeline. Annovar [9] and Variant Effect Predictor (VEP) [10] were used to functionally annotate the detected variants, retrieving RefSeq gene annotation, dbSNP rs identifiers, ClinVar accession, and allele frequency observed in the population (1000-Genome Project, NHLBI GO Exome Sequencing Project ESP6500SI-V2, Exome and Aggregation Consortium ExAC 0.3). Variants with low coverage or low frequency (<30 reads or <30%, resp.) were filtered out. The synonymous variants and variants having an allele frequency greater than 1% reported in the population were discarded as well. In addition, an internal database, built with all variants present in our cohort of processed samples, allowed recognizing and classifying as polymorphisms variants not listed in public databases. Variants were further annotated with conservation scores and functional predictions listed in dbNSFP [11–13], a database which compiles scores from various prediction algorithms, among which are SIFT, Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM. Retina International (http://www.retina-international.org/), RPGR database (http://rpgr.hgu.mrc.ac.uk/index.php?select_db=RPGR), CEP290base (http://cep290base.cmgg.be/), and BEST1 LOVD database (http://www-huge.uni-regensburg.de/BEST1_database) were used to explore additional annotations and literature information, if present. Splice-altering predictions were obtained using the online tools Human Splicing Finder (HSF 3.0) [14] and NNSPLICE 0.9 [15] and the databases dbscSNV [16] and SPIDEX [17], which provide predicted effects for all of the potential variants within splicing consensus regions or across the entire genome, respectively. For the prioritization of pathogenetic mutations, the evaluation of inheritance mode was taken into account, along with segregation information coming from the sequencing of healthy family members, if available.NGS procedure and data analysis were tested on the four control samples with known molecular diagnosis as proof of concept. In all cases the previously identified variants were correctly detected and prioritized as pathogenic variants.


## 2.1. AmpliSeq Panel Design and Ion Torrent™ PGM™ Library Preparation and Sequencing

The Ion AmpliSeq technology (Life Technologies Ltd., Paisley, UK) was used to design a panel of 72 genes (Supplementary Table  2) associated with the following IRD forms: RP, LCA, STGD, BMD, and USH [RetNet,https://sph.uth.edu/retnet/]. The Ion AmpliSeq Designer tool (https://www.ampliseq.com/browse.action) generated an optimized primers design encompassing the coding DNA sequence of the selected genes, for a total of 1.649 amplicons divided into two pools to optimize coverage and multiplex PCR conditions. Libraries were prepared using the Ion AmpliSeq Library Kit 2.0 starting from 15 ng of gDNA/pool according to manufacturer’s recommendations. Template preparation was performed using an Ion OneTouch™ 2 System following the latest version of the manufacturer’s manuals. The template positive Ion Sphere Particles (ISPs+) were sequenced on an Ion Torrent Personal Genome Machine® (PGM) System (Life Technologies Ltd., Paisley, UK) using the Ion 318™ Chip kit v2 following the Ion PGM Sequencing 200 Kit v2 manual.


## 2.2. Sanger Sequencing

Sanger sequencing was performed to validateCNGB1 c.875-5_891dup mutation (identified with an anomalous distribution of NGS reads attributable to amplification problems due to the insertion itself located at the end of the target region) and to sequenceRPGRORF15 partially uncovered by the NGS panel. Primers for PCR and sequencing are shown in Supplementary Table  3. The following conditions were used: a 50 μL PCR reaction containing 100 ng of DNA, 100 pmol of forward and reverse primers, 5 μL of buffer, and 0.5 μL of Taq Expand High Fidelity™ DNA Polymerase (Roche). PCR amplification (see Supplementary Table  3) was performed using a Gene Amp PCR System 9700 (Applied Biosystems, California, USA). The resultant amplicons were purified using High Pure PCR Product Purification Kit (Roche). Additional primers forRPGR sequencing were used. The sequencing reactions were performed with BigDye Terminator v1.0 (Life Technologies) and run on ABI PRISM® 3130XL Genetic Analyzer (Life Technologies). Due to sequence composition and technical difficulties, part ofRPGR ORF15 (~250 bp, chrX: 38145343–38145593) could not be accurately sequenced with Sanger sequencing.


## 2.3. Data Analysis

Samples were processed using the Ion Torrent Suite™ (TS) Software for raw data processing and sequence alignment to the human genome reference sequence hg19. The TS Variant Caller was used for the detection of germline variants that were subsequently analyzed using the following optimized filtering and annotation pipeline. Annovar [9] and Variant Effect Predictor (VEP) [10] were used to functionally annotate the detected variants, retrieving RefSeq gene annotation, dbSNP rs identifiers, ClinVar accession, and allele frequency observed in the population (1000-Genome Project, NHLBI GO Exome Sequencing Project ESP6500SI-V2, Exome and Aggregation Consortium ExAC 0.3). Variants with low coverage or low frequency (<30 reads or <30%, resp.) were filtered out. The synonymous variants and variants having an allele frequency greater than 1% reported in the population were discarded as well. In addition, an internal database, built with all variants present in our cohort of processed samples, allowed recognizing and classifying as polymorphisms variants not listed in public databases. Variants were further annotated with conservation scores and functional predictions listed in dbNSFP [11–13], a database which compiles scores from various prediction algorithms, among which are SIFT, Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM. Retina International (http://www.retina-international.org/), RPGR database (http://rpgr.hgu.mrc.ac.uk/index.php?select_db=RPGR), CEP290base (http://cep290base.cmgg.be/), and BEST1 LOVD database (http://www-huge.uni-regensburg.de/BEST1_database) were used to explore additional annotations and literature information, if present. Splice-altering predictions were obtained using the online tools Human Splicing Finder (HSF 3.0) [14] and NNSPLICE 0.9 [15] and the databases dbscSNV [16] and SPIDEX [17], which provide predicted effects for all of the potential variants within splicing consensus regions or across the entire genome, respectively. For the prioritization of pathogenetic mutations, the evaluation of inheritance mode was taken into account, along with segregation information coming from the sequencing of healthy family members, if available.NGS procedure and data analysis were tested on the four control samples with known molecular diagnosis as proof of concept. In all cases the previously identified variants were correctly detected and prioritized as pathogenic variants.


## 3. Results

A cohort of 109 samples (Table1), including 88 IRDs affected probands without molecular diagnosis and 21 unaffected family members, was analyzed by the newly developed system based on NGS and data analysis. A total of 19 sequencing runs were performed (6 samples/Ion Chip 318), obtaining on average a mean coverage of 450 mapped reads, with 92% mean uniformity and 97.6% (S
D
±
1.4) of target regions covered at least 30x (96.2% > 50x). For each sample, 242 raw variants were detected on average. Annotation and filtering procedure resulted in the identification of possibly causative mutations in 59.1% of patients (n
=
52/88) (Table 2, Figure 1). The majority of the obtained molecular diagnoses were consistent with the subject’s clinical presentation and family history.Table 2
Diagnostic yields for the clinical subtypes of this study.
Clinicaldiagnosis
Cases(n)
Geneticdiagnosis (n)
Unsolvedcases (n)
Clinical reassessment(final diagnosis)
Diagnosticyield (%)
BMD
4
4
—
100
LCA
5
4
1
80
STGD
14
11
3
78.5
RP
45
27
18
2 (USH)
60.0
USH
3
3
—
100
nd IRD
17
3
14
3 (ACHM, LCA, STGD)
17.6
Total
88
52
36
5
59.1
BMD: Best Macular Dystrophy; LCA: Leber Congenital Amaurosis; STGD: Stargardt Disease; RP: Retinitis Pigmentosa; USH: Usher Syndrome; nd IRD: inherited retinal degeneration not otherwise specified without precisely defined diagnosis; ACHM: Achromatopsia.Figure 1
The chart summarizes the diagnostic yields obtained for the clinical subtypes of this study. The different levels of circles (from inner to outside) specify clinical diagnoses, inheritance mode, mutated genes, and clinical reassessment.We found pathogenic mutations in 16 genes, with the most recurrent beingABCA4 for STGD andUSH2A for RP/USH patients. The majority of the mutated genes were inherited with an AR pattern (78.9%), followed in order by AD (11.5%) and XL (9.6%) inheritance. The majority of cases displaying recessive inheritance were compound heterozygous of two different pathogenic variants, in line with the low frequency of consanguineous marriages in ItalyIdentified candidate pathogenic mutations are shown in Table3. Overall, 63 different mutations were identified: 62.5% of variants were already reported in previous studies, while 37.5% were novel. Among the list of novel variants, 56% were missense predicted to have deleterious protein functional effect by the prediction algorithms described in the Patients and Methods (predicted to be damaging by at least three of the applied algorithms), and 44% were frameshift, nonsense, or splice-site mutations that might severely affect protein function. Notably, 12% of identified variants were located within splicing consensus regions, and additional 12% were exonic variants predicted to alter splicing through enhancer/silencer motif modification or the creation of new potential donor/acceptor sites.Table 3
Patient ID
Family
Clinical diagnosis
Clinical reassessment
Genotype
Inheritance
Gene
Mutation type
Region
cds change
IRD027
STGD
Comp Het
ar
ABCA4
Splice_region
INTRON_40
c.5714+5G>A
ABCA4
Frameshift
EXON_11
c.1375delA
IRD036
Familiar case
STGD
Comp Het
ar
ABCA4
Stop_gained
EXON_14
c.2099G>A
ABCA4
Splice_region syn
EXON_6
c.768G>T
IRD037
STGD
Comp Het
ar
ABCA4
Stop_gained
EXON_14
c.2099G>A
ABCA4
Splice_region syn
EXON_6
c.768G>T
IRD042
Familiar case
STGD
Comp Het
ar
ABCA4
Missense
EXON_42
c.5882G>A
ABCA4
Missense
EXON_6
c.634C>T
IRD043
STGD
Comp Het
ar
ABCA4
Missense
EXON_42
c.5882G>A
ABCA4
Missense
EXON_12
c.1622T>C
IRD050
STGD
Comp Het
ar
ABCA4
Missense
EXON_16
c.2461T>A
ABCA4
Missense
EXON_15
c.2300T>A
IRD054
STGD
Comp Het
ar
ABCA4
Stop_gained
EXON_47
c.6445C>T
ABCA4
Missense
EXON_42
c.5882G>A
IRD055
STGD
Comp Het
ar
ABCA4
Missense
EXON_19
c.2842C>T
ABCA4
Missense
EXON_15
c.2300T>A
IRD061
STGD
Comp Het
ar
ABCA4
Missense
EXON_42
c.5882G>A
ABCA4
Missense
EXON_28
c.4139C>T
IRD062
STGD
Comp Het
ar
ABCA4
Missense
EXON_42
c.5882G>A
ABCA4
Missense
EXON_16
c.2549A>G
IRD073
nd IRD
STGD
Hom
ar
ABCA4
Missense
EXON_19
c.2894A>G
IRD077
STGD
Comp Het
ar
ABCA4
Missense
EXON_37
c.5285C>A
ABCA4
Missense
EXON_15
c.2300T>A
IRD047
BMD
Het
ad
BEST1
Missense
EXON_2
c.73C>T
IRD057
Familiar case
BMD
Het
ad
BEST1
Missense
EXON_2
c.80G>C
IRD058
BMD
Het
ad
BEST1
Missense
EXON_2
c.80G>C
IRD064
BMD
Het
ad
BEST1
Missense
EXON_2
c.80G>C
IRD010
LCA
Comp Het
ar
CEP290
Missense
EXON_33
c.4237G>C
CEP290
Frameshift
EXON_23
c.2390delA
IRD066
RP
Comp Het
ar
CEP290
Stop_gained
EXON_48
c.6640A>T
CEP290
Frameshift
EXON_14
c.1219_1220delAT
IRD072
nd IRD
LCA
Comp Het
ar
CEP290
Missense
EXON_14
c.1298A>G
CEP290
Frameshift
EXON_3
c.164_167delCTCA
IRD039
RP
Hom
ar
CNGB1
Frameshift
EXON_13
c.875-5_891dup
IRD052
RP
Comp Het
ar
CNGB1
Missense
EXON_29
c.2957A>T
CNGB1
Frameshift
EXON_13
c.875-5_891dup
IRD068
RP
Comp Het
ar
CNGB1
Splicing, syn
EXON_26
c.2526C>T
CNGB1
Missense
EXON_21
c.2153G>C
IRD085
RP
Hom
ar
CNGB1
Missense
EXON_23
c.2284C>T
IRD032
nd IRD
ACHM
Comp Het
ar
CNGB3
Splice_donor
INTRON_13
c.1578+1G>A
CNGB3
Frameshift
EXON_10
c.1148delC
IRD029
Familiar case
RP
Hom
ar
CRB1
Missense
EXON_5
c.2200G>A
IRD030
RP
Hom
ar
CRB1
Missense
EXON_5
c.2200G>A
IRD031
RP
Hom
ar
CRB1
Missense
EXON_5
c.2200G>A
IRD035
LCA
Het
ad
CRX
Frameshift
EXON_4
c.514delC
IRD008
RP
Hom
ar
PDE6B
Splice_region
EXON_18
c.2193+1delG
IRD013
RP
Comp Het
ar
PDE6B
Missense
EXON_4
c.794G>A
ar
PDE6B
Intron
INTRON_8
c.1108-10G>A
IRD026
RP
Het
ad
RHO
Missense
EXON_3
c.568G>T
IRD016
RP
Comp Het
ar
ROM1
Missense
EXON_1
c.178C>A
ROM1
Missense
EXON_1
c.323C>T
IRD033
RP
Hem
xl
RP2
Frameshift
EXON_2
c.382_383delTT
IRD076
RP
Hom
ar
RPE65
Missense
EXON_2
c.65T>C
IRD001
RP
Comp Het
ar
RPE65
Missense
EXON_2
c.65T>C
RPE65
Frameshift
EXON_9
c.893delA
IRD074
LCA
Hom
ar
RPE65
Missense
EXON_5
c.430T>G
IRD002
LCA
Comp Het
ar
RPGRIP1
Frameshift
EXON_15
c.2225_2226delGA
RPGRIP1
Frameshift
EXON_17
c.2795_2796insT
IRD012
RP
Hem
xl
RPGR
Missense
EXON_8
c.785C>G
IRD067
RP
Hem
xl
RPGR
Missense
EXON_8
c.814G>T
IRD075
RP
Hem
xl
RPGR
Missense, Splice_region
EXON_2
c.154G>A
IRD017
RP
Hem
De novo
RPGR
Frameshift
EXON_2
c.89delT
IRD059
Familiar case
RP
Comp Het
ar
TULP1
Missense
EXON_15
c.1590C>G
TULP1
Missense
EXON_13
c.1255C>T
IRD060
RP
Comp Het
ar
TULP1
Missense
EXON_15
c.1590C>G
TULP1
Missense
EXON_13
c.1255C>T
IRD041
RP
Comp Het
ar
TULP1
Splice_region
INTRON_14
c.1496-6C>A
TULP1
Missense
EXON_14
c.1445G>A
IRD007
USH
Comp Het
ar
USH2A
Missense
EXON_63
c.12420T>G
USH2A
splice_region, syn
EXON_28
c.5775A>T
IRD009
USH
Comp Het
ar
USH2A
Missense
EXON_63
c.13546G>T
USH2A
splice_region, Missense
EXON_10
c.1645T>C
IRD021
RP
Comp Het
ar
USH2A
Missense
EXON_69
c.14995A>G
USH2A
Missense
EXON_8
c.1481A>G
IRD023
Familiar case
RP
USH
Comp Het
ar
USH2A
Missense
EXON_13
c.2296T>C
USH2A
Frameshift
EXON_3
c.545_548delAAGA
IRD024
RP
USH
Comp Het
ar
USH2A
Missense
EXON_13
c.2296T>C
USH2A
Frameshift
EXON_3
c.545_548delAAGA
IRD038
RP
Comp Het
ar
USH2A
Missense
EXON_13
c.2296T>C
USH2A
Missense
EXON_13
c.2276G>T
IRD084
USH
Hom
ar
USH2A
Frameshift
EXON_69
c.14977_14978delTT
IRD034
RP
Hom
ar
USH2A
Missense
EXON_63
c.12574C>T
Patient ID
Protein change
Frequency  (%)
Coverage(# reads)
Segregation and unaffected siblings
Functional predictions  (dbNSFP)
Splicing predictions
Reference
Human Splicing Finder
dbscSNV
SPIDEX
IRD027
44.9
514
Broken WT Donor Site
0.999|0.988
−3.21
PMID: 15494742
p.Thr459GlnfsX2
47.7
1179
PMID: 21911583
IRD036
p.Trp700X
48.2
303
.|..|N|A|.|.|.|.|.|D
PMID: 11702214
p.Val256Val
47.2
53
Broken WT Donor Site
1.000|0.952
−2.43
PMID: 12037008
IRD037
p.Trp700X
44.5
110
.|..|N|A|.|.|.|.|.|D
New Acceptor Site
−5.41
PMID: 11702214
p.Val256Val
48.3
29
Broken WT Donor Site
1.000|0.952
−2.43
PMID: 12037008
IRD042
p.Gly1961Glu
47.1
1325
D|DD|D|D|N|D|D|D|D|D
PMID: 9295268
p.Arg212Cys
49.1
432
D|DD|D|A|M|D|D|D|D|D
PMID: 11726554
IRD043
p.Gly1961Glu
46.9
796
D|DD|D|D|N|D|D|D|D|D
PMID: 9295268
p.Leu541Pro
51.9
727
D|DD|D|A|M|D|D|D|D|D
PMID: 11527935
IRD050
p.Trp821Arg
43.8
309
D|DD|D|D|H|T|D|D|D|D
PMID: 11527935
p.Val767Asp
46.3
452
D|BB|D|D|M|D|T|D|D|D
PMID: 15494742
IRD054
p.Arg2149X
49.1
422
.|..|D|A|.|.|.|.|.|D
New ESS site
−58.3
PMID: 12202497
p.Gly1961Glu
49.4
1448
D|DD|D|D|N|D|D|D|D|D
PMID: 9295268
IRD055
p.Arg948Cys
52.0
175
T|BB|N|D|L|D|T|T|N|N
This study
p.Val767Asp
51.5
437
D|BB|D|D|M|D|T|D|D|D
PMID: 15494742
IRD061
p.Gly1961Glu
50.0
729
D|DD|D|D|N|D|D|D|D|D
PMID: 9295268
p.Pro1380Leu
55.8
437
D|DP|N|A|M|D|D|D|D|D
New ESS site
−5.44
PMID: 11726554
IRD062
p.Gly1961Glu
100
787
D|DD|D|D|N|D|D|D|D|D
PMID: 9295268
p.Tyr850Cys
49.4
176
D|DD|D|D|M|T|D|D|D|D
PMID: 23096905
IRD073
p.Asn965Ser
100
225
D|DD|D|D|L|D|D|D|D|D
PMID: 9054934
IRD077
p.Ala1762Asp
50.8
259
D|DD|D|A|M|D|D|D|D|D
PMID: 15192030
p.Val767Asp
51.4
752
D|BB|D|D|M|D|T|D|D|D
PMID: 15494742
IRD047
p.Arg25Trp
56.0
348
D|DD|U|D|M|D|D|D|D|D
New Donor Site, New ESS site
PMID: 10798642
IRD057
p.Ser27Thr
46.8
344
D|DD|U|D|H|D|D|D|D|D
This study
IRD058
p.Ser27Thr
45.5
317
D|DD|U|D|H|D|D|D|D|D
This study
IRD064
p.Ser27Thr
47.1
453
D|DD|U|D|H|D|D|D|D|D
This study
IRD010
p.Asp1413His
49.2
413
D|BB|D|D|N|T|T|T|N|D
ClinVar: RCV000082249.5
p.Lys797SerfsX2
30.1
163
This study
IRD066
p.Lys2214X
47.5
705
.|..|D|A|.|.|.|.|.|D
ESE Site Broken
−86.6
This study
p.Met407GlufsX14
51.1
225
PMID: 17724218
IRD072
p.Asp433Gly
53.4
116
T|DP|D|D|L|T|T|T|D|D
New ESS site, New donor site
This study
p.Thr55SerfsX3
43.2
243
PMID: 20690115
IRD039
p.Gly298CysfsX13
100
∗
This study
IRD052
p.Asn986Ile
51.7
471
D|DD|D|D|M|D|D|D|D|D
PMID: 21147909
p.Gly298CysfsX13
26,7
∗
258
This study
IRD068
Thr842Thr
52.1
431
ESE Site Broken
This study
p.Gly718Ala
47.1
153
D|PP|D|D|M|T|T|T|D|D
This study
IRD085
p.Arg762Cys
100
57
D|DD|D|D|H|D|D|D|D|D
This study
IRD032
47.8
907
Broken WT Donor Site
−8.56
PMID: 15657609
p.Thr383IlefsX13
46.5
588
PMID: 15657609
IRD029
p.Gly734Arg
100
397
D|DD|.|D|M|T|D|D|D|D
This study
IRD030
p.Gly734Arg
100
397
D|DD|.|D|M|T|D|D|D|D
This study
IRD031
p.Gly734Arg
100
397
D|DD|.|D|M|T|D|D|D|D
This study
IRD035
p.Pro172LeufsX15
50.5
521
This study
IRD008
100
395
Brother: Het
Broken WT Donor Site
This study
IRD013
p.Arg265Gln
51.7
319
n.a.
T|DD|D|D|L|T|T|T|N|D
ClinVar: RCV000178068.1
54.7
75
Mother: Het
0.001|0.096
PMID: 8698075
IRD026
p.Asp190Tyr
44.6
168
D|DD|D|D|M|T|T|T|D|D
PMID: 8401533
IRD016
p.Pro60Thr
56.1
278
T|BB|N|N|L|T|T|T|N|N
PMID: 8595413
p.Thr108Met
52.8
108
T|PB|N|D|L|T|T|T|N|D
PMID: 8595413
IRD033
p.Leu129ValfsX9
100
392
This study
IRD076
p.Leu22Pro
100
495
T|BB|D|D|M|D|D|D|N|D
PMID: 9801879
IRD001
p.Leu22Pro
46.3
257
Brother: wt
T|BB|D|D|M|D|D|D|N|D
PMID: 9801879
p.Lys298SerfsX27
98
150
Brother: wt
PMID: 11462243
IRD074
p.Tyr144Asp
100
430
Father: Het
D|DD|D|D|M|D|D|D|D|D
PMID: 11462243
IRD002
p.Glu743ArgfsX24
48.8
570
Father: Het
This study
p.Glu933X
48.8
400
Mother: Het
This study
IRD012
p.Ala262Gly
100
280
T|BB|N|N|L|D|T|T|N|N
This study
IRD067
p.Gly272Cys
100
155
D|DD|D|D|H|D|D|D|D|D
This study
IRD075
p.Gly52Arg
100
348
D|DP|U|D|M|T|T|T|D|D
Broken WT Donor Site
PMID: 15364249
IRD017
p.Phe30SerfsX38
100
113
Brother: wtFemale twin: wt
This study
IRD059
p.Ile530Met
50.6
682
D|DD|D|D|H|D|D|D|D|N
This study
p.Arg419Trp
49.5
645
D|DD|D|D|H|D|D|D|D|D
PMID: 25342620
IRD060
p.Ile530Met
51.0
655
D|DD|D|D|H|D|D|D|D|N
This study
p.Arg419Trp
45.3
575
D|DD|D|D|H|D|D|D|D|D
PMID: 25342620
IRD041
54.1
727
Father: Het
0.005|0.419
PMID: 9660588
p.Arg482Gln
48.5
485
Mother: Het
D|DD|D|D|H|D|D|D|D|D
New Acceptor Site
−1.28
PMID: 22665969
IRD007
p.Cys4140Trp
50.5
214
D|DD|D|D|M|T|T|T|D|D
This study
49.5
398
Broken WT Donor Site
0.998|0.986
−4.24
This study
IRD009
p.Gly4516Trp
53.8
239
D|DD|U|D|H|T|D|D|D|D
This study
p.Cys549Arg
49.2
566
D|DD|U|D|H|D|D|D|D|D
0.417|0.520
This study
IRD021
p.Thr4999Ala
51.0
400
D|DD|U|D|M|T|T|T|D|D
This study
p.Tyr494Cys
49.0
400
D|DD|N|D|L|T|T|T|D|D
This study
IRD023
p.Cys766Arg
39.0
82
D|DD|D|D|H|D|D|D|D|D
PMID: 23591405
p.Lys182ArgfsX9
61.4
202
This study
IRD024
p.Cys766Arg
43.5
124
D|DD|D|D|H|D|D|D|D|D
PMID: 23591405
p.Lys182ArgfsX9
48.0
225
This study
IRD038
p.Cys766Arg
47.2
89
D|DD|D|D|H|D|D|D|D|D
PMID: 23591405
p.Cys759Phe
51.1
90
D|DD|D|A|H|D|D|D|D|D
PMID: 10775529
IRD084
p.Phe4993ProfsX7
100
483
PMID: 24944099
IRD034
p.Arg4192Cys
100
515
D|DP|N|D|M|D|D|D|D|D
PMID: 24498627
ACHM: Achromatopsia; ad: autosomal dominant; ar: autosomal recessive; BMD: best macular disease; Comp Het: compound heterozygous; ESE: exonic splicing enhancer; ESS: exonic splicing silencer; Hem: Hemizygous; Het: heterozygous; Hom: homozygous; LCA: Leber Congenital Amaurosis; nd IRD: inherited retinal degeneration not otherwise specified without precisely defined diagnosis; RP: Retinitis Pigmentosa; STGD: Stargardt Disease; USH: Usher Syndrome; wt: wild-type; xl: X-linked. For nonsynonymous variants, predictions from dbNSFP are reported, comprising scores from the following alghoritms: SIFT | Polyphen2HDIV Polypehn2HVAR | LRT | MutationTaster | MutationAssessor | FATHMM | MetaSVM | MetaLR | PROVEAN | fathmm-MKL. For splicing variants, predictions from Human Splicing Finder, dbscSNV (ada_score|rf_score) and SPIDEX are reported. For SPIDEX, max dPSI is shown if lower than −1 (maximum mutation − induced change in the percentage of transcripts with the exon spliced in). Familiar case: the patients were from the same family.*Sanger sequencing was performed to confirm mutation frequency.Table2 summarizes the mutation detection rates obtained for the different clinical subtypes of our study cohort. The highest diagnostic yields were achieved for BMD, LCA, USH, and STGD patients with well-defined clinical diagnosis, where the number of known genes associated with each disease is relatively limited.For BMD cases, all diagnosed patients were heterozygous for mutations onBEST1. Three patients (mother and son) were found to harbour a novelBEST1 missense mutation c.80G>C (p.Ser27Thr) located in the immediate N-terminus, in one of the four mutational hotspots regions in the highly conserved N-terminal half of the protein [18] and predicted to be deleterious by all interrogated algorithms.For STGD patients, genetic diagnosis was achieved in 11 out of 14 (78.5% of the cases). All diagnosed patients in our cohort carried mutations onABCA4. In 75% of the unsolved cases at least oneABCA4 pathogenic allele was identified, suggesting the presence of disease-causing mutations lying outside the coding sequence covered by our panel, as reported in a previous study [19].In LCA patients, causative mutations were identified inCEP290, RPE65, RPGRIP1, andCRX genes, and only one case remained unsolved (20% of the total LCA cases), whereas all Usher 2 syndrome cases were found to carry mutations in USH2A gene.For RP patients, genetic diagnosis was achieved in 27 out of 45 (60% of the cases), involving mutations in 11 different genes: confirming that these phenotypes are genetically heterogeneous (Figure1). Dominant mutations were identified inRHO gene, whereasUSH2A, CNGB1, andTULP1 were the most recurrently mutated genes in ARRP. X-linked inheritance was established for 5 RP male patients (4 probands had mutations inRPGR, whereas one had a mutation in RP2). The identification ofUSH2A as the defective gene in patients with initial clinical diagnosis of RP was followed by audiometric testing to establish if there were any hearing deficiencies. A hearing impairment was found in 2 cases out of 5 leading to clinical reassessment and final diagnosis of USH (Table 2).For patients with IRD without a defined clinical diagnosis or with unclear disease manifestations, we identified causative mutations in 7 out of 17 probands (23.5% of the total IRD cases). In two cases the molecular results allowed a refined clinical diagnosis: a compound heterozygosity of two mutations inCEP290 led to a genetic diagnosis of LCA in a patient with initial diagnosis of North Carolina or Stargardt macular dystrophy, whereas a homozygous pathogenic variant inABCA4 was found in a patient with tapetoretinal degeneration.In 36 patients (12 familiar and 24 sporadic) the molecular analysis did not achieve any definitive result, even after the analysis of the healthy family members, which was performed in 8 cases. Half of the cases with a negative test result (18 out of 36) were affected by RP. The additional analysis of theRPGR ORF15 (a mutational hotspot which was nonsufficiently covered in our panel) for the male patients with a sporadic or suspected X-linked pattern of inheritance (10 patients) by Sanger sequencing yielded no additional mutations.


## 4. Discussion

The results of the present study confirm that high-throughput Next-Generation Sequencing represents a comprehensive cost-effective approach for the molecular diagnosis of Inherited Retinal Dystrophies (IRDs), achieving a molecular diagnosis for 59.1% of the studied cases. More specifically, among the different clinical phenotypes, the highest detection rates were achieved for BMD, LCA, USH, and STGD patients, in whom the genetic test clearly confirmed the clinical diagnoses (Table2). The results of the RP and of the not defined IRD cohorts, instead, demonstrated the high genetic heterogeneity of this diseases and the essential contribution of our NGS analysis to achieving an accurate diagnosis, with the involvement of 12 different genes in 28 sporadic cases. Revision of the initial diagnosis, performed for 9.6% of the genetically diagnosed patients, further emphasizes the importance of a comprehensive genotype/phenotype analysis to unravel the extensive heterogeneity of these diseases. Notably, a remarkable fraction of identified variants are splice-altering mutations (25% of the total mutation burden, 16 out of 64), located within splicing consensus regions, or exonic variants predicted to cause enhancer/silencer motif modification or the creation of new potential donor/acceptor, which are amenable to the antisense-mediated splicing-correction approaches, as recently reported for several genetic diseases, includingCEP290-caused LCA [20, 21].The prevalence of IRD and most importantly the frequency of gene mutations causing those diseases are not well characterized in Italy and only few data have been reported [22–24].RPE65, CRB1, andGUCY2D were identified as the most prevalent mutated genes in Italian LCA patients [22] andRHO was reported to be the gene most commonly responsible for ADRP [23] andEYS the most recurrent for nonsyndromic ARRP and sporadic cases [24]. Our study contributes only partially to the knowledge of the gene mutation frequencies, since each IRD type is represented by small cohorts of cases (i.e., the LCA and dominant RP phenotypes were accounted for by 5 and 6 cases, resp.), and some probands of other ethnicities have been included too. Indeed, regarding LCA, we identified mutations in CEP290,RPE65,CRX, andRPGRIP1 genes.For ADRP,RHO was identified to be responsible for the phenotype in one case, whereas, in ARRP and sporadic RP,USH2A, CNGB1, andTULP1 were the most recurrently mutated genes.RPE65 mutations were found in two ARRP cases: in one more case, still unsolved, a singleRPE65 heterozygous pathogenic variant was found.ROM1 compound heterozygosity was established in one RP proband, suggesting a mechanism of recessive inheritance for this gene associated with dominant and digenic forms. X-linked inheritance was established for 5 RP affected probands, withRPGR andRP2 identified as the disease-causing gene in 4 cases and 1 case, respectively. All BMD diagnosed patients were heterozygous for mutations onBEST1 gene, the major gene responsible for Best’s juvenile form [25], whereas the 78.5% of patients with clinically diagnosed STGD carried pathogenic variants onABCA4[26].Similarly to a recent study [6], the clinical sensitivity of our NGS analysis was not uniform, with the highest diagnostic yields obtained in conditions where the disease-causing genes have been nearly all identified.Direct comparison of our findings with other recently published NGS studies [2–6, 27] is not straightforward, due to differences in the number of genes analyzed but especially due to composition and relative representation of the different phenotypes in the patients cohorts. However, the finding ofUSH2A andABCA4 as the most mutated genes for RP/USH and STGD patients is consistent with previous reports [27–29]. In our RP cohort,USH2A is followed byCNGB1 andRPGR. These two genes, already reported among the most frequently mutated genes in IRD patients [29], were not highly frequently altered in the Saudi population [6] or in a large cohort of Western European and South Asian individuals [27]. Also, we did not find any alteration inEYS, one of the top three genes contributing to IRD in other populations [28, 29].The different gene alterations identified in our LCA cohort (CEP290, RPE65, RPGRIP1, andCRX genes) were consistent with the different disease manifestations of the analyzed patients, in accordance with the specific clinical features described for each of the LCA-associated genes [30, 31]. Less direct is the correlation between the genes involved and the phenotypic features in RP, due to the known contribution of environmental factors to late-childhood- and adult-onset-diseases.Allelic heterogeneity, with different mutations in the same gene causing different phenotypes, is evident also inUSH2A-related retinal disease. Genotype-phenotype correlations observed in our cohort were in accordance with the allelic hierarchy proposed in a recent study [32], supporting the model that USH represents the null phenotype consequent upon severeUSH2A defects, whereas milder mutations in at least one allele result in a pure retinal phenotype associated with normal auditory function.IRD genetic heterogeneity, reflected in the identification of mutations in many genes with a considerable number of previously undescribed alterations, supported the conclusion that molecular diagnosis of these disorders should rely on massive parallel multigene sequencing. Nevertheless, for 36 probands, including 12 familiar cases and 24 unrelated probands, our NGS procedure did not result in the identification of a clear genetic cause of the disease. Some subjects may have mutations that cannot be detected by our amplicon-based approach, such as deep intronic mutations, copy-number variations, or large deletions. In the perspective of the design of a more complete new version of the panel, additional deep intronic regions reported in the literature as carrying disease-causing mutations [19, 33, 34] or a higher exon padding (5 bp in our design, up to 100 bp available in the current pipeline version of the Ion AmpliSeq Designer tool) could be implemented. Moreover, technical limitations, including the difficult amplification ofRPGR ORF15, a mutational hotspot for X-linked RP, may have accounted for some of the missed diagnosis (our panel is presently covering only 30% of this critical exon), but the addition of the specific analysis by Sanger sequencing of the ORF15 of theRPGR gene in 10 males patients, with sporadic/X-linked RP and previously testing negative for pathogenic mutations using our NGS panel, did not reveal any mutation in the analyzed region. Finally, as an improvement to further support the pathogenicity of novel mutations identified in probands, the analysis of both affected and unaffected family member should be performed, when possible.In some of the patients who tested negative we however identified single potentially pathogenic heterozygous mutations in recessive genes or novel heterozygous missense variants in dominant genes with unknown significance, lacking the appropriate level of evidence to classify them as disease-causing or not in concordance with patients’ clinical presentations or family data. The contribution of these variants in combination with deep intronic mutations or large deletions is suspected but could not be demonstrated with the present technique.Database incompleteness further complicates variant interpretation. Two probands with BMD phenotype andBEST1 mutation were found to harbour also heterozygous mutation inRHO (c.578C>T, p.Thr193Met), which was predicted to be damaging and listed as associated with ADRP in a public database [http://www.retina-international.org/sci-news/databases/mutation-database] but in our cohort was carried also by healthy subject, reinforcing the need of a critical interpretation of the molecular findings in view of the phenotypic features of the patients with IRD until a more thorough knowledge of the frequency of the variants and a critical amount of data present in the public disease databases are reached.In conclusion, by presenting profoundly different mutation rates varying according to the clinical diagnosis and by reporting 9.61% of cases of reassessment of the initial diagnosis on the basis of the results of the test, our study reinforces the need of a multidisciplinary work-up before and after the genetic testing, due to the implications of the results in terms of risk assessment for family members and inclusion in gene-based clinical trials.



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*Source: 6341870-2016-12-29.xml*