Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency.

PURPOSE: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. METHODS: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease-gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein-protein association neighbors. RESULTS: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease-gene associations and ranked the correct seeded variant in up to 87% when detectable disease-gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. CONCLUSION: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.Genet Med 18 6, 608-617.

PhenomeCentral: a portal for phenotypic and genotypic matchmaking of patients with rare genetic diseases.

The discovery of disease-causing mutations typically requires confirmation of the variant or gene in multiple unrelated individuals, and a large number of rare genetic diseases remain unsolved due to difficulty identifying second families. To enable the secure sharing of case records by clinicians and rare disease scientists, we have developed the PhenomeCentral portal (https://phenomecentral.org). Each record includes a phenotypic description and relevant genetic information (exome or candidate genes). PhenomeCentral identifies similar patients in the database based on semantic similarity between clinical features, automatically prioritized genes from whole-exome data, and candidate genes entered by the users, enabling both hypothesis-free and hypothesis-driven matchmaking. Users can then contact other submitters to follow up on promising matches. PhenomeCentral incorporates data for over 1,000 patients with rare genetic diseases, contributed by the FORGE and Care4Rare Canada projects, the US NIH Undiagnosed Diseases Program, the EU Neuromics and ANDDIrare projects, as well as numerous independent clinicians and scientists. Though the majority of these records have associated exome data, most lack a molecular diagnosis. PhenomeCentral has already been used to identify causative mutations for several patients, and its ability to find matching patients and diagnose these diseases will grow with each additional patient that is entered.

Massive CAG repeat expansion and somatic instability in maternally transmitted infantile spinocerebellar ataxia type 7.

IMPORTANCE: We report the first case to date of maternally transmitted infantile spinocerebellar ataxia type 7 (SCA7), in which a tract of (CAG)45 expands to lengths as large as (CAG)92-250. OBSERVATIONS: A 38-year-old woman with classic SCA7 (and a son, who died at age 3 years) had pronounced cerebellar atrophy and a renal biopsy specimen that showed focal segmental glomerulosclerosis with abnormal podocytes containing cytoplasmic inclusions. Polymerase chain reaction amplification across the SCA7 repeat tract assessed expansion levels in tissues of the affected son. High levels of somatic CAG instability were observed in blood, kidney, and skeletal muscle. This transmitted expansion is considerably larger than previously reported maternal transmission expansions of 5 to 10 gained repeats. CONCLUSIONS AND RELEVANCE: We document the first intertissue CAG instability reported to date in patients with SCA7, similar to SCA7 mouse models. Infantile SCA7, which is often paternally transmitted, can rarely arise by maternal transmission, which has implications for diagnosis and counseling among families of patients with SCA7.

Fusion analysis of functional MRI data for classification of individuals based on patterns of activation.

Classification of individuals based on patterns of brain activity observed in functional MRI contrasts may be helpful for diagnosis of neurological disorders. Prior work for classification based on these patterns have primarily focused on using a single contrast, which does not take advantage of complementary information that may be available in multiple contrasts. Where multiple contrasts are used, the objective has been only to identify the joint, distinct brain activity patterns that differ between groups of subjects; not to use the information to classify individuals. Here, we use joint Independent Component Analysis (jICA) within a Support Vector Machine (SVM) classification method, and take advantage of the relative contribution of activation patterns generated from multiple fMRI contrasts to improve classification accuracy. Young (age: 19-26) and older (age: 57-73) adults (16 each) were scanned while listening to noise alone and to speech degraded with noise, half of which contained meaningful context that could be used to enhance intelligibility. Functional contrasts based on these conditions (and a silent baseline condition) were used within jICA to generate spatially independent joint activation sources and their corresponding modulation profiles. Modulation profiles were used within a non-linear SVM framework to classify individuals as young or older. Results demonstrate that a combination of activation maps across the multiple contrasts yielded an area under ROC curve of 0.86, superior to classification resulting from individual contrasts. Moreover, class separability, measured by a divergence criterion, was substantially higher when using the combination of activation maps.

Swinging at a cocktail party: voice familiarity aids speech perception in the presence of a competing voice.

People often have to listen to someone speak in the presence of competing voices. Much is known about the acoustic cues used to overcome this challenge, but almost nothing is known about the utility of cues derived from experience with particular voices--cues that may be particularly important for older people and others with impaired hearing. Here, we use a version of the coordinate-response-measure procedure to show that people can exploit knowledge of a highly familiar voice (their spouse's) not only to track it better in the presence of an interfering stranger's voice, but also, crucially, to ignore it so as to comprehend a stranger's voice more effectively. Although performance declines with increasing age when the target voice is novel, there is no decline when the target voice belongs to the listener's spouse. This finding indicates that older listeners can exploit their familiarity with a speaker's voice to mitigate the effects of sensory and cognitive decline.