12 research outputs found
Is Persistent Motor or Vocal Tic Disorder a Milder Form of Tourette Syndrome?
BACKGROUND: Persistent motor or vocal tic disorder (PMVT) has been hypothesized to be a forme fruste of Tourette syndrome (TS). Although the primary diagnostic criterion for PMVT (presence of motor or vocal tics, but not both) is clear, less is known about its clinical presentation. OBJECTIVE: The goals of this study were to compare the prevalence and number of comorbid psychiatric disorders, tic severity, age at tic onset, and family history for TS and PMVT. METHODS: We analyzed data from two independent cohorts using generalized linear equations and confirmed our findings using meta‐analyses, incorporating data from previously published literature. RESULTS: Rates of obsessive–compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) were lower in PMVT than in TS in all analyses. Other psychiatric comorbidities occurred with similar frequencies in PMVT and TS in both cohorts, although meta‐analyses suggested lower rates of most psychiatric disorders in PMVT compared with TS. ADHD and OCD increased the odds of comorbid mood, anxiety, substance use, and disruptive behaviors, and accounted for observed differences between PMVT and TS. Age of tic onset was approximately 2 years later, and tic severity was lower in PMVT than in TS. First‐degree relatives had elevated rates of TS, PMVT, OCD, and ADHD compared with population prevalences, with rates of TS equal to or greater than PMVT rates. CONCLUSIONS: Our findings support the hypothesis that PMVT and TS occur along a clinical spectrum in which TS is a more severe and PMVT a less severe manifestation of a continuous neurodevelopmental tic spectrum disorder. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Societ
Phenotype harmonization and analysis for The Populations Underrepresented in Mental illness Association Studies (the PUMAS Project)
Background
The Populations Underrepresented in Mental illness Association Studies (PUMAS) project is attempting to remediate the historical underrepresentation of African and Latin American populations in psychiatric genetics through large-scale genetic association studies of individuals diagnosed with a serious mental illness [SMI, including schizophrenia (SCZ), schizoaffective disorder (SZA) bipolar disorder (BP), and severe major depressive disorder (MDD)] and matched controls. Given growing evidence indicating substantial symptomatic and genetic overlap between these diagnoses, we sought to enable transdiagnostic genetic analyses of PUMAS data by conducting phenotype alignment and harmonization for 89,320 participants (48,165 cases and 41,155 controls) from four cohorts, each of which used different ascertainment and assessment methods: PAISA n=9,105; PUMAS-LATAM n=14,638; NGAP n=42,953 and GPC n=22,624. As we describe here, these efforts have yielded harmonized datasets enabling us to analyze PUMAS genetic variation data at three levels: SMI overall, diagnoses, and individual symptoms.
Methods
In aligning item-level phenotypes obtained from 14 different clinical instruments, we incorporated content, branching nature, and time frame for each phenotype; standardized diagnoses; and selected 19 core SMI item-level phenotypes for analyses. The harmonization was evaluated in PUMAS cases using multiple correspondence analysis (MCA), co-occurrence analyses, and item-level endorsement.
Outcomes
We mapped >6,895 item-level phenotypes in the aggregated PUMAS data, in which SCZ (44.97%) and severe BP (BP-I, 31.53%) were the most common diagnoses. Twelve of the 19 core item-level phenotypes occurred at frequencies of > 10% across all diagnoses, indicating their potential utility for transdiagnostic genetic analyses. MCA of the 14 phenotypes that were present for all cohorts revealed consistency across cohorts, and placed MDD and SCZ into separate clusters, while other diagnoses showed no significant phenotypic clustering.
Interpretation
Our alignment strategy effectively aggregated extensive phenotypic data obtained using diverse assessment tools. The MCA yielded dimensional scores which we will use for genetic analyses along with the item level phenotypes. After successful harmonization, residual phenotypic heterogeneity between cohorts reflects differences in branching structure of diagnostic instruments, recruitment strategies, and symptom interpretation (due to cultural variation)
SFMetaDB: A Comprehensive Annotation of Mouse RNA Splicing Factor RNA-Seq Datasets
AbstractAlthough the number of RNA-Seq datasets deposited publicly has increased over the past few years, incomplete annotation of the associated metadata limits their potential use. Because of the importance of RNA splicing in diseases and biological processes, we constructed a database called SFMetaDB by curating datasets related with RNA splicing factors. Our effort focused on the RNA-Seq datasets in which splicing factors were knocked-down, knocked-out or over-expressed, leading to 75 datasets corresponding to 56 splicing factors. These datasets can be used in differential alternative splicing analysis for the identification of the potential targets of these splicing factors and other functional studies. Surprisingly, only ∼15% of all the splicing factors have been studied by loss- or gain-of-function experiments using RNA-Seq. In particular, splicing factors with domains from a few dominant Pfam domain families have not been studied. This suggests a significant gap that needs to be addressed to fully elucidate the splicing regulatory landscape. Indeed, there are already mouse models available for ∼20 of the unstudied splicing factors, and it can be a fruitful research direction to study these splicing factors in vitro and in vivo using RNA-Seq.Database URLhttp://sfmetadb.ece.tamu.edu/</jats:sec
RBPMetaDB: A comprehensive annotation of mouse RNA-Seq datasets with perturbations of RNA-binding proteins
AbstractRNA-binding proteins may play a critical role in gene regulation in various diseases or biological processes by controlling post-transcriptional events such as polyadenylation, splicing, and mRNA stabilization via binding activities to RNA molecules. Due to the importance of RNA-binding proteins in gene regulation, a great number of studies have been conducted, resulting in a large amount of RNA-Seq datasets. However, these datasets usually do not have structured organization of metadata, which limits their potentially wide use. To bridge this gap, the metadata of a comprehensive set of publicly available mouse RNA-Seq datasets with perturbed RNA-binding proteins were collected and integrated into a database called RBPMetaDB. This database contains 278 mouse RNA-Seq datasets for a comprehensive list of 163 RNA-binding proteins. These RNA-binding proteins account for only ∼10% of all known RNA-binding proteins annotated in Gene Ontology, indicating that most are still unexplored using high-throughput sequencing. This negative information provides a great pool of candidate RNA-binding proteins for biologists to conduct future experimental studies. In addition, we found that DNA-binding activities are significantly enriched among RNA-binding proteins in RBPMetaDB, suggesting that prior studies of these DNA- and RNA-binding factors focus more on DNA-binding activities instead of RNA-binding activities. This result reveals the opportunity to efficiently reuse these data for investigation of the roles of their RNA-binding activities. A web application has also been implemented to enable easy access and wide use of RBPMetaDB. It is expected that RBPMetaDB will be a great resource for improving understanding of the biological roles of RNA-binding proteins.Database URL: http://rbpmetadb.yubiolab.org</jats:p
Cell-type-specific dysregulation of RNA alternative splicing in short tandem repeat mouse knockin models of myotonic dystrophy
Short tandem repeats (STRs) are prone to expansion mutations that cause multiple hereditary neurological and neuromuscular diseases. To study pathomechanisms using mouse models that recapitulate the tissue specificity and developmental timing of an STR expansion gene, we used rolling circle amplification and CRISPR/Cas9-mediated genome editing to generate Dmpk CTG expansion (CTGexp) knockin models of myotonic dystrophy type 1 (DM1). We demonstrate that skeletal muscle myoblasts and brain choroid plexus epithelial cells are particularly susceptible to Dmpk CTGexp mutations and RNA missplicing. Our results implicate dysregulation of muscle regeneration and cerebrospinal fluid homeostasis as early pathogenic events in DM1.</jats:p
