Concordance of genetic variation that increases risk for tourette syndrome and that influences its underlying neurocircuitry

Trends of Tourette Syndrome in children from 2011 to 2021: A bibliometric analysis

Objective

Analyze the research status of Tourette Syndrome (TS) in children by CiteSpace and determine the current research hotspots and frontiers.

Materials and methods

We chose publications indexed in the Web of Science Core Collection (WoSCC) database for studies related to TS in children from 2011 to 2021. We built online cooperation maps of countries/regions, institutions, authors, journals, references, and keywords by CiteSpace, and identified hotspots and frontiers of study for children’s TS.

Results

A total of 1,232 publications about TS in children were downloaded from the WoSCC. The USA (414) was the country with the highest rate of production, and University College London (87) was the institution that had the highest publication rate. Andrea Eugenio Cavanna was the most prolific author (39 papers). There was inactive cooperation between institutions, countries/regions, and authors. The Journal of European Child & Adolescent Psychiatry was the most active journal. Hot topics focused on epidemiology, comorbidities, deep brain stimulation, behavioral therapy, basal ganglia, pharmacological treatment, and risk factors of TS in children.

Conclusion

According to the CiteSpace results, this study found that authors, countries/regions, and institutions were not actively working together. Current research hotspots mainly consist of epidemiology, comorbidities, deep brain stimulation, behavior therapy, and basal ganglia. The main research trends include comorbidities, pharmacological treatment, and risk factors. Therefore, international cooperation should be strengthened in the future, and it should be mindful of the psychiatric comorbidities of TS, the choice of intervention measures, and early warning of risk factors.

Dopamine-2 receptor antibody encephalitis presenting as pure tongue-biting in a tourette syndrome patient: a case report

BACKGROUND

Tourette syndrome (TS) is a neuropsychiatric disorder characterized by repetitive and patterned tics. Its onset correlates with dysfunctions in immunological activation and neurotransmitters. Autoimmune movement disorders such as dopamine-2 receptor antibody encephalitis (D2R encephalitis) may go undiagnosed in TS patients seeking medical help for tic symptoms only. Here, we present a clinical case of D2R encephalitis in a TS patient.

CASE PRESENTATION

A 13-year-old boy with a history of TS presented with acute tongue-biting without positive neurologic examination or auxiliary examination results, except for a weakly positive finding for D2R antibodies in the serum sample. He was initially diagnosed with possible D2R encephalitis, but the influence of TS could not be ruled out. In addition to psychotropics, we administered immunotherapy early based on clinical characteristics, and his symptoms were ameliorated significantly. During the follow-up, he was diagnosed with definite D2R encephalitis, and the dosage of psychotropics was further adjusted for fluctuating symptoms.

CONCLUSIONS

Our case suggests that clinicians should discern D2R encephalitis in TS patients when tics are the primary symptoms. Administering immunotherapy early, according to clinical characteristics, may benefit the patient. Moreover, the features of premonitory urges could help evaluate the state of TS.

Current Understanding of the Genetics of Tourette Syndrome

Gilles de la Tourette syndrome (TS) is a common, childhood-onset psychiatric disorder characterized by persistent motor and vocal tics. It is a heterogeneous disorder in which the phenotypic expression may be affected by environmental factors, such as immune responses. Furthermore, several studies have shown that genetic factors play a vital role in the etiology of TS, as well as its comorbidity with other disorders, including attention deficit hyperactivity disorder, obsessive-compulsive disorder, and autism spectrum disorder. TS has a complex inheritance pattern and, according to various genetic studies, several genes and loci have been correlated with TS. Genome-wide linkage studies have identified Slit and Trk-like 1 (SLITRK1) and histidine decarboxylase (HDC) genes, and candidate gene association studies have extensively investigated the dopamine and serotonin system genes, but there have been no consistent results. Moreover, genome-wide association studies have implicated several genetic loci; however, larger study cohorts are needed to confirm this. Copy number variations, which are polymorphisms in the number of gene copies due to chromosomal deletions or duplications, are considered another significant source of mutations in TS. In the last decade, whole genome/exome sequencing has identified several novel genetic mutations in patients with TS. In conclusion, more studies are needed to reveal the exact mechanisms of underlying TS, which may help to provide more information on the prognosis and therapeutic plans for TS.

Enhancing neuroimaging genetics through meta-analysis for Tourette syndrome (ENIGMA-TS): A worldwide platform for collaboration

Tourette syndrome (TS) is characterized by multiple motor and vocal tics, and high-comorbidity rates with other neuropsychiatric disorders. Obsessive compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), major depressive disorder (MDD), and anxiety disorders (AXDs) are among the most prevalent TS comorbidities. To date, studies on TS brain structure and function have been limited in size with efforts mostly fragmented. This leads to low-statistical power, discordant results due to differences in approaches, and hinders the ability to stratify patients according to clinical parameters and investigate comorbidity patterns. Here, we present the scientific premise, perspectives, and key goals that have motivated the establishment of the Enhancing Neuroimaging Genetics through Meta-Analysis for TS (ENIGMA-TS) working group. The ENIGMA-TS working group is an international collaborative effort bringing together a large network of investigators who aim to understand brain structure and function in TS and dissect the underlying neurobiology that leads to observed comorbidity patterns and clinical heterogeneity. Previously collected TS neuroimaging data will be analyzed jointly and integrated with TS genomic data, as well as equivalently large and already existing studies of highly comorbid OCD, ADHD, ASD, MDD, and AXD. Our work highlights the power of collaborative efforts and transdiagnostic approaches, and points to the existence of different TS subtypes. ENIGMA-TS will offer large-scale, high-powered studies that will lead to important insights toward understanding brain structure and function and genetic effects in TS and related disorders, and the identification of biomarkers that could help inform improved clinical practice.

Grey matter abnormalities in Tourette syndrome: an activation likelihood estimation meta-analysis

BACKGROUND

Tourette syndrome (TS) is a neurodevelopmental disorder defined by the continual presence of primary motor and vocal tics. Grey matter abnormalities have been identified in numerous studies of TS, but conflicting results have been reported. This study was an unbiased statistical meta-analysis of published neuroimaging studies of TS structures.

METHODS

A voxel quantitative meta-analysis technique called activation likelihood estimation (ALE) was used. The meta-analysis included six neuroimaging studies involving 247 TS patients and 236 healthy controls. A statistical threshold of p < 0.05 was established based on the false discovery rate and a cluster extent threshold of 50 voxels.

RESULTS

We found that grey matter volumes were significantly increased in the bilateral thalamus, right hypothalamus, right precentral gyrus, left postcentral gyrus, left inferior parietal lobule, right lentiform nucleus, and left insula of TS patients compared to those of healthy controls. In contrast, grey matter volumes were significantly decreased in the bilateral postcentral gyrus, bilateral anterior cingulate, bilateral insula, left posterior cingulate and left postcentral gyrus of TS patients compared to those of healthy controls.

CONCLUSIONS

Our present meta-analysis primarily revealed significant increases in grey matter volumes in the thalamus and lentiform nucleus, and decreased grey matter volumes in the anterior cingulate gyrus, of TS patients compared to those in healthy controls. Most of these identified regions are associated with cortico-striato-thalamo-cortical circuits. Further studies with larger sample sizes are needed to confirm these changes in grey matter volumes in TS patients.

Overlap in genetic risk for cross-disorder vulnerability to mental disorders and genetic risk for altered subcortical brain volumes

BACKGROUND

There have been considerable recent advances in understanding the genetic architecture of psychiatric disorders as well as the underlying neurocircuitry. However, there is little work on the concordance of genetic variations that increase risk for cross-disorder vulnerability, and those that influence subcortical brain structures. We undertook a genome-wide investigation of the genetic overlap between cross-disorder vulnerability to psychiatric disorders (p-factor) and subcortical brain structures.

METHODS

Summary statistics were obtained from the PGC cross-disorder genome-wide association study (GWAS) (N_case= 232,964, N_control= 494,162) and the CHARGE-ENIGMA subcortical brain volumes GWAS (N=38,851). SNP effect concordance analysis (SECA) was used to assess pleiotropy and concordance. Linkage Disequilibrium (LD) Score Regression and ρ-HESS were used to assess genetic correlation and conditional false discovery (cFDR) was used to identify variants associated with p-factor, conditional on the variants association with subcortical brain volumes.

RESULTS

Evidence of global pleiotropy between p-factor and all subcortical brain regions was observed. Risk variants for p-factor correlated negatively with brainstem. A total of 787 LD-independent variants were significantly associated with p-factor when conditioned on the subcortical GWAS results. Gene set enrichment analysis of these variants implicated actin binding and neuronal regulation.

LIMITATIONS

SECA could be biased due to the potential presence of overlapping study participants in the p-factor and subcortical GWASs.

CONCLUSION

Findings of genome-wide pleiotropy and possible concordance between genetic variants that contribute to p-factor and smaller brainstem volumes, are consistent with previous work. cFDR results highlight actin binding and neuron regulation as key underlying mechanisms. Further fine-grained delineation of these mechanisms is needed to advance the field.

Hippocampal Volume in Provisional Tic Disorder Predicts Tic Severity at 12-Month Follow-up

Previous studies have investigated differences in the volumes of subcortical structures (e.g., caudate nucleus, putamen, thalamus, amygdala, and hippocampus) between individuals with and without Tourette syndrome (TS), as well as the relationships between these volumes and tic symptom severity. These volumes may also predict clinical outcome in Provisional Tic Disorder (PTD), but that hypothesis has never been tested. This study aimed to examine whether the volumes of subcortical structures measured shortly after tic onset can predict tic symptom severity at one-year post-tic onset, when TS can first be diagnosed. We obtained T1-weighted structural MRI scans from 41 children with PTD (25 with prospective motion correction (vNavs)) whose tics had begun less than 9 months (mean 4.04 months) prior to the first study visit (baseline). We re-examined them at the 12-month anniversary of their first tic (follow-up), assessing tic severity using the Yale Global Tic Severity Scale. We quantified the volumes of subcortical structures using volBrain software. Baseline hippocampal volume was correlated with tic severity at the 12-month follow-up, with a larger hippocampus at baseline predicting worse tic severity at follow-up. The volumes of other subcortical structures did not significantly predict tic severity at follow-up. Hippocampal volume may be an important marker in predicting prognosis in Provisional Tic Disorder.

Translating insights from neuropsychiatric genetics and genomics for precision psychiatry

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.

Discovery of shared genomic loci using the conditional false discovery rate approach

In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.

Tourette syndrome research highlights from 2018

This is the fifth yearly article in the Tourette Syndrome Research Highlights series, summarizing research from 2018 relevant to Tourette syndrome and other tic disorders. The authors briefly summarize reports they consider most important or interesting. The  highlights from 2019 article is being drafted on the Authorea online authoring platform, and readers are encouraged to add references or give feedback on our selections using the comments feature on that page. After the calendar year ends, the article is submitted as the annual update for the  Tics collection on F1000Research.