OBJECTIVE
Mental disorders are heritable and polygenic, and genome-wide genetic correlations (rg) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, rg may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions.


METHODS
The authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of "causal" variants for a given trait ("polygenicity"), the number of variants shared between traits, and the genetic correlation of shared variants (rgs). Local rg was investigated using LAVA.


RESULTS
Among mental disorders, ADHD was the least polygenic (5.6K "causal" variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in rg and rgs. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local rg (r=0.88, p<0.001).


CONCLUSIONS
There is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction.

Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation.

Summary Background T cells control viral infection, promote vaccine durability, and in coronavirus disease 2019 (COVID-19) associate with mild disease. We investigated whether prior measles-mumps-rubella (MMR) or tetanus-diphtheria-pertussis (Tdap) vaccination elicits cross-reactive T cells that mitigate COVID-19. Methods Antigen-presenting cells (APC) loaded ex vivo with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), MMR, or Tdap antigens and autologous T cells from COVID-19-convalescent participants, uninfected individuals, and COVID-19 mRNA-vaccinated donors were co-cultured. T cell activation and phenotype were detected by interferon-γ (IFN-γ) enzyme-linked immunospot (ELISpot) assays and flow cytometry. ELISAs (enzyme-linked immunosorbant assays) and validation studies identified the APC-derived cytokine(s) driving T cell activation. TCR clonotyping and single-cell RNA sequencing (scRNA-seq) identified cross-reactive T cells and their transcriptional profile. A propensity-weighted analysis of COVID-19 patients estimated the effects of MMR and Tdap vaccination on COVID-19 outcomes. Findings High correlation was observed between T cell responses to SARS-CoV-2 (spike-S1 and nucleocapsid) and MMR and Tdap proteins in COVID-19-convalescent and -vaccinated individuals. The overlapping T cell population contained an effector memory T cell subset (effector memory re-expressing CD45RA on T cells [TEMRA]) implicated in protective, anti-viral immunity, and their detection required APC-derived IL-15, known to sensitize T cells to activation. Cross-reactive TCR repertoires detected in antigen-experienced T cells recognizing SARS-CoV-2, MMR, and Tdap epitopes had TEMRA features. Indices of disease severity were reduced in MMR- or Tdap-vaccinated individuals by 32%–38% and 20%–23%, respectively, among COVID-19 patients. Conclusions Tdap and MMR memory T cells reactivated by SARS-CoV-2 may provide protection against severe COVID-19. Funding This study was supported by a National Institutes of Health (R01HL065095, R01AI152522, R01NS097719) donation from Barbara and Amos Hostetter and the Chleck Foundation.

Protective heterologous T cell immunity in COVID-19 induced by the trivalent MMR and Tdap vaccine antigens.

Epigenetic lesions that disrupt regulatory elements represent potential cancer drivers. However, we lack experimental models for validating their tumorigenic impact. Here, we model aberrations arising in isocitrate dehydrogenase-mutant gliomas, which exhibit DNA hypermethylation. We focus on a CTCF insulator near the PDGFRA oncogene that is recurrently disrupted by methylation in these tumors. We demonstrate that disruption of the syntenic insulator in mouse oligodendrocyte progenitor cells (OPCs) allows an OPC-specific enhancer to contact and induce Pdgfra, thereby increasing proliferation. We show that a second lesion, methylation-dependent silencing of the Cdkn2a tumor suppressor, cooperates with insulator loss in OPCs. Coordinate inactivation of the Pdgfra insulator and Cdkn2a drives gliomagenesis in vivo. Despite locus synteny, the insulator is CpG-rich only in humans, a feature that may confer human glioma risk but complicates mouse modeling. Our study demonstrates the capacity of recurrent epigenetic lesions to drive OPC proliferation in vitro and gliomagenesis in vivo. 

Modeling epigenetic lesions that cause gliomas

Cortical morphology is a key determinant of cognitive ability and mental health. Its development is a highly intricate process spanning decades, involving the coordinated, localized expression of thousands of genes. We are now beginning to unravel the genetic architecture of cortical morphology, thanks to the recent availability of large-scale neuroimaging and genomic data and the development of powerful biostatistical tools. Here, we review the progress made in this field, providing an overview of the lessons learned from genetic studies of cortical volume, thickness, surface area, and folding as captured by neuroimaging. It is now clear that morphology is shaped by thousands of genetic variants, with effects that are region- and time-dependent, thereby challenging conventional study approaches. The most recent genome-wide association studies have started discovering common genetic variants influencing cortical thickness and surface area, yet together these explain only a fraction of the high heritability of these measures. Further, the impact of rare variants and non-additive effects remains elusive. There are indications that the quickly increasing availability of data from whole-genome sequencing and large, deeply phenotyped population cohorts across the lifespan will enable us to uncover much of the missing heritability in the upcoming years. Novel approaches leveraging shared information across measures will accelerate this process by providing substantial increases in statistical power, together with more accurate mapping of genetic relationships. Important challenges remain, including better representation of understudied demographic groups, integration of other 'omics data, and mapping of effects from gene to brain to behavior across the lifespan. 

https://www.nature.com/articles/s41398-022-02193-5.pdf

Mapping the genetic architecture of cortical morphology through neuroimaging: progress and perspectives

The integration of quantitative trait loci (QTL) with disease genome-wide association studies (GWAS) has proven successful at prioritizing candidate genes at disease-associated loci. QTL mapping has mainly been focused on multi-tissue expression QTL or plasma protein QTL (pQTL). Here we generated the largest-to-date cerebrospinal fluid (CSF) pQTL atlas by analyzing 7,028 proteins in 3,107 samples. We identified 3,373 independent study-wide associations for 1,961 proteins, including 2,448 novel pQTLs of which 1,585 are unique to CSF, demonstrating unique genetic regulation of the CSF proteome. In addition to the established chr6p22.2-21.32 HLA region, we identified pleiotropic regions on chr3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron-specificity and neurological development. We also integrated this pQTL atlas with the latest Alzheimer's disease (AD) GWAS through PWAS, colocalization and Mendelian Randomization and identified 42 putative causal proteins for AD, 15 of which have drugs available. Finally, we developed a proteomics-based risk score for AD that outperforms genetics-based polygenic risk scores. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits. 

/pdf/proteogenomic-analysis-of-human-cerebrospinal-fluid-428ghogf.pdf

Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and informs causal proteins for Alzheimer’s disease

https://escholarship.org/content/qt9mb5c7gd/qt9mb5c7gd.pdf?t=r18b93

Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology

Background COVID-19 is characterized by strikingly large, mostly unexplained, interindividual variation in symptom severity: while some individuals remain nearly asymptomatic, others suffer from severe respiratory failure. Previous vaccinations for other pathogens, in particular tetanus, may partly explain this variation, possibly by readying the immune system. Methods We made use of data on COVID-19 testing from 103,049 participants of the UK Biobank (mean age 71.5 years, 54.2% female), coupled to immunization records of the last ten years. Using logistic regression, covarying for age, sex, respiratory disease diagnosis, and socioeconomic status, we tested whether individuals vaccinated for tetanus, diphtheria or pertussis, differed from individuals that had only received other vaccinations on 1) undergoing a COVID-19 test, 2) being diagnosed with COVID-19, and 3) whether they developed severe COVID-19 symptoms. Results We found that individuals with registered diphtheria or tetanus vaccinations are less likely to develop severe COVID-19 than people who had only received other vaccinations (diphtheria odds ratio (OR)=0.47, p-value=5.3*10-5; tetanus OR=0.52, p-value=1.2*10-4). Discussion These results indicate that a history of diphtheria or tetanus vaccinations is associated with less severe manifestations of COVID-19. These vaccinations may protect against severe COVID-19 symptoms by stimulating the immune system. We note the correlational nature of these results, yet the possibility that these vaccinations may influence the severity of COVID-19 warrants follow-up investigations.

/pdf/diphtheria-and-tetanus-vaccination-history-is-associated-13qbn8fgrg.pdf

Diphtheria And Tetanus Vaccination History Is Associated With Lower Odds of COVID-19 Hospitalization.

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Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology

Diphtheria And Tetanus Vaccination History Is Associated With Lower Odds of COVID-19 Hospitalization.