Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies.

Whether neurodegenerative diseases linked to misfolding of the same protein share genetic risk drivers or whether different protein-aggregation pathologies in neurodegeneration are mechanistically related remains uncertain. Conventional genetic analyses are underpowered to address these questions. Through careful selection of patients based on protein aggregation phenotype (rather than clinical diagnosis) we can increase statistical power to detect associated variants in a targeted set of genes that modify proteotoxicities. Genetic modifiers of alpha-synuclein (ɑS) and beta-amyloid (Aß) cytotoxicity in yeast are enriched in risk factors for Parkinson's disease (PD) and Alzheimer's disease (AD), respectively. Here, along with known AD/PD risk genes, we deeply sequenced exomes of 430 ɑS/Aß modifier genes in patients across alpha-synucleinopathies (PD, Lewy body dementia and multiple system atrophy). Beyond known PD genes GBA1 and LRRK2, rare variants AD genes (CD33, CR1 and PSEN2) and Aß toxicity modifiers involved in RhoA/actin cytoskeleton regulation (ARGHEF1, ARHGEF28, MICAL3, PASK, PKN2, PSEN2) were shared risk factors across synucleinopathies. Actin pathology occurred in iPSC synucleinopathy models and RhoA downregulation exacerbated ɑS pathology. Even in sporadic PD, the expression of these genes was altered across CNS cell types. Genome-wide CRISPR screens revealed the essentiality of PSEN2 in both human cortical and dopaminergic neurons, and PSEN2 mutation carriers exhibited diffuse brainstem and cortical synucleinopathy independent of AD pathology. PSEN2 contributes to a common-risk signal in PD GWAS and regulates ɑS expression in neurons. Our results identify convergent mechanisms across synucleinopathies, some shared with AD.

Low-frequency inherited complement receptor variants are associated with purpura fulminans.

ABSTRACT: Extreme disease phenotypes can provide key insights into the pathophysiology of common conditions, but studying such cases is challenging due to their rarity and the limited statistical power of existing methods. Herein, we used a novel approach to pathway-based mutational burden testing, the rare variant trend test (RVTT), to investigate genetic risk factors for an extreme form of sepsis-induced coagulopathy, infectious purpura fulminans (PF). In addition to prospective patient sample collection, we electronically screened over 10.4 million medical records from 4 large hospital systems and identified historical cases of PF for which archived specimens were available to perform germline whole-exome sequencing. We found a significantly increased burden of low-frequency, putatively function-altering variants in the complement system in patients with PF compared with unselected patients with sepsis (P = .01). A multivariable logistic regression analysis found that the number of complement system variants per patient was independently associated with PF after controlling for age, sex, and disease acuity (P = .01). Functional characterization of PF-associated variants in the immunomodulatory complement receptors CR3 and CR4 revealed that they result in partial or complete loss of anti-inflammatory CR3 function and/or gain of proinflammatory CR4 function. Taken together, these findings suggest that inherited defects in CR3 and CR4 predispose to the maladaptive hyperinflammation that characterizes severe sepsis with coagulopathy.

The missing link between genetic association and regulatory function.

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.'

The Parkinson's disease protein alpha-synuclein is a modulator of processing bodies and mRNA stability.

Alpha-synuclein (αS) is a conformationally plastic protein that reversibly binds to cellular membranes. It aggregates and is genetically linked to Parkinson's disease (PD). Here, we show that αS directly modulates processing bodies (P-bodies), membraneless organelles that function in mRNA turnover and storage. The N terminus of αS, but not other synucleins, dictates mutually exclusive binding either to cellular membranes or to P-bodies in the cytosol. αS associates with multiple decapping proteins in close proximity on the Edc4 scaffold. As αS pathologically accumulates, aberrant interaction with Edc4 occurs at the expense of physiologic decapping-module interactions. mRNA decay kinetics within PD-relevant pathways are correspondingly disrupted in PD patient neurons and brain. Genetic modulation of P-body components alters αS toxicity, and human genetic analysis lends support to the disease-relevance of these interactions. Beyond revealing an unexpected aspect of αS function and pathology, our data highlight the versatility of conformationally plastic proteins with high intrinsic disorder.

Carnelian uncovers hidden functional patterns across diverse study populations from whole metagenome sequencing reads.

Microbial populations exhibit functional changes in response to different ambient environments. Although whole metagenome sequencing promises enough raw data to study those changes, existing tools are limited in their ability to directly compare microbial metabolic function across samples and studies. We introduce Carnelian, an end-to-end pipeline for metabolic functional profiling uniquely suited to finding functional trends across diverse datasets. Carnelian is able to find shared metabolic pathways, concordant functional dysbioses, and distinguish Enzyme Commission (EC) terms missed by existing methodologies. We demonstrate Carnelian's effectiveness on type 2 diabetes, Crohn's disease, Parkinson's disease, and industrialized and non-industrialized gut microbiome cohorts.

Integrative analysis of genetic data sets reveals a shared innate immune component in autism spectrum disorder and its co-morbidities.

BACKGROUND: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder that tends to co-occur with other diseases, including asthma, inflammatory bowel disease, infections, cerebral palsy, dilated cardiomyopathy, muscular dystrophy, and schizophrenia. However, the molecular basis of this co-occurrence, and whether it is due to a shared component that influences both pathophysiology and environmental triggering of illness, has not been elucidated. To address this, we deploy a three-tiered transcriptomic meta-analysis that functions at the gene, pathway, and disease levels across ASD and its co-morbidities. RESULTS: Our analysis reveals a novel shared innate immune component between ASD and all but three of its co-morbidities that were examined. In particular, we find that the Toll-like receptor signaling and the chemokine signaling pathways, which are key pathways in the innate immune response, have the highest shared statistical significance. Moreover, the disease genes that overlap these two innate immunity pathways can be used to classify the cases of ASD and its co-morbidities vs. controls with at least 70 % accuracy. CONCLUSIONS: This finding suggests that a neuropsychiatric condition and the majority of its non-brain-related co-morbidities share a dysregulated signal that serves as not only a common genetic basis for the diseases but also as a link to environmental triggers. It also raises the possibility that treatment and/or prophylaxis used for disorders of innate immunity may be successfully used for ASD patients with immune-related phenotypes.