Comparative yield of molecular diagnostic algorithms for autism spectrum disorder diagnosis in India: evidence supporting whole exome sequencing as first tier test

Rare Pathogenic Variants Identified in Whole Exome Sequencing of Monozygotic Twins With Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a childhood-onset complex neurodevelopmental disorder characterized by problems with communication and social interaction and restricted, repetitive, stereotyped behavior. The prevalence of ASD is one in 36 children. The genetic architecture of ASD is complex in spite of its high heritability. To identify the potential candidate genes of ASD, we carried out a comprehensive genetic study of monozygotic (MZ) twins concordant or discordant for ASD.

METHODS

Five MZ twins and their parents were recruited for the study. Four of the twins were concordant, whereas one was discordant for ASD. Whole exome sequencing was conducted for the twins and their parents. The exome DNA was enriched using Twist Human Customized Core Exome Kit, and paired-end sequencing was performed on HiSeq system.

RESULTS

We identified several rare and pathogenic variants (homozygous recessive, compound heterozygous, de novo) in ASD-affected individuals.

CONCLUSION

We report novel variants in individuals diagnosed with ASD. Several of these genes are involved in brain-related functions and not previously reported in ASD. Intriguingly, some of the variants were observed in the genes involved in sensory perception (auditory [MYO15A, PLEC, CDH23, UBR3, GPSM2], olfactory [OR9K2], gustatory [TAS2R31], and visual [CDH23, UBR3]). This is the first comprehensive genetic study of MZ twins in an Indian population. Further validation is required to determine whether these variants are associated with ASD.

Burden of rare genetic disorders in India: twenty-two years' experience of a tertiary centre

BACKGROUND

Rare disorders comprise of ~ 7500 different conditions affecting multiple systems. Diagnosis of rare diseases is complex due to dearth of specialized medical professionals, testing labs and limited therapeutic options. There is scarcity of data on the prevalence of rare diseases in different populations. India being home to a large population comprising of 4600 population groups, of which several thousand are endogamous, is likely to have a high burden of rare diseases. The present study provides a retrospective overview of a cohort of patients with rare genetic diseases identified at a tertiary genetic test centre in India.

RESULTS

Overall, 3294 patients with 305 rare diseases were identified in the present study cohort. These were categorized into 14 disease groups based on the major organ/ organ system affected. Highest number of rare diseases (D = 149/305, 48.9%) were identified in the neuromuscular and neurodevelopmental (NMND) group followed by inborn errors of metabolism (IEM) (D = 47/305; 15.4%). Majority patients in the present cohort (N = 1992, 61%) were diagnosed under IEM group, of which Gaucher disease constituted maximum cases (N = 224, 11.2%). Under the NMND group, Duchenne muscular dystrophy (N = 291/885, 32.9%), trinucleotide repeat expansion disorders (N = 242/885; 27.3%) and spinal muscular atrophy (N = 141/885, 15.9%) were the most common. Majority cases of β-thalassemia (N = 120/149, 80.5%) and cystic fibrosis (N = 74/75, 98.7%) under the haematological and pulmonary groups were observed, respectively. Founder variants were identified for Tay-Sachs disease and mucopolysaccharidosis IVA diseases. Recurrent variants for Gaucher disease (GBA:c.1448T > C), β-thalassemia (HBB:c.92.+5G > C), non-syndromic hearing loss (GJB2:c.71G > A), albinism (TYR:c.832 C > T), congenital adrenal hyperplasia (CYP21A2:c.29-13 C > G) and progressive pseudo rheumatoid dysplasia (CCN6:c.298T > A) were observed in the present study.

CONCLUSION

The present retrospective study of rare disease patients diagnosed at a tertiary genetic test centre provides first insight into the distribution of rare genetic diseases across the country. This information will likely aid in drafting future health policies, including newborn screening programs, development of target specific panel for affordable diagnosis of rare diseases and eventually build a platform for devising novel treatment strategies for rare diseases.

Potential clinical applications of advanced genomic analysis in cerebral palsy

Cerebral palsy (CP) has historically been attributed to acquired insults, but emerging research suggests that genetic variations are also important causes of CP. While microarray and whole-exome sequencing based studies have been the primary methods for establishing new CP-gene relationships and providing a genetic etiology for individual patients, the cause of their condition remains unknown for many patients with CP. Recent advancements in genomic technologies offer additional opportunities to uncover variations in human genomes, transcriptomes, and epigenomes that have previously escaped detection. In this review, we outline the use of these state-of-the-art technologies to address the molecular diagnostic challenges experienced by individuals with CP. We also explore the importance of identifying a molecular etiology whenever possible, given the potential for genomic medicine to provide opportunities to treat patients with CP in new and more precise ways.

Reanalysis of Trio Whole-Genome Sequencing Data Doubles the Yield in Autism Spectrum Disorder: De Novo Variants Present in Half

Autism spectrum disorder (ASD) is a common condition with lifelong implications. The last decade has seen dramatic improvements in DNA sequencing and related bioinformatics and databases. We analyzed the raw DNA sequencing files on the Variantyx® bioinformatics platform for the last 50 ASD patients evaluated with trio whole-genome sequencing (trio-WGS). "Qualified" variants were defined as coding, rare, and evolutionarily conserved. Primary Diagnostic Variants (PDV), additionally, were present in genes directly linked to ASD and matched clinical correlation. A PDV was identified in 34/50 (68%) of cases, including 25 (50%) cases with heterozygous de novo and 10 (20%) with inherited variants. De novo variants in genes directly associated with ASD were far more likely to be Qualifying than non-Qualifying versus a control group of genes (p = 0.0002), validating that most are indeed disease related. Sequence reanalysis increased diagnostic yield from 28% to 68%, mostly through inclusion of de novo PDVs in genes not yet reported as ASD associated. Thirty-three subjects (66%) had treatment recommendation(s) based on DNA analyses. Our results demonstrate a high yield of trio-WGS for revealing molecular diagnoses in ASD, which is greatly enhanced by reanalyzing DNA sequencing files. In contrast to previous reports, de novo variants dominate the findings, mostly representing novel conditions. This has implications to the cause and rising prevalence of autism.

Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders-an important consideration for resource-constrained settings

Exome sequencing (ES) is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single-nucleotide variants (SNVs) and copy number variants (CNVs) in coding exonic regions of the genome in a single test, and this dual analysis is a valuable approach, especially in limited resource settings. Single-nucleotide variants are well studied; however, the incorporation of copy number variant analysis tools into variant calling pipelines has not been implemented yet as a routine diagnostic test, and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single and copy number variant analysis can lead to a diagnostic yield of up to 58%, increasing the yield with as much as 18% from the single-nucleotide variant only pipeline. Importantly, this is achieved with the consideration of computational costs only, without incurring any additional sequencing costs. This mini review provides an overview of copy number variant analysis from exome data and what the current recommendations are for this type of analysis. We also present an overview on rare monogenic disease research standard practices in resource-limited settings. We present evidence that integrating copy number variant detection tools into a standard exome sequencing analysis pipeline improves diagnostic yield and should be considered a significantly beneficial addition, with relatively low-cost implications. Routine implementation in underrepresented populations and limited resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centers for this niche within genomic medicine.