Assessing utility of clinical exome sequencing in diagnosis of rare idiopathic neurodevelopmental disorders in Indian population

doi:10.21203/rs.2.10139/v1

Background: Neurological diseases are phenotypically and genotypically heterogeneous. Clinical exome sequencing (CES) has been shown to provide a high diagnostic yield for these disorders in the European population but remains to be demonstrated for the Indian population.

Methods: A cohort of 19 idiopathic patients with neurological phenotypes, primarily intellectual disability and developmental delay, were recruited. CES covering 4620 genes was performed on all patients. Candidate variants were validated by Sanger sequencing.

Results: CES in 19 patients provided identified 21 variants across 16 genes which have been associated with different neurological disorders. Fifteen variants were reported previously and 6 variants were novel to our study. Eleven patients were diagnosed with autosomal dominant de novo variants, 7 with autosomal recessive and 1 with X-linked recessive variants. CES provided definitive diagnosis to 10 patients, hence the diagnostic yield was 53%.

Conclusion: Our study suggests that the diagnostic yield of CES in the Indian population is comparable to that reported in the European population. CES together with deep phenotyping could be a cost-effective way of diagnosing rare neurological disorders in the Indian population.

Neurology

Neurological disorders

Intellectual disability

Developmental delay

Clinical exome sequencing

Diagnostic yield

de novo inheritance.

The brain is an incredibly complex organ consisting of a plethora of interconnected cell types. During development and day-to-day functioning, a variety of neurons and numerous proteins are required in the right amount at the right place and at the right time. Hence, any pathogenic mutation affecting genes that are involved in the production of these proteins can have consequences on brain development and functioning. Neurological disorders are conditions in which the motor, sensory, and cognitive functions decline due to variation(s) in the genotype of one or more genes involved in the functions of neurons, spinal cord, and peripheral nerves [1]. They are ranked as the leading disorder to cause 10.2% of global disability-adjusted-life-years compared to 7.3% in 1990, and second-leading disorder responsible for 16.8% of the global deaths [2, 3]. These disorders are clinically heterogeneous and genetically diverse group of disorders affecting all age group with sporadic (autosomal dominant) or acquired (autosomal or X-linked recessive) inheritance. This makes the diagnosis more challenging using the conventional techniques and often deprives the patient of proper treatment. Furthermore, genetic counselling during pregnancy becomes challenging when families approach for prenatal diagnosis.

An extensive genotypic overlap amongst a range of neurodegenerative disease involving neuropathy, myopathy, epileptic encephalopathy, ataxia, paraphasia, intellectual disability, and sensory impairment hampers the genetic diagnosis and makes it difficult to target specific genes for study [4]. For instance, EpilepsyGene, designed in 2015, includes 499 genes and 3931 variants associated with epilepsy [5]. Moreover, with respect to intellectual disability, 528 confirmed genes and 628 candidate genes are reported .[6] Different variations in a single gene can lead to different clinical entities in neurological disorders. An ideal example is of a variation in LIS1 gene (also called as PAFAH1B1: platelet activating factor acetylhydrolase 1b regulatory subunit 1 gene). A small deletion in LIS1 gene leads to an isolated lissencephaly sequence. However, a large deletion covering LIS1 gene and neighbouring genes causes Miller-Dieker syndrome [7]. Both the diseases exhibit similar clinical traits except for the facial dysmorphism, as observed only in Miller-Dieker syndrome [8]. Thus, identification of the genetic cause of a neurological disease using conventional techniques like polymerase chain reaction (PCR) and Sanger sequencing (one-loci-at-a-time approach) seems true in the diseases with well-established genotypic-phenotypic correlation. However, many neurological disorders, even after a meticulous evaluation, remain undiagnosed due to the presence of mild or unusual traits, and lack of precise molecular basis. Sanger sequencing approach is laborious, expensive and falls short in detecting nucleotide repeat expansions, large indels, or copy number variations.

Clinical and whole exome sequencing (CES and WES) has facilitated clinical utility in identifying and characterizing the genes and variants involved in the clinical presentation of the idiopathic neurological disorders because of their ability to sequence multiple genes at a time in a cost-effective manner. With the application of WES, the diagnosis rate in clinical practice has increased which helps in early diagnosis, prognosis, reproductive counselling, medical management and prenatal diagnosis [9]. Furthermore, it is useful in the diagnosis of the etiologically misleading neurological disorders that give false positive result using conventional techniques.

However, most of the studies carried out to date has been in the white European population and western healthcare settings. The diagnostic utility and cost-effectiveness of WES and CES is currently unknown for the Indian population. Since the goal of introducing any technique in clinical practice is to maximize diagnostic yield and minimize cost to the patient, our aim was to assess the utility of CES in diagnosing rare idiopathic neurological disorders in a cohort of 19 patients from the Indian population.

Patient recruitment

The present study comprised of 19 unrelated idiopathic patients with variable neurodevelopmental phenotypes including intellectual disability and developmental delay that were referred between 2015 and 2017. All patients were evaluated according to the clinically validated developmental scales by their referring clinicians. Each referring physician provided details on their phenotype, particularly: developmental, neurological, behavioral and epilepsy history, accompanied by imaging data if available. At the time of recruitment, a pro forma comprising of patient’s clinical details including history of clinical test performed previously, family history, parent’s consanguinity and ethnicity was recorded. The ethics committee of the Foundation for Research in Genetics and Endocrinology at the Institute of Human Genetics approved the study and it was performed in accordance with the tenets of the Declaration of Helsinki. A written informed consent for investigation and publication of the data was obtained from the patients or from the guardian of the patients at the time of recruitment, as per the institutional ethics committee guidelines. Peripheral blood was collected from all patients and their parents, if consented, for downstream genomic testing.

DNA extraction

Four milliliters of whole blood drawn from each patient in an EDTA vacutainer was used for the genomic DNA isolation using the salting-out technique [15]. DNA was quantified using QIAxpert (Qiagen, Germany). To ensure the absence of any salts or inhibitors in downstream applications, all DNA samples were purified using Genomic DNA Clean & Concentrator™-25 kit (Zymo Research, U.S.A) as per the manufacturer’s instructions. High quality DNA was subsequently used for clinical exome and Sanger sequencing.

Clinical exome sequencing and variant validation

DNA from probands were sequenced for clinical exome by Strand Life Sciences, India. Exon and sploce site regions of >4600 genes associated with known inherited diseases were captured using TruSight One kit (Illumina, USA) (Supplementary File 1). Paired-end 150bp sequencing was carried out on Illumina HiSeq 2500 platform (Illumina, USA) in accordance with the manufacturer’s protocols, with an average coverage of 100x. Bioinformatic analysis was subsequently carried out using an in-house pipeline developed by Strand Life Sciences. Briefly, unique sequencing reads passing quality filters were aligned against the reference genome (GRCh37/ hg19) using a local alignment tool called STRAND® NGS v2.5 (Strand Life Sciences, India). Single nucleotide variants (SNVs) and small indels were called using STRAND® NGS v2.5 variant caller at loci that were covered by atleast 10 reads and had a variant allele in atleast 2 reads. Copy number variants (CNVs) were called following sequence coverage normalization and Z-score estimation for a panel of regions against a profile of multiple control samples in the in-house database. All the variants were exported to StrandOmics v5.0 (Strand Life Sciences, India) where variant annotation, filtering and prioritization was carried out. Variants were filtered based on their impact on gene (missense, nonsense, frameshift or canonical splice site variants) and a minor allele frequency of <1% in databases (1000 Genomes Database, HapMap Database, Exome Variant Server, Exome Aggregation Consortium, gnomAD and in-house database consisting data of >1500 people) Lastly, candidate variants were annotated according to the ACMG-AMG classification into 5 classes: benign, likely binging, uncertain significance, likely pathogenic and pathogenic using semi-automated InterVar [10].

Candidate SNVs were validated using bi-directional Sanger sequencing on the SeqStuido Genetic Analyzer platform (Applied Biosystems, USA), according to the manufacturer’s protocols. Primer sequences were designed using Primer3 v0.4.0 online tool (http://bioinfo.ut.ee/primer3-0.4.0/) and PCR conditions used for validation are listed in Supplementary Table 1.

Clinical presentation

Out of 19 patients in our cohort, 12 were males and 9 were females, with the mean age at the time of study being 10.8 years (range 9 months to 45 years) (Figure 1). Recurrent features included global developmental delay, intellectual disability and muscle abnormalities such as hypotonia, walking difficulty and poor control of neck and body in these patients (Table 1, Supplementary Table 2). Approximately 30% of the patients also suffered from seizures and epilepsy. Genomic DNA from all patients were analysed by clinical exome sequencing.

Genetic analysis of patients

In our cohort of 19 patients with neurodevelopmental disorders, we identified 21 variants across 16 genes which have been associated with different neurological disorders (Table 2, Supplementary File 2). Interestingly, 15 of the 21 variants have been reported previously in the literature and the remaining were novel to our study. Out of 21 variants, 14 were missense, 3 splice site, 2 frameshift and 2 nonsense variants. Out of 19 patients, 7 patients were identified with autosomal recessive, 1 with X-linked recessive and 11 with autosomal dominant disorders. Of 11 patients with autosomal dominant de novo variants, 8 (73%) have been described previously in the literature [Table 2]. Three novel de novo variants included 2 missense variants in genes SCN1A (c.5351T>A/ p.Val1784Asp) and BSCL2 (c.461C>T/ p.Ser154Leu), and a frameshift mutation that led to a premature stop in gene SCN2A (c.1153delT/ p.Phe385SerfsTer8). With the unavailability of parental samples for all 11 patients with presumed de novo mutations, Sanger sequencing for de novo mutation confirmation was not carried out.

Of interest, out of the 5 novel mutations identified in the current study, 1 was classed as pathogenic (SCN2A c.1153delT), 2 as likely pathogenic (SCN1A c.5351T>A and BSCL2 c.461C>T) and 2 as variants of unknown significance (PGAP1 c.2286+5G>A and AFG3L2 c.1951A>G). Furthermore, segregation analysis of PGAP1 c.2286+5G>A variant showed parents to be heterozygous carriers and affected siblings to be homozygous for the variants. However, due to the absence of parental DNA for the patient with AFG3L2 c.1951A>G mutation, segregation analysis was not carried.

Overall, out of 21 variants, 4 were classed as pathogenic, 9 as likely pathogenic and 8 as variant of unknown significance according to the ACMG-AMG guidelines. With the clinical exome sequencing approach, we were able to provide definitive diagnosis to 10 patients; hence, our diagnostic yield with this approach was 53%.

In the current study, our aim was to assess the utility of clinical exome sequencing in the diagnosis of rare neurological disorders in India. Exome sequencing of 19 patients with intellectual disability and/ or developmental delay provided confirmed diagnosis of 10 patients, whereby, ~50% of the mutations were of de novo origin. The study also elucidated 15 rare diseases that were diagnosed in these patients that would have otherwise been difficult to diagnose with cheaper but lower-resolution orthogonal methods such as microarray and karyotyping.

Eleven patients were identified carrying autosomal dominant de novo mutations, which is a known disease mechanism in rare neurological disorders [26, 27]. Furthermore, 8 out of 11 variants have previously been reported in other studies, thereby, further strengthening the evidence for the role of these variants in causing respective diseases. It is noteworthy that out of these 8 known de novo variants, 50% were missense variants and the remaining were either splice site or nonsense mutations. This finding has direct implication on genetic counselling whereby, de novo missense mutations can be associated with incomplete penetrance, whereas, nonsense and splice site mutations are not, as shown for SCN1A gene [28].

Despite finding known disease associated variants in majority of the patients, our study identified 5 novel variants in 5 genes- SCN1A, SCN2A, PGAP1, AFG3L2 and BSCL2. Diseases associated with these genes include Dravet syndrome (OMIM#607208), early infantile epileptic encephalopathy type 11 (OMIM#613721), mental retardation type 42 (OMIM#615802), spastic ataxia type 5 (OMIM#614487) and hereditary spastic paraplegia (OMIM#270685), respectively. Whilst 3 of the 5 variants are classed as pathogenic or likely pathogenic according to the ACMG-AMG classification [29], they are to be interpreted with caution as these variants would require replication in other patient and control cohorts as well as functional follow-up to implicate them as disease causing [30]. None of the novel variants identified in the current study had an autosomal recessive or X-linked recessive inheritance pattern. This suggests an intriguing hypothesis of a reduced probability of finding novel recessive genes compared to dominant genes in neurological diseases in the Indian population; one that is supported by the data available from studies in the European population [27].

Interestingly, the diagnostic yield of clinical exome in our cohort was 53%, which is in concordance with the published literature [27]. However, this needs to be placed in contrast with the role of de novo copy number variants (CNVs) that also play role in neurological disorder pathogenesis[27]. Genomic microarray-based studies have shown a strong correlation between the number of genes affected by a CNV and phenotypic severity [27, 31]. Indeed, microarray-based studies have shown presence of rare, autosomal dominant form of de novo CNVs in approximately 10% of patients [27]. Whilst microarray has been the mainstay for detection of CNVs, exome sequencing based large CNV detection (>400 kb) are increasingly becoming prominent in diagnosing neurological disorders [32]. Furthermore, it is estimated that 45-60 de novo single nucleotide variants occur per genome per generation whereas the frequency of de novo >500kb CNVs is approximately 0.01 per genome per generation [33, 34]. This difference in mutation rates together with difference in mutation detection abilities could explain an enhancement in the diagnostic yield of exome sequencing by 24-33% over microarray [27]. Therefore, utilization of an exome sequencing technique in identifying de novo variants (both SNV and CNV) compared to microarray-based approach in identifying only de novo CNVs in neurological diseases is likely to be an attractive approach.

Whilst the current study highlights several benefits of using an exome sequencing based approach in diagnosing neurological diseases, there are some caveats which needs to be highlighted. First, the diagnostic yield of 53% in our study could be misleading if taken at face value. Indeed, overall diagnostic yield has been reported between 50-70% in diagnosing moderate to severe intellectual disability diseases [27], depth and quality of patient phenotyping can impact diagnostic yield [35]. The current study carried out an in-depth patient phenotype which may have aided in interpreting genotype data and disease diagnosis. Second, 11 patients in whom de novo SNVs were identified, Sanger validation for the mode of inheritance confirmation wasn’t carried out due to the unavailability of parental samples. Without Sanger sequencing confirmation in parental samples, it is conceivable that these variants may have been inherited from one of the parents. However, since these disorders have a significant impact on patient’s fitness [27], it is unlikely for either of the parents to be a carrier of these mutations. Hence, despite the absence of parental samples, replication of variants from the literature together with heterozygous status in the patient’s sample suggests these variants to be likely of de novo origin. Third, the current study had a small sample size compared to the large multicenter project like Deciphering Developmental Disorders (https://www.ddduk.org). However, the study was aimed to assess the utility of clinical exome sequencing in the Indian population rather than identification of novel genes and pathways involved in neurological disorders, hence had a requirement for a small sample size.

Genetic studies have significantly improved in the past decade and consequently, there has been a substantial improvement in the diagnosis of neurological disorders. Due to the phenotypic and genetic heterogeneity of neurological disorders, it is required to carry out hypothesis-free exome-wide approaches as a first-tier diagnostic test. Even with the current lack of knowledge around all neurological disease causing genes and pathogenic variants, it seems that de novo mutations are the main cause of neurological diseases. Results from our study suggests carrying out deep phenotyping along with clinical exome sequencing as a first-line diagnostic test in neurological disorders in the Indian population.

ABCD1: ATP binding cassette subfamily D member 1, ACMG: American College of Medical Genetics and Genomics, AFG3L2: AFG3 like matrix AAA peptidase subunit 2, ALD: adrenoleukodystrophy, ASSP: Alternative Splice Site Predictor, BSCL2: Berardinelli-Seip Congenital Lipodystrophy 2, CDCBM7: complex cortical dysplasia with other brain malformations-7, CES: clinical exome sequencing CSMD1: cub and sushi multiple domains 1, dbSNP: Single Nucleotide Polymorphism Database, EDTA: Ethylenediaminetetraacetic acid, EIEE: Early Infantile Epileptic Encephalopathy, ExAC: The Exome Aggregation Consortium, FATHMM: Functional Analysis Through Hidden Markov Models, GPI: glycosylphosphatidylinositol, GWAS: Genome-wide association study, HGMD: Human Gene Mutation Database, HPO: Human Phenotype Ontology, LINS1: lines homolog 1, LIS1: Lissencephaly 1, LIS2: Lissencephaly-2, LTR: Long terminal repeats LZTR1: leucine zipper like transcription regulator 1, MRD5: mental retardation 5, MRT27: mental retardation 27, MRT42: mental retardation 42, NCBI: The National Center for Biotechnology Information, NGS: Next generation sequencing, NNSPLICE: Splice Site Prediction by Neural Network, NS10: Noonan syndrome-10, OMIM: Online Mendelian Inheritance in Man, PAFAH1B1: platelet activating factor acetylhydrolase 1b regulatory subunit 1 gene, PARK: Parkinson disease, PCR: polymerase chain reaction, PGAP1: post-GPI attachment to proteins 1, RefSeq: Reference Sequence database, RELN: reelin, RFLP: Restriction Fragment Length Polymorphism, SCN1A: sodium voltage-gated channel alpha subunit 1, SCN2A: sodium voltage-gated channel alpha subunit 1, SD: Salla disease, SIFT: Scale-invariant feature transform, SLC17A5: solute carrier family 17 member 5, SPAX5: spastic ataxia-5, SPG17: spastic paraplegia, SYNGAP1: synaptic Ras GTPase activating protein 1, TCOF1: treacle ribosome biogenesis factor 1, TCS1: Treacher Collins syndrome 1, TUBB2B: tubulin beta 2B class IIb.

Ethics approval and consent to participate

The present study has been approved by the institutional ethics committee [FRIGE’s Institute of Human Genetics] with approval number FRIGE/IEC/14/2016 dated 19^thNovember 2016. This process is in accordance with the declaration of Helsinki. An informed consent for investigation was obtained from the family of the proband at the time of enrollment for the study [This was in accordance with the requirement of the institutional ethics committee]. An informed consent for publication was also obtained from the individuals included in the submission [This was in accordance with the requirement of the institutional ethics committee].

Consent for publication

Informed written consent was obtained from parents for publication of the proband’s clinical details and/or clinical images. A copy of the written consent is available for review to the editor of this journal.

Availability of data and material

Fastq files are available upon request from the corresponding authors JS and HS.

Competing Interests

The authors declare that they have no competing interests (financial or non-financial) in the present study.

Funding

This work is partly supported by Gujarat State Biotechnology Mission (GSBTM) [grant no.: GSBTM/MD/PROJECTS/SSA/505/4865/2016-17]. The funding agency was not involved in the study design, specimen collection, analysis, interpretation and preparation of the manuscript.

Authors’ contributions

Conceived and designed the experiments: JS, FS and HS; Clinical analysis: JS, FS, MC, SS, and DS; Manuscript writing, tables and figure preparation: DP and HS; Laboratory workup: RB, DP, AM, and AG; Data analysis: AUM, AG and HS; Critical revisions and approval of final manuscript: JS, HS, and FS. All authors reviewed and approved the final manuscript.

Acknowledgments

We show our gratitude to the proband and their families for their support and without whose consent this study would not have been possible. We also appreciate Dr. Neelu Desai, Dr. Harshruti shah, Dr. Priyank Shah, Dr. Yogendra Jhala, Dr. Ami Trivedi, Dr. Namita Chhajed, Dr. K.M. Gabu, Dr. Krati Shah, Dr. Harshruti Shah, Dr. Neelu Desai, Dr. Vrajesh Udani, Dr. Heli Shah, and Dr. Pranav Joshi for referring patients at our institute.

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Table 1: Clinical details and demographic profile of the patients with neurological disorder.

Patient ID

P₁

P₂

P₃

P₄

P₅

P₆

P₇

P₈

P₉

P₁₀

P₁₁

P₁₂

P₁₃

P₁₄

P₁₅

P₁₆

P₁₇

P₁₈

P₁₉

Age at the time of investigation (in years)

3.5

19

12

3.6

5

21

7

2

5.9

9 months

28

45

2

17

5

10

7

2

10

Sex

M

F

M

F

M

F

M

F

M

F

M

F

M

Symptoms

Seizures

+

Motor seizures

+

Epilepsy

+

Up rolling eyes

+

Vision regression

+

Hearing regression

+

Drop attacks

+

Day time sleepiness

+

Increased dullness

+

Failure to thrive

+

Tongue bite

+

Obesity

+

Global developmental delay

Autism

+

Developmental delay

+

Cognitive impairment

+

Motor delay

+

Intellectual disability

+

Speech delay

+

Hyperactive behavior

+

Poor eye contact

+

Poor psychosocial development

+

Blank facial expressions

+

Cortical sensory deficit

+

Brain abnormalities

Microcephaly

+

Chorea

+

Lissencephaly

+

Leukodystrophy

+

Muscle abnormalities

Walking difficulty

+

Hypotonia

+

Foot drop

+

Poor neck control

+

Poor body control

+

Brisk reflexes

+

Myoclonus

+

Drooling of saliva

+

Bladder and bowel dysfunction

+

Facial dysmorphism

Low hairline

+

Elongated face

+

Large ears

+

Strabismus

+

Thick lower lip

+

Coarse features

+

Kinky hair

+

Neck webbing

+

Skeletal abnormalities

Arachnodactyly

+

Limb-Trunk dyskinesia

+

Painful/restricted hand movements (can’t eat/write)

+

Abbreviations: Female (F), Male (M)

+ sign indicates the presence of symptom

Table 2: Candidate variants identified by clinical exome sequencing in patients with idiopathic neurological disorders.

ID

Gene

gDNA

cDNA

Protein

Zygosity

Disease^†(Inheritance pattern)

NGS coverage depth

Allele Frequency

dbSNP reference sequence

Transcript No.

(Reference sequence)

Variant classification using ACMG-AMP2015 guidelines

Reference

Confirmed diagnosis

1000 Genomes

ExAC

P₁

SCN1A

Chr2:166848434

c.5351T>A

p.Val1784Asp

Het

EIEE6 (AD)

>10x

NR

rs1057518671

ENST00000303395.8 (NM_001165963.2)

Likely Pathogenic

In this study

No

P₂

SCN1A

Chr2:166911147

c.602+1G>A

Het

EIEE6 (AD)

121x

NR

rs794726827

ENST00000303395.8 (NM_001165963.2)

Pathogenic

[11]

Yes

P₃

SCN1A

Chr2:166911245

c.505T>C

p.Ser169Pro

Het

EIEE6 (AD)

>10x

NR

rs796052957

ENST00000375405.7 (NM_001165963.2)

Likely Pathogenic

[12]

Yes

P₄

SCN2A

Chr2:166170248

c.1153delT

p.Phe385SerfsTer8

Het

EIEE11 (AD)

320x

NR

rs879253767

ENST00000375437.6 (NM_001040142.1)

Pathogenic

In this study

No

P₅

SYNGAP1

Chr6:33400447

c.403C>T

p.Arg135Ter

Het

MRD5 (AD)

128x

NR

rs1131692154

ENST00000629380.2 (NM_006772.2)

Likely Pathogenic

[13]

Yes

P₆

LINS1

Chr15:101114141

c.937G>A

p.Glu313Lys

Hom

MRT27 (AR)

>10x

NR

rs1057519019

ENST00000314742.12

(MN_001040616.2)

Uncertain significance

[14]

No

P₇

PGAP1

Chr2:197710601

c.2286+5G>A

Hom

MRT42 (AR)

127x

NR

rs937847069

ENST00000354764.8 (NM_024989.3)

Uncertain significance

In this study

No

P₈

PAFAH1B1

Chr17:2541604

c.22C>T

p.Arg8Ter

Het

LIS1 (AD)

73x

NR

rs121434489

ENST00000397195.9

(NM_000430.3)

Pathogenic

[15]

Yes

P₉

PAFAH1B1

Chr17:2569296

c.118-14_118-10delTTTAT

Het

LIS1 (AD)

48x

NR

ENST00000397195

(NM_000430.4)

Likely pathogenic

[16]

Yes

P₁₀

RELN

Chr7:103126831

c.9796C>T

p.Pro3266Ser

Het

LIS2 (AR)

130x

0.0008

0.0001486

rs544906913

ENST00000428762.5 (NM_005045.3)

Uncertain significance

[17]

No

RELN

Chr7:103236965

c.3477C>A

p.Asn1159Lys

Het

189x

0.0010

0.001723

rs114684479

Uncertain significance

[18]

P₁₁

PLA2G6

Chr22:38511674

c.1894C>T

p.Arg632Trp

Hom

PARK14 (AR)

71x

NR

0.00003239

rs121908683

ENST00000332509.7

(NM_003560.3)

Likely pathogenic

[19]

Yes

P₁₂

FBXO7

Chr22:32875119

c.274G>C

p.Asp92His

Het

PARK15 (AR)

263x

NR

0.0003048

rs139135860

ENST00000266087.11 (NM_012179.3)

Uncertain significance

[20]

No

FBXO7

Chr22:32879986

c.520T>A

p.Ser174Thr

Het

293x

NR

Uncertain significance

In this study

No

P₁₃

AFG3L2

Chr18:12340229

c.1951A>G

p.Arg651Gly

Hom

SPAX5 (AR)

456x

NR

rs764254189

ENST00000269143.7 (NM_006796.2)

Uncertain significance

In this study

No

P₁₄

BSCL2

Chr11:62469965

c.461C>T

p.Ser154Leu

Het

SPG17 (AD)

222x

NR

rs137852973

ENST00000360796.9
(NM_001122955.3)

Likely pathogenic

In this study

No

P₁₅

TUBB2B

Chr6:3227745

c.33G>C

p.Gln11His

Het

CDCBM7 (AD)

42x

NR

rs1135401758

ENST00000259818.7

(NM_178012.4)

Likely pathogenic

[21]

Yes

P₁₆

ABCD1

chrX:152990970

c.253_254insC

p.Arg85ProfsTer110

Hemi

ALD (XLR)

NA

NR

rs713993050

ENST00000218104.5

(NM_000033.4)

Pathogenic

[22]

Yes

P₁₇

TCOF1

Chr5:149755284

c.1705G>A

p.Glu569Lys

Het

TCS1 (AD)

>10x

NR

0.00006056

rs764314276

ENST00000439160.6

(NM_001135243.1)

Likely pathogenic

[23]

Yes

P₁₈

LZTR1

Chr22:21349277

c.1904C>T

p.Pro635Leu

Het

NS10 (AD)

55x

0.0004

0.0002191

rs148677674

ENST00000215739.12

(NM_006767.3)

Likely pathogenic

[24]

Yes

P₁₉

SLC17A5

Chr6:74354305

c.116G>A

p.Arg39His

Hom

SD (AR)

166x

NR

0.000008246

rs769235753

ENST00000355773.5 (NM_012434.4)

Uncertain significance

[25]

No

Abbreviations: Autosomal dominant (AD), Autosomal recessive (AR), Heterozygous (Het), Homozygous (Hom), Hemizygous (Hemi), Not Applicable (NA), Next Generation Sequencing (NGS), X-Linked recessive (XLR).

† Disease names are abbreviated as per Online Mendelian Inheritance in Men (OMIN)

Assessing utility of clinical exome sequencing in diagnosis of rare idiopathic neurodevelopmental disorders in Indian population

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

Version 1