Cross-Sectional Analysis of Exome Sequencing Diagnosis in Patients With Neurologic Phenotypes Facing Barriers to Clinical Testing.

Background and Objectives: Exome sequencing (ES) demonstrates a 20-50 percent diagnostic yield for patients with a suspected monogenic neurologic disease. Despite the proven efficacy in achieving a diagnosis for such patients, multiple barriers for obtaining exome sequencing remain. This study set out to assess the efficacy of ES in patients with primary neurologic phenotypes who were appropriate candidates for testing but had been unable to pursue clinical testing. Methods: A total of 297 patients were identified from the UCLA Clinical Neurogenomics Research Center Biobank, and ES was performed, including bioinformatic assessment of copy number variation and repeat expansions. Information regarding demographics, clinical indication for ES, and reason for not pursuing ES clinically were recorded. To assess diagnostic efficacy, variants were interpreted by a multidisciplinary team of clinicians, bioinformaticians, and genetic counselors in accordance with the American College of Medical Genetics and Genomics variant classification guidelines. We next examined the specific barriers to testing for these patients, including how frequently insurance-related barriers such as coverage denials and inadequate coverage of cost were obstacles to pursuing exome sequencing. Results: The cohort primarily consisted of patients with sporadic conditions (n = 126, 42.4%) of adult-onset (n = 239, 80.5%). Cerebellar ataxia (n = 225, 75.8%) was the most common presenting neurologic phenotype. Our study found that in this population of mostly adult patients with primary neurologic phenotypes that were unable to pursue exome sequencing clinically, 47 (15.8%) had diagnostic results while an additional 24 patients (8.1%) had uncertain results. Of the 297 patients, 206 were initially recommended for clinical exome but 88 (42.7%) could not pursue ES because of insurance barriers, of whom 14 (15.9%) had diagnostic findings, representing 29.8% of all patients with diagnostic findings. In addition, the incorporation of bioinformatic repeat expansion testing was valuable, identifying a total of 8 pathogenic repeat expansions (17.0% of all diagnostic findings) including 3 of the common spinocerebellar ataxias and 2 patients with Huntington disease. Discussion: These findings underscore the importance and value of clinical ES as a diagnostic tool for neurogenetic disease and highlight key barriers that prevent patients from receiving important clinical information with potential treatment and psychosocial implications for patients and family members.

Multi-class Modeling Identifies Shared Genetic Risk for Late-onset Epilepsy and Alzheimer's Disease.

Background: Previous studies have established a strong link between late-onset epilepsy (LOE) and Alzheimer's disease (AD). However, their shared genetic risk beyond the APOE gene remains unclear. Our study sought to examine the shared genetic factors of AD and LOE, interpret the biological pathways involved, and evaluate how AD onset may be mediated by LOE and shared genetic risks. Methods: We defined phenotypes using phecodes mapped from diagnosis codes, with patients' records aged 60-90. A two-step Least Absolute Shrinkage and Selection Operator (LASSO) workflow was used to identify shared genetic variants based on prior AD GWAS integrated with functional genomic data. We calculated an AD-LOE shared risk score and used it as a proxy in a causal mediation analysis. We used electronic health records from an academic health center (UCLA Health) for discovery analyses and validated our findings in a multi-institutional EHR database (All of Us). Results: The two-step LASSO method identified 34 shared genetic loci between AD and LOE, including the APOE region. These loci were mapped to 65 genes, which showed enrichment in molecular functions and pathways such as tau protein binding and lipoprotein metabolism. Individuals with high predicted shared risk scores have a higher risk of developing AD, LOE, or both in their later life compared to those with low-risk scores. LOE partially mediates the effect of AD-LOE shared genetic risk on AD (15% proportion mediated on average). Validation results from All of Us were consistent with findings from the UCLA sample. Conclusions: We employed a machine learning approach to identify shared genetic risks of AD and LOE. In addition to providing substantial evidence for the significant contribution of the APOE-TOMM40-APOC1 gene cluster to shared risk, we uncovered novel genes that may contribute. Our study is one of the first to utilize All of Us genetic data to investigate AD, and provides valuable insights into the potential common and disease-specific mechanisms underlying AD and LOE, which could have profound implications for the future of disease prevention and the development of targeted treatment strategies to combat the co-occurrence of these two diseases.

The UCLA ATLAS Community Health Initiative: Promoting precision health research in a diverse biobank.

The UCLA ATLAS Community Health Initiative (ATLAS) has an initial target to recruit 150,000 participants from across the UCLA Health system with the goal of creating a genomic database to accelerate precision medicine efforts in California. This initiative includes a biobank embedded within the UCLA Health system that comprises de-identified genomic data linked to electronic health records (EHRs). The first freeze of data from September 2020 contains 27,987 genotyped samples imputed to 7.9 million SNPs across the genome and is linked with de-identified versions of the EHRs from UCLA Health. Here, we describe a centralized repository of the genotype data and provide tools and pipelines to perform genome- and phenome-wide association studies across a wide range of EHR-derived phenotypes and genetic ancestry groups. We demonstrate the utility of this resource through the analysis of 7 well-studied traits and recapitulate many previous genetic and phenotypic associations.

Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer.

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative.

BACKGROUND: Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative-an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736). METHODS: We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and >1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes. RESULTS: We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals' SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10-16, EAA p-value=6.73×10-11). A subsequent PheWAS at the top SNP reveals significant associations with neurologic and neoplastic phenotypes specifically within the HL GIA group. CONCLUSIONS: Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.

An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study.

BACKGROUND: Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. OBJECTIVE: We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. METHODS: The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. RESULTS: The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P<.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; P<.001), Asian (OR 0.72, 95% CI 0.68-0.77; P<.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; P<.001) were less likely to participate than White individuals. CONCLUSIONS: This is one of the few large-scale, electronic video-based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.

Correction: Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study.

[This corrects the article DOI: 10.2196/29123.].

Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study.

BACKGROUND: Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. OBJECTIVE: This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. METHODS: The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. RESULTS: The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (P<.001). There were significant differences between those who opted in and opted out in their beliefs concerning the usefulness of tissue, trusting researchers, the importance of contributing to science, and privacy risk (P<.001). The results showed that "I trust researchers to use leftover biological specimens to promote the public's health" and "Sharing a biological sample for research is safe because of the privacy protections in place" discriminated opt-in statuses were the strongest predictors (both areas under the curve were 0.88). Privacy concerns seemed universal in individuals who opted out. CONCLUSIONS: Efforts to better educate the community may be needed to help overcome some of the barriers in engaging individuals to participate in precision health initiatives.

ASD symptoms in toddlers and preschoolers: An examination of sex differences.

Although considerable work has documented higher prevalence rates of autism spectrum disorder (ASD) in boys, fewer studies have focused on sex differences within samples of young children at-risk for ASD. This study examined sex differences in ASD symptom domains and ASD screening outcomes among toddlers (18-35 months) and preschoolers (36-72 months) with ASD-related concerns. Participants included 480 children between 18 and 72 months evaluated by university-based ASD specialty clinics. Results revealed significant sex differences in severity of social communication (SC) deficits across age groups. Within the toddler group, girls diagnosed with ASD displayed greater SC deficits according to standardized observation and clinician severity ratings. Within the preschool group, girls diagnosed with ASD were rated by parents as having more severe SC deficits, but these differences were not corroborated by standardized observations or clinician ratings. No sex differences emerged for severity of restricted repetitive behaviors (RRBs) for either age group. Across the entire referred sample, boys and girls did not differ in terms of scores on commonly used screening instruments. Importantly, results suggest that two of the most commonly used ASD screeners (i.e., Modified-Checklist for Autism in Toddlers-Revised with Follow-up and Social Communication Questionnaire ) may underidentify RRBs in toddler and preschool-aged girls as screening scores were only influenced by severity of SC deficits. Greater SC deficits in young girls with ASD along with its impact on screening status suggests greater attention be placed on the under-identification of ASD in girls as well as current screening measures' ability to tap into the topography of ASD symptoms across genders. Autism Res 2020, 13: 157-166. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: In this study, we found that young girls diagnosed with autism spectrum disorder tend to have greater social communication deficits than young boys and that these differences vary by age. Specifically, toddler-aged girls receive higher clinician ratings of social communication deficits when compared to boys, while preschool-aged girls receive higher parent ratings of social communication deficits. For girls, current screening tools seem to be more highly influenced by severity of social communication deficits than by restricted repetitive behaviors.

When Are We Sure? Predictors of Clinician Certainty in the Diagnosis of Autism Spectrum Disorder.

Differential diagnosis of autism spectrum disorder (ASD) is challenging, and uncertainty regarding a child's diagnosis may result in under-identification or prolonged diagnostic pathways. The current study examined diagnostic certainty, or how sure clinicians were that their diagnosis was accurate, among 478 toddler and preschool-aged children referred for possible ASD to academic medical specialty clinics. Overall, 60 percent of diagnoses were made with complete certainty. Clinicians were more certain when positively identifying ASD than ruling it out. Children presenting with a moderate (vs high or low) level of observable ASD symptoms were less likely to have a certain diagnosis. Further, clinicians rated less diagnostic certainty for older children, those with public insurance, and those with higher IQ and adaptive behavior abilities.

Strategies for Disseminating Information on Biomedical Research on Autism to Hispanic Parents.

Low income Hispanic families experience multiple barriers to accessing evidence-based information on Autism Spectrum Disorders (ASD). This study utilized a mixed-strategy intervention to create access to information in published bio-medical research articles on ASD by distilling the content into parent-friendly English- and Spanish-language ASD Science Briefs and presenting them to participants using two socially-oriented dissemination methods. There was a main effect for short-term knowledge gains associated with the Science Briefs but no effect for the dissemination method. After 5 months, participants reported utilizing the information learned and 90% wanted to read more Science Briefs. These preliminary findings highlight the potential benefits of distilling biomedical research articles on ASD into parent-friendly educational products for currently underserved Hispanic parents.

Prenatal and perinatal risk factors in a twin study of autism spectrum disorders.

INTRODUCTION: Multiple studies associate prenatal and perinatal complications with increased risks for autism spectrum disorders (ASDs). The objectives of this study were to utilize a twin study design to 1) Investigate whether shared gestational and perinatal factors increase concordance for ASDs in twins, 2) Determine whether individual neonatal factors are associated with the presence of ASDs in twins, and 3) Explore whether associated factors may influence males and females differently. METHODS: Data from medical records and parent response questionnaires from 194 twin pairs, in which at least one twin had an ASD, were analyzed. RESULTS: Shared factors including parental age, prenatal use of medications, uterine bleeding, and prematurity did not increase concordance risks for ASDs in twins. Among the individual factors, respiratory distress demonstrated the strongest association with increased risk for ASDs in the group as a whole (OR 2.11, 95% CI 1.27-3.51). Furthermore, respiratory distress (OR 2.29, 95% CI 1.12-4.67) and other markers of hypoxia (OR 1.99, 95% CI 1.04-3.80) were associated with increased risks for ASDs in males, while jaundice was associated with an increased risk for ASDs in females (OR 2.94, 95% CI 1.28-6.74). CONCLUSIONS: Perinatal factors associated with respiratory distress and other markers of hypoxia appear to increase risk for autism in a subgroup of twins. Future studies examining potential gender differences and additional prenatal, perinatal and postnatal environmental factors are required for elucidating the etiology of ASDs and suggesting new methods for treatment and prevention.

Assessing behavioural and cognitive domains of autism spectrum disorders in rodents: current status and future perspectives.

The establishment of robust and replicable behavioural testing paradigms with translational value for psychiatric diseases is a major step forward in developing and testing etiology-directed treatment for these complex disorders. Based on the existing literature, we have generated an inventory of applied rodent behavioural testing paradigms relevant to autism spectrum disorders (ASD). This inventory focused on previously used paradigms that assess behavioural domains that are affected in ASD, such as social interaction, social communication, repetitive behaviours and behavioural inflexibility, cognition as well as anxiety behaviour. A wide range of behavioural testing paradigms for rodents were identified. However, the level of face and construct validity is highly variable. The predictive validity of these paradigms is unknown, as etiology-directed treatments for ASD are currently not on the market. To optimise these studies, future efforts should address aspects of reproducibility and take into account data about the neurodevelopmental underpinnings and trajectory of ASD. In addition, with the increasing knowledge of processes underlying ASD, such as sensory information processes and synaptic plasticity, phenotyping efforts should include multi-level automated analysis of, for example, representative task-related behavioural and electrophysiological read-outs.

Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

Head circumferences in twins with and without Autism Spectrum Disorders.

To determine the genetic relationship between head circumference (HC) and Autism Spectrum Disorders (ASDs). Twin pairs with at least one twin with an ASD were assessed. HCs in affected and unaffected individuals were compared, as were HC correlations in monozygotic and dizygotic pairs. 404 subjects, ages 4-18, were included. 20 % of males and 27 % of females with an ASD had macrocephaly. Unaffected co-twins showed similar rates (16 % of males and 22 % of females). Statistical analysis revealed no significant difference in HCs between affected and unaffected twins. Twins with ASDs and unaffected co-twins have similar HCs and increased rates of macrocephaly. Correlations demonstrated partial inheritance of HCs. Thus, macrocephaly may represent an endophenotype in ASDs.

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.