Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders.

Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate <0.05, four of which were associated with all epilepsies and 39 with genetic generalized epilepsy. Most epilepsy risk loci were shared with schizophrenia (n = 31). Among the identified loci, 32 were novel for genetic generalized epilepsy, and two were novel for all epilepsies. There was a mixture of concordant and discordant allelic effects in the shared loci. The sign concordance of the identified variants was highly consistent between the discovery and independent datasets for all disorders, supporting the validity of the findings. Gene-set analysis for the shared loci between schizophrenia and genetic generalized epilepsy implicated biological processes related to cell cycle regulation, protein phosphatase activity, and membrane and vesicle function; the gene-set analyses for the other loci were underpowered. The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders.

Shared genetic loci between Alzheimer's disease and multiple sclerosis: Crossroads between neurodegeneration and immune system.

BACKGROUND: Neuroinflammation is involved in the pathophysiology of Alzheimer's disease (AD), including immune-linked genetic variants and molecular pathways, microglia and astrocytes. Multiple Sclerosis (MS) is a chronic, immune-mediated disease with genetic and environmental risk factors and neuropathological features. There are clinical and pathobiological similarities between AD and MS. Here, we investigated shared genetic susceptibility between AD and MS to identify putative pathological mechanisms shared between neurodegeneration and the immune system. METHODS: We analysed GWAS data for late-onset AD (N cases = 64,549, N controls = 634,442) and MS (N cases = 14,802, N controls = 26,703). Gaussian causal mixture modelling (MiXeR) was applied to characterise the genetic architecture and overlap between AD and MS. Local genetic correlation was investigated with Local Analysis of [co]Variant Association (LAVA). The conjunctional false discovery rate (conjFDR) framework was used to identify the specific shared genetic loci, for which functional annotation was conducted with FUMA and Open Targets. RESULTS: MiXeR analysis showed comparable polygenicities for AD and MS (approximately 1800 trait-influencing variants) and genetic overlap with 20% of shared trait-influencing variants despite negligible genetic correlation (rg = 0.03), suggesting mixed directions of genetic effects across shared variants. conjFDR analysis identified 16 shared genetic loci, with 8 having concordant direction of effects in AD and MS. Annotated genes in shared loci were enriched in molecular signalling pathways involved in inflammation and the structural organisation of neurons. CONCLUSIONS: Despite low global genetic correlation, the current results provide evidence for polygenic overlap between AD and MS. The shared loci between AD and MS were enriched in pathways involved in inflammation and neurodegeneration, highlighting new opportunities for future investigation.

Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures.

INTRODUCTION: There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD). METHODS: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS. RESULTS: The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau. DISCUSSION: The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment. HIGHLIGHTS: A multimodal hazard score (MHS) combined age, genetics, brain atrophy, and memory. The MHS predicted time to conversion from mild cognitive impairment to dementia. MHS reduced hypothetical Alzheimer's disease (AD) clinical trial sample sizes by 67%. A polygenic hazard score predicted age of onset of AD neuropathology.

CLIPPERS and its mimics: evaluation of new criteria for the diagnosis of CLIPPERS.

OBJECTIVE: To evaluate the accuracy of the recently proposed diagnostic criteria for chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS). METHODS: We enrolled 42 patients with hindbrain punctate and/or linear enhancements (<3 mm in diameter) and tested the CLIPPERS criteria. RESULTS: After a median follow-up of 50 months (IQR 25-82), 13 out of 42 patients were CLIPPERS-mimics: systemic and central nervous system lymphomas (n=7), primary central nervous system angiitis (n=4) and autoimmune gliopathies (n=2). The sensitivity and specificity of the CLIPPERS criteria were 93% and 69%, respectively. Nodular enhancement ( ≥ 3 mm in diameter), considered as a red flag in CLIPPERS criteria, was present in 4 out of 13 CLIPPERS-mimics but also in 2 out of 29 patients with CLIPPERS, explaining the lack of sensitivity. Four out of 13 CLIPPERS-mimics who initially met the CLIPPERS criteria displayed red flags at the second attack with a median time of 5.5 months (min 3, max 18), explaining the lack of specificity. One of these four patients had antimyelin oligodendrocyte glycoprotein antibodies, and the three remaining patients relapsed despite a daily dose of prednisone/prednisolone ≥ 30 mg and a biopsy targeting atypical enhancing lesions revealed a lymphoma. CONCLUSIONS: Our study highlights that (1) nodular enhancement should be considered more as an unusual finding than a red flag excluding the diagnosis of CLIPPERS; (2) red flags may occur up to 18 months after disease onset; (3) as opposed to CLIPPERS-mimics, no relapse occurs when the daily dose of prednisone/prednisolone is ≥ 30 mg; and (4) brain biopsy should target an atypical enhancing lesion when non-invasive investigations remain inconclusive.

Linking sarcopenia, brain structure and cognitive performance: a large-scale UK Biobank study.

Sarcopenia refers to age-related loss of muscle mass and function and is related to impaired somatic and brain health, including cognitive decline and Alzheimer's disease. However, the relationships between sarcopenia, brain structure and cognition are poorly understood. Here, we investigate the associations between sarcopenic traits, brain structure and cognitive performance. We included 33 709 UK Biobank participants (54.2% female; age range 44-82 years) with structural and diffusion magnetic resonance imaging, thigh muscle fat infiltration (n = 30 561) from whole-body magnetic resonance imaging (muscle quality indicator) and general cognitive performance as indicated by the first principal component of a principal component analysis across multiple cognitive tests (n = 22 530). Of these, 1703 participants qualified for probable sarcopenia based on low handgrip strength, and we assigned the remaining 32 006 participants to the non-sarcopenia group. We used multiple linear regression to test how sarcopenic traits (probable sarcopenia versus non-sarcopenia and percentage of thigh muscle fat infiltration) relate to cognitive performance and brain structure (cortical thickness and area, white matter fractional anisotropy and deep and lower brain volumes). Next, we used structural equation modelling to test whether brain structure mediated the association between sarcopenic and cognitive traits. We adjusted all statistical analyses for confounders. We show that sarcopenic traits (probable sarcopenia versus non-sarcopenia and muscle fat infiltration) are significantly associated with lower cognitive performance and various brain magnetic resonance imaging measures. In probable sarcopenia, for the included brain regions, we observed widespread significant lower white matter fractional anisotropy (77.1% of tracts), predominantly lower regional brain volumes (61.3% of volumes) and thinner cortical thickness (37.9% of parcellations), with |r| effect sizes in (0.02, 0.06) and P-values in (0.0002, 4.2e-29). In contrast, we observed significant associations between higher muscle fat infiltration and widespread thinner cortical thickness (76.5% of parcellations), lower white matter fractional anisotropy (62.5% of tracts) and predominantly lower brain volumes (35.5% of volumes), with |r| effect sizes in (0.02, 0.07) and P-values in (0.0002, 1.9e-31). The regions showing the most significant effect sizes across the cortex, white matter and volumes were of the sensorimotor system. Structural equation modelling analysis revealed that sensorimotor brain regions mediate the link between sarcopenic and cognitive traits [probable sarcopenia: P-values in (0.0001, 1.0e-11); muscle fat infiltration: P-values in (7.7e-05, 1.7e-12)]. Our findings show significant associations between sarcopenic traits, brain structure and cognitive performance in a middle-aged and older adult population. Mediation analyses suggest that regional brain structure mediates the association between sarcopenic and cognitive traits, with potential implications for dementia development and prevention.

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology.

Background and Objectives: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results: The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

Dissecting the genetic overlap between three complex phenotypes with trivariate MiXeR.

Comorbidities are an increasing global health challenge. Accumulating evidence suggests overlapping genetic architectures underlying comorbid complex human traits and disorders. The bivariate causal mixture model (MiXeR) can quantify the polygenic overlap between complex phenotypes beyond global genetic correlation. Still, the pattern of genetic overlap between three distinct phenotypes, which is important to better characterize multimorbidities, has previously not been possible to quantify. Here, we present and validate the trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three phenotypes using summary statistics from genome-wide association studies (GWAS). Our simulations show that the trivariate MiXeR can reliably reconstruct different patterns of genetic overlap. We further demonstrate how the tool can be used to estimate the proportions of genetic overlap between three phenotypes using real GWAS data, providing examples of complex patterns of genetic overlap between diverse human traits and diseases that could not be deduced from bivariate analyses. This contributes to a better understanding of the etiology of complex phenotypes and the nature of their relationship, which may aid in dissecting comorbidity patterns and their biological underpinnings.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

The shared genetic risk architecture of neurological and psychiatric disorders: a genome-wide analysis.

While neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathobiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here, we performed a comprehensive analysis of GWAS data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic risk and biological underpinnings. Using complementary statistical tools, we demonstrate widespread genetic overlap across the disorders, even in the absence of genetic correlations. This indicates that a large set of common variants impact risk of multiple neurological and psychiatric disorders, but with divergent effect sizes. Furthermore, biological interrogation revealed a range of biological processes associated with neurological diseases, while psychiatric disorders consistently implicated neuronal biology. Altogether, the study indicates that neurological and psychiatric disorders share key etiological aspects, which has important implications for disease classification, precision medicine, and clinical practice.

Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders.

Importance: Premenstrual disorders are heritable, clinically heterogenous, with a range of affective spectrum comorbidities. It is unclear whether genetic predispositions to affective spectrum disorders or other major psychiatric disorders are associated with symptoms of premenstrual disorders. Objective: To assesss whether symptoms of premenstrual disorders are associated with the genetic liability for major psychiatric disorders, as indexed by polygenic risk scores (PRSs). Design, Setting, and Participants: Women from the Norwegian Mother, Father and Child Cohort Study were included in this genetic association study. PRSs were used to determine whether genetic liability for major depression, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism spectrum disorder were associated with the symptoms of premenstrual disorders, using the PRS for height as a somatic comparator. The sample was recruited across Norway between June 1999 and December 2008, and analyses were performed from July 1 to October 14, 2022. Main Outcomes and Measures: The symptoms of premenstrual disorders were assessed at recruitment at week 15 of pregnancy with self-reported severity of depression and irritability before menstruation. Logistic regression was applied to test for the association between the presence of premenstrual disorder symptoms and the PRSs for major psychiatric disorders. Results: The mean (SD) age of 56 725 women included in the study was 29.0 (4.6) years. Premenstrual disorder symptoms were present in 12 316 of 56 725 participants (21.7%). The symptoms of premenstrual disorders were associated with the PRSs for major depression (ß = 0.13; 95% CI, 0.11-0.15; P = 1.21 × 10-36), bipolar disorder (ß = 0.07; 95% CI, 0.05-0.09; P = 1.74 × 10-11), attention deficit/hyperactivity disorder (ß = 0.07; 95% CI, 0.04-0.09; P = 1.58 × 10-9), schizophrenia (ß = 0.11; 95% CI, 0.09-0.13; P = 7.61 × 10-25), and autism spectrum disorder (ß = 0.03; 95% CI, 0.01-0.05; P = .02) but not with the PRS for height. The findings were confirmed in a subsample of women without a history of psychiatric diagnosis. Conclusions: The results of this genetic association study show that genetic liability for both affective spectrum disorder and major psychiatric disorders was associated with symptoms of premenstrual disorders, indicating that premenstrual disorders have overlapping genetic foundations with major psychiatric disorders.

The epidemiology of amyotrophic lateral sclerosis in Moscow (Russia).

Objectives: To estimate the incidence of amyotrophic lateral sclerosis (ALS) in Moscow by investigating multiple sources of cases. Incidence rates from previous Russian studies ranged from 0.3 to 0.7 per 100,000/year. Methods: A retrospective study of the incidence of ALS was performed in the South district of Moscow (population, 1,760,000, 2015). Several data sources were investigated. The medical records of the calendar year 2015 were examined by an ALS expert who accepted only patients with definite or probable ALS according to the revised El Escorial criteria. Crude and standardized incidence rates were calculated, the latter adjusted to the Russian and the European population. Results: Twenty-two patients were found, accounting for a crude incidence of 1.25/100,000/year (95% CI 0.78-1.89) and a standardized incidence of 1.22 (Russia) and 1.28 (Europe). The sample included 11 men and 11 women aged 36-73 years (mean 56). Five patients (23%) had bulbar onset ALS. The mean diagnostic delay was 12.8 ± 9.2 months (8.5 ± 4.8 in men and 17.2 ± 10.6 in women) (p = 0.02). Family history of ALS was present in two cases. Conclusion: The incidence of ALS in the Russian Federation is higher than previously reported but lower than in other countries. Poor diagnostic ascertainment, particularly in women, and the shorter life expectancy of the Russian population are possible explanations.

Interleukin-6, S-Nitrosothiols, and Neurodegeneration in Different Central Nervous System Demyelinating Disorders: Is There a Relationship?

BACKGROUND AND PURPOSE: A few groups have suggested that activated cytokines and nitrosative stress are closely involved in the pathogenesis of different demyelinating disorders induced by the neuroinflammatory destruction of neurons. The purpose of this study was to elucidate the associations of cytokines and S-nitrosothiols (RSNO) with the severity of neurodegeneration during relapse in demyelinating disorders of the central nervous system. METHODS: We measured levels of interleukin-6 (IL-6), erythropoietin, RSNO, and phosphorylated neurofilament heavy chain (pNfh) in cerebrospinal fluid (CSF) samples obtained from patients with different demyelinating disorders: multiple sclerosis (MS, n=52), acute disseminated encephalomyelitis (ADEM, n=9), and neuromyelitis optica spectrum disorders (NMOSD) with aquaporin-4 immunoglobulin G (AQP4-IgG, n=12). We compared these levels with those measured in a control group (n=24). RESULTS: We found that IL-6 in CSF was elevated in NMOSD with AQP4-IgG and ADEM patients as well as in MS patients after the destruction of soluble IL-6. Erythropoietin levels were lower in MS, while RSNO levels were higher in NMOSD with AQP4-IgG and MS patients than in the control group. CSF pNfh levels were elevated in MS and ADEM patients. CONCLUSIONS: These results confirm that IL-6 is activated in different demyelinating disorders, with this elevation being more prominent in the CSF of NMOSD with AQP4-IgG and ADEM patients. Moreover, S-nitrosylation is activated in demyelinating disorders with spinal-cord injury and neurodegeneration in these patients. However, we found no correlation between these biochemical markers, and so we could not confirm whether IL-6-mediated nitric oxide production is involved in spinal-cord lesions.

Coexistence of multiple sclerosis and ankylosing spondylitis: Report of four cases from Russia and review of the literature.

Multiple sclerosis is a chronic demyelinating disorder of the central nervous system. There are many cases of multiple sclerosis - like syndrome and demyelinating disorders in systemic lupus erythematosus, Sjogren disease, Behcet disease and other autoimmune conditions. Coexistence of ankylosing spondylitis and multiple sclerosis usually is rare but in this article we report 4 Russian patients with concomitant multiple sclerosis and ankylosing spondylitis diseases. None of these patients received anti-tumor necrosis factor alpha therapy prior to diagnosis of multiple sclerosis. Pathogenesis, diagnostic and treatment challenges are discussed.

Increased S-nitrosothiols are associated with spinal cord injury in multiple sclerosis.

Multiple sclerosis (MS) is an immune-mediated disorder associated with inflammation, demyelination and axonal damage. In search of potential biomarkers of spinal cord lesions in MS related to nitric oxide metabolites, we measured total nitrite and nitrate levels, and protein-bound nitrotyrosine and S-nitrosothiol concentrations in the serum of MS patients at different stages of the disease. Sixty-eight patients and 36 healthy volunteers were included in the study. Total nitrite and nitrate levels were augmented in relapsing-remitting MS, while increased S-nitrosothiol concentrations were found both in relapsing-remitting and secondary-progressive MS. Further analysis demonstrated that S-nitrosothiol levels were selectively increased in patients with spinal cord injury. The data suggest that high S-nitrosothiol concentration may be a potential serum biomarker for spinal cord injury in MS.