Top 99 Genetic Causes of Developmental Delay Panel

Developmental delay can describe any youth who is not meeting typical milestones in one or more of the following areas: physical, cognitive, communication, social/emotional, or adaptive development. Developmental delays are common: In a typical classroom of 30 students, ~ 5 will have a developmental disability (DD), according to a recent Center for Disease Control and Prevention survey of parents (Zablotsky et al. 2019. PubMed ID: 31558576). Patients with developmental delays may benefit from an early molecular diagnosis of the cause of their delay in order to receive specialty treatments or access to patient support groups. Families may benefit from diagnosis for prognostic information, and future family planning decisions. Testing this panel of 99 genes provides a low-cost opportunity to diagnose the most common genetic causes of developmental delay at an early age.

Many developmental disabilities are suspected to be genetic in origin (~40%), yet will go undiagnosed for years due to the high cost of genetic testing, among other barriers. This financial burden stems from the enormous diversity of genes known to cause DDs, and the broad differential diagnosis for most children with delays. While trio whole exome/genome sequencing is likely to be the most effective test for diagnosis, its high cost limits accessibility. In order to make genetic testing available to more children, we sought to determine which genes account for the greatest number of diagnoses in patients with DD. We reasoned that sequencing a smaller number of genes would reduce cost, thus increasing accessibility.

Therefore, we curated this list of 99 genes that account for the largest number of developmental delay diagnoses. To develop this list, we used information from three sources: 1) Exome-level data from >1,500 PreventionGenetics patients with DD, ~300 positive cases, 2) Published and unpublished DD cohorts - including the Deciphering Developmental Disorders study, the CAUSES study, and data from other large clinical labs (see references section for published cohorts included), and 3) Variant tallies from the Human Gene Mutation Database (HGMD) and Clinvar database of disease-causing variants. We first calculated a “Gene Score” for predicted diagnostic yield for DD based on numbers of diagnoses across cohorts (formula = [Sum of LP/P diagnoses in NNNN gene across six cohorts analyzed] + [Sum of cohorts with a LP/P case for NNNN gene]). Sum of cohorts with a diagnosis in NNNN gene was included in the score to address possible cohort-specific biases, by giving additional weight to genes with diagnoses well-spread across cohorts (i.e. a gene with a single diagnosis in each of six cohorts would be scored higher than a gene with six diagnoses in a single cohort). Gene score values in our study ranged from 35 for ARID1B - with 29 total diagnoses, and positive ARID1B-related Coffin-Siris cases observed in all six cohorts analyzed (29 + 6 = 35), down to 4 (i.e. two total diagnoses in MAGEL2 were observed in two of the six cohorts analyzed, 2+2 = 4). After including all genes on the list with a gene score of 7 or higher (observed in ≥ two studies, and ≥ four patients with developmental delays within those studies), we picked genes 88-99 within the lower-range of gene-scores, based on combined frequency of database entries in ClinVar and HGMD. To summarize, we created a list of 99 genes with the highest predicted diagnostic yield for DDs.

Ranking at the top, the most-common causes of DD include ARID1B - Coffin Siris syndrome, ANKRD11 - KBG syndrome, KMT2A - Wiedemann Steiner syndrome, KMT2D - Kabuki syndrome, MECP2 - Rett syndrome, SYNGAP1 - AD intellectual disability type 5, BRPF1 - intellectual developmental disorder with dysmorphic facies and ptosis, DDX3X - X-linked intellectual disability type 102. These 8 genes account for 15% of positive DD diagnoses at PreventionGenetics. In total, the 99 genes on this panel account for over 50% of PG positive findings in patients with developmental disabilities (not explained by large copy number variants). Genes with autosomal dominant or X-linked inheritance and frequent de novo occurrences top the list.

We hope this panel will increase accessibility to genetic testing for the ~17% of the population affected by a developmental disability.

While the genetic causes of developmental delays are enormously diverse, some genetic causes of developmental disability are more common than others. An analysis of past results shows that the 99 genes on this panel account for more than 50% of positive developmental delay diagnoses at PreventionGenetics. Positive diagnosis indicates a likely pathogenic or pathogenic variant detected that fully explains a patient's phenotype. Additionally, this panel provides exome-wide CNV analysis, a chromosomal microarray (CMA) alternative, which can increase diagnostic yield, especially for patients who have not had a prior CMA. Considering past diagnostic rates, we expect this 99-gene panel to have a diagnostic yield of 10-15% for patients with developmental delay (for patients with prior microarray, or higher for those without).

This test will detect both large deletions and insertions (Copy Number Variants(CNVS)) as well as smaller sequence variants (nucleotide substitutions and small deletions and insertions (SNVs)) with high analytical sensitivity. Detection of trinucleotide repeat expansions (as seen in fragile X syndrome for example) requires an alternate test.

This test is performed using Next-Gen sequencing with additional Sanger sequencing as necessary.

This panel typically provides 99.7% average coverage of all coding exons of the genes plus 10 bases of flanking noncoding DNA in all available transcripts along with other non-coding regions in which pathogenic variants have been identified at PreventionGenetics or reported elsewhere. We define coverage as ≥20X NGS reads or Sanger sequencing. PGnome panels typically provide slightly increased coverage over the PGxome equivalent. PGnome sequencing panels have the added benefit of additional analysis and reporting of deep intronic regions (where applicable).

Dependent on the sequencing backbone selected for this testing, discounted reflex testing to any other similar backbone-based test is available (i.e., PGxome panel to whole PGxome; PGnome panel to whole PGnome).