Prevalence of autoimmune diseases in functional neurological disorder: influence of psychiatric comorbidities and biological sex.

BACKGROUND: Functional neurological disorder (FND) is a common and disabling neuropsychiatric condition, which disproportionally affects women compared with men. While the etiopathogenesis of this disorder remains elusive, immune dysregulation is emerging as one potential mechanism. To begin to understand the role of immune dysfunctions in FND, we assessed the prevalence of several common autoimmune diseases (ADs) in a large cohort of patients with FND and examined the influence of psychiatric comorbidities and biological sex. METHODS: Using a large biorepository database (Mass General Brigham Biobank), we obtained demographic and clinical data of a cohort of 643 patients diagnosed with FND between January 2015 and December 2021. The proportion of ADs was calculated overall, by sex and by the presence of psychiatric comorbidities. RESULTS: The overall prevalence of ADs in our sample was 41.9%, with connective tissue and autoimmune endocrine diseases being the most commonly observed ADs. Among patients with FND and ADs, 27.7% had ≥2 ADs and 8% met criteria for multiple autoimmune syndrome. Rates of ADs were significantly higher in subjects with comorbid major depressive disorder and post-traumatic stress disorder (p= 0.02). Women represented the largest proportion of patients with concurrent ADs, both in the overall sample and in the subgroups of interest (p's < 0.05). CONCLUSIONS: This study is unique in providing evidence of an association between FND and ADs. Future studies are needed to investigate the mechanisms underlying this association and to understand whether FND is characterised by distinct dysregulations in immune response.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways.

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Multi-Trait Analysis of GWAS and Biological Insights Into Cognition: A Response to Hill (2018).

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

A genetic association study of CSMD1 and CSMD2 with cognitive function.

The complement cascade plays a role in synaptic pruning and synaptic plasticity, which seem to be involved in cognitive functions and psychiatric disorders. Genetic variants in the closely related CSMD1 and CSMD2 genes, which are implicated in complement regulation, are associated with schizophrenia. Since patients with schizophrenia often show cognitive impairments, we tested whether variants in CSMD1 and CSMD2 are also associated with cognitive functions per se. We took a discovery-replication approach, using well-characterized Scandinavian cohorts. A total of 1637 SNPs in CSMD1 and 206 SNPs in CSMD2 were tested for association with cognitive functions in the NCNG sample (Norwegian Cognitive NeuroGenetics; n=670). Replication testing of SNPs with p-value<0.001 (7 in CSMD1 and 3 in CSMD2) was carried out in the TOP sample (Thematically Organized Psychosis; n=1025) and the BETULA sample (Betula Longitudinal Study on aging, memory and dementia; n=1742). Finally, we conducted a meta-analysis of these SNPs using all three samples. The previously identified schizophrenia marker in CSMD1 (SNP rs10503253) was also included. The strongest association was observed between the CSMD1 SNP rs2740931 and performance in immediate episodic memory (p-value=5×10-6, minor allele A, MAF 0.48-0.49, negative direction of effect). This association reached the study-wide significance level (p⩽1.2×10-5). SNP rs10503253 was not significantly associated with cognitive functions in our samples. In conclusion, we studied n=3437 individuals and found evidence that a variant in CSMD1 is associated with cognitive function. Additional studies of larger samples with cognitive phenotypes will be needed to further clarify the role of CSMD1 in cognitive phenotypes in health and disease.

Linkage-disequilibrium-based binning affects the interpretation of GWASs.

Genome-wide association studies (GWASs) are critically dependent on detailed knowledge of the pattern of linkage disequilibrium (LD) in the human genome. GWASs generate lists of variants, usually SNPs, ranked according to the significance of their association to a trait. Downstream analyses generally focus on the gene or genes that are physically closest to these SNPs and ignore their LD profile with other SNPs. We have developed a flexible R package (LDsnpR) that efficiently assigns SNPs to genes on the basis of both their physical position and their pairwise LD with other SNPs. We used the positional-binning and LD-based-binning approaches to investigate whether including these "LD-based" SNPs would affect the interpretation of three published GWASs on bipolar affective disorder (BP) and of the imputed versions of two of these GWASs. We show how including LD can be important for interpreting and comparing GWASs. In the published, unimputed GWASs, LD-based binning effectively "recovered" 6.1%-8.3% of Ensembl-defined genes. It altered the ranks of the genes and resulted in nonnegligible differences between the lists of the top 2,000 genes emerging from the two binning approaches. It also improved the overall gene-based concordance between independent BP studies. In the imputed datasets, although the increases in coverage (>0.4%) and rank changes were more modest, even greater concordance between the studies was observed, attesting to the potential of LD-based binning on imputed data as well. Thus, ignoring LD can result in the misinterpretation of the GWAS findings and have an impact on subsequent genetic and functional studies.

Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment.

Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.

SUMO modification is required for in vivo Hox gene regulation by the Caenorhabditis elegans Polycomb group protein SOP-2.

Post-translational modification of proteins by the ubiquitin-like molecule SUMO (sumoylation) regulates their subcellular localization and affects their functional properties in vitro, but the physiological function of sumoylation in multicellular organisms is largely unknown. Here, we show that the C. elegans Polycomb group (PcG) protein SOP-2 interacts with the SUMO-conjugating enzyme UBC-9 through its evolutionarily conserved SAM domain. Sumoylation of SOP-2 is required for its localization to nuclear bodies in vivo and for its physiological repression of Hox genes. Global disruption of sumoylation phenocopies a sop-2 mutation by causing ectopic Hox gene expression and homeotic transformations. Chimeric constructs in which the SOP-2 SAM domain is replaced with that derived from fruit fly or mammalian PcG proteins, but not those in which the SOP-2 SAM domain is replaced with the SAM domains of non-PcG proteins, confer appropriate in vivo nuclear localization and Hox gene repression. These observations indicate that sumoylation of PcG proteins, modulated by their evolutionarily conserved SAM domain, is essential to their physiological repression of Hox genes.

Imaging and cognitive genetics: the Norwegian Cognitive NeuroGenetics sample.

Data collection for the Norwegian Cognitive NeuroGenetics sample (NCNG) was initiated in 2003 with a research grant (to Ivar Reinvang) to study cognitive aging, brain function, and genetic risk factors. The original focus was on the effects of aging (from middle age and up) and candidate genes (e.g., APOE, CHRNA4) in cross-sectional and longitudinal designs, with the cognitive and MRI-based data primarily being used for this purpose. However, as the main topic of the project broadened from cognitive aging to imaging and cognitive genetics more generally, the sample size, age range of the participants, and scope of available phenotypes and genotypes, have developed beyond the initial project. In 2009, a genome-wide association (GWA) study was undertaken, and the NCNG proper was established to study the genetics of cognitive and brain function more comprehensively. The NCNG is now controlled by the NCNG Study Group, which consists of the present authors. Prominent features of the NCNG are the adult life-span coverage of healthy participants with high-dimensional imaging, and cognitive data from a genetically homogenous sample. Another unique property is the large-scale (sample size 300-700) use of experimental cognitive tasks focusing on attention and working memory. The NCNG data is now used in numerous ongoing GWA-based studies and has contributed to several international consortia on imaging and cognitive genetics. The objective of the following presentation is to give other researchers the information necessary to evaluate possible contributions from the NCNG to various multi-sample data analyses.

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Which behaviours are first to emerge during recovery of consciousness after severe brain injury?

BACKGROUND: Early detection of consciousness after severe brain injury is critical for establishing an accurate prognosis and planning appropriate treatment. OBJECTIVES: To determine which behavioural signs of consciousness emerge first and to estimate the time course to recovery of consciousness in patients with severe acquired brain injury. METHODS: Retrospective observational study using the Coma Recovery Scale-Revised and days to recovery of consciousness in 79 patients (51 males; 34 with traumatic brain injury; median [IQR] age 48 [26-61] years; median time since injury 26 [20-36] days) who transitioned from coma or unresponsive wakefulness syndrome (UWS)/vegetative state (VS) to the minimally conscious state (MCS) or emerged from MCS during inpatient rehabilitation. RESULTS: Visual pursuit was the most common initial sign of MCS (41% of patients; 95% CI [30-52]), followed by reproducible command-following (25% [16-35]) and automatic movements (24% [15-33]). Ten other behaviours emerged first in less than 16% of cases. Median [IQR] time to recovery of consciousness was 44 [33-59] days. Etiology did not significantly affect time to recovered consciousness. CONCLUSION: Recovery of consciousness after severe brain injury is most often signalled by reemergence of visual pursuit, reproducible command-following and automatic movements. Clinicians should use assessment measures that are sensitive to these behaviours because early detection of consciousness is critical for accurate prognostication and treatment planning.