Genetic Approach to Diagnosis of Intellectual Disability

Next-Generation Sequencing in Unexplained Intellectual Disability

OBJECTIVES

To determine the diagnostic yield of next generation sequencing (NGS) in patients with moderate/severe/profound intellectual disability (ID) unexplained by conventional tests and to assess the impact of definitive diagnosis on the clinical management and genetic counselling of these families.

METHODS

This was a ambi-directional study conducted at Institute of Medical Genetics and Genomics, Sir Ganga Ram Hospital, New Delhi. The study comprised 227 patients (prospective cohort - 126, retrospective cohort - 101) in whom NGS based tests were performed.

RESULTS

The mean age of study cohort was 4.5 ± 4.4 y (2.5 mo to 37.3 y). The male: female ratio was 1.6:1. The overall diagnostic yield of NGS was 53.3% (121/227) with causative variants identified in 84 known ID genes. Autosomal recessive intellectual disability (ARID) (23.3%, 53/227) was the most common followed by autosomal dominant intellectual disability (ADID) (20.7%, 47/227) and X-linked intellectual disability (XLID) (9.2%, 21/227). The diagnostic yield was notably higher for ID plus associated condition group (55.6% vs. 20%) (p = 0.0075, Fisher's exact test) compared to isolated ID group. The impact of diagnosis on active or long-term management was observed in 17/121 (14%) and on reproductive outcomes in 26/121 (21.4%) families.

CONCLUSIONS

There is paucity of data on molecular genetic spectrum of ID from India. The current study identifies extensive genetic heterogeneity and the impact of NGS in patients with ID unexplained by standard genetic tests. The study identified ARID as the most common cause of ID with additional implications for reproductive outcomes. It reiterates the importance of phenotype in genetic testing.

Diagnostic yield of patients with undiagnosed intellectual disability, global developmental delay and multiples congenital anomalies using karyotype, microarray analysis, whole exome sequencing from Central Brazil

Intellectual Disability (ID) is a neurodevelopmental disorder that affects approximately 3% of children and adolescents worldwide. It is a heterogeneous and multifactorial clinical condition. Several methodologies have been used to identify the genetic causes of ID and in recent years new generation sequencing techniques, such as exome sequencing, have enabled an increase in the detection of new pathogenic variants and new genes associated with ID. The aim of this study was to evaluate exome sequencing with analysis of the ID gene panel as a tool to increase the diagnostic yield of patients with ID/GDD/MCA in Central Brazil, together with karyotype and CMA tests. A retrospective cohort study was carried out with 369 patients encompassing both sexes. Karyotype analysis was performed for all patients. CMA was performed for patients who did not present structural and or numerical alterations in the karyotype. Cases that were not diagnosed after performing karyotyping and CMA were referred for exome sequencing using a gene panel for ID that included 1,252 genes. The karyotype identified chromosomal alterations in 34.7% (128/369). CMA was performed in 83 patients who had normal karyotype results resulting in a diagnostic yield of 21.7% (18/83). Exome sequencing with analysis of the ID gene panel was performed in 19 trios of families that had negative results with previous methodologies. With the ID gene panel analysis, we identified mutations in 63.1% (12/19) of the cases of which 75% (9/12) were pathogenic variants,8.3% (1/12) likely pathogenic and in 16.7% (2/12) it concerned a Variant of Uncertain Significance. With the three methodologies applied, it was possible to identify the genetic cause of ID in 42.3% (156/369) of the patients. In conclusion, our studies show the different methodologies that can be useful in diagnosing ID/GDD/MCA and that whole exome sequencing followed by gene panel analysis, when combined with clinical and laboratory screening, is an efficient diagnostic strategy.

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

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.

Challenges in molecular diagnosis of X-linked Intellectual disability

BACKGROUND

Intellectual disability (ID) affects 1-3% of the Western population and is heterogeneous in origin. Mutations in X-linked genes represent 5-10% of ID in males. Fragile X syndrome, due to the silencing of the FMR1 gene, is the most common form of ID, with a prevalence of around 1:5000 males. Females are usually non- or mildly affected carriers, and in a few rare cases, the only gender affected. Array comparative genome hybridization (aCGH) and next-generation sequencing (NGS) have dramatically changed the nature of human genome analysis leading to the identification of new X-linked intellectual disability syndromes and disease-causing genes.

SOURCES OF DATA

Original papers, reviews, guidelines and experiences of the diagnostic laboratories.

AREAS OF AGREEMENT

Family history and clinical examination still are essential to choose the appropriate diagnostic tests, including, a disease-specific genetic test, aCGH or FMR1 molecular analysis. If negative, NGS approaches like well-defined gene panels, whole exome, or even whole genome sequencing, are increasingly being used, improving diagnostics and leading to the identification of novel disease mechanisms.

AREAS OF CONTROVERSY

The main challenge in the era of NGS is filtering and interpretation of the data generated by the analysis of a single individual. In X-linked cases, assessing pathogenicity is particularly challenging, even more when the variant is found to be inherited from a healthy carrier mother or when a heterozygous X-linked mutation is found in an impaired female.

GROWING POINTS

At present, variant interpretation remains a challenging task, especially in X-linked disorders. We review the main difficulties and propose a comprehensive overview that might aid in variant interpretation. Establishing a genetic diagnosis facilitates counseling and allows better delineation of clinical phenotypes.

AREAS TIMELY FOR DEVELOPING RESEARCH

To improve variant interpretation, there is need to refine in silico predictions with specific criteria for each gene, and to develop cost-effective functional tools, which can be easily transferred to diagnostics.

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

Background

In 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 presentation

We 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.

Conclusions

These 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.

Needles in the haystack: Using open-text fields to identify persons with intellectual and developmental disabilities in administrative home care data

BACKGROUND

Use of administrative health data to study populations of interest is becoming more common. Identifying individuals with intellectual and developmental disabilities (IDD) in existing databases can be challenging due to inconsistent definitions and terminologies of IDD over time and across sectors, and the inability to rely on etiologies of IDD as they are frequently unknown.

AIMS

To identify diagnoses related to IDD in an administrative database and create a cohort of persons with IDD.

METHODS

Open-text diagnostic entries related to IDD were identified in an Ontario home care database (2003-2015) and coded as being either acceptable (e.g. Down syndrome) or ambiguous (e.g. intellectually challenged). The cognitive and functional skills of the resulting groups were compared using logistic regressions and standardized differences, and their age distributions were compared to that of the general home care population.

RESULTS

Just under 1% of the home care population had a diagnostic entry related to IDD. Ambiguous terms were most commonly used (61%), and this group tended to be older and less impaired than the group with more acceptable terms used to describe their IDD.

CONCLUSIONS

Open-text diagnostic variables in administrative health records can be used to identify and study individuals with IDD.

IMPLICATIONS

Future work is needed to educate assessors on the importance of using standard, accepted terminology when recording diagnoses related to IDD.

Metabolic screening and its impact in children with nonsyndromic intellectual disability

OBJECTIVE

The 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 METHODS

This 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.

RESULTS

Positive 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.

CONCLUSION

Metabolic 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.