Examining Sex Differences in Autism Heritability.

Importance: Autism spectrum disorder (ASD) is a neurodevelopmental disorder more prevalent in males than in females. The cause of ASD is largely genetic, but the association of genetics with the skewed sex ratio is not yet understood. To our knowledge, no large population-based study has provided estimates of heritability by sex. Objective: To estimate the sex-specific heritability of ASD. Design, Setting, and Participants: This was a population-based, retrospective analysis using national health registers of nontwin siblings and cousins from Sweden born between January 1, 1985, and December 31, 1998, with follow-up to 19 years of age. Data analysis occurred from August 2022 to November 2023. Main Outcomes and Measures: Models were fitted to estimate the relative variance in risk for ASD occurrence owing to sex-specific additive genetics, shared environmental effects, and a common residual term. The residual term conceptually captured other factors that promote individual behavioral variation (eg, maternal effects, de novo variants, rare genetic variants not additively inherited, or gene-environment interactions). Estimates were adjusted for differences in prevalence due to birth year and maternal and paternal age by sex. Results: The sample included 1 047 649 individuals in 456 832 families (538 283 males [51.38%]; 509 366 females [48.62%]). Within the entire sample, 12 226 (1.17%) received a diagnosis of ASD, comprising 8128 (1.51%) males and 4098 (0.80%) females. ASD heritability was estimated at 87.0% (95% CI, 81.4%-92.6%) for males and 75.7% (95% CI, 68.4%-83.1%) for females with a difference in heritability estimated at 11.3% (95% CI, 1.0%-21.6%). There was no support for shared environmental contributions. Conclusions and Relevance: These findings suggest that the degree of phenotypic variation attributable to genetic differences (heritability) differs between males and females, indicating that some of the underlying causes of the condition may differ between the 2 sexes. The skewed sex ratio in ASD may be partly explained by differences in genetic variance between the sexes.

Prenatal delivery of a therapeutic antisense oligonucleotide achieves broad biodistribution in the brain and ameliorates Angelman syndrome phenotype in mice.

Angelman syndrome (AS), an early-onset neurodevelopmental disorder characterized by abnormal gait, intellectual disabilities, and seizures, occurs when the maternal allele of the UBE3A gene is disrupted, since the paternal allele is silenced in neurons by the UBE3A antisense (UBE3A-AS) transcript. Given the importance of early treatment, we hypothesized that prenatal delivery of an antisense oligonucleotide (ASO) would downregulate the murine Ube3a-AS, resulting in increased UBE3A protein and functional rescue. Using a mouse model with a Ube3a-YFP allele that reports on-target ASO activity, we found that in utero, intracranial (IC) injection of the ASO resulted in dose-dependent activation of paternal Ube3a, with broad biodistribution. Accordingly, in utero injection of the ASO in a mouse model of AS also resulted in successful restoration of UBE3A and phenotypic improvements in treated mice on the accelerating rotarod and fear conditioning. Strikingly, even intra-amniotic (IA) injection resulted in systemic biodistribution and high levels of UBE3A reactivation throughout the brain. These findings offer a novel strategy for early treatment of AS using an ASO, with two potential routes of administration in the prenatal window. Beyond AS, successful delivery of a therapeutic ASO into neurons has implications for a clinically feasible prenatal treatment for numerous neurodevelopmental disorders.

Thalamocortical organoids enable in vitro modeling of 22q11.2 microdeletion associated with neuropsychiatric disorders.

Thalamic dysfunction has been implicated in multiple psychiatric disorders. We sought to study the mechanisms by which abnormalities emerge in the context of the 22q11.2 microdeletion, which confers significant genetic risk for psychiatric disorders. We investigated early stages of human thalamus development using human pluripotent stem cell-derived organoids and show that the 22q11.2 microdeletion underlies widespread transcriptional dysregulation associated with psychiatric disorders in thalamic neurons and glia, including elevated expression of FOXP2. Using an organoid co-culture model, we demonstrate that the 22q11.2 microdeletion mediates an overgrowth of thalamic axons in a FOXP2-dependent manner. Finally, we identify ROBO2 as a candidate molecular mediator of the effects of FOXP2 overexpression on thalamic axon overgrowth. Together, our study suggests that early steps in thalamic development are dysregulated in a model of genetic risk for schizophrenia and contribute to neural phenotypes in 22q11.2 deletion syndrome.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Physical and functional convergence of the autism risk genes Scn2a and Ank2 in neocortical pyramidal cell dendrites.

Dysfunction in sodium channels and their ankyrin scaffolding partners have both been implicated in neurodevelopmental disorders, including autism spectrum disorder (ASD). In particular, the genes SCN2A, which encodes the sodium channel NaV1.2, and ANK2, which encodes ankyrin-B, have strong ASD association. Recent studies indicate that ASD-associated haploinsufficiency in Scn2a impairs dendritic excitability and synaptic function in neocortical pyramidal cells, but how NaV1.2 is anchored within dendritic regions is unknown. Here, we show that ankyrin-B is essential for scaffolding NaV1.2 to the dendritic membrane of mouse neocortical neurons and that haploinsufficiency of Ank2 phenocopies intrinsic dendritic excitability and synaptic deficits observed in Scn2a+/- conditions. These results establish a direct, convergent link between two major ASD risk genes and reinforce an emerging framework suggesting that neocortical pyramidal cell dendritic dysfunction can contribute to neurodevelopmental disorder pathophysiology.

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diagnosis. Biopsy evaluation requires copious examination by trained pathologists, which can be tedious and prone to human error. In this study, we propose an artificial intelligence (AI) method to assist pathologists in accurate segmentation and classification of pediatric kidney structures, named as AI-based Pediatric Kidney Diagnosis (APKD). RESULTS: We collected 2935 pediatric patients diagnosed with kidney disease for the development of APKD. The dataset comprised 93 932 histological structures annotated manually by three skilled nephropathologists. APKD scored an average accuracy of 94% for each kidney structure category, including 99% in the glomerulus. We found strong correlation between the model and manual detection in detected glomeruli (Spearman correlation coefficient r = 0.98, P < .001; intraclass correlation coefficient ICC = 0.98, 95% CI = 0.96-0.98). Compared to manual detection, APKD was approximately 5.5 times faster in segmenting glomeruli. Finally, we show how the pathological features extracted by APKD can identify focal abnormalities of the glomerular capillary wall to aid in the early diagnosis of pediatric kidney disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/ChunyueFeng/Kidney-DataSet.

A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo.

The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3'UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.

AlphaMissense is better correlated with functional assays of missense impact than earlier prediction algorithms.

Missense variants that alter a single amino acid in the encoded protein contribute to many human disorders but pose a substantial challenge in interpretation. Though these variants can be reliably identified through sequencing, distinguishing the clinically significant ones remains difficult, such that "Variants of Unknown Significance" outnumber those classified as "Pathogenic" or "Likely Pathogenic." Numerous in silico approaches have been developed to predict the functional impact of missense variants to inform clinical interpretation, the latest being AlphaMissense, which uses artificial intelligence methods trained on predicted protein structure. To independently assess the performance of AlphaMissense and 38 other predictors of missense severity, we compared predictions to data from multiplexed assays of variant effect (MAVE). MAVE experiments generate almost every possible individual amino acid change in a gene and measure their functional impact using a high-throughput assay. Assessing 17,696 variants across five genes (DDX3X, MSH2, PTEN, KCNQ4, and BRCA1), we find that AlphaMissense is consistently one of the top five algorithms based on correlation with functional impact and is the best-correlated algorithm for two genes. We conclude that AlphaMissense represents the current best-in-class predictor by this metric; however, the improvement over other algorithms is modest. We note that multiple missense predictors, including AlphaMissense, appear to overcall variants as pathogenic despite minimal functional impact and that substantially more high-quality training data, including consistently analyzed patient cohorts and MAVE analyses, are required to improve accuracy.

Astrocytic ß-catenin signaling via TCF7L2 regulates synapse development and social behavior.

The Wnt/ß-catenin pathway contains multiple high-confidence risk genes that are linked to neurodevelopmental disorders, including autism spectrum disorder. However, its ubiquitous roles across brain cell types and developmental stages have made it challenging to define its impact on neural circuit development and behavior. Here, we show that TCF7L2, which is a key transcriptional effector of the Wnt/ß-catenin pathway, plays a cell-autonomous role in postnatal astrocyte maturation and impacts adult social behavior. TCF7L2 was the dominant Wnt effector that was expressed in both mouse and human astrocytes, with a peak during astrocyte maturation. The conditional knockout of Tcf7l2 in postnatal astrocytes led to an enlargement of astrocytes with defective tiling and gap junction coupling. These mice also exhibited an increase in the number of cortical excitatory and inhibitory synapses and a marked increase in social interaction by adulthood. These data reveal an astrocytic role for developmental Wnt/ß-catenin signaling in restricting excitatory synapse numbers and regulating adult social behavior.

Neuropsychiatric biomarker discovery: go big or go home.

Technological advances have enabled high-throughput omics assays, such as parallelized screening of lipids across plasma samples. Pioneering a new paradigm for neuropsychiatric biomarker discovery, Yap et al. describe a large-scale systematic analysis of comprehensive phenotypic, genotypic, environmental, and lipidomic data to unravel the intricate interplay between these and autism-associated traits.

Systematic identification of disease-causing promoter and untranslated region variants in 8,040 undiagnosed individuals with rare disease.

Background: Both promoters and untranslated regions (UTRs) have critical regulatory roles, yet variants in these regions are largely excluded from clinical genetic testing due to difficulty in interpreting pathogenicity. The extent to which these regions may harbour diagnoses for individuals with rare disease is currently unknown. Methods: We present a framework for the identification and annotation of potentially deleterious proximal promoter and UTR variants in known dominant disease genes. We use this framework to annotate de novo variants (DNVs) in 8,040 undiagnosed individuals in the Genomics England 100,000 genomes project, which were subject to strict region-based filtering, clinical review, and validation studies where possible. In addition, we performed region and variant annotation-based burden testing in 7,862 unrelated probands against matched unaffected controls. Results: We prioritised eleven DNVs and identified an additional variant overlapping one of the eleven. Ten of these twelve variants (82%) are in genes that are a strong match to the individual's phenotype and six had not previously been identified. Through burden testing, we did not observe a significant enrichment of potentially deleterious promoter and/or UTR variants in individuals with rare disease collectively across any of our region or variant annotations. Conclusions: Overall, we demonstrate the value of screening promoters and UTRs to uncover additional diagnoses for previously undiagnosed individuals with rare disease and provide a framework for doing so without dramatically increasing interpretation burden.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements.

CRISPR-based gene activation (CRISPRa) is a promising therapeutic approach for gene therapy, upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis- regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to candidate cis- regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically and potently upregulating target genes, including autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans- acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate therapeutically relevant genes in a cell type-specific manner.

KCNT2-Related Disorders: Phenotypes, Functional, and Pharmacological Properties.

OBJECTIVE: Pathogenic variants in KCNT2 are rare causes of developmental epileptic encephalopathy (DEE). We herein describe the phenotypic and genetic features of patients with KCNT2-related DEE, and the in vitro functional and pharmacological properties of KCNT2 channels carrying 14 novel or previously untested variants. METHODS: Twenty-five patients harboring KCNT2 variants were investigated: 12 were identified through an international collaborative network, 13 were retrieved from the literature. Clinical data were collected and included in a standardized phenotyping sheet. Novel variants were detected using exome sequencing and classified using ACMG criteria. Functional and pharmacological studies were performed by whole-cell electrophysiology in HEK-293 and SH-SY5Y cells. RESULTS: The phenotypic spectrum encompassed: (a) intellectual disability/developmental delay (21/22 individuals with available information), ranging from mild to severe/profound; (b) epilepsy (15/25); (c) neurological impairment, with altered muscle tone (14/22); (d) dysmorphisms (13/20). Nineteen pathogenic KCNT2 variants were found (9 new, 10 reported previously): 16 missense, 1 in-frame deletion of a single amino acid, 1 nonsense, and 1 frameshift. Among tested variants, 8 showed gain-of-function (GoF), and 6 loss-of-function (LoF) features when expressed heterologously in vitro. Quinidine and fluoxetine blocked all GoF variants, whereas loxapine and riluzole activated some LoF variants while blocking others. INTERPRETATION: We expanded the phenotypic and genotypic spectrum of KCNT2-related disorders, highlighting novel genotype-phenotype associations. Pathogenic KCNT2 variants cause GoF or LoF in vitro phenotypes, and each shows a unique pharmacological profile, suggesting the need for in vitro functional and pharmacological investigation to enable targeted therapies based on the molecular phenotype. ANN NEUROL 2023;94:332-349.

Characterization of De Novo Promoter Variants in Autism Spectrum Disorder with Massively Parallel Reporter Assays.

Autism spectrum disorder (ASD) is a common, complex, and highly heritable condition with contributions from both common and rare genetic variations. While disruptive, rare variants in protein-coding regions clearly contribute to symptoms, the role of rare non-coding remains unclear. Variants in these regions, including promoters, can alter downstream RNA and protein quantity; however, the functional impacts of specific variants observed in ASD cohorts remain largely uncharacterized. Here, we analyzed 3600 de novo mutations in promoter regions previously identified by whole-genome sequencing of autistic probands and neurotypical siblings to test the hypothesis that mutations in cases have a greater functional impact than those in controls. We leveraged massively parallel reporter assays (MPRAs) to detect transcriptional consequences of these variants in neural progenitor cells and identified 165 functionally high confidence de novo variants (HcDNVs). While these HcDNVs are enriched for markers of active transcription, disruption to transcription factor binding sites, and open chromatin, we did not identify differences in functional impact based on ASD diagnostic status.

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review.

OBJECTIVE: The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. METHODS: A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included. RESULTS: A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis." CONCLUSIONS: There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Spatiotemporal and genetic regulation of A-to-I editing throughout human brain development.

Posttranscriptional RNA modifications by adenosine-to-inosine (A-to-I) editing are abundant in the brain, yet elucidating functional sites remains challenging. To bridge this gap, we investigate spatiotemporal and genetically regulated A-to-I editing sites across prenatal and postnatal stages of human brain development. More than 10,000 spatiotemporally regulated A-to-I sites were identified that occur predominately in 3' UTRs and introns, as well as 37 sites that recode amino acids in protein coding regions with precise changes in editing levels across development. Hyper-edited transcripts are also enriched in the aging brain and stabilize RNA secondary structures. These features are conserved in murine and non-human primate models of neurodevelopment. Finally, thousands of cis-editing quantitative trait loci (edQTLs) were identified with unique regulatory effects during prenatal and postnatal development. Collectively, this work offers a resolved atlas linking spatiotemporal variation in editing levels to genetic regulatory effects throughout distinct stages of brain maturation.

A biomedical open knowledge network harnesses the power of AI to understand deep human biology.

Knowledge representation and reasoning (KR&R) has been successfully implemented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article we describe concrete uses of SPOKE, an open knowledge network that connects curated information from 37 specialized and human-curated databases into a single property graph, with 3 million nodes and 15 million edges to date. Applications discussed in this article include drug discovery, COVID-19 research and chronic disease diagnosis and management.

Prenatal Somatic Cell Gene Therapies: Charting a Path Toward Clinical Applications (Proceedings of the CERSI-FDA Meeting).

We are living in a golden age of medicine in which the availability of prenatal diagnosis, fetal therapy, and gene therapy/editing make it theoretically possible to repair almost any defect in the genetic code. Furthermore, the ability to diagnose genetic disorders before birth and the presence of established surgical techniques enable these therapies to be delivered safely to the fetus. Prenatal therapies are generally used in the second or early third trimester for severe, life-threatening disorders for which there is a clear rationale for intervening before birth. While there has been promising work for prenatal gene therapy in preclinical models, the path to a clinical prenatal gene therapy approach is complex. We recently held a conference with the University of California, San Francisco-Stanford Center of Excellence in Regulatory Science and Innovation, researchers, patient advocates, regulatory (members of the Food and Drug Administration), and other stakeholders to review the scientific background and rationale for prenatal somatic cell gene therapy for severe monogenic diseases and initiate a dialogue toward a safe regulatory path for phase 1 clinical trials. This review represents a summary of the considerations and discussions from these conversations.

Enhancing Clinical Information Display to Improve Patient Encounters: Human-Centered Design and Evaluation of the Parkinson Disease-BRIDGE Platform.

BACKGROUND: People with Parkinson disease (PD) have a variety of complex medical problems that require detailed review at each clinical encounter for appropriate management. Care of other complex conditions has benefited from digital health solutions that efficiently integrate disparate clinical information. Although various digital approaches have been developed for research and care in PD, no digital solution to personalize and improve communication in a clinical encounter is readily available. OBJECTIVE: We intend to improve the efficacy and efficiency of clinical encounters with people with PD through the development of a platform (PD-BRIDGE) with personalized clinical information from the electronic health record (EHR) and patient-reported outcome (PRO) data. METHODS: Using human-centered design (HCD) processes, we engaged clinician and patient stakeholders in developing PD-BRIDGE through three phases: an inspiration phase involving focus groups and discussions with people having PD, an ideation phase generating preliminary mock-ups for feedback, and an implementation phase testing the platform. To qualitatively evaluate the platform, movement disorders neurologists and people with PD were sent questionnaires asking about the technical validity, usability, and clinical relevance of PD-BRIDGE after their encounter. RESULTS: The HCD process led to a platform with 4 modules. Among these, 3 modules that pulled data from the EHR include a longitudinal module showing motor ratings over time, a display module showing the most recently collected clinical rating scales, and another display module showing relevant laboratory values and diagnoses; the fourth module displays motor symptom fluctuation based on an at-home diary. In the implementation phase, PD-BRIDGE was used in 17 clinical encounters for patients cared for by 1 of 11 movement disorders neurologists. Most patients felt that PD-BRIDGE facilitated communication with their clinician (n=14, 83%) and helped them understand their disease trajectory (n=11, 65%) and their clinician's recommendations (n=11, 65%). Neurologists felt that PD-BRIDGE improved their ability to understand the patients' disease course (n=13, 75% of encounters), supported clinical care recommendations (n=15, 87%), and helped them communicate with their patients (n=14, 81%). In terms of improvements, neurologists noted that data in PD-BRIDGE were not exhaustive in 62% (n=11) of the encounters. CONCLUSIONS: Integrating clinically relevant information from EHR and PRO data into a visually efficient platform (PD-BRIDGE) can facilitate clinical encounters with people with PD. Developing new modules with more disparate information could improve these complex encounters even further.