Genetic Approach to Diagnosis of Intellectual Disability

Puri, Ratna Dua; Tuteja, Moni; Verma, Ishwar C.

doi:10.1007/s12098-016-2205-0

Cited by 9 publications

(6 citation statements)

References 42 publications

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“…These tests are used to confirm known or suspected diagnosis, carrier status determination, identification of at-risk genetic relatives, optimize treatments, and clinical decisions ( Gupta et al, 2017 ; Aravind et al, 2019 ; Uttarilli et al, 2019 ). There are different types of diagnostic genetic tests currently available in India such as single-gene and multigene testing, exome, and genome sequencing, carrier and newborn screening ( Puri et al, 2017 ; Singh et al, 2018 ). Other types of tests include those which assess reproductive risk, such as prenatal testing and preimplantation genetic diagnosis ( Dada et al, 2008 ).…”

Section: Current State Of Genetic Testingmentioning

confidence: 99%

A Review on the Challenges in Indian Genomics Research for Variant Identification and Interpretation

et al. 2020

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Today, genomic data holds great potential to improve healthcare strategies across various dimensions-be it disease prevention, enhanced diagnosis, or optimized treatment. The biggest hurdle faced by the medical and research community in India is the lack of genotype-phenotype correlations for Indians at a population-wide and an individual level. This leads to inefficient translation of genomic information during clinical decision making. Population-wide sequencing projects for Indian genomes help overcome hurdles and enable us to unearth and validate the genetic markers for different health conditions. Machine learning algorithms are essential to analyze huge amounts of genotype data in synergy with gene expression, demographic, clinical, and pathological data. Predictive models developed through these algorithms help in classifying the individuals into different risk groups, so that preventive measures and personalized therapies can be designed. They also help in identifying the impact of each genetic marker with the associated condition, from a clinical perspective. In India, genome sequencing technologies have now become more accessible to the general population. However, information on variants associated with several major diseases is not available in publicly-accessible databases. Creating a centralized database of variants facilitates early detection and mitigation of health risks in individuals. In this article, we discuss the challenges faced by genetic researchers and genomic testing facilities in India, in terms of dearth of public databases, people with knowledge on machine learning algorithms, computational resources and awareness in the medical community in interpreting genetic variants. Potential solutions to enhance genomic research in India, are also discussed.

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Section: Current State Of Genetic Testingmentioning

confidence: 99%

A Review on the Challenges in Indian Genomics Research for Variant Identification and Interpretation

et al. 2020

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“…In Mexico and other developing countries, the genetic approach for patients with intellectual disability (ID) and congenital malformations (CM) uses conventional G-banded karyotyping as the first-choice diagnostic test. It is usually performed at a 500-band level that allows the detection of 5–10 Mb abnormalities and results in an etiological diagnosis in approximately 3–10% of patients with a suspected chromosomopathy [ 1 – 3 ]. However, some structurally abnormal chromosomes with rearrangements larger than 5 Mb may go unnoticed by conventional cytogenetics.…”

Section: Introductionmentioning

confidence: 99%

“…However, some structurally abnormal chromosomes with rearrangements larger than 5 Mb may go unnoticed by conventional cytogenetics. This may occur with derivative chromosomes, which are unbalanced intra- or inter-chromosomal rearrangements, in which the exchanged segments share a similar size and banding pattern, making them difficult to identify by conventional karyotyping [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Derivative chromosomes involving 5p large rearranged segments went unnoticed with the use of conventional cytogenetics

et al. 2018

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BackgroundIn countries where comparative genomic hybridization arrays (aCGH) and next generation sequencing are not widely available due to accessibility and economic constraints, conventional 400–500-band karyotyping is the first-line choice for the etiological diagnosis of patients with congenital malformations and intellectual disability. Conventional karyotype analysis can rule out chromosomal alterations greater than 10 Mb. However, some large structural abnormalities, such as derivative chromosomes, may go undetected when the analysis is performed at less than a 550-band resolution and the size and banding pattern of the interchanged segments are similar. Derivatives frequently originate from inter-chromosomal exchanges and sometimes are inherited from a parent who carries a reciprocal translocation.Case presentationWe present two cases with derivative chromosomes involving a 9.1 Mb 5p deletion/14.8 Mb 10p duplication in the first patient and a 19.9 Mb 5p deletion/ 18.5 Mb 9p duplication in the second patient. These long chromosomal imbalances were ascertained by aCGH but not by conventional cytogenetics. Both patients presented with a deletion of the Cri du chat syndrome region and a duplication of another genomic region. Each patient had a unique clinical picture, and although they presented some features of Cri du chat syndrome, the phenotype did not conclusively point towards this diagnosis, although a chromosomopathy was suspected.ConclusionsThese cases highlight the fundamental role of the clinical suspicion in guiding the approach for the etiological diagnosis of patients. Molecular cytogenetics techniques, such as aCGH, should be considered when the clinician suspects the presence of a chromosomal imbalance in spite of a normal karyotype.

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“…Nonsyndromic ID is characterized by a lack of known pathology 1. ID is a common problem in children with a reported frequency of ~2%–3% 2. The severity of ID has been based on the IQ score (ID defined as an IQ score of <70, at the age of ≥5 years).…”

Section: Introductionmentioning

confidence: 99%

Metabolic screening and its impact in children with non-syndromic intellectual disability

Ali¹,

El-Morshedy²,

Elsayed³

et al. 2017

NDT

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ObjectiveThe objective of this study was to analyze the value of routine metabolic screening tests in children with an intellectual disability (ID) and its impact on improving their outcome and quality of life through appropriate intervention and treatment.Patients and methodsThis cross-sectional study was conducted in the Pediatric Neurology Clinic, Al Khafji Joint Operations Hospital, Kingdom of Saudi Arabia. A total of 150 children with nonsyndromic ID (66% males) in the age range of 5–17 years were compared with 50 apparently healthy age- and sex-matched controls. All studied groups were subjected to detailed history taking, family pedigree, thorough clinical examination, anthropometric measurements, routine laboratory investigations and urine metabolic screening tests (ferric chloride test and toluidine blue spot test and gas chromatography–mass spectrometry). Electroencephalography, IQ, psychiatric assessment and chromosomal study were done for the patient group only.ResultsPositive consanguineous marriage, older maternal or paternal age and family history of mental disabilities in other siblings were considered as risk factors for the development of mental disabilities. History of admission to neonatal intensive care unit was significantly higher among the patient group than among the controls (P<0.05). Metabolic screening tests showed that up to 35% of patients were positive for ferric chloride test, 9% of patients were positive for gas chromatography–mass spectrometry, and only 7 out of 150 (4.7%) patients were toluidine blue test positive.ConclusionMetabolic testing should be considered in the workup of individuals with nonsyndromic ID, which will need further specific investigations to confirm the diagnosis and determine the possible treatable cases.

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Genetic Approach to Diagnosis of Intellectual Disability

Cited by 9 publications

References 42 publications

A Review on the Challenges in Indian Genomics Research for Variant Identification and Interpretation

A Review on the Challenges in Indian Genomics Research for Variant Identification and Interpretation

Derivative chromosomes involving 5p large rearranged segments went unnoticed with the use of conventional cytogenetics

Metabolic screening and its impact in children with non-syndromic intellectual disability

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