Cavalleri, Gianpiero L.

Abstract Objective Autoimmune encephalitis is a cause of brain inflammation characterized by auto‐antibodies, which target cell surface neuronal proteins and lead to neuronal dysfunction. The most common form is associated with auto‐antibodies to leucine‐rich glioma‐inactivated 1 (LGI1) protein, the presentation of which includes frequent focal seizures. The exact cause of these auto‐antibodies remains unknown, but established predispositions include overrepresented human leukocyte antigen ( HLA ) alleles. Yet, these HLA alleles are themselves common in the healthy ancestry‐matched population. One potential etiological hypothesis is that an environmental trigger, such as the gut microbiome, interacts with a genetically predisposed individual. Methods To investigate this, we studied 42 patients with LGI1‐antibody encephalitis (LGI1‐Ab‐E) and 27 familial/environmentally matched controls, and performed metagenomic shotgun sequencing, to describe the compositional and functional differences in the gut microbiome. Results We observed that LGI1‐Ab‐E gut microbiomes exhibited a significant reduction in the ratio of Firmicutes (or Bacillota) and Bacteroidetes phyla, which is associated with the dosage of HLA susceptibility allele count in patients with LGI1‐Ab‐E. Furthermore, we identified differences in functional gene profiles in the gut microbiome that led to a reduction of neuroinflammatory protective short‐chain fatty acids (SCFAs) in LGI1‐Ab‐E patients. Significance Taken together, our results suggest that a compositional shift in the gut microbiome of LGI1‐Ab‐E associates with a neuroinflammatory state, possibly through the reduction of SCFA production. Our study highlights the potential of the gut microbiome to explain some of the complex condition and unravel etiological questions. Validation studies with greater sample sizes are recommended.

Abstract Encephalitis with antibodies to leucine-rich glioma-inactivated 1 (LGI1-Ab-E) is a common form of autoimmune encephalitis, presenting with seizures and neuropsychiatric changes, predominantly in older males. More than 90% of patients carry the human leukocyte antigen (HLA) class II allele, HLA-DRB1*07:01. However, this is also present in 25% of healthy controls. Therefore, we hypothesized the presence of additional genetic predispositions. In this genome-wide association study and meta-analysis, we studied a discovery cohort of 131 French LGI1-Ab-E and a validation cohort of 126 American, British and Irish LGI1-Ab-E patients, ancestry-matched to 2613 and 2538 European controls, respectively. Outside the known major HLA signal, we found two single nucleotide polymorphisms at genome-wide significance (P < 5 × 10−8), implicating PTPRD, a protein tyrosine phosphatase, and LINC00670, a non-protein coding RNA gene. Meta-analysis defined four additional non-HLA loci, including the protein coding COBL gene. Polygenic risk scores with and without HLA variants proposed a contribution of non-HLA loci. In silico network analyses suggested LGI1 and PTPRD-mediated interactions via the established receptors of LGI1, ADAM22 and ADAM23. Our results identify new genetic loci in LGI1-Ab-E. These findings present opportunities for mechanistic studies and offer potential markers of susceptibility, prognostics and therapeutic responses.

Abstract Aims The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems‐level analysis. Methods Imaging‐based cortical structural maps from a large‐scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell‐type deconvolution, differential expression analysis and cell‐type enrichment analyses were used to identify differences in cell‐type distribution. These differences were followed up in post‐mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell‐type‐specific depletion was used in a murine model of acquired epilepsy. Results We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post‐mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non‐spatial memory test seen in epileptic mice not depleted of microglia. Conclusions These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS