Diagnosis of Intellectual Disability via Genetic Analysis

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Diagnosis of Intellectual Disability/Global Developmental Delay via Genetic Analysis in a Central Region of China

Introduction

Intellectual disability (ID) and global developmental delay (GDD) are significant health concerns. ID involves deficits in intellectual and adaptive functioning, while GDD is a delay in two or more developmental domains, often in younger children. A confirmed etiologic diagnosis is crucial for treatment, symptom management, and predicting complications. Genetic analysis, such as chromosomal microarray analysis, has shown promise, but the role of targeted high-throughput sequencing remains debated. This study aimed to explore the role of genetic analysis in confirming the etiology of ID/GDD in central China.

Methods

Ethical Approval

The study was approved by the Institutional Research Ethics Committee of Xiangya Hospital, Central South University. Informed consents were obtained from guardians of ID/GDD patients.

Patients and Diagnostic Criteria

1051 ID/GDD children aged 6 months to 18 years were recruited from Xiangya Hospital from March 2009 to April 2017. They were diagnosed by experienced pediatric neurologists based on the American Association of Mental Retardation and the Diagnostic and Statistical Manual of Mental Disorders. Severity was classified by IQ scores: mild (55–70), moderate (40–54), severe (25–39), or profoundly severe (less than 25).

Test Scales

Different intelligence tests were used depending on age. For example, Gesell Developmental Schedules or Bayley Scales for infants, Wechsler scales for older children, and a neuropsychological development scale for younger patients.

Data Collection and Clinical Examinations

Basic clinical information, including medical history, family history, and social environment, was collected. Screening for inherited metabolic disorders (e.g., urine organic acid analysis, acylcarnitine analysis) and neuroimaging (e.g., X-rays, MRI, EEG) were performed. Genetic tests included karyotype analysis, genome-wide copy number variation (CNV) detection, and second-generation sequencing (e.g., targeted genomic capture, mitochondrial gene testing, whole exon sequencing).

Procedure of Etiology Confirmation

  • Phase I: Classification based on initial tests (metabolic disease screening, neuroimaging, EEG, karyotype analysis).
  • Phase II: Metabolic disease screening for remaining cases.
  • Phase III: Further genetic tests (targeted genomic capture, mitochondrial gene testing, WES) for unresolved cases.

Statistical Analysis

Normality was tested. Categorical variables were compared using Fisher exact probability tests. SPSS Statistics software was used, and P < 0.05 was significant.

Results

General Information and Clinical Manifestations

  • Demographics: 1051 children (685 males, 366 females). 596 were under 3 years old. Severity: mild (367, 34.9%), moderate (301, 28.6%), severe (310, 29.5%), profoundly severe (73, 6.9%).
  • Clinical Manifestations:
    • Mild ID/GDD: Language development retardation (306, 83.5%), learning disabilities (271, 73.8%), fine motor retardation (267, 72.8%).
    • Severe ID/GDD: Prominent speech delay, gross motor delay since birth, dysmorphic features. Karyotype and/or CNVs variation was higher in severe (46/96, 47.9%) than mild (34/96, 35.4%) and moderate (15/96, 15.6%) cases.
    • Neuroimaging: 211 with abnormal signs (encephalomalacia foci, ventricular system expansion, etc.). Absenteeism of corpus callosum and gyrus deformity in severe cases.

Genetic Analysis and Etiological Diagnostic Yield

  • Phase I: 536 (51.0%) had a definite etiology.
  • Phase II: 798 evaluated, 56.3% confirmed. 253 (24.1%) didn’t do CNV detection due to cost.
  • Phase III: 679 underwent all phases. 536 (78.9%) had a definite etiology. 143 remained unidentified.
  • Genetic Analysis Comparison: More patients with clear etiology (331/536, 61.8%) had genetic analysis than unclear (262/515, 50.9%) (x² = 12.645, P < 0.001).

Concrete Etiological Spectrum

  • Inherited Metabolic Diseases: 8 cases (e.g., glutaric aciduria types 1 and 2).
  • Chromosomal Abnormalities:
    • Karyotype: 25 abnormal. Microdeletion syndrome (52.3%), microduplication syndrome (23.0%), combined (24.6%). Known syndromes (e.g., 1q42-q44 microdeletion, Angelman, Prader-Willi).
    • CNVs: More common in chromosomes 7/8/9/10/17/22.
  • Single Gene Disorders: 87 cases with pathogenic or likely pathogenic variants. 10 novel mutations. Recessive mutations in X-linked genes (ATP7A, BRWD3) and dominant de novo heterozygous mutations in X-linked genes (CDKL5, PCDH19, IQSEC2, MECP2).

Discussion

Genetic Analysis Effectiveness

Genetic testing (karyotype, CNV, second-generation sequencing) increased the proportion of definite etiological confirmation from 51.0% to 78.9%. X-linked gene mutations were reported.

Non-Genetic Factors

  • Perinatal Factors: 11.6% (122/1051) affected. Improved pregnancy care and neonatal technology could reduce ID/GDD.
  • Congenital Cerebral Malformations: 39 cases (3.7%). Brain imaging may help with certain symptoms.

Genetic Factors

  • Inherited Metabolic Diseases: 0.8% (8/1051). Neonatal screening improves diagnosis.
  • Chromosomal Abnormalities: Common genetic risk. CNV detection had a positive rate (16.9% in this study, consistent with reports).
  • Single Gene Disorders: Advances in gene identification (over 800 genes known). Custom probe libraries improved diagnostic yield (e.g., 30.9% for monogenic disorder-related genes).

Limitations

  • Single-Center: Limited inference. Multi-center studies needed.
  • Sample Size: Small for epidemiology. Continued data collection is needed.

Conclusion

Genetic analysis is effective for confirming ID/GDD etiology, especially in uncertain cases. Perinatal factors are important. Advances in genetic analysis enable early diagnosis.

doi.org/10.1097/CM9.0000000000000295

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