Skip to main content

“Down syndrome: an insight of the disease”


Down syndrome (DS) is one of the commonest disorders with huge medical and social cost. DS is associated with number of phenotypes including congenital heart defects, leukemia, Alzeihmer’s disease, Hirschsprung disease etc. DS individuals are affected by these phenotypes to a variable extent thus understanding the cause of this variation is a key challenge. In the present review article, we emphasize an overview of DS, DS-associated phenotypes diagnosis and management of the disease. The genes or miRNA involved in Down syndrome associated Alzheimer’s disease, congenital heart defects (AVSD), leukemia including AMKL and ALL, hypertension and Hirschprung disease are discussed in this article. Moreover, we have also reviewed various prenatal diagnostic method from karyotyping to rapid molecular methods -  MLPA, FISH, QF-PCR, PSQ, NGS and noninvasive prenatal diagnosis in detail.


Down syndrome is one of the most leading causes of intellectual disability and millions of these patients face various health issues including learning and memory, congenital heart diseases(CHD), Alzheimer’s diseases (AD), leukemia, cancers and Hirschprung disease(HD). The incidence of trisomy is influenced by maternal age and differs in population (between 1 in 319 and 1 in 1000 live births) [1-5]. DS has high genetic complexity and phenotype variability [6-8]. Trisomic fetuses are at elevated risk of miscarriages and DS people have increased incidence of developing several medical conditions [9]. Recent advancement in medical treatment with social support has increased the life expectancy for DS population. In developed countries, the average life span for DS population is 55 years [10].

Figure 1
figure 1

Various conditions associated with Downs’s syndrome with its causative genes.


Human Chromosome 21

DS complex phenotype results from dosage imbalance of genes located on human chromosome 21(Hsa 21). The genetic nature of DS together with the relatively small size of Hsa 21 encouraged scientist to concentrate efforts towards the complete characterization of this chromosome in the past few years. The length of 21q is 33.5 Mb [11] and 21 p is 5–15 Mb [12]. A total 225 genes was estimated when initial sequence of 21q was published [11]. Hsa 21 has 40.06% repeat content out of which the repeat content of SINE’s, LINE’s, and LTR are 10.84%, 15.15%, 9.21% respectively. The Table 1 given below highlights some of the genes present on chromosome 21.

Table 1 Some common gene present in chromosome 21

Features of DS

There are various conserved features occurring in all DS population, including learning disabilities, craniofacial abnormality and hypotonia in early infancy [13]. Some people of DS are affected by variant phenotypes including atrioventricular septal defects (AVSD) in heart, leukemia’s (both acute megakaryoblastic leukemia(AMKL) and acute lymphoblastic leukemia(ALL)), AD and HD. DS individual have variety of physical characteristics like a small chin, slanted eye, poor muscle tone, a flat nasal bridge, a single crease of the palm and a protuding due to small mouth and large tongue [14]. Other features includes big toe, abnormal pattern of fingerprint and short fingers.

Genetics of the disease

The most common cause of having a DS babies is presence extra copy chromosome 21 resulting in trisomy. The other causes can be Robertsonian translocation and isochromosomal or ring chromosome. Ischromosome is a term used to describe a condition in which two long arms of chromosome separate together rather than the long and short arm separating together during egg sperm development. Trisomy 21 (karyotype 47, XX, + 21 for females and 47, XY, + 21 for males) is caused by a failure of the chromosome 21 to separate during egg or sperm development. In Robertsonian translocation which occurs only in 2-4% of the cases, the long arm of the chromosome 21 is attached to another chromosome (generally chromosome 14). While mosaicism deals with the error or misdivision occurs after fertilization at some point during cell division. Due to this people with mosaic DS have two cell lineages which contribute to tissues and organs of individuals with Mosacism (one with the normal number of chromosomes, and other one with an extra number 21) [15].

Genotype-phenotype correlation

Gene dosage imbalance hypothesis states that DS patients have an increased dosage or copy number of genes on Hsa 21 that may lead to an increase in gene expression [13-15]. This hypothesis has been extended to include the possibility that specific genes or subsets of genes may control specific DS phenotypes [16]. Amplified developmental instability hypothesis states that a non-specific dosage of a number of trisomic genes leads to a genetic imbalance that causes a great impact on the expression and regulation of many genes throughout the genome [13, 14]. Another hypothesis known as critical region hypothesis was also added to this list. Phenotypic analyses was done on individuals with partial trisomy for Hsa21 identified that only one or a few small chromosomal regions, termed “Down syndrome critical regions” (DSCR) a region of 3.8-6.5 Mb on 21q21.22, with approximately 30 genes responsible for the majority of DS phenotypes [15,16]. Previously a region of 1.6 to 2.5 Mb was recognised as sufficient cause for DS pehnotype [17, 18]. The sequencing of Hsa 21 proved to be an important factor in the progression of DS research [19] and led to further insight into genotype-phenotype correlations associated with DS and precise characterizations of DSCR regions [13]. A “critical region” within 21q22 was believed to be responsible for several DS phenotypes including craniofacial abnormalities, congenital heart defects of the endocardial cushions, clinodactyly of the fifth finger and mental retardation [20].

Dual-specificity tyrosine phosphorylation-regulated kinase (DYRK1A) and regulator of calcineurin 1 (RCAN1), Down syndrome cell adhesion molecule (DSCAM) has been suggested to play a critical role in the developing brain and has also been identified as a candidate gene for the increased risk of CHD in DS individuals [21,22]. DSCAM is a critical factor in neural differentiation, axon guidance, and the establishment of neural networks and it has been suggested that the disruption of these processes contributes to the DS neurocognitive phenotype [22]. Based on thorough analyses of studies on humans and DS mouse models, it is evident that there is not a single critical region of genes sufficient to cause all DS phenotypes. Alternatively, it is likely that there are multiple critical regions or critical genes contributing to a respective phenotype or group of phenotypes associated with DS [23].

Various clinical conditions associated to Down syndrome

The various clinical conditions associated with DS are Alzheimer’s disease, heart defects, leukemia, hypertension and gastrointestinal problems (Figure 1). The molecular pathogenesis mechanism of these DS related phenotype must be studied along with its causative agents in order to have a better understanding of the disease. Below are some DS related phenotype discussed in detail which are as follows:

Neurological problems

DS patients have greatly increased risk of early onset AD. After the age of 50, the risk of developing dementia increases in DS patients up to 70% [23-27]. There are various genes reported to cause early onset AD. Some of the genes described in the current literature are APP (amyloid precursor protein), BACE2 (beta secretase 2), PICALM (Phosphatidylinositol binding clathrin assembly protein) and APOE(Apolipoprotein E) etc. APP is an integral membrane protein which is concentrated in synapse of neurons and trisomy of this protein is likely to make significant contribution to the increased frequency of dementia in DS individuals. The triplication of Hsa 21 along with APP in people without DS has been recently shown to be associated with early onset AD. A tetranucleotide repeat, ATTT , in intron 7 of the amyloid precursor protein has been associated with the age of onset of AD in DS in a preliminary study [28]. Various mouse models are used to observe degeneration of basal forebrain cholinergic neurons (BFCNs). Ts65Dn mice is dependent on trisomy of APP expression of retrograde axonal transport [29]. Studies have also revealed that BACE2 which encodes enzyme beta secretase 2 is also involved in AD. APP and BACE 2 genes are located on chromosome 21. The current data on DS support the association of haplotypes in BACE2 with AD [30]. Besides APP and BACE2 genes, other genes like PICALM and APOE are also found to be associated with the age of onset of Alzheimer’s dimentia in DS [31].

Cardiac problems

The incidence of CHD in newborn babies with DS is up to 50% [32]. Endocardial cushion defect also called as atrioventricular cushion defect is most common form which affects up to 40% of the patients. Ventricular septal defect (VSD) is also present in these population which affects up to 35% of the patients [33]. The essential morphological hallmark of an AVSD is the presence of a common atrioventricular junction as compared to the separate right and left atrioventricular junction in the normal heart. Other morphological features include defects of the muscular and membranous atrioventricular septum and an ovoid shape of the common atrioventricular junction. There is disproportion of outlet and inlet dimensions of the left ventricle, with the former greater than the latter as compared to the normal heart where both dimensions are similar [34]. While in case of VSD, the defect lies in ventricular septum of the heart due to which some of the blood from the left ventricle leaks into the right ventric leading to pulmonary hypertension. Mutation in non Hsa 21 CRELD1 (Cysteine rich EGF like domain1) gene contributes to the development of AVSD in DS [35]. CRELD1 is located on chromosome 3p25. It encodes a cell surface protein that functions as cell adhesion molecule and is expressed during cardiac cushion development. CRELD1 gene contains 11 exons spanning approximately 12 kb [36]. To the present, two specific genetic loci for AVSD have been identified. One was AVSD 1 locus present on chromosome 1p31-p21 [37]. Other locus was present on chromosome 3p25 and the corresponding gene was CRELD1 [36,38]. Maslen et al. in [33] have identified two heterozygous missense mutation (p.R329C and p.E414K) with two subjects in DS and AVSD. They have recruited 39 individual of DS with complete AVSD and have found the same mutations. In the same study, DNA of 30 individual of trisomy without CHD was studied for both mutations, no such mutation was identified [35]. R329C which was originally reported in an individual with sporadic partial AVSD and now it is also detected in individual of DS with AVSD. Interestingly, with the same mutation (p.R329C), the severity of heart defect was greater in patients of DS with AVSD. Thus, identification of CRELD 1 mutation in 2/39 individual (5.1%) of DS with complete AVSD suggests the defects in CRELD 1 contribute to pathogenesis of AVSD in context with trisomy 21.

Hematological problems

Patients with DS display a unique spectrum of malignancies, which include leukemia’s as well as solid tumors. The first report of leukemia in a DS patient occurred in 1930 [39] and the first systematic study in 1957 [40]. Studies indicate that patients with DS have a 10–20 fold increased relative risk of leukemia, with a cumulative risk of 2% by age 5 and 2.7% by age 30 [41]. They constitute approximately 2% of all pediatric acute lymphoblastic leukemia(ALL) and approximately 10% of pediatric acute myeloid leukemia (AML). Leukemogenesis of acute megakaryoblastic leukemia (AMKL) in DS patients is associated with the presence of somatic mutations involving GATA 1 gene (or also called as GATA-binding factor 1) [42]. GATA 1 is a chromosome X- linked transcription factor which is essential for erythoid and megakaryocytic differentiation. Because of these GATA 1 mutations, there is a production of shorter GATA 1 protein thereby leading to uncontrolled proliferation of immature megakaryocytes [42,43]. On the other hand, acquired gain of function mutation in Janus Kinase 2 gene are present in approximately 30% of cases with ALL in DS [44,45].


People with DS have been reported to have a reduced incidence of hypertension [46,47]. Trisomy of the Hsa21 microRNA hsa-miR-155 contributes to this [48]. Hsa-miR-155 is proposed to specifically target one allele of the type-1 angiotensin II receptor (AGTR1) gene, resulting in it’s under- expression, which contribute to a reduced risk of hypertension. Further studies are required to validate this hypothesis and determine whether other genes may also protect people with DS against hypertension.

Gastrointestinal problems

DS patients constitute ~12% of all cases of HD. Duodenal stenosis (DST) and imperforate anus (IA) are 260 and 33 times more likely to occur DS [23,49]. HD is a form of low intestinal obstruction caused by the absence of normal myenteric ganglion cells in a segment of the colon [50]. In HD children, the absence of ganglion cells results in the failure of the distal intestine to relax normally. Peristaltic waves do not pass through the aganglionic segment and there is no normal defecation, leading to functional obstruction. Abdominal distention, failure to pass meconium, enterocolitis and bilious vomiting are the predominant signs and symptoms and appear within a few days after birth. Infants with duodenal atresia or DST present with bilious vomiting early in the neonatal period. If left untreated, it will result in severe dehydration and electrolyte imbalance. IA is a birth defects in which the rectum is malformed and it is associated with an increased incidence of some other specific anomalies as well, together being called the VACTERL association: vertebral anomalies, anal atresia, cardiovascular anomalies, tracheoesophageal fistula, esophageal atresia, renal and limb defects.

Alterations of approximately 10 non Hsa21 genes have been linked to this disease [51]. Several researches have shown that HD contain the DSCAM gene which is expressed in neural crest that give rise to enteric nervous system [49]. Overlapping critical region was described both for DST and IA [51]. No other Hsa21 genes have been implicated so far.

Diagnostic methods

Prevention of DS depends upon offering prenatal diagnosis to high risk pregnancies via amniocentesis and chorionic villus sampling (CVS). Amniocentesis and CVS are quite reliable but offers risk of miscarriage of between 0.5 to 1% [52]. Based soft markers like small or no nasal bone, large ventricles and nuchal fold thickness, the risk of DS for fetus can be identified through ultrasound generally at 14 to 24 weeks of gestation [53]. Increased fetal nuchal translucency indicates an increased risk of DS [54]. The other methods used for prenatal diagnosis in which traditional cytogenic analysis is still widely used in different countries. However some rapid molecular assays-FISH(fluorescent in situ hybridization), QF-PCR (quantitative fluorescence PCR), and MLPA(multiplex probe ligation assay)- also used for prenatal diagnosis.

Routine karyotyping

Cytogenetic analysis of metaphase karyotype remains the standard practice to identify not only trisomy 21, but also all other aneuploidies and balanced translocations. Details on diagnostic methods with advantages and disadvantages are mentioned in Table 2.

Table 2 Common techniques used for diagnosis of Down’s syndrome along with its advantages and disadvantages

Rapid aneuploidy testing methods

Over the past 10 years however, several other methods have been developed and used for the rapid detection of trisomy 21, either in fetal life or after birth. The most widely used is FISH of interphase nuclei, using Hsa 21-specific probes or whole-Hsa 21 [55]. An alternative method that is now widely used in some countries is QF-PCR, in which DNA polymorphic markers (microsatellites) on Hsa 21 are used to determine the presence of three different alleles [56]. This method relies on informative markers and the availability of DNA. Rapid diagnosis by PCR-based methods using polymorphic STR markers may reduce these difficulties using conventional approach. Using STR markers method we can detect trisomy in 86.67% cases with only two markers. Using more number of markers can further increase the reliability of the test. Simultaneously parental origin of the nondysjunction can also be detected [57,58]. Additional method to measure copy number of DNA sequences include MLPA [59] which was first introduced in 2002 as a method of relative quantification in DNA. MLPA offers various advantages like – a very short time for diagnosis (2–4 days), effectiveness, simplicity and relatively low costs. It is based on hybridization and PCR method and is divided into four steps: DNA denaturation, hybridization of probe to the complementary target sequence, probe ligation and PCR amplification. And finally capillary electrophoresis of PCR amplified products is carried out. However MLPA is unable to exclude low level placental and true mosaicism [60].

Advancement in the diagnosis

A recent method, termed paralogous sequence quantification (PSQ), uses paralogous sequences to quantify the Hsa 21 copy number. PSQ is a PCR based method for the detection of targeted chromosome number abnormalities termed paralogous sequence quantification (PSQ), based on the use of paralogous genes. Paralogous sequences have a high degree of sequence identity, but accumulate nucleotide substitutions in a locus specific manner. These sequence differences, which are termed as paralogous sequence mismatches (PSMs), can be quantified using pyrosequencing technology, to estimate the relative dosage between different chromosomes. PSQ is a robust, easy to interpret, and easy to set up method for the diagnosis of common aneuploidies, and can be performed in less than 48 h, representing a competitive alternative for widespread use in diagnostic laboratories. The sequencing is quantitatively done by using pyrosequencing [61]. Finally, comparative genomic hybridization (CGH) on BAC chips can be used for the diagnosis of full trisomy or monosomy, and for partial (segmental) aneuploidies [62,63].

Noninvasive Prenatal diagnosis

Fetal cells in maternal ciruculation: Ever since the discovery of presence of fetal lymphocytes in maternal blood was made in 1969, the investigators are trying to develop genetics-based noninvasive prenatal diagnostics (NIPD) [64]. Despite several advantages offered by this approach, the use of fetal cells for NIPD has never reached clinical implementation because of their paucity (on the order of a few cells per milliliter of maternal blood) and concerns of fetal cell persistence in the maternal circulation between pregnancies.

Cell free fetal DNA from maternal serum: This novel approach was proposed in 1997. Cell-free fetal DNA constitutes between 5% and 10% of the total DNA in maternal plasma and increases during gestation and rapidly clears from the circulation post delivery. Several clinical applications based on the analysis of cell-free fetal DNA have been developed like determining fetal Rh D status in Rh D-negative women [65], sex in sex-linked disorders [66,67], and detection of paternally inherited autosomal recessive and dominant mutations [68]. However, there remains the outstanding challenge of the use of cell-free fetal DNA for the detection of chromosomal aneuploidy, in particular trisomies 21, 18, and 13. Several approaches have been adopted like the origin of circulating cell-free fetal DNA is primarily the placenta, whereas maternal cell-free DNA is derived from maternal leukocytes [69]. The approach includes studying differences in genomic DNA methylation between the placenta and paired maternal leukocytes, investigators have characterized placenta-specific epigenetic markers [70] and also finding of circulating cell-free placenta-derived mRNA allowed the identification of placenta-specific mRNA production [71].

The concept of digital PCR was also introduced to serve the same purpose. In digital PCR, individual fetal and maternal circulating cell-free DNA fragments are amplified under limiting-dilution conditions and the total number of chromosome 21 amplifications (representing maternal plus fetal contributions) divided by the number of reference chromosome amplifications should yield a ratio indicating an over- or underrepresentation of chromosome 21.

Although the digital PCR approach is conceptually solid, the low percentage of cell-free fetal DNA in the maternal plasma sample requires the performance of thousands of PCRs to generate a ratio with statistical confidence. This can be overcome by using of multiple target amplifications and enrichment of cell-free fetal DNA which are still under research trail.

Next recent method added to the list is next generation sequencing (NGS) which is based on the principle of clonally amplified DNA templates (or, most recently, single DNA molecules) are sequenced in a massively parallel fashion within a flow cell [72,73]. NGS provides digital quantitative information, in which each sequence read is a countable “sequence tag” representing an individual clonal DNA template or a single DNA molecule. This quantification allows NGS to expand the digital PCR concept of counting cell-free DNA molecules.

Fan et al. and Chiu et al. in 2008 described noninvasive detection of trisomy 21 by NGS [74]. Both groups extracted cell-free DNA from maternal plasma samples from both euploid and trisomy pregnancies. DNA from each sample was sequenced on the Illumina Genome Analyzer, and each sequence read was aligned to the reference human genome. Chiu et al. build on their earlier work with the Illumina Genome Analyzer and demonstrate noninvasive NGS-based trisomy 21 detection with the sequencing-by-ligation approach on the Life Technologies SOLiD platform [75]. Cell-free DNA was extracted from 15 pregnant women, 5 of whom carried trisomy 21 fetuses and it was clonally amplified by emulsion PCR, and sequenced in 1 chamber of an 8-chamber SOLiD slide. This process yielded a median of 59 × 106 50-base reads per sample. A median of 12 × 106 reads (or 21%) were each aligned uniquely to one location of the reference human genome (with masking of repeat regions), for a coverage of approximately 20% of the haploid human genome. For each trisomy 21 case, the chromosome 21 z score value indicated a 99% chance of a statistically significant difference from the chromosome 21 z scores for the controls. As reported earlier with the Illumina Genome Analyzer, a nonuniform distribution of aligned sequence reads was observed with the SOLiD data.

The current time for sample processing, sequencing, and data interpretation in experienced hands is 5 to 8 days for the Genome Analyzer and SOLiD platforms respectively with the cost of approximately $700 – $1000 per sample. Going forward, one can expect streamlining and automation of technical processes and data analysis, coupled with reduced sequencing costs.

Ultimately, reduced sequencing costs and turnaround times could pave the way for NGS-based NIPD to be considered as an alternative to serum biomarker screening, which,while cost-effective remains prone to false positives. Forty years after the discovery of circulating fetal cells, the vision of NIPD appears clearer and closer.

Management of the disease

One of the hallmarks of DS is the variability in the way that the condition affects people with DS. With the third 21st chromosome existing in every cell, it is not surprising to find that every system in the body is affected in some way. However, not every child with DS has the same problems or associated conditions. Parents of children with DS should be aware of these possible conditions so they can be diagnosed and treated quickly and appropriately. The goal of the study is to point out the most common problems of which parents should be aware.

Timely surgical treatment of cardiac defects during first 6 months of life may prevent from serious complications. Congenital cataracts occur in about 3% of children and must be extracted soon after birth to allow light to reach the retina. A balance diet and regular exercise are needed to maintain appropriate weight. Feeding problems and failure to thrive usually improve after cardiac surgery. A DS child should have regular check up from various consultants. These include:

  • Clinical geneticist - Referral to a genetics counseling program is highly desirable

  • Developmental pediatrician

  • Cardiologist - Early cardiologic evaluation is crucial for diagnosing and treating congenital heart defects, which occur in as many as 60% of these patients

  • Pediatric pneumonologist -Recurrent respiratory tract infections are common in patients with DS

  • Ophthalmologist

  • Neurologist/Neurosurgeon – As many as 10% of patients with DS have epilepsy; therefore, neurologic evaluation may be needed

  • Orthopedic specialist

  • Child psychiatrist - A child psychiatrist should lead liaison interventions, family therapies, and psychometric evaluations

  • Physical and occupational therapist

  • Speech-language pathologist

  • Audiologist


DS or Trisomy 21, being the most common chromosomal abnormality among live born infants, is associated with a number of congenital malformations. Several theories have been put forward to increase our understanding in phenotype and genotype correlation. A “critical region” within 21q22 was believed to be responsible for several DS phenotypes including craniofacial abnormalities, congenital heart defects of the endocardial cushions, clinodactyly of the fifth finger and mental retardation and several other features. The primary goal of this review is to unravel the common genes involved in DS associated phenotypes, including APP, BACE2, PICALM, APOE, GATA 1, JAK 2, CRELD 1 and DSCAM. This reviews also provides the detailed description on the application of techniques to prenatal diagnosis in DS. Rapid aneuploidy testing has been introduced in mid 1990’s in the form of FISH where testing can be done on uncultured amniocytes. Within a couple of years, MLPA and QF-PCR has been added in the list of rapid aneuploidy testing. The other methods includes: NGS for cell free fetal DNA screening for maternal plasma. Except ,FISH, MLPA and QF-PCR other method are not commercialized for aneuploidy diagnosis due to their running cost, labor intensive protocol and complex data analysis. Since various clinical conditions are associated with DS, hence the management of these patients requires an organized multidisciplinary approach and continuous monitoring of these patients which has been discussed in this review article.


  1. O’ Nuallain S, Flanagan O, Raffat I, Avalos G, Dineen B. The prevalence of Down syndrome in County Galway. Ir Med. 2009;100:329–31.

    Google Scholar 

  2. Carothers AD, Hecht CA, Hook EB. International variation in reported live birth prevalence rates of Down syndrome, adjusted for maternal age. J Med Genet. 1999;36:386–93.

  3. Canfield MA, Honein MA, Yuskiv N, Xing J, Mai CT, Collins JS, et al. National estimates and race/ethnic-specific variation of selected birth defects in the United States. Birth Defects Res A Clin Mol Teratol. 2006;76:747–56.

  4. Murthy SK, Malhotra AK, Mani S, Shara ME, Al Rowaished EE, Naveed S, et al. Incidence of Down syndrome in Dubai. Med Princ Pract. 2007;16:25–8.

    Article  PubMed  Google Scholar 

  5. Wahab AA, Bener A, Teebi AS. The incidence patterns of Down syndrome in Qatar. Clin Genet. 2006;69:360–2.

    Article  PubMed  Google Scholar 

  6. Mégarbané A, Ravel A, Mircher C, Sturtz F, Grattau Y, Rethoré MO et al. The 50th anniversary of the discovery of trisomy 21: the past, present, and future of research and treatment of Down syndrome. Genet Med. 2009;11:611–6.

    Article  PubMed  Google Scholar 

  7. Gardiner KJ. Molecular basis of pharmacotherapies for cognition in Down syndrome. Trends Pharmacol Sci. 2010;31:66–73.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Prandini P, Deutsch S, Lyle R, Gagnebin M, Delucinge Vivier C, Delorenzi M et al. Natural gene-expression variation in Down syndrome modulates the outcome of gene-dosage imbalance. Am J Hum Genet. 2007;81:252–63.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Morris JK, Wald NJ, Watt HC. Fetal loss in Down syndrome pregnancies. Prenat Diagn. 1999;19:142–5.

    Article  CAS  PubMed  Google Scholar 

  10. Glasson EJ, Sullivan SG, Hussain R, Petterson BA, Montgomery PD, Bittles AH, et al. The changing survival profile of people with Down’s syndrome: implications for genetic counselling. Clin Genet. 2002;62:390–3.

    Article  CAS  PubMed  Google Scholar 

  11. Lyle R, Bena F, Gagos S, Gehrig C, Lopez G, Schinzel A, et al. Genotype–phenotype correlations in Down syndrome identified by array CGH in 30 cases of partial trisomy and partial monosomy chromosome 21. Eur J Hum Genet. 2009;17:454–66.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Ermak G, Harris CD, Battocchio D, Davies KJ. RCAN1 (DSCR1 or Adapt78) stimulates expression of GSK-3beta. FEBS J. 2006;273:2100–9.

    Article  CAS  PubMed  Google Scholar 

  13. Antonarakis SE, Lyle R, Dermitzakis ET, Reymond A, Deutsch S. Chromosome 21 and Down syndrome: from genomics to pathophysiology. Nat Rev Genet. 2004;5:725–38.

    Article  CAS  PubMed  Google Scholar 

  14. Sinet PM, Theopile D, Rahmani Z, Chettouch Z, Blovin JL, Prier M, et al. Mapping of Down syndrome phenotype on chromosome 21 at the molecular level. Biomed Pharmacother. 1994;48(5–6):247–52.

    Article  CAS  PubMed  Google Scholar 

  15. Epstein CJ, Scriver CR, Beaudet AL, Sly WS, Valle D, editors. The Metabolic & Molecular Bases of Inherited Disease. New York: McGraw-Hill; 2001. p. 1223–56.

    Google Scholar 

  16. Pritchard MA, Kola I. The "gene dosage effect" hypothesis versus the "amplified developmental instability" hypothesis in Down syndrome. J Neural Transm Suppl. 1999;57:293–303.

    CAS  PubMed  Google Scholar 

  17. Patterson D. Genetic mechanisms involved in the phenotype of Down syndrome. Ment Retard Dev Disabil Res Rev. 2007;13:199–206.

    Article  PubMed  Google Scholar 

  18. Shapiro BL. Down syndrome–a disruption of homeostasis. Am J Med Genet. 1983;14:241–69.

    Article  CAS  PubMed  Google Scholar 

  19. Delabar JM, Theophile D, Rahmani Z, Chettouh Z, Blouin JL, Prieur M, et al. Molecular mapping of twenty-four features of Down syndrome on chromosome 21. Eur J Hum Genet. 1993;1:114–24.

    CAS  PubMed  Google Scholar 

  20. Ohira M, Ichikawa H, Suzuki E, Iwaki M, Suzuki K, Saito-Ohara F, et al. A 1.6-Mb P1-based physical map of the Down syndrome region on chromosome 21. Genomics. 1996;33:65–74.

    Article  CAS  PubMed  Google Scholar 

  21. Korbel JO, Tirosh-Wagner T, Urban AE, Chen XN, Kasowski M, Dai L, et al. The genetic architecture of Down syndrome phenotypes revealed by high-resolution analysis of human segmental trisomies. Proc Natl Acad Sci U S A. 2009;106:12031–6.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Niebuhr E. Down's syndrome. The possibility of a pathogenetic segment on chromosome no. 21. Humangenetik. 1974;21:99–101.

    CAS  PubMed  Google Scholar 

  23. Holland AJ, Hon J, Huppert FA, Stevens F. Incidence and course of dementia in people with Down’s syndrome: findings from a population-based study. J Intellect Disabil Res. 2000;44:138–46.

    Article  PubMed  Google Scholar 

  24. Holland AJ, Hon J, Huppert FA, Stevens F, Watson P. Population-based study of the prevalence and presentation of dementia in adults with Down’s syndrome. Br J Psychiatry. 1998;172:493–8.

    Article  CAS  PubMed  Google Scholar 

  25. Janicki MP, Dalton AJ. Prevalence of dementia and impact on intellectual disability services. Ment Retard. 2000;38:276–88.

    Article  CAS  PubMed  Google Scholar 

  26. Johannsen P, Christensen JE, Mai J. The prevalence of dementia in Down syndrome. Dementia. 1996;7:221–5.

    CAS  PubMed  Google Scholar 

  27. Lai F, Williams RS. A prospective study of Alzheimer disease in Down syndrome. Arch Neurol. 1989;46:849–53.

    Article  CAS  PubMed  Google Scholar 

  28. EL Jones, CG Ballard, VP Prasher, M Arno, S Tyrer, B Moore et al. An Intron 7 polymorphism in APP affects the age of Dimentia in Down Syndrome. Int J Alzheimers Dis. 2011;5. doi:10.4061/2011/929102

  29. Salehi A, Delcroix JD, Belichenko PV, Zhan KWC, Valletta JS, Takimoto-Kimura, et al. Increased App expression in a mouse model of Down’s syndrome disrupts NGF transport and causes cholinergic neuron degeneration. Neuron. 2006;51:29–42.23.

    Article  CAS  PubMed  Google Scholar 

  30. Myllykangas L, Wavrant –De Vrieze F, Polvikoski T, Notkola IL, Sulkava R, Niinisto L. Chromosome 21 BACE2 haplotype associates with Alzheimer's disease: a two-stage study. J Neurol Sci. 2005;236(1–2):17–24.

    Article  CAS  PubMed  Google Scholar 

  31. Jones EL, Mok K, Hanney M, Harold D, Sims R, Williams J. Evidence that PICALM affects age at onset of Alzheimer’s dementia in Down syndrome. Neurobiol Aging. 2013;34(10):244.

    Article  Google Scholar 

  32. Urbano R. Health issues among person with down syndrome. 2012.

  33. Maslen CL, Babcock D, Robinson SW, Bean LJ, Dooley KJ, Willour VL, et al. CRELD1 mutations contribute to the occurrence of cardiac atrioventricular septal defects in Down syndrome. Am J Med Genet. 2006;140:2501–5.

  34. Craig B. Atrioventricular septal defect: from fetus to adult. Heart. 2006;92(12):1879–85.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Rup PA, Fouad GT, Egelston CA, Reifsteck CA, Oslon SB, Knosp WM, et al. Identification, genomic organization and mRNA expression of CRELD1, the founding member of a unique family of matricellular proteins. Gene. 2002;293:47–57.

    Article  Google Scholar 

  36. Sheffield VC, Pierpont ME, Nishimura D, Beek JS, Burns TL, Berg MA, et al. Identification of a complex congenital heart defect susceptibility locus by using DNA pooling and shared segment analysis. Hum Mol Genet. 1997;6:117–21.

    Article  CAS  PubMed  Google Scholar 

  37. Priestley MD, Water J, Maliszewska C, Latif F, Maher ER. Detailed mapping of a congenital heart disease gene in chromosome 3p25. J Med Genet. 2000;37:581–7.

    Article  PubMed Central  PubMed  Google Scholar 

  38. Robinsom SW, Morris CD, Goldmuntz E, Reller MD, Jones MA, Maslen CL, et al. Missense mutation in CRELD1 are associated with cardiac atrioventricular septal defects. Am J Hum Genet. 2003;72:1047–52.

    Article  Google Scholar 

  39. Brewster HF, Cannon HE. Acute lymphatic leukemia: Report of a case in eleventh month mongolina idiot. New Orleans Med Surg J. 1930;82:872–3.

    Google Scholar 

  40. Krivit W, Good RA. Simultaneous occurrence of mongolism and leukemia; report of a nationwide survey. AMA J Dis Child. 1957;94:289–93.

    Article  CAS  PubMed  Google Scholar 

  41. Hasle H, Clemmensen IH, Mikkelsen M. Risks of leukaemia and solid tumours in individuals with Down’s syndrome. Lancet. 2000;355:165–9.

    Article  CAS  PubMed  Google Scholar 

  42. Wechsler J, Greene M, McDevitt MA, Anastasi J, Karp JE, Le Beau MM, et al. Acquired mutations in GATA1 in the megakaryoblastic leukemia of Down syndrome. Nat Genet. 2002;32(1):148–52.

    Article  CAS  PubMed  Google Scholar 

  43. Shivdasani RA, Fujiwara Y, McDevitt MA, Orkin SH. A lineage-selective knockout establishes the critical role of transcription factor GATA-1 in megakaryocyte growth and platelet development. EMBO J. 1997;16(13):3965–73.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  44. Kearney L, Gonzalez De Castro D, Yeung J, Procter J, Horsley SW, Eguchi-Ishimae M, et al. Specific JAK2 mutation (JAK2R683) andmultiple gene deletions in Down syndrome acute lymphoblastic leukemia. Blood. 2009;113(3):646–8.

    Article  CAS  PubMed  Google Scholar 

  45. Morrison RA, McGrath A, Davidson G, Brown JJ, Murray GD, Lever AF. Low blood pressure in Down’s syndrome, a link with Alzheimer’s disease? Hypertension. 1996;28:569–75.

    Article  CAS  PubMed  Google Scholar 

  46. Draheim CC, McCubbin JA, Williams DP. Differences in cardiovascular disease risk between nondiabetic adults with mental retardation with and without Down syndrome. Am J Ment Retard. 2002;107:201–11.

    Article  PubMed  Google Scholar 

  47. Sethupathy P, Borel C, Gagnebin M, Grant GR, Deutsch S, Elton TS, et al. Human microRNA-155 on chromosome 21 differentially interacts with its polymorphic target in the AGTR1 3’ untranslated region: a mechanism for functional single-nucleotide polymorphisms related to phenotypes. Am J Hum Genet. 2007;81:405–13.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  48. Torfs CP, Christianson RE. Anomalies in Down syndrome individuals in a large population-based registry. Am J Med Genet. 1998;77:431–8.

    Article  CAS  PubMed  Google Scholar 

  49. Berrocal T, Lamas M, Gutiérrez J. Congenital Anomalies of the Small Intestine, Colon, and Rectum. Radiographics Radiol Bras. 1999;19:1219–36.

    Article  CAS  Google Scholar 

  50. Amiel J, Sproat-Emison E, Garcia-Barcelo M, Lantieri F, Burzynski G, Borrego S, et al. Hirschsprung disease, associated syndromes and genetics: a review. J Med Genet. 2008;45:1–14.

    Article  CAS  PubMed  Google Scholar 

  51. Tabor A, Alfirevic Z. Update on procedure-related risks for prenatal diagnosis techniques. Fetal Diagn Ther. 2010;27(1):1–7.

    Article  PubMed  Google Scholar 

  52. Reena MS, Pisani PO Conversano F, Perrone E, Casciaro E, Renzo GCD et al. Sonographic markers for early diagnosis of fetal malformations. World J Radiol. 2013;10:356-371.

  53. Agathokleous M, Chaveeva P, Poon LC, Kosinski P, Nicolaides KH. Meta-analysis of second-trimester markers for trisomy 21. Ultrasound Obstetrics Gynecol. 2013;41(3):247–61.

    Article  CAS  Google Scholar 

  54. F.D. Malone, M.E D'Alton. First trimester sonographic screenign for Down syndrome. Obstetrics and Gynecology. 2003;102:1066-79.

  55. Kuo WL. Detection of aneuploidy involving chromosomes 13, 18, or 21, by fluorescence in situ hybridization (FISH) to interphase and metaphase amniocytes. Am J Hum Genet. 1991;49:112–9.

    CAS  PubMed Central  PubMed  Google Scholar 

  56. Shalu J, Sarita A, Inusha P, Parag T, Shubha P. Diagnosis of Down Syndrome and Detection of Origin of Nondisjunction by Short Tandem Repeat Analysis. Genetic Test Mol Biomark. 2010;14:4.

    Google Scholar 

  57. Shalu J, Inusha P, Shubha RP, Sarita A. Multiplex quantitative fluorescent polymerase chain reaction for detection of aneuploidies. Genet Test Mol Biomarker. 2012;16:624–7.

    Article  Google Scholar 

  58. Armour JA, Sismani C, Patsalis PC, Cross G. Measurement of locus copy number by hybridisation with amplifiable probes. Nucleic Acids Res. 2000;28:605–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  59. Slater HR, Bruno DL, Ren H, Pertile M, Schouten JP, Choo KH. Rapid, high throughput prenatal detection of aneuploidy using a novel quantitative method (MLPA). J Med Genet. 2003;40:907–12.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  60. Van Veghel-Plandsoen M, Wouters C, Kromosoeto J. Multiplex ligation-dependent probe amplification is not suitable for detection of low-grade mosaicism. Eur J Hum Genet. 2011;19:1009–12.

    Article  PubMed Central  PubMed  Google Scholar 

  61. S Deutsch, U Choudhury, SE Antonarakis. Detection of trisomy 21 and other aneuploidies by paralogous gene quantification. J Med Genet (in the press).

  62. Ishkanian AS, Malloff CA, Watson SK, DeLeeuw RJ, Chi B, Coe BP. A tiling resolution DNA microarray with complete coverage of the human genome. Nature Genet. 2004;36:299–303.

    Article  CAS  PubMed  Google Scholar 

  63. Snijders AM, Nowak N, Segraves R, Blackwood S, Brown N, Conroy J et al. Assembly of microarrays for genome- wide measurement of DNA copy number. Nature Genet. 2001;29:263–4.

    Article  CAS  PubMed  Google Scholar 

  64. Walknowska J, Conte FA, Grumbach MM. Practical and theoretical implications of fetal- maternal lymphocyte transfer. Lancet. 1969;1:1119–22.

    Article  CAS  PubMed  Google Scholar 

  65. Daniels G, Finning K, Martin P, Massey E. Noninvasive prenatal diagnosis of fetal blood group phenotypes: current practice and future prospects. Prenat Diagn. 2009;29:101–7.

    Article  CAS  PubMed  Google Scholar 

  66. Lo YM, Corbetta N, Chamberlain PF, Rai V, Sargent IL, Redman CW, et al. Presence of fetal DNA in maternal plasma and serum. Lancet. 1997;350:485–7.

  67. Costa JM, Benachi A, Gautier E. New strategy for prenatal diagnosis of X-linked disorders. N Engl J Med. 2002;346:1502.

    Article  PubMed  Google Scholar 

  68. Wright CF, Burton H. The use of cell-free fetal nucleic acids in maternal blood for non-invasive prenatal diagnosis. Hum Reprod Update. 2009;15:139–51.

    Article  CAS  PubMed  Google Scholar 

  69. Alberry M, Maddocks D, Jones M, Abdel Hadi M, Abdel-Fattah S, Avent N, et al. Free fetal DNA in maternal plasma in anembryonic pregnancies: confirmation that the origin is the trophoblast. Prenat Diagn. 2007;27:415–8.

  70. Chim SS, Jin S, Lee TY, Lun FM, Lee WS, Chan LY, et al. Systematic search for placental DNA-methylation markers on chromosome 21: toward a maternal plasma-based epigenetic test for fetal trisomy 21. Clin Chem. 2008;54:500–11.

    Article  CAS  PubMed  Google Scholar 

  71. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet. 2008;24:133–41.

    Article  CAS  PubMed  Google Scholar 

  72. Voelkerding KV, Dames SA, Durtschi JD. Next-generation sequencing: from basic research to diagnostics. Clin Chem. 2009;55:641–58.

    Article  CAS  PubMed  Google Scholar 

  73. Fan HC, Blumenfeld YJ, Chitkara U, Hudgins L, Quake SR. Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A. 2008;105:16266–71.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  74. Chiu RW, Chan KC, Gao Y, Lau VY, Zheng W, Leung TY, et al. Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. Proc Natl Acad Sci U S A. 2008;105:20458–63.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  75. Chiu RWK, Sun H, Akolekar R, Clouser C, Lee C, McKernan K, et al. Maternal plasma DNA analysis with massively parallel sequencing by ligation for noninvasive prenatal diagnosis of trisomy 21. Clin Chem. 2010;56:459–63.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Sarita Agarwal.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors' contribution

AA drafting of the manuscript, AS and MS, did substantial contribution in finalising, correcting and critical review of manuscript, KA and JS contributed in review and collection of articles. All authors read and approved the final manuscript.

Rights and permissions

Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit

The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Asim, A., Kumar, A., Muthuswamy, S. et al. “Down syndrome: an insight of the disease”. J Biomed Sci 22, 41 (2015).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: