FIVEx: an interactive eQTL browser across public datasets

Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3

INTRODUCTION

Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear.

METHODS

We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269).

RESULTS

CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9).

DISCUSSION

These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels.

HIGHLIGHTS

Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.

Adaptive and Innate Immunity Are Key Drivers of Age at Onset of Multiple Sclerosis

Background and Objectives

Multiple sclerosis (MS) age at onset (AAO) is a clinical predictor of long-term disease outcomes, independent of disease duration. Little is known about the genetic and biological mechanisms underlying age of first symptoms. We conducted a genome-wide association study (GWAS) to investigate associations between individual genetic variation and the MS AAO phenotype.

Methods

The study population was comprised participants with MS in 6 clinical trials: ADVANCE (N = 655; relapsing-remitting [RR] MS), ASCEND (N = 555; secondary-progressive [SP] MS), DECIDE (N = 1,017; RRMS), OPERA1 (N = 581; RRMS), OPERA2 (N = 577; RRMS), and ORATORIO (N = 529; primary-progressive [PP] MS). Altogether, 3,905 persons with MS of European ancestry were analyzed. GWAS were conducted for MS AAO in each trial using linear additive models controlling for sex and 10 principal components. Resultant summary statistics across the 6 trials were then meta-analyzed, for a total of 8.3 × 10-6 single nucleotide polymorphisms (SNPs) across all trials after quality control and filtering for heterogeneity. Gene-based tests of associations, pathway enrichment analyses, and Mendelian randomization analyses for select exposures were also performed.

Results

Four lead SNPs within 2 loci were identified (p < 5 × 10-8), including a) 3 SNPs in the major histocompatibility complex and their effects were independent of HLA-DRB1*15:01 and b) a LOC105375167 variant on chromosome 7. At the gene level, the top association was HLA-C (p = 1.2 × 10-7), which plays an important role in antiviral immunity. Functional annotation revealed the enrichment of pathways related to T-cell receptor signaling, autoimmunity, and the complement cascade. Mendelian randomization analyses suggested a link between both earlier age at puberty and shorter telomere length and earlier AAO, while there was no evidence for a role for either body mass index or vitamin D levels.

Discussion

Two genetic loci associated with MS AAO were identified, and functional annotation demonstrated an enrichment of genes involved in adaptive and complement immunity. There was also evidence supporting a link with age at puberty and telomere length. The findings suggest that AAO in MS is multifactorial, and the factors driving onset of symptoms overlap with those influencing MS risk.

Integrated multiplexed assays of variant effect reveal determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase or decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Investigation of genetic determinants of cognitive change in later life

Cognitive decline is a major health concern and identification of genes that may serve as drug targets to slow decline is important to adequately support an aging population. Whilst genetic studies of cross-sectional cognition have been carried out, cognitive change is less well-understood. Here, using data from the TOMMORROW trial, we investigate genetic associations with cognitive change in a cognitively normal older cohort. We conducted a genome-wide association study of trajectories of repeated cognitive measures (using generalised estimating equation (GEE) modelling) and tested associations with polygenic risk scores (PRS) of potential risk factors. We identified two genetic variants associated with change in attention domain scores, rs534221751 (p = 1 × 10-8 with slope 1) and rs34743896 (p = 5 × 10-10 with slope 2), implicating NCAM2 and CRIPT/ATP6V1E2 genes, respectively. We also found evidence for the association between an education PRS and baseline cognition (at >65 years of age), particularly in the language domain. We demonstrate the feasibility of conducting GWAS of cognitive change using GEE modelling and our results suggest that there may be novel genetic associations for cognitive change that have not previously been associated with cross-sectional cognition. We also show the importance of the education PRS on cognition much later in life. These findings warrant further investigation and demonstrate the potential value of using trial data and trajectory modelling to identify genetic variants associated with cognitive change.

Spatiotemporal expression patterns of anxiety disorder-associated genes

Anxiety disorders (ADs) are the most common form of mental disorder that affects millions of individuals worldwide. Although physiological studies have revealed the neural circuits related to AD symptoms, how AD-associated genes are spatiotemporally expressed in the human brain still remains unclear. In this study, we integrated genome-wide association studies of four human AD subtypes-generalized anxiety disorder, social anxiety disorder, panic disorder, and obsessive-compulsive disorder-with spatial gene expression patterns. Our investigation uncovered a novel division among AD-associated genes, marked by significant and distinct expression enrichments in the cerebral nuclei, limbic, and midbrain regions. Each gene cluster was associated with specific anxiety-related behaviors, signaling pathways, region-specific gene networks, and cell types. Notably, we observed a significant negative correlation in the temporal expression patterns of these gene clusters during various developmental stages. Moreover, the specific brain regions enriched in each gene group aligned with neural circuits previously associated with negative decision-making and anxious temperament. These results suggest that the two distinct gene clusters may underlie separate neural systems involved in anxiety. As a result, our findings bridge the gap between genes and neural circuitry, shedding light on the mechanisms underlying AD-associated behaviors.

Integrated multiplexed assays of variant effect reveal cis-regulatory determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase and decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Genome-wide census of ATF4 binding sites and functional profiling of trait-associated genetic variants overlapping ATF4 binding motifs

Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation.

In silico prioritisation of microRNA-associated common variants in multiple sclerosis

BACKGROUND

Genome-wide association studies (GWAS) have highlighted over 200 autosomal variants associated with multiple sclerosis (MS). However, variants in non-coding regions such as those encoding microRNAs have not been explored thoroughly, despite strong evidence of microRNA dysregulation in MS patients and model organisms. This study explores the effect of microRNA-associated variants in MS, through the largest publicly available GWAS, which involved 47,429 MS cases and 68,374 controls.

METHODS

We identified SNPs within the coordinates of microRNAs, ± 5-kb microRNA flanking regions and predicted 3'UTR target-binding sites using miRBase v22, TargetScan 7.0 RNA22 v2.0 and dbSNP v151. We established the subset of microRNA-associated SNPs which were tested in the summary statistics of the largest MS GWAS by intersecting these datasets. Next, we prioritised those microRNA-associated SNPs which are among known MS susceptibility SNPs, are in strong linkage disequilibrium with the former or meet a microRNA-specific Bonferroni-corrected threshold. Finally, we predicted the effects of those prioritised SNPs on their microRNAs and 3'UTR target-binding sites using TargetScan v7.0, miRVaS and ADmiRE.

RESULTS

We have identified 30 candidate microRNA-associated variants which meet at least one of our prioritisation criteria. Among these, we highlighted one microRNA variant rs1414273 (MIR548AC) and four 3'UTR microRNA-binding site variants within SLC2A4RG (rs6742), CD27 (rs1059501), MMEL1 (rs881640) and BCL2L13 (rs2587100). We determined changes to the predicted microRNA stability and binding site recognition of these microRNA and target sites.

CONCLUSIONS

We have systematically examined the functional, structural and regulatory effects of candidate MS variants among microRNAs and 3'UTR targets. This analysis allowed us to identify candidate microRNA-associated MS SNPs and highlights the value of prioritising non-coding RNA variation in GWAS. These candidate SNPs could influence microRNA regulation in MS patients. Our study is the first thorough investigation of both microRNA and 3'UTR target-binding site variation in multiple sclerosis using GWAS summary statistics.

Multi-Omics Studies in Historically Excluded Populations: The Road to Equity

Over the past few decades, genomewide association studies (GWASs) have identified the specific genetics variants contributing to many complex diseases by testing millions of genetic variations across the human genome against a variety of phenotypes. However, GWASs are limited in their ability to uncover mechanistic insight given that most significant associations are found in non-coding region of the genome. Furthermore, the lack of diversity in studies has stymied the advance of precision medicine for many historically excluded populations. In this review, we summarize most popular multi-omics approaches (genomics, transcriptomics, proteomics, and metabolomics) related to precision medicine and highlight if diverse populations have been included and how their findings have advance biological understanding of disease and drug response. New methods that incorporate local ancestry have been to improve the power of GWASs for admixed populations (such as African Americans and Latinx). Because most signals from GWAS are in the non-coding region, other machine learning and omics approaches have been developed to identify the potential causative single-nucleotide polymorphisms and genes that explain these phenotypes. These include polygenic risk scores, expression quantitative trait locus mapping, and transcriptome-wide association studies. Analogous protein methods, such as proteins quantitative trait locus mapping, proteome-wide association studies, and metabolomic approaches provide insight into the consequences of genetic variation on protein abundance. Whereas, integrated multi-omics studies have improved our understanding of the mechanisms for genetic association, we still lack the datasets and cohorts for historically excluded populations to provide equity in precision medicine and pharmacogenomics.

GeneticsMakie.jl: a versatile and scalable toolkit for visualizing locus-level genetic and genomic data

SUMMARY

With the continued deluge of results from genome-wide association and functional genomic studies, it has become increasingly imperative to quickly combine and visualize different layers of genetic and genomic data within a given locus to facilitate exploratory and integrative data analyses. While several tools have been developed to visualize locus-level genetic results, the limited speed, scalability and flexibility of current approaches remain a significant bottleneck. Here, we present a Julia package for high-performance genetics and genomics-related data visualization that enables fast, simultaneous plotting of hundreds of association results along with multiple relevant genomic annotations. Leveraging the powerful plotting and layout utilities from Makie.jl facilitates the customization and extensibility of every component of a plot, enabling generation of publication-ready figures.

AVAILABILITY AND IMPLEMENTATION

The GeneticsMakie.jl package is open source and distributed under the MIT license via GitHub (https://github.com/mmkim1210/GeneticsMakie.jl). The GitHub repository contains installation instructions as well as examples and documentation for built-in functions.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-Wide Pleiotropy Study Identifies Association of PDGFB with Age-Related Macular Degeneration and COVID-19 Infection Outcomes

Age-related macular degeneration (AMD) has been implicated as a risk factor for severe consequences from COVID-19. We evaluated the genetic architecture shared between AMD and COVID-19 (critical illness, hospitalization, and infections) using analyses of genetic correlations and pleiotropy (i.e., cross-phenotype meta-analysis) of AMD (n = 33,976) and COVID-19 (n ≥ 1,388,342) and subsequent analyses including expression quantitative trait locus (eQTL), differential gene expression, and Mendelian randomization (MR). We observed a significant genetic correlation between AMD and COVID-19 infection (r_G = 0.10, p = 0.02) and identified novel genome-wide significant associations near PDGFB (best SNP: rs130651; p = 2.4 × 10^-8) in the pleiotropy analysis of the two diseases. The disease-risk allele of rs130651 was significantly associated with increased gene expression levels of PDGFB in multiple tissues (best eQTL p = 1.8 × 10^-11 in whole blood) and immune cells (best eQTL p = 7.1 × 10^-20 in T-cells). PDGFB expression was observed to be higher in AMD cases than AMD controls {fold change (FC) = 1.02; p = 0.067}, as well as in the peak COVID-19 symptom stage (11-20 days after the symptom onset) compared to early/progressive stage (0-10 days) among COVID-19 patients over age 40 (FC = 2.17; p = 0.03) and age 50 (FC = 2.15; p = 0.04). Our MR analysis found that the liability of AMD risk derived from complement system dysfunction {OR (95% CI); hospitalization = 1.02 (1.01-1.03), infection = 1.02 (1.01-1.03) and increased levels of serum cytokine PDGF-BB {β (95% CI); critical illness = 0.07 (0.02-0.11)} are significantly associated with COVID-19 outcomes. Our study demonstrated that the liability of AMD is associated with an increased risk of COVID-19, and PDGFB may be responsible for the severe COVID-19 outcomes among AMD patients.

MicroRNA-7 regulates melanocortin circuits involved in mammalian energy homeostasis

MicroRNAs (miRNAs) modulate physiological responses by repressing the expression of gene networks. We found that global deletion of microRNA-7 (miR-7), the most enriched miRNA in the hypothalamus, causes obesity in mice. Targeted deletion of miR-7 in Single-minded homolog 1 (Sim1) neurons, a critical component of the hypothalamic melanocortin pathway, causes hyperphagia, obesity and increased linear growth, mirroring Sim1 and Melanocortin-4 receptor (MC4R) haplo-insufficiency in mice and humans. We identified Snca (α-Synuclein) and Igsf8 (Immunoglobulin Superfamily Member 8) as miR-7 target genes that act in Sim1 neurons to regulate body weight and endocrine axes. In humans, MIR-7-1 is located in the last intron of HNRNPK, whose promoter drives the expression of both genes. Genetic variants at the HNRNPK locus that reduce its expression are associated with increased height and truncal fat mass. These findings demonstrate that miR-7 suppresses gene networks involved in the hypothalamic melanocortin pathway to regulate mammalian energy homeostasis.

Synonymous mutation rs1129293 is associated with PIK3CG expression and PI3Kγ activation in patients with chronic Chagas cardiomyopathy

Single nucleotide polymorphisms (SNPs) that do not change the composition of amino acids and cause synonymous mutations (sSNPs) were previously considered to lack any functional roles. However, sSNPs have recently been shown to interfere with protein expression owing to a myriad of factors related to the regulation of transcription, mRNA stability, and protein translation processes. In patients with Chagas disease, the presence of the synonymous mutation rs1129293 in phosphatidylinositol-4,5-bisphosphate 3-kinase gamma (PIK3CG) gene contributes to the development of the chronic Chagas cardiomyopathy (CCC), instead of the digestive or asymptomatic forms. In this study, we aimed to investigate whether rs1129293 is associated with the transcription of PIK3CG mRNA and its activity by quantifying AKT phosphorylation in the heart samples of 26 chagasic patients with CCC. Our results showed an association between rs1129293 and decreased PIK3CG mRNA expression levels in the cardiac tissues of patients with CCC. The phosphorylation levels of AKT, the protein target of PI3K, were also reduced in patients with this mutation, but were not correlated with PI3KCG mRNA expression levels. Moreover, bioinformatics analysis showed that rs1129293 and other SNPs in linkage disequilibrium (LD) were associated with the transcriptional regulatory elements, post-transcriptional modifications, and cell-specific splicing expression of PIK3CG mRNA. Therefore, our data demonstrates that the synonymous SNP rs1129293 is capable of affecting the PIK3CG mRNA expression and PI3Kγ activation.