Adaptive optics (AO) imaging tools enable direct visualization of the cone photoreceptor mosaic, which facilitates quantitative measurements such as cone density. However, in many individuals, low image quality or excessive eye movements precludes making such measures. As foveal cone specialization is associated with both increased density and outer segment (OS) elongation, we sought to examine whether OS length could be used as a surrogate measure of foveal cone density. The retinas of 43 subjects (23 normal and 20 albinism; aged 6–67 years) were examined. Peak foveal cone density was measured using confocal adaptive optics scanning light ophthalmoscopy (AOSLO), and OS length was measured using optical coherence tomography (OCT) and longitudinal reflectivity profile-based approach. Peak cone density ranged from 29,200 to 214,000 cones/mm2 (111,700 ± 46,300 cones/mm2); OS length ranged from 26.3 to 54.5 μm (40.5 ± 7.7 μm). Density was significantly correlated with OS length in albinism (p < 0.0001), but not normals (p = 0.98). A cubic model of density as a function of OS length was created based on histology and optimized to fit the albinism data. The model includes triangular cone packing, a cylindrical OS with a fixed volume of 136.6 μm3, and a ratio of OS to inner segment width that increased linearly with increasing OS length (R2 = 0.72). Normal subjects showed no apparent relationship between cone density and OS length. In the absence of adequate AOSLO imagery, OS length may be used to estimate cone density in patients with albinism.

This Commentary explores the challenges in launching a medical genomics clinic for whole genome sequencing and analysis of patient samples.

BackgroundChildhood apraxia of speech (CAS) is a rare, severe, persistent pediatric motor speech disorder with associated deficits in sensorimotor, cognitive, language, learning and affective processes. Among other neurogenetic origins, CAS is the disorder segregating with a mutation in FOXP2 in a widely studied, multigenerational London family. We report the first whole-exome sequencing (WES) findings from a cohort of 10 unrelated participants, ages 3 to 19 years, with well-characterized CAS.MethodsAs part of a larger study of children and youth with motor speech sound disorders, 32 participants were classified as positive for CAS on the basis of a behavioral classification marker using auditory-perceptual and acoustic methods that quantify the competence, precision and stability of a speaker’s speech, prosody and voice. WES of 10 randomly selected participants was completed using the Illumina Genome Analyzer IIx Sequencing System. Image analysis, base calling, demultiplexing, read mapping, and variant calling were performed using Illumina software. Software developed in-house was used for variant annotation, prioritization and interpretation to identify those variants likely to be deleterious to neurodevelopmental substrates of speech-language development.ResultsAmong potentially deleterious variants, clinically reportable findings of interest occurred on a total of five chromosomes (Chr3, Chr6, Chr7, Chr9 and Chr17), which included six genes either strongly associated with CAS (FOXP1 and CNTNAP2) or associated with disorders with phenotypes overlapping CAS (ATP13A4, CNTNAP1, KIAA0319 and SETX). A total of 8 (80%) of the 10 participants had clinically reportable variants in one or two of the six genes, with variants in ATP13A4, KIAA0319 and CNTNAP2 being the most prevalent.ConclusionsSimilar to the results reported in emerging WES studies of other complex neurodevelopmental disorders, our findings from this first WES study of CAS are interpreted as support for heterogeneous genetic origins of this pediatric motor speech disorder with multiple genes, pathways and complex interactions. We also submit that our findings illustrate the potential use of WES for both gene identification and case-by-case clinical diagnostics in pediatric motor speech disorders.

Purpose: Clinical whole genome sequencing is becoming more common for determining the molecular diagnosis of rare disease. However, standard clinical practice often focuses on small variants such as single nucleotide variants and small insertions/deletions. This leaves a wide range of larger "structural variants" that are not commonly analyzed in patients. Methods: We developed a pipeline for processing structural variants for patients who received whole genome sequencing through the Undiagnosed Diseases Network (UDN). This pipeline called structural variants, stored them in an internal database, and filtered the variants based on internal frequencies and external annotations. The remaining variants were manually inspected and then interesting findings were reported as research variants to clinical sites in the UDN. Results: Of 477 analyzed UDN cases, 286 cases (≈ 60%) received at least one structural variant as a research finding. The variants in 16 cases (≈ 4%) are considered "Certain" or "Highly likely" molecularly diagnosed and another 4 cases are currently in review. Of those 20 cases, at least 13 were identified originally through our pipeline with one finding leading to identification of a new disease. As part of this paper, we have also released the collection of variant calls identified in our cohort along with heterozygous and homozygous call counts. This data is available at https://github.com/HudsonAlpha/UDN_SV_export. Conclusion: Structural variants are key genetic features that should be analyzed during routine clinical genomic analysis. For our UDN patients, structural variants helped solve ≈ 4% of the total number of cases (≈ 13% of all genome sequencing solves), a success rate we expect to improve with better tools and greater understanding of the human genome.