Singh et al. BMC Medical Genetics(2020) 21:216
https://doi.org/10.1186/s12881-020-01153-4

RESEARCH ARTICLE

Open Access

NGS-based expanded carrier screening for
genetic disorders in North Indian population
reveals unexpected results – a pilot study
Kanika Singh1, Sunita Bijarnia-Mahay1* , V. L. Ramprasad2, Ratna Dua Puri1, Sandhya Nair2, Sheetal Sharda2,
Renu Saxena1, Sudha Kohli1, Samarth Kulshreshtha1, Indrani Ganguli3, Kanwal Gujral3 and Ishwar C. Verma1*

Abstract
Background: To determine the carrier frequency and pathogenic variants of common genetic disorders in thenorth Indian population by using next generation sequencing (NGS).
Methods: After pre-test counselling, 200 unrelated individuals (including 88 couples) were screened for pathogenic
variants in 88 genes by NGS technology. The variants were classified as per American College of Medical Genetics
criteria. Pathogenic and likely pathogenic variants were subjected to thorough literature-based curation in addition
to the regular filters. Variants of unknown significance were not reported. Individuals were counselled explaining
the implications of the results, and cascade screening was advised when necessary.
Results: Of the 200 participants, 52 (26%) were found to be carrier of one or more disorders. Twelve individuals
were identified to be carriers for congenital deafness, giving a carrier frequency of one in 17 for one of the fourgenes tested (SLC26A4, GJB2, TMPRSS3 and TMC1 in decreasing order). Nine individuals were observed to be carriers
for cystic fibrosis, with a frequency of one in 22. Three individuals were detected to be carriers for Pompe disease(frequency one in 67). None of the 88 couples screened were found to be carriers for the same disorder. The
pathogenic variants observed in many disorders (such as deafness, cystic fibrosis, Pompe disease, Canavan disease,primary hyperoxaluria, junctional epidermolysis bullosa, galactosemia, medium chain acyl CoA deficiency etc.) weredifferent from those commonly observed in the West.
Conclusion: A higher carrier frequency for genetic deafness, cystic fibrosis and Pompe disease was unexpected,
and contrary to the generally held view about their prevalence in Asian Indians. In spite of the small sample size,
this study would suggest that population-based carrier screening panels for India would differ from those in theWest, and need to be selected with due care. Testing should comprise the study of all the coding exons with its
boundaries in the genes through NGS, as all the variants are not well characterized. Only study of entire coding
regions in the genes will detect carriers with adequate efficiency, in order to reduce the burden of genetic
disorders in India and other resource poor countries.
Keywords: Carrier screening, Cystic fibrosis, Hearing loss, Pompe disease, Asian Indians* Correspondence: bijarnia@gmail.com; icverma@gmail.com
1
Institute of Medical Genetics and Genomics, Sir Ganga Ram Hospital, New
Delhi, India
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Singh et al. BMC Medical Genetics(2020) 21:216

Background
Birth defects, defined as abnormalities of structure andfunction present from birth, are progressively contributing to a greater proportion of fetal, neonatal, infant andchildhood mortality in developing countries. This is dueto the decline in infectious and nutritional causes due toextensive use of immunizations, control of diarrheal andrespiratory infections, and improvements in health care[1]. In the West, 29.8% of early mortality and 29.2% ofchronic problems, are due to birth defects [2]. The
major difference in the type of disorders observed in developing and developed countries is a higher incidenceof autosomal recessive single gene disorders due to consanguinity and endogamous marriages in the former [2,3]. WHO estimated that globally 206,000 deaths andabout 7% of all neonatal deaths are caused by birth defects [4]. In India, the Sample Registration System Survey during 2010–2013 showed the contribution ofcongenital malformations to childhood mortality, infantmortality and neonatal mortality as 4.4, 4.6 and 4.0% respectively [5]. In the tertiary care hospitals birth defects
contributed from 4.2 to 13.4% of perinatal mortality,
making congenital malformations and genetic disorders
as the third leading cause of neonatal mortality [6]. The
burden of genetic disorders in India has been presented
in a number of publications and their prevention
through screening has been emphasized [3, 7].
Birth defects, including genetic disorders, can causesignificant mortality, diminish productivity and qualityof life and cause social stigmatization and economic burden especially in resource poor countries. Their prevention is therefore a priority in all countries.
Most countries carry out prevention by screening forinfections during pregnancy by serology, chromosomal
disorders by biochemical test and structural abnormalities by ultrasonography. However, population prevalence studies have shown that the number of single genedisorders is almost equal to or exceeds chromosomal
disorders and congenital malformations combined [3, 7–
9]. The cost of prevention through screening for single
gene disorders is much less than the cost of treatment.
For example, in Cyprus where thalassemia is common, it
was shown that the cost of 8 weeks of prevention was
equivalent to the cost of 1 week of treatment of the thalassemia population [10]. The Ministry of Health of Israel
reported that the life time health care cost for persons
with thalassemia vs the cost of national screening program was in a ratio of 4.22 to 1 [11]. The need to reduce
the prevalence of genetic disorders in developing countries is greater now as the new treatments of genetic disorders are exorbitantly expensive and out of reach forthese families [12, 13]. Moreover most of this expenditure has to be covered by out of pocket expenses by thepatients/parents themselves.

Page 2 of 15

Screening for carriers of single gene disorders such as
cystic fibrosis and Tay Sach disease has also been shown
to be cost effective [14, 15]. Beauchamp et al. examinedthe clinical impact of a 176-condition expanded carrier
screening and demonstrated its cost-effectiveness to reduce the burden of Mendelian disease as compared withminimal screening [16]. Zhanga et al. considered the impact and cost-effectiveness of offering preventive population genomic screening for BRCA1/2, MLH1/MSH2
genes, cystic fibrosis, spinal muscular atrophy and fragile
X syndrome to all young adults (18–25 years) in asingle-payer health-care system in Australia, and reported that it would be highly cost-effective, but ethicalissues need to be considered [17].
The basic objective of carrier screening is to identify carriers and offer them reproductive options from choosing
to marry someone who is not a carrier of the same disease(premarital screening) or prenatal diagnosis. In the eventthat both the husband and wife are carriers of the same
disorder, preimplantation genetic diagnosis (after in vitro
fertilisation) or prenatal diagnosis (during early stages of anaturally conceived pregnancy) can be carried out [18].
Screening only those families who have a previously affected child is very inefficient, as majority of affected children are born to couples with no previous family history.
Similarly screening only those who have an a-priori increased risk of being a carrier based on their personal andfamily history or who are consanguineously married, or in
couples who are opting for sperm or egg donation(Assisted Reproduction Technologies) would still be an inadequate strategy to identify the carriers of genetic disorders. It is best to screen all couples for the genetic
disorders common in that population.
World-wide, carrier screening has evolved from anancestry-based (e.g. in Jewish populations) to pan-ethnic
testing, and from single gene disorders, such as cystic fibrosis or α/β-thalassemia, by Sanger sequencing or
hematologic techniques, to multiple disorders throughNext Generation Sequencing (NGS) [19]. In the West,carrier screening by NGS was initially limited to targeted
genotyping because most of the pathogenic variants in
the Caucasian population had been characterized andthe results were easier to interpret as the subjects werescreened for known variants [19]. This approach is notsuitable in resource poor countries as most of the pathogenic variants in different genes have not been characterized. However, screening later shifted to NGS of allcoding exons of genes to identify carriers more efficiently. This is more suited in India and other resourcepoor countries, identifying only the variants that arepathogenic or likely pathogenic and ignoring variants ofuncertain significance.
Carrier screening studies for single gene disorders inIndia, as a service, have chiefly been carried out for β-Singh et al. BMC Medical Genetics(2020) 21:216

Page 3 of 15

A sample size of 200 unrelated individuals was plannedfor enrolment in this pilot study.

was estimated as 1:500 in one study in 2009 [27]. The true
prevalence of cystic fibrosis in India is unknown but suspected to be high in a recent review done by Mandal et al.
[28], based on the increased citations in recent years.
Lazarin et al., [29] also observed a carrier frequency of 1:
40 for cystic fibrosis in South Asian population, muchhigher than expected from data in India. The genetic
register maintained about patients evaluated at our centre
was analysed. Eighty eight genes [72 autosomal recessive(AR), 7 X-Linked (XL), 9 autosomal dominant (AD/AR)
were selected for testing (Supplementary file 2). A smaller
number of disorders were aimed at to develop a short but
efficient panel that could be offered at a low cost. Two recessive disorders (cystic megalencephaly and calpainopathy) were included as they are common in an ethnic
group (Agrawals) in North India [26]. Familial Hypercholesterolemia, though an autosomal dominant disorder wasstudied as it is life threatening and early treatment cansave lives. The study was planned in coherence with
American College of Medical Genetics (ACMG) position
statement on prenatal/preconception expanded carrier
screening [30]. Some common disorders were excluded either because these are not detectable by
NGS technology with accuracy or the disorder canbe screened easily by haematological tests. These included β-thalassemia, deletions in SMN1 (survival
motor neuron 1) causing SMA (spinal muscular atrophy), FXS (Fragile X syndrome), and DMD (Duchenne muscular dystrophy). Deletion study of CAH
was excluded, although sequencing of the gene was
performed. Large copy number variations in any of
the 88 genes were also not included, in this sequence – based study.

Statistical analysis

Pre and post-test counselling

Descriptive analysis was done, and outcome reported
as proportion of carriers upon total individuals tested(n/200). Confidence interval was calculated by Wilson
method [24].

Prior to the testing, all individuals were counselled about
the type of disorders being tested, the implications of being a carrier, the benefits of enrolment of the partnerand voluntary nature of testing. Relevant personal, family
and ethnic data were recorded. Subjects were clinicallyexamined to rule out any chronic disorder. In post-test
counselling the individuals were explained about carrier
status and its implications, cascade screening of family
members and residual risks remaining after the results(unscreened disorders, chromosomal disorders andindels). The study methodology is depicted in Fig. 1.

thalassemia, based on hematologic technique [20]. Isolated studies for p.Phe508del in cystic fibrosis [21] andp.Trp24Ter in GJB2 related hearing loss [22] and more
recently SMN1 deletion in SMA (Spinal muscular atrophy) [23] have been performed as research studies. The
objectives of the present study were to determine thecarrier frequency of variants in 88 genes expected to becommon in Asian Indians and to identify the pathogenic
or likely pathogenic variants.

Methods
Subjects

This study was carried out at Sir Ganga Ram Hospital, atertiary care multispecialty facility, over a period of 22months from October 2016 through June 2018. Institutional ethical clearance was obtained prior to commencing the study (Ethical clearance number EC/08/ 16/1066). The molecular analysis was performed at Medgenome Laboratories Ltd., Bangalore. Two hundred unrelated individual (n = 101 male, n = 99 female) between
the age of 20–60 years, visiting the Medical Genetics andObstetrics and/or Gynaecology out-patient clinic forvarious reasons unrelated to genetic disorders were enrolled, after pre-test counselling. Individuals known tobe carriers of any genetic disease, or with history of achronic medical disorder or familial genetic disorderwere excluded from the study. The relevant history andclinical data of each individual was recorded on standard
case record proformas (Supplementary file 1).
Sample size

Selection of gene panel

The selection of genes followed the Wilson and Jungner
criteria [25]. Genes selected were those which cause highimpact disorders that have significant effect on lifespan or
reduce quality of life; or genes with moderate impact that
do not reduce lifespan but impact quality of life; or disorders with significant socioeconomic burden for which
couples would consider prenatal diagnosis. Limited literature available on the prevalence of various monogenic disorders in India was reviewed. The study by Ankala et al.
[26], summarised the prevalence of galactosemia in India
1:10,300, congenital adrenal hyperplasia (CAH) 1:2600,
phenylketonuria 1:18,300, and amino acid disorders 1:
3600. The prevalence of childhood hearing loss in India

Molecular and Bioinformatic analysis

DNA was extracted from blood using Qiagen kit, andtargeted genes were captured by a custom kit. The libraries were sequenced to mean coverage of > 80-100X
on Illumina sequencing platform. The sequences obtained were aligned to human reference genome(GRCh37/hg19) using BWA program [31, 32] andSingh et al. BMC Medical Genetics(2020) 21:216

Page 4 of 15

Fig. 1 Study flow chart

analysed using Picard and GATK version 3.6 [33, 34].
Gene annotation of the variants was performed using VEP(Variant effect predictor) program against the Ensembl release 87 human gene model [35]. Clinically relevant
pathogenic variants were annotated using published variants in the literature and a set of diseases databases –ClinVar [36], OMIM (Online Mendelian inheritance inman) [37], GWAS catalogue (Genome wide association
study in man) [38], HGMD (Human gene pathogenic variant database) [39] and SwissVar [40].

Common variants were filtered based on allele frequency in 1000Genome Phase 3 [41], GnomAD [42],dbSNP147 [43], and an in house database of 100,000
exomes in Indian subjects (Medgenome). Nonsynonymous variants effect was calculated using multiple
algorithms such as PolyPhen-2 (polymorphism phenotyping v2) [44], SIFT (Sorts intolerant from tolerant)[45], Mutationtaster2 [46], Mutation Assessor [47] andLRT (Likelihood ratio test) [48]. Splicing prediction tools
used were Mutationtaster2 [46], BDGP (Berkeley

Singh et al. BMC Medical Genetics(2020) 21:216

Page 5 of 15

drosophila genome project) [49] and HSF (human splicing finder) [50]. Various filters applied to variants included Variant quality (pass), 1000 genomes MAF (<0.05), exonic and canonical splice site and read depth(>10x). Variants remaining after applying the listed filters were subjected to ACMG classification. Only thosevariants fulfilling the ACMG criteria for pathogenic andlikely pathogenic were shortlisted [51]. The literature
was reviewed for the filtered variants before assigning
carrier status.
Validation of NGS results

All disease associated variants were manually inspectedusing IGV (integrative genomics viewer). It was observedthat all variants had sequencing depth > 30. No strand
biasness was observed. All variants were of good mapping quality. None of the variants were in highly repetitive regions. These were further validated using Sanger
sequencing.

Results
Population demographics

Of the 200 individuals enrolled, 61.5% belonged to the
31–40 years age group (Table 1). Eighty eight percent had
enrolled with their partner and none of them were consanguineously married. Maximum number of persons
belonged to the northern states of India (Delhi (n = 74),

Punjab (n = 50), Haryana (n = 44), Uttar Pradesh (n = 18),
Himachal Pradesh (n = 5), Jammu and Kashmir (n = 5)
and Rajasthan (n = 4). Majority of the individuals identified themselves as Hindu Punjabi (20.5%). Detailed religious and ethnic characteristics of the subjects is listed inTable 1. Some individuals (5%) could not be classified asthey were either unsure of their caste and origin or wereborn of an inter-caste marriage.
Carrier frequency

Of the 200 participants, 52 (26%) were found to be carrierof one or more disorders (Table 2). Congenital deafness as
the most common disorder identified, with a carrier frequency of 1 in 17, for one of the four genes SLC26A4 (solute carrier family 26, member 4), GJB2 (gap junction beta
2 protein), TMPRSS3 (transmembrane protease, serine 3)
and TMC1 (transmembrane channel like protein 1), in decreasing order. Cystic fibrosis was the second most commonly observed disorder with a carrier frequency of 1 in
22. Three subjects were detected to be carriers for Pompedisease (frequency 1 in 67) (Table 2).
There was no couple where both husband and wife werecarriers for the same disorder. No woman was found to be a
carrier for the seven X-linked disorders included in thepanel (Fabry disease, Ornithine transcarbamylase deficiency,
hemophilia A and B, Hunter syndrome, severe combined
immunodeficiency (SCID) and adrenoleukodystrophy).

Table 1 Demographic characteristics of the individuals enrolled in the study
Parameter
Age

Sex

Religion & Caste

No of individuals (n = 200)

Percentage

20–30 yrs

61

30.5%

31–40 yrs

123

61.5%

41–50 yrs

13

6.5%

51–60 yrs

3

1.5%

Male

101

50.5%

Female

99

49.5%

Hindu

Punjabi

41

20.5%

Brahmin30

15%

Agarwal

28

14%

Jat

18

9%

Punjabi

14

7%

Rajput6

3%

Pahadi6

3%

BrahminBengali

42%Marwari

2

1%

Kashmiri Pandit

2

1%

10

5%

Jain

Other

18

9%

Sikh

12

6%

Muslim9

4.5%

Singh et al. BMC Medical Genetics(2020) 21:216

Page 6 of 15

Table 2 Carrier frequency of the disorders screened
S.no

Disease name (OMIM no.)N (no. ofcarriers)/200
individuals

%

1 in
_

Wilson 95% Confidence Interval
Lower %

Upper %

Total no. of carrier individuals

52

26

3.84

19.9

31.9

1

Cystic fibrosis - CFTR (219700)

2

Deafness - SCL26A4 (274600)

9

4.5

22.22

2.4

8.3

5

2.5

40.0

0.78

5

3
4

Deafness - GJB2 (220290)

3

1.5

66.67

0.5

4.3

Deafness - TMPRSS3 (601072)

3

1.5

66.67

0.5

4.3

5

GSD type II - GAA (232300)

3

1.5

66.67

0.5

4.3

6

Methyl malonicaciduria mut A – MMAA (251100)

2

1

100

0.27

3.6

7

AR polycystic kidney – PKHD1 (263200)

2

1

100

0.27

3.6

8

Galactosemia - GALT (230400)

2

1

100

0.27

3.6

9

Smith Lemli Opitz syndrome – DHCR7 (270400)

2

1

100

0.27

3.6

10

Albinism type II - OCA2 (203200)

2

1

100

0.27

3.6

11

Megalencephalic leukoencephalopathy withcysts -MLC1 (604004)

2

1

100

0.27

3.6

12

Gaucher disease - GBA (230800)

2

1

100

0.27

3.6

13

Phenylketonuria – PAH (261600)

2

1

100

0.27

3.6

14

Epidermolysis bullosa (Junctional) -LAMC2(226,700, 226,650)

2

1

100

0.27

3.6

15

Niemann Pick disease type C1 – NPC1 (257220)

1

0.5

200

0.088

2.77

16

Deafness - TMC1 (600974)

1

0.5

200

0.088

2.77

17

Biotinidase deficiency - BTD (253260)

1

0.5

200

0.088

2.77

18

Medium chain acyl CoA deficiency -ACADM (201450)

1

0.5

200

0.088

2.77

19

Limb girdle muscle dystrophy type 2A -CAPN3 (253600)

1

0.5

200

0.088

2.77

20

Congenital adrenal hyperplasia -CYP21A2(201910)

1

0.5

200

0.088

2.77

21

Primary hyperoxaluria type 1 - AGXT (259900)

1

0.5

200

0.088

2.77

22

Argininosuccinic aciduria - ASL (207900)

1

0.5

200

0.088

2.77

23

Canavan disease - ASPA (271900)

1

0.5

200

0.088

2.77

24

Glutaric aciduria type 1 – GCDH (231670)

1

0.5

200

0.088

2.77

25

Krabbe disease - GALC (245200)

1

0.5

200

0.088

2.77

26

Congenital ichthyosis - TGM1 (242300)

1

0.5

200

0.088

2.77

27

Metachromatic leukodystrophy – ARSA (250100)

1

0.5

200

0.088

2.77

28

Zellweger syndrome – PEX1 (214100)

1

0.5

200

0.088

2.77

29

Epidermolysis bullosa dystrophica – COL7A1 (226600)

1

0.5

200

0.088

2.77

30

Very long chain acyl CoA dehydrogenase
deficiency - ACADVL (201475)

1

0.5

200

0.088

2.77

P Pathogenic, LP Likely pathogenic

Disease causing variants

described in patients belonging to the Indian subcontinent (India, Pakistan, Bangladesh). The individual variants
are listed in Tables 3 & 4 and discussed in more detaillater. Three splice site variants were novel (not reported
in the literature or locus specific databases) and fulfilled
ACMG criteria for pathogenicity (Table 4).

The disease-causing variants were identified 57 times in
52 of 200 subjects (Table 3). Number of variants were47, as some variants were identified more than once.
Majority were of missense type (72.34%). Among thealready reported variants, 29.5% (n = 13/44) have been

Discussion
The study was designed to determine the carrier frequency of single gene disorders other than β-thalassemia
for which has a carrier frequency of about 3–4% has

Of the 52 (26%) subjects found to be carriers, majority
were carriers for one disorder (n = 47/200 = 23.5%) andfive for two disorders (n = 5/200 = 2.5%). No individual
was found to be a carrier for three or more disorders.

Deafness, AR 4, withenlarged vestibular
aqueduct, SLC26A4

Deafness, AR,1A, GJB2

Deafness, AR, 8, TMPRSS3

Deafness AR,7, TMC1

Cystic fibrosis, CFTR

Glycogen storage
disease II, GAA

1

2

3

4

5

6

ENST00000302262

ENST00000003084

ENST00000297784

ENST00000291532

ENST00000382844

ENST00000265715

Transcript no.

1

9

1

2

2

4

Number of
Variantsac.1859A > T, p.His620Leu

PS4 + PM1 + PM2 + PM5 + PP2 + PP3 + PP5

PM1 + PM2 + PP2 + PP3
PM1 + PM2 + PM5 + PP2 + PP3

c.4009 T > G, p.Phe1337Val

c.1933G > A, p.Asp645Asn

PM1 + PM2 + PP2 + PP3
PM1 + PM2 + PP2 + PP3

PS3 + PM1 + PM4 + PP2 + PP3

p.Phe508delc.1472G > T, p.Cys491Phe

PS3 + PM1 + PM5 + PP2 + PP3 + PP5

c.3209G > A, p.Arg1070Gln

c.4096A > T, p.Ile1366Phe

PS3 + PM1 + PM2 + PM5 + PP2 + PP3 + PP5

PS3 + PM1 + PM2 + PM5 + PP2 + PP3 + PP5

PVS1 + PS3 + PM2 + PM4 + PP2 + PP3

c.595C > T, p.His199Tyrc.1646G > A, p.Ser549Asn

c.223C > T, p.Arg75Ter

PVS1 + PS3 + PM2 + PM4 + PP3

PS3 + PS4 + PM2 + PP3

c.1165C > T, p.Arg389Ter

PM1 + PM2 + PP2 + PP3

c.413C > A, p.Ala138Glu

PVS1 + PS3 + PM1 + PM4 + PP2 + PP3

PVS1 + PS3 + PM1 + PM4 + PP2 + PP3

PS1 + PP2 + PP3 + PP5

c.323-6G > Aa

c.71G > A, p.Trp24Terac.231G > A, p.Trp77Ter

ac.1003 T > C, p.Phe335Leu

c.1468A > C, p.Ile490Leu

PS1 + PM1 + PP2 + PP3 + PP5

PM2 + PM5 + PP2 + PP3 + PP5aPS3 + PM2 + PP2 + PP3 + PP4 + PP5

c.1226G > C, p.Arg409Proa

ACMG criteriac.1001G > T, p.Gly334Val

Variant description:
cDNA position
Protein change

PVS Pathogenic very strong, PS Pathogenic strong, PM pathogenic moderate, PP Pathogenic supporting [51] (Supplementary file 3), adescribed from the Indian subcontinent

Disorder and GeneS. noTable 3 Pathogenic and likely pathogenic variants observed in the three commonest disorders

3

1

1

1

1

1

1

1

1

1

1

2

1

1

2

1

1

1

2

No of
individuals

Singh et al. BMC Medical Genetics(2020) 21:216
Page 7 of 15

Peroxisome biogenesis disorder 1A (Zellweger), PEX1

Limb Girdle muscle dystrophy type 2A, CAPN3

Congenital adrenal hyperplasia, CYP21A2

Megalencephalic leukoencephalopathy with
subcortical cysts, MLC1

16

17

21

2

c.1448 T > C
p.Leu483Prob

c.866G > C
p.Gly289Alab

PVS1 + PS3 + PM2 + PM4 + PP2

1
1

PS3 + PM5 + PP2 + PP3 + PP5

1

1

1

1

1

2

2

1

PM2 + PP2 + PP3 + PP4 + PP5

PS3 + PM2 + PP2 + PP3

PS3 + PM2 + PP2 + PP3 + PP5

PS3 + PP2 + PP3 + PP4

PM2 + PP2 + PP3 + PP4 + PP5

PM1 + PM2 + PM5 + PP2 + PP3

PS4 + PM1 + PP2 + PP3 + PP5

PM2 + PP2 + PP3 + PP4 + PP5

1

1

1

2

1

1

1

1

2

1

2

No of individuals(2020) 21:216

ENST00000327247

Gaucher disease, GBA

201c.302 T > C
p.Leu101Prob

ENST00000307503

Primary hyperoxaluria type 1, AGXT

19c.65G > A
p.Arg22Gln

c.373C > T
p.Arg125Cys

c.1504A > G
p.Ile502Val

c.959C > A
p.Thr320Lys

2

1

1

18

ENST00000311597

ENST00000418967

ENST00000397163

c.688G > A
p.Val230Ile

15

1

Phenylketonuria, PAH

14

ENST00000553106

c.1580 T > G
p.Leu527Argb

1c.1480C > T, p.Arg494Ter
ENST00000354638

c.8441-1G > Ca

Albinism type 2, OCA2

PVS1 + PM2 + PP3 + PP5
PVS1 + PM2 + PP3

c.2926 + 2 T > C

13

2

1

12

ENST00000371117

ENST00000248633

PVS1 + PM2 + PP3 + PP5

Polycystic kidney disease, AR, PKHD1

PVS1 + PM2 + PP3

101

c.1210 + 1G > Ta

11

ENST00000216124

c.2138-2A > Ga

Metachromatic leukodystrophy, ARSA

1

PS1 + PS3 + PP2 + PP3 + PP5

PS3 + PM1 + PM2 + PM5 + PP2 + PP3

PM2 + PP1 + PP2 + PP3 + PP4 + PP5

PS1 + PM2 + PP2 + PP3 + PP4 + PP5

PS3 + PM1 + PP2 + PP3 + PP4 + PP5

PVS1 + PM1 + PM4 + PP2

PVS1 + PS3 + PM4 + PP2 + PP3

ACMG criteriac.811G > G/A
p.Gly271Arg

9

ENST00000391911

1

Junctional Epidermolysis bullosa, LAMB3

ENST00000420607

8c.730G > A
p.Gly244Arg

Medium chain ACYL-CoA dehydrogenase
deficiency, ACADM

12c.563A > G
p.Gln188Arg

7

ENST00000303498

ENST00000355527

1

c.5287C > T
p.Arg1763Ter

c.469C > T
p.Arg157Cys

Smith-Lemli-Opitz syndrome, DHCR7

4

ENST00000378842

1c.433C > T
p.Arg145Ter

Biotinidase deficiency, BTD

Galactosemia, GALT3

ENST00000328333

1

Variant description: cDNA
positionProtein change

6

Epidermolysis bullosa dystrophica, AR, COL7A1

2

ENST00000281317

Number of variants

c.862G > A
p.Glu288Lys

Methylmalonic aciduria, cbla type, MMAA

1

Transcript

5

Disorder and GeneS. noTable 4 Pathogenic and likely pathogenic variants in other genes

Singh et al. BMC Medical Genetics
Page 8 of 15

Argininosuccinic aciduria, ASL

Canavan disease, ASPA

Glutaric acidemia type 1, GCDH

Krabbe disease, GALC

Congenital ichthyosis, AR 1, TGM1

Very Long chain fatty acid acyl-CoA
dehydrogenase deficiency, ACADVL

Niemann Pick disease type C1, NPC1

22

23

24

25

26

27

28

ENST00000269228

ENST00000543245

ENST00000206765

ENST00000261304

ENST00000222214

ENST00000263080

ENST00000304874

Transcript

1

1

1

1

1

1

1

Number of variants

c.3560C > T
p.Ala1187Val

c.1480 T > C
p.Phe494Leuc.550C > T
p.Pro184Ser

c.956A > G
p.Tyr319Cysb

c.281G > A
p.Arg94Glnb

c.902 T > C
p.Leu301Prob

c.857A > G
p.Gln286Arg

Variant description: cDNA
positionProtein change

PM5 + PP2 + PP3 + PP4 + PP5

PM1 + PM2 + PP2 + PP3

1

1

1

1

PM1 + PM2 + PM5 + PP2 + PP3
PM2 + PM3 + PP2 + PP3 + PP5

1

1

1

No of individuals

PM2 + PM5 + PP2 + PP3 + PP4 + PP5

PM2 + PP2 + PP3 + PP4 + PP5

PS4 + PP2 + PP3 + PP5

ACMG criteria

PVS – pathogenic very strong, PS – pathogenic strong, PM– pathogenic moderate, PP – pathogenic supporting [51] (Supplementary file 3), aNovel variant, bdescribed from the Indian subcontinent

Disorder and GeneS. noTable 4 Pathogenic and likely pathogenic variants in other genes (Continued)

Singh et al. BMC Medical Genetics(2020) 21:216
Page 9 of 15

Singh et al. BMC Medical Genetics(2020) 21:216

been shown in many studies in India [52]. Disorders
such as spinal muscular atrophy (SMA), fragile X syndrome (FXS) and Duchenne muscular dystrophy (DMD)
are common in all populations including South Asians
were also excluded as these are difficult to detect withNGS [53]. Recently, we showed the carrier frequency of
SMA in North India to be 2.25% [23]. However, carrier
frequency for other single gene recessive disorders is
not known and significant differences in prevalenceand pathogenic variants have been seen in different
populations [54].
CFTR (cystic fibrosis transmembrane conductanceregulator) pathogenic and likely pathogenic variants

There were nine disease-causing variants identified in
the CFTR gene in this cohort. Of these, only one case
had the common p.Phe508del pathogenic variant i.e.
11% (n = 1/9). Two pathogenic variants detected in
CFTR gene in this study have been observed before in
our laboratory (p.Arg75Ter and p.Ser549Asn). The
remaining six pathogenic variants have not been reported in Indians earlier (Table 3). The variants
p.Ser549Asn, p.His199Tyr, p.Arg1070Gln have been described by multiple authors and functional studies havebeen carried out classifying them as pathogenic as per
ACMG criteria. The other four variants p.Ile1366Phe,
p.Cys491Phe, p.Phe1337Val, p.His620Leu have been
documented to be associated with disease, however lackadequate functional studies. They meet the ACMG criteria for likely pathogenicity (Table 3).
CFTR c.3854C > T, p.Ala1285Val variant was identified
in three individuals, which though has been reported in
the literature [55] associated with congenital bilateral absence of vas deferens CBAVD), is more likely to represent a common polymorphism due to its observance inhigh frequency in the NGS data in the Indian population(0.5% minor allele frequency in South Asians in GnomAD exomes). This variant was not included in the listof disease associated variants.
Studies on the genetic profile of cystic fibrosis patientsin India shows high variability, and many rare and newvariants have been observed, while only few pathogenic
variants (p.Arg1162Ter, p.Met1Thr, c.1161delC, p.Ser549Asp and c.1525-1G > A) are reported more than once
[56–58]. This suggests the lack of founder or common
mutations in CFTR gene and thus emphasises the needfor sequencing of all coding regions of the CFTR gene insuspected cases in the Indian population. In the present
study except for p.Phe508del no other pathogenic variant
was present in the ACMG panel of cystic fibrosis [59]. Inview of the heterogeneity in pathogenic variants, Mandal
et al. also suggested that a single panel of pathogenic variants cannot be used for diagnosis or carrier testing of CF
in India [28]. Archibald et al. also observed that the

Page 10 of 15

pathogenic variants in cystic fibrosis vary according to
ethnic origin [53]. Lim et al. reported in ExAC databasethat the pathogenic variants in the CFTR in nonEuropeans are different from those in people of European
descent. They noted that none of the current genetic
screening panels or existing CFTR pathogenic variant databases cover a majority of deleterious variants in any geographical region outside of Europe [60].
Among the nine disease causing variants identified in
the CFTR gene in the present cohort, only one case had
the common p.Phe508del pathogenic variant i.e. 11%(n = 1/9). Kapoor and Kabra et al. studied cord blood
samples of 955 newborns and reported a p.Phe508delcarrier frequency of one in 238 (0.42%) [21]. They estimated the frequency of homozygous p.Phe508del as 1/
228,006. However, this cannot be considered to represent the true prevalence of cystic fibrosis in India as it
took into account only one pathogenic variant. Comparison of p.Phe508del allele frequency with that reported
from the West shows that Indians have a low frequency(19–44%) of the p.Phe508del pathogenic variant [61–63].
Cystic fibrosis was thought to be extremely rare in India.
However, a growing number of publications in the lasttwo decades have suggested a higher prevalence [28, 63,64]. This indicates that CF may be much more common
in the Indian population with majority of cases being
missed or undiagnosed. CFTR related pathogenic variants may be rarely recognized in Indians in view of thedifferent phenotypes (including cystic fibrosis and congenital absence of vas deferens), variable clinical severity
and lack of availability of sweat testing, and absence of
new born screening.
GJB2 c.231G > A, p.Trp77Ter and c.71G > A, p.Trp24Ter

Biallelic variants in the GJB2 gene or deletion in thegene cause congenital nonprogressive mild to profoundsensorineural hearing impairment. The pathogenic variants identified in GJB2 represent have been previously
reported in Indian subjects. Ram Shankar et al. studied
the pathogenic variants in GJB2 gene in Indian patientswith deafness and found p.Trp24Ter to be the mostcommon pathogenic variant India [22]. In addition, they
documented two other common pathogenic variants
p.Trp77Ter and IVS1 + 1G > A. These differ from thecommon pathogenic variants identified in the Western(c.35delG) [65] and Japanese (c.235delC) and Korean(p.Val37Ile) populations [66, 67].
SLC26A4 related hearing loss

Hearing loss due to SLC26A4 has been reported as third
most common cause of hearing loss in a study in a panethnic population [68]. This occurs due to an enlarged
vestibular aqueduct and temporal bone abnormalities
which can be appreciated on imaging. In addition toSingh et al. BMC Medical Genetics(2020) 21:216

hearing loss, these individuals may have euthyroid goitre(Pendred syndrome). In this study, two out of the four
disease - causing variants reported have been previously
described in individuals of Indian ethnic origin:
p.Arg409Pro [69, 70] and p.Ile490Leu [71]. Other variants found in our study include p.Gly334Val, that has
been described chiefly in people of Mediterranean origin[72] and p.Phe335Leu which is a common variant reported worldwide [73].
Carrier screening and prenatal diagnosis for a disorder
like hearing loss which impairs quality of life can havediffering perceptions among families in different countries. The parental perceptions in Indian culture where
resources are scarce towards congenital hearing loss
have been pointed out by Nahar et al. previously [74].
While some families are interested in using the information to help in the management, planning and emotional
adjustment to the birth of a child with deafness others
opt for discontinuing an affected fetus especially if financial resources are scarce.
GBA c.1448 T > C, and c.866G > C, p.Gly289Ala

Biallelic variants in the GBA gene causing a deficiency ofacid β-glucosidase and cause Gaucher disease, the mostcommon lysosomal storage disorder in the world [75].
The variant p.Gly289Ala and p.Leu483Pro were observedin one individual in the present cohort. Ankleshwari
et al. studied 33 Indian patients with Gaucher disease,and identified p.Leu483Pro as the most common pathogenic variant 60.6% (n = 20/33). In addition, they reported p.Gly289Ala as a novel pathogenic variant in apatient with type I disease [76]. Homozygosity for thep.Leu483Pro variant is associated with neuronopathic involvement (type III) ranging from mild oculomotor
apraxia to more severe involvement as well as lethalcases of collodion skin baby phenotype [77, 78]. The
variant most commonly observed in Western population(p.Asn370Ser) and associated with type I Gaucher disease is observed less commonly in India [77, 79].
GAA c.1933G > A, p.Asp645Asn variant

Biallelic pathogenic variants in the GAA gene cause
deficiency of acid α-glucosidase resulting in Pompedisease. We observed three individuals to be carriers
for p.Asp645Asn variant in the GAA gene. This variant was reported for the first time in 1998 by Huieet al. and demonstrated low enzyme activity with thispathogenic variant in vitro and in vivo [80]. Subsequently this pathogenic variant has been reported inpatients affected with infantile onset Pompe disease in
several studies [81]. This variant lies in exon 14 of
the gene, reported to be a hot spot for this gene [81].
However a study done on Indian ethnic patients reported no hot spots for this gene [82].

Page 11 of 15

OCA2 c.1580 T > G, p.Leu527Arg variant

Oculocutaneous albinism type II (tyrosinase positive)
is caused by biallelic pathogenic variants in the OCA2
gene. These individuals acquire small amounts of pigment with age and tend to have less severe visual abnormalities. The p.Leu527Arg variant was observed inheterozygous in two individuals in our cohort. It wasreported for the first time by Jowerek et al. in a Pakistani family with some pigmentation of hair [83].
They reported that this pathogenic variant lies inhighly conserved residue of amino acids in the transmembrane 8 domain of the protein and segregatedwith affected member.
AGXT c.302 T > C, p.Leu101Pro variant

Primary hyperoxaluria occurs due to deficiency of theliver peroxisomal enzyme alanine:glyoxylate-aminotransferase encoded by the AGXT gene. We observed
one carrier (belonging to Punjabi community) for
p.Leu101Pro variant in our cohort. This variant wasreported for the first time by Williams et al. [84],who demonstrated that the mutant gene protein had
less than 1% of normal activity in vitro. Subsequently,
Chanchlani et al. documented three patients with primary hyperoxaluria type 1 to have the p.Leu101Pro
variant in homozygous state [85]. All the three patients belonged to north India or Pakistan. They suggested a possibility of this being a founder pathogenic
variant in India although larger studies and haplotype
analysis are required.
ASPA c.902 T > C, p.Leu301Pro

The ASPA gene encodes for aspartoacylase enzyme,
deficiency of which results in Canavan disease. One
individual was found to be carrier for the p.Leu301Pro variant. This variant has been reported by ourgroup previously in a patient of Indian ethnicity withclassical Canavan disease and raised urine N-acetyl
aspartate [86]. On the basis of the reported literature
this variant has classified using ACMG criteria as
likely pathogenic.
ACADM c.811G > A, p.Gly271Arg

Biallelic pathogenic variants in ACADM affect mitochondrial fatty acid β-oxidation due to deficiency of the
enzyme medium-chain acyl-coenzyme A dehydrogenase.
The p.Gly271Arg is a well reported pathogenic variant
in the ACADM gene worldwide. It was observed in one
individual in this study. The c.985A > G pathogenic variant commonly seen in the West, believed to be afounder pathogenic variant in Caucasians originatingfrom an ancient Germanic tribe was not observed in thepresent cohort [87].

Singh et al. BMC Medical Genetics(2020) 21:216

Disorders like AR polycystic kidney disease, methyl
malonic acidemia, galactosemia, Smith-Lemli Opitz
syndrome, oculocutaneous albinism type II, cystic
megalencephalic leukoencephalopathy, phenylketonuria
and junctional epidermolysis bullosa can be expected
to be common in the Indian population as at least
two cases were detected among the 200 individuals
screened.
Other investigators and our group have identified anumber of disorders with founder mutations among the
Agarwal community [88, 89]. Carriers for only two ofthese were identified in the current panel of genes - calpainopathy and megalencephalic leukodystrophy withcysts. The mutations detected are not the common ones
noted in the Agarwal community. However there were
only 28 individuals in the cohort belonging to the Agarwal community and larger studies are indicated to determine their carrier frequency.

Conclusions
Carrier screening has been widely offered in the preconception period in the West. However, in India it has
mostly been offered to those who have a family history
or consanguinity. With decreasing costs of NGS panels,
carrier screening is being increasingly utilised in recent
times in India. It is likely to become the method of
choice to decrease the burden of genetic diseases inIndia, as treatment is not funded by state agencies andfamily’s financial resources are scarce. This study also
brings out the differences in common pathogenic variants between the West and in Asian Indians, an ethnically distinct population. The variant filtration andinterpretation strategies in a healthy population are challenging and literature review is essential before assigning
pathogenic status to a variant. With the availability of
NGS based testing in India and growing amount of literature on Indian pathogenic variants and their representation in databases, the sensitivity of carrier screening
is likely to improve. Targeted genotyping panels like the‘23 pathogenic variant panel’ developed by ACMG for
cystic fibrosis are not suitable and will miss many
carriers.
This study highlights the importance of an Indian
database in improving the classification of variants. It
is creditable that many genetic centres are poolingtheir data to develop such a database. The high carrier frequency of cystic fibrosis, if substantiated in larger population studies, would be sufficient ground toinitiate new-born screening in the Indian population.
One major limitation of this study is the small sample
size, and a larger studies would be justified to serve
as a valuable tool for reducing the burden of genetic
disorders.

Page 12 of 15

Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12881-020-01153-4.
Additional file 1. Case record proforma used in the study to record
clinical data.
Additional file 2: Table S1. table of disorders tested in the study.
Additional file 3: Tables S2 and S3. criteria used to assign
pathogenicity to variants (adapted from ACMG, 2015 variant classification
criteria).
Abbreviations
ACMG: American College of Medical Genetics; AR: Autosomal recessive;
AD: Autosomal Dominant; BDGP: Berkeley drosophila genome project;
BWA: Burrow wheeler aligner; CAH: Congenital adrenal hyperplasia;
CBAVD: Congenital bilateral absence of vas deferens; DMD: Duchenne
muscular dystrophy; ECS: Expanded carrier screening; FXS: Fragile X
syndrome; GWAS catalogue: Genome wide association study in man;
HGMD: Human gene pathogenic variant database; HSF: Human splicing
finder; IGV: Integrative genomics viewer; LRT: Likelihood ratio test; NGS: Next
generation sequencing; OMIM: Online mendelian inheritance in man;
SCID: Severe combined immunodeficiency; SIFT: Sorts intolerant fromtolerant; SMA: Spinal muscular atrophy; VEP: Variant effect predictor;
VUS: Variants of uncertain significance; XL: X linked
Acknowledgements
To the patients for their kind participation.
Authors’ contributions
ICV, SBM, RDP and VLR conceptualized and designed the details of the study.
KS enrolled the subjects and counselled them as a part of a thesis dissertation
under the guidance of ICV, SBM, RDP, SK1, KG and IG. VLR, SN and SS carriedout the next generation sequencing and analysis of molecular data. SK2 reanalysed all the molecular data, formatted the files and uploaded them on public database. RS and SK1 interpreted the variants and evaluated their occurrencein house database. KS and SBM re-checked the individual annotated variant
excel sheets, compiled all the results, carried out review of literature, and analysed the individual variants before post-test counselling of the individuals. KS,
SBM and ICV drafted the manuscript and carried out the subsequent revisions.
All authors read and approved the manuscript and agreed to be personally accountable for all the contributions in the manuscript.
Funding
The expense of NGS was funded by Medgenome Laboratories Pvt. Ltd.,
Bangalore, India. Medgenome Laboratories Pvt. Ltd., carried out the next
generation sequencing and molecular analysis. The data was re-analysed at
Sir Ganga Ram Hospital, New Delhi.
Availability of data and materials
The datasets generated and analysed during the current study are available in
the European Variation Archive (EVA) repository, under the study browser athttps://www.ebi.ac.uk/eva. The project number is PRJEB40310. The direct
weblink to the data files is https://www.ebi.ac.uk/ena/browser/view/PRJEB40310
The direct weblink to the human reference genome (GRCh37/hg19) dataset
used in this study is as follows: ftp://ftp.ensembl.org/pub/grch37/current/
fasta/homo_sapiens/dna/Accession numbers are also listed in Table 3 and Table 4 and their respective
datasets can be found in the Ensemble database.
The supplementary tables 2 and 3 provide the evidence of pathogenicity,and classification of pathogenic and likely pathogenic variants according to
ACMG guidelines, 2015.
Ethics approval and consent to participate
Ethical clearance was obtained by the Ethics committee, Sir Ganga Ram
Hospital, New Delhi prior to commencing the study (Ethical clearance
number EC/08/ 16/1066). All individuals were given pre-test counselling, informed about the disorders being tested and voluntary nature of participation. Written informed consent was obtained from all individuals prior to
testing.

Singh et al. BMC Medical Genetics(2020) 21:216

Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Institute of Medical Genetics and Genomics, Sir Ganga Ram Hospital, New
Delhi, India. 2Medgenome Laboratories Pvt Ltd., Bangalore, India. 3Institute of
Obstetrics and Gynaecology, Sir Ganga Ram Hospital, New Delhi, India.
Received: 17 April 2020 Accepted: 20 October 2020

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