MungeSumstats: A Bioconductor package for the standardisation and quality control of many GWAS summary statistics

Dissecting Schizophrenia Biology Using Pleiotropy with Cognitive Genomics

Given the increasingly large number of loci discovered by psychiatric GWAS, specification of the key biological pathways underlying these loci has become a priority for the field. We have previously leveraged the pleiotropic genetic relationships between schizophrenia and two cognitive phenotypes (educational attainment and cognitive task performance) to differentiate two subsets of illness-relevant SNPs: (1) those with "concordant" alleles, which are associated with reduced cognitive ability/education and increased schizophrenia risk; and (2) those with "discordant" alleles linked to reduced educational and/or cognitive levels but lower schizophrenia susceptibility. In the present study, we extend our prior work, utilizing larger input GWAS datasets and a more powerful statistical approach to pleiotropic meta-analysis, the Pleiotropic Locus Exploration and Interpretation using Optimal test (PLEIO). Our pleiotropic meta-analysis of schizophrenia and the two cognitive phenotypes revealed 768 significant loci (159 novel). Among these, 347 loci harbored concordant SNPs, 270 encompassed discordant SNPs, and 151 "dual" loci contained concordant and discordant SNPs. Competitive gene-set analysis using MAGMA related concordant SNP loci with neurodevelopmental pathways (e.g., neurogenesis), whereas discordant loci were associated with mature neuronal synaptic functions. These distinctions were also observed in BrainSpan analysis of temporal enrichment patterns across developmental periods, with concordant loci containing more prenatally expressed genes than discordant loci. Dual loci were enriched for genes related to mRNA translation initiation, representing a novel finding in the schizophrenia literature.

Single-cell dissection of the human motor and prefrontal cortices in ALS and FTLD

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) share many clinical, pathological, and genetic features, but a detailed understanding of their associated transcriptional alterations across vulnerable cortical cell types is lacking. Here, we report a high-resolution, comparative single-cell molecular atlas of the human primary motor and dorsolateral prefrontal cortices and their transcriptional alterations in sporadic and familial ALS and FTLD. By integrating transcriptional and genetic information, we identify known and previously unidentified vulnerable populations in cortical layer 5 and show that ALS- and FTLD-implicated motor and spindle neurons possess a virtually indistinguishable molecular identity. We implicate potential disease mechanisms affecting these cell types as well as non-neuronal drivers of pathogenesis. Finally, we show that neuron loss in cortical layer 5 tracks more closely with transcriptional identity rather than cellular morphology and extends beyond previously reported vulnerable cell types.

A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.

A single nuclear transcriptomic characterisation of mechanisms responsible for impaired angiogenesis and blood-brain barrier function in Alzheimer's disease

Brain perfusion and blood-brain barrier (BBB) integrity are reduced early in Alzheimer's disease (AD). We performed single nucleus RNA sequencing of vascular cells isolated from AD and non-diseased control brains to characterise pathological transcriptional signatures responsible for this. We show that endothelial cells (EC) are enriched for expression of genes associated with susceptibility to AD. Increased β-amyloid is associated with BBB impairment and a dysfunctional angiogenic response related to a failure of increased pro-angiogenic HIF1A to increased VEGFA signalling to EC. This is associated with vascular inflammatory activation, EC senescence and apoptosis. Our genomic dissection of vascular cell risk gene enrichment provides evidence for a role of EC pathology in AD and suggests that reducing vascular inflammatory activation and restoring effective angiogenesis could reduce vascular dysfunction contributing to the genesis or progression of early AD.

Single-Nucleus RNA-Seq Characterizes the Cell Types Along the Neuronal Lineage in the Adult Human Subependymal Zone and Reveals Reduced Oligodendrocyte Progenitor Abundance with Age

The subependymal zone (SEZ), also known as the subventricular zone (SVZ), constitutes a neurogenic niche that persists during postnatal life. In humans, the neurogenic potential of the SEZ declines after the first year of life. However, studies discovering markers of stem and progenitor cells highlight the neurogenic capacity of progenitors in the adult human SEZ, with increased neurogenic activity occurring under pathological conditions. In the present study, the complete cellular niche of the adult human SEZ was characterized by single-nucleus RNA sequencing, and compared between four youth (age 16-22) and four middle-aged adults (age 44-53). We identified 11 cellular clusters including clusters expressing marker genes for neural stem cells (NSCs), neuroblasts, immature neurons, and oligodendrocyte progenitor cells. The relative abundance of NSC and neuroblast clusters did not differ between the two age groups, indicating that the pool of SEZ NSCs does not decline in this age range. The relative abundance of oligodendrocyte progenitors and microglia decreased in middle-age, indicating that the cellular composition of human SEZ is remodeled between youth and adulthood. The expression of genes related to nervous system development was higher across different cell types, including NSCs, in youth as compared with middle-age. These transcriptional changes suggest ongoing central nervous system plasticity in the SEZ in youth, which declined in middle-age.

BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies

MOTIVATION

Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted. As a result, many researchers continue to work with and publish using legacy genomic coordinates.

RESULTS

Here we present BCFtools/liftover, a tool to convert genomic coordinates across genome assemblies for variants encoded in the variant call format with improved support for indels represented by different reference alleles across genome assemblies and full support for multi-allelic variants. It further supports variant annotation fields updates whenever the reference allele changes across genome assemblies. The tool has the lowest rate of variants being dropped with an order of magnitude less indels dropped or incorrectly converted and is an order of magnitude faster than other tools typically used for the same task. It is particularly suited for converting variant callsets from large cohorts to novel telomere-to-telomere assemblies as well as summary statistics from genome-wide association studies tied to legacy genome assemblies.

AVAILABILITY AND IMPLEMENTATION

The tool is written in C and freely available under the MIT open source license as a BCFtools plugin available at http://github.com/freeseek/score.

Genomic analysis identifies risk factors in restless legs syndrome

Restless legs syndrome (RLS) is a neurological condition that causes uncomfortable sensations in the legs and an irresistible urge to move them, typically during periods of rest. The genetic basis and pathophysiology of RLS are incompletely understood. Here, we present a whole-genome sequencing and genome-wide association meta-analysis of RLS cases (n = 9,851) and controls (n = 38,957) in three population-based biobanks (All of Us, Canadian Longitudinal Study on Aging, and CARTaGENE). Genome-wide association analysis identified nine independent risk loci, of which eight had been previously reported, and one was a novel risk locus (LMX1B, rs35196838, OR = 1.14, 95% CI = 1.09-1.19, p-value = 2.2 × 10-9). A genome-wide, gene-based common variant analysis identified GLO1 as an additional risk gene (p-value = 8.45 × 10-7). Furthermore, a transcriptome-wide association study also identified GLO1 and a previously unreported gene, ELFN1. A genetic correlation analysis revealed significant common variant overlaps between RLS and neuroticism (rg = 0.40, se = 0.08, p-value = 5.4 × 10-7), depression (rg = 0.35, se = 0.06, p-value = 2.17 × 10-8), and intelligence (rg = -0.20, se = 0.06, p-value = 4.0 × 10-4). Our study expands the understanding of the genetic architecture of RLS and highlights the contributions of common variants to this prevalent neurological disorder.

Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation

BACKGROUND

Systematic characterization of how  genetic variation modulates gene regulation in a cell type-specific context is essential for understanding complex traits. To address this question, we profile gene expression and chromatin accessibility in cells from healthy retinae of 20 human donors through single-cell multiomics and genomic sequencing.

RESULTS

We map eQTL, caQTL, allelic-specific expression, and allelic-specific chromatin accessibility in major retinal cell types. By integrating these results, we identify and characterize regulatory elements and genetic variants effective on gene regulation in individual cell types. The majority of identified sc-eQTLs and sc-caQTLs display cell type-specific effects, while the cis-elements containing genetic variants with cell type-specific effects are often accessible in multiple cell types. Furthermore, the transcription factors whose binding sites are perturbed by genetic variants tend to have higher expression levels in the cell types where the variants exert their effects, compared to the cell types where the variants have no impact. We further validate our findings with high-throughput reporter assays. Lastly, we identify the enriched cell types, candidate causal variants and genes, and cell type-specific regulatory mechanism underlying GWAS loci.

CONCLUSIONS

Overall, genetic effects on gene regulation are highly context dependent. Our results suggest that cell type-dependent genetic effect is driven by precise modulation of both trans-factor expression and chromatin accessibility of cis-elements. Our findings indicate hierarchical collaboration among transcription factors plays a crucial role in mediating cell type-specific effects of genetic variants on gene regulation.

Integrated multi-omics single cell atlas of the human retina

Single-cell sequencing has revolutionized the scale and resolution of molecular profiling of tissues and organs. Here, we present an integrated multimodal reference atlas of the most accessible portion of the mammalian central nervous system, the retina. We compiled around 2.4 million cells from 55 donors, including 1.4 million unpublished data points, to create a comprehensive human retina cell atlas (HRCA) of transcriptome and chromatin accessibility, unveiling over 110 types. Engaging the retina community, we annotated each cluster, refined the Cell Ontology for the retina, identified distinct marker genes, and characterized cis-regulatory elements and gene regulatory networks (GRNs) for these cell types. Our analysis uncovered intriguing differences in transcriptome, chromatin, and GRNs across cell types. In addition, we modeled changes in gene expression and chromatin openness across gender and age. This integrated atlas also enabled the fine-mapping of GWAS and eQTL variants. Accessible through interactive browsers, this multimodal cross-donor and cross-lab HRCA, can facilitate a better understanding of retinal function and pathology.

Human brain single nucleus cell type enrichments in neurodegenerative diseases

Background

Single-cell RNA sequencing has opened a window into clarifying the complex underpinnings of disease, particularly in quantifying the relevance of tissue- and cell-type-specific gene expression.

Methods

To identify the cell types and genes important to therapeutic target development across the neurodegenerative disease spectrum, we leveraged genome-wide association studies, recent single-cell sequencing data, and bulk expression studies in a diverse series of brain region tissues.

Results

We were able to identify significant immune-related cell types in the brain across three major neurodegenerative diseases: Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. Subsequently, putative roles of 30 fine-mapped loci implicating seven genes in multiple neurodegenerative diseases and their pathogenesis were identified.

Conclusions

We have helped refine the genetic regions and cell types effected across multiple neurodegenerative diseases, helping focus future translational research efforts.

hipFG: high-throughput harmonization and integration pipeline for functional genomics data

SUMMARY

Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG (Harmonization and Integration Pipeline for Functional Genomics), an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g. chromatin interactions, genomic intervals, quantitative trait loci).

AVAILABILITY AND IMPLEMENTATION

hipFG is freely available at https://bitbucket.org/wanglab-upenn/hipFG. A Docker container is available at https://hub.docker.com/r/wanglab/hipfg.

Causal association between inflammatory bowel disease and 32 site-specific extracolonic cancers: a Mendelian randomization study

BACKGROUND

The risk of extracolonic cancer is increased in inflammatory bowel disease (IBD) patients, but it is not clear whether there is a causal relationship. We aimed to systematically estimate the causal relationship between IBD and extracolonic cancers.

METHODS

Independent genetic variants strongly associated with IBD were extracted as instrumental variables from genome-wide association study (GWAS) conducted by the International IBD Genetics Consortium including 12,882 IBD patients, 5956 Crohn's disease (CD) patients, and 6968 ulcerative colitis (UC) patients. Three sources of cancer GWAS were selected as outcome data. Two-sample Mendelian randomization (MR) analysis was conducted to assess the causal effects of IBD on 32 extracolonic cancers. The meta-analysis was applied to assess the combined causal effect with multiple MR results.

RESULTS

IBD, CD, and UC have potential causal associations with oral cavity cancer (IBD: OR = 1.180, 95% CI: 1.059 to 1.316, P = 0.003; CD: OR = 1.112, 95% CI: 1.008 to 1.227, P = 0.034; UC: OR = 1.158, 95% CI: 1.041 to 1.288, P = 0.007). Meta-analysis showed a significant positive causal relationship between IBD and breast cancer (OR = 1.059; 95% CI: 1.033 to 1.086; P < 0.0001) as well as a potential causal relationship between CD and breast cancer (OR = 1.029; 95% CI: 1.002 to 1.055; P = 0.032) based on combining multiple MR results.

CONCLUSIONS

This comprehensive MR analysis suggested that genetically predicted IBD, as well as its subtypes, may be a risk factor in the development of oral cavity and breast cancer.

Correlation study of malignant lymphoma and breast Cancer in different gender European populations: mendelian randomization analysis

BACKGROUND

Previous research has already indicated an elevated risk of breast cancer (BC) among survivors of malignant lymphoma, but the underlying reasons remain unknown. Our objective is to elucidate the causal relationship between malignant lymphoma and BC through Mendelian randomization (MR). Genome-wide association studies (GWAS) data from 181,125 Hodgkin lymphoma (HL) patients and 181,289 non-Hodgkin lymphoma (NHL) patients from the FinnGen Consortium were utilized as exposure. We selected single nucleotide polymorphisms (SNPs) strongly associated with the exposure as instrumental variables to investigate their relationship with BC in a cohort of 107,722 participants. Subsequently, we obtained data from the UK Biobank containing gender-stratified information on HL, NHL, and BC. We validated the findings from our analysis and explored the impact of gender. The Inverse-Variance Weighted (IVW) method served as the primary reference for the two-sample MR, accompanied by tests for heterogeneity and pleiotropy.

RESULTS

The analysis results from the FinnGen consortium indicate that there is no causal relationship between HL and NHL with BC. HL (OR = 1.01, 95% CI = 0.98-1.04, p = 0.29), NHL (OR = 1.01, 95% CI = 0.96-1.05, p = 0.64). When utilizing GWAS data from the UK Biobank that includes different gender cohorts, the lack of association between HL, NHL, and BC remains consistent. HL (OR = 1.08, 95% CI = 0.74-1.56, p = 0.69), HL-Female (OR = 0.84, 95% CI = 0.59-1.19, p = 0.33), NHL (OR = 0.89, 95% CI = 0.66-1.19, p = 0.44), and NHL-Female (OR = 0.81, 95% CI = 0.58-1.11, p = 0.18).

CONCLUSIONS

The two-sample MR analysis indicates that there is no significant causal relationship between malignant lymphoma (HL and NHL) and BC. The association between malignant lymphoma and breast cancer requires further in-depth research and exploration.

Shared genetic basis informs the roles of polyunsaturated fatty acids in brain disorders

The neural tissue is rich in polyunsaturated fatty acids (PUFAs), components that are indispensable for the proper functioning of neurons, such as neurotransmission. PUFA nutritional deficiency and imbalance have been linked to a variety of chronic brain disorders, including major depressive disorder (MDD), anxiety, and anorexia. However, the effects of PUFAs on brain disorders remain inconclusive, and the extent of their shared genetic determinants is largely unknown. Here, we used genome-wide association summary statistics to systematically examine the shared genetic basis between six phenotypes of circulating PUFAs (N = 114,999) and 20 brain disorders (N = 9,725-762,917), infer their potential causal relationships, identify colocalized regions, and pinpoint shared genetic variants. Genetic correlation and polygenic overlap analyses revealed a widespread shared genetic basis for 77 trait pairs between six PUFA phenotypes and 16 brain disorders. Two-sample Mendelian randomization analysis indicated potential causal relationships for 16 pairs of PUFAs and brain disorders, including alcohol consumption, bipolar disorder (BIP), and MDD. Colocalization analysis identified 40 shared loci (13 unique) among six PUFAs and ten brain disorders. Twenty-two unique variants were statistically inferred as candidate shared causal variants, including rs1260326 (GCKR), rs174564 (FADS2) and rs4818766 (ADARB1). These findings reveal a widespread shared genetic basis between PUFAs and brain disorders, pinpoint specific shared variants, and provide support for the potential effects of PUFAs on certain brain disorders, especially MDD, BIP, and alcohol consumption.

Pregnancy-Associated Bleeding and Genetics: Five Sequence Variants in the Myometrium and Progesterone Signaling Pathway are associated with postpartum hemorrhage

Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severity of these complications in maternal-fetal health. Here, we investigated the genetic variation underlying aspects of pregnancy-associated bleeding and identified five loci associated with PPH through a meta-analysis of 21,512 cases and 259,500 controls. Functional annotation analysis indicated candidate genes, HAND2, TBX3, and RAP2C/FRMD7, at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors (PGR). Furthermore, there were strong genetic correlations with birth weight, gestational duration, and uterine fibroids. Early bleeding during pregnancy (28,898 cases and 302,894 controls) yielded no genome-wide association signals, but showed strong genetic correlation with a variety of human traits, indicative of polygenic and pleiotropic effects. Our results suggest that postpartum bleeding is related to myometrium dysregulation, whereas early bleeding is a complex trait related to underlying health and possibly socioeconomic status.

Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Human brain single nucleus cell type enrichments in neurodegenerative diseases

Single cell RNA sequencing has opened a window into clarifying the complex underpinnings of disease, particularly in quantifying the relevance of tissue- and cell-type-specific gene expression. To identify the cell types and genes important to therapeutic target development across the neurodegenerative disease spectrum, we leveraged genome-wide association studies, recent single cell sequencing data, and bulk expression studies in a diverse series of brain region tissues. We were able to identify significant immune-related cell types in the brain across three major neurodegenerative diseases: Alzheimer's Disease, Amyotrophic Lateral Sclerosis, and Parkinson's Diseases. Subsequently, we identified the major role of 30 fine-mapped loci implicating seven genes in multiple neurodegenerative diseases and their pathogenesis.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

eXclusionarY: 10 years later, where are the sex chromosomes in GWASs?

10 years ago, a detailed analysis showed that only 33% of genome-wide association study (GWAS) results included the X chromosome. Multiple recommendations were made to combat such exclusion. Here, we re-surveyed the research landscape to determine whether these earlier recommendations had been translated. Unfortunately, among the genome-wide summary statistics reported in 2021 in the NHGRI-EBI GWAS Catalog, only 25% provided results for the X chromosome and 3% for the Y chromosome, suggesting that the exclusion phenomenon not only persists but has also expanded into an exclusionary problem. Normalizing by physical length of the chromosome, the average number of studies published through November 2022 with genome-wide-significant findings on the X chromosome is ∼1 study/Mb. By contrast, it ranges from ∼6 to ∼16 studies/Mb for chromosomes 4 and 19, respectively. Compared with the autosomal growth rate of ∼0.086 studies/Mb/year over the last decade, studies of the X chromosome grew at less than one-seventh that rate, only ∼0.012 studies/Mb/year. Among the studies that reported significant associations on the X chromosome, we noted extreme heterogeneities in data analysis and reporting of results, suggesting the need for clear guidelines. Unsurprisingly, among the 430 scores sampled from the PolyGenic Score Catalog, 0% contained weights for sex chromosomal SNPs. To overcome the dearth of sex chromosome analyses, we provide five sets of recommendations and future directions. Finally, until the sex chromosomes are included in a whole-genome study, instead of GWASs, we propose such studies would more properly be referred to as "AWASs," meaning "autosome-wide scans."

Cross-disorder genetic analysis of immune diseases reveals distinct gene associations that converge on common pathways

Genome-wide association studies (GWAS) have mapped thousands of susceptibility loci associated with immune-mediated diseases. To assess the extent of the genetic sharing across nine immune-mediated diseases we apply genomic structural equation modelling to GWAS data from European populations. We identify three disease groups: gastrointestinal tract diseases, rheumatic and systemic diseases, and allergic diseases. Although loci associated with the disease groups are highly specific, they converge on perturbing the same pathways. Finally, we test for colocalization between loci and single-cell eQTLs derived from peripheral blood mononuclear cells. We identify the causal route by which 46 loci predispose to three disease groups and find evidence for eight genes being candidates for drug repurposing. Taken together, here we show that different constellations of diseases have distinct patterns of genetic associations, but that associated loci converge on perturbing different nodes in T cell activation and signalling pathways.

Multi-ancestry GWAS of Fuchs corneal dystrophy highlights roles of laminins, collagen, and endothelial cell regulation

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular pathophysiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program (MVP) and meta-analyzed with the previous largest FECD GWAS, finding twelve significant loci (eight novel). We further confirmed the TCF4 locus in admixed African and Hispanic/Latino ancestries, and found an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and co-localization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.

hipFG: High-throughput harmonization and integration pipeline for functional genomics data

Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG, an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g., chromatin interactions, genomic intervals, quantitative trait loci).

Neurodegenerative disease and antioxidant biomarkers: A bidirectional Mendelian randomization study

Objective

Previous observational studies have suggested that antioxidant imbalance is correlated with neurodegenerative diseases, while its cause-effect remains unclear. Thus, the goal of the present study is to explore the causal relationship between 11 antioxidant biomarkers and 3 most common neurodegenerative diseases [Alzheimer's disease (AD), Amyotrophic Lateral Sclerosis (ALS) and Parkinson's disease (PD)].

Methods

A bidirectional Mendelian randomization (MR) study was performed to investigate the causal effects by using 3 main methods (Variance Weighted (IVW), Weighted Median (WM), and MR-Egger regression) in the European population. The data of 11 antioxidant biomarkers were obtained from the open database by the most up-to-date Genome-Wide Association Studies (GWAS), the summary statistics of PD and ALS were obtained from the International Parkinson's Disease Genomics Consortium (IPDGC) (33,674 cases, and 449,056 controls), and the International Amyotrophic Lateral Sclerosis Genomics Consortium (IALSC) (20,806 cases and 59,804 controls), respectively. For AD, we specifically used two recently published GWAS data, one from the International Genomics of Alzheimer's Project (IGAP) (21,982 cases and 41,944 controls), and the other from a large meta-analysis (71,880 cases and 383,378 controls) as validation data.

Results

Based on the Bonferroni correction p < 0.0015, there was no significant causal evidence for the antioxidant biomarkers on neurodegenerative diseases, however, the reverse analysis found that AD was significantly related to the decrease in retinol (IVW: beta = -0.023, p = 0.0007; WM: beta = -0.025, p = 0.0121), while the same analysis was carried out between the AD validation database and retinol, the results were consistent (IVW: beta = -0.064, p = 0.025). Moreover, AD on Glutathione S-transferase (GST), PD on Glutathione Peroxidase (GPX) as well as PD on uric acid (UA) also indicated potential causal-and-effect associations (IVW: p = 0.025; p = 0.027; p = 0.021, respectively).

Conclusions

There was no sufficient evidence that antioxidant imbalance has a significant causal effect on neurodegenerative diseases. However, this study revealed that genetically predicted AD was significantly related to the decrease in retinol, which provides a new insight into previous research and indicates the possibility to regard retinol as potential biomarker for the diagnosis and progress of AD.

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.

SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration

Background

Generating polygenic risk scores for diseases and complex traits requires high quality GWAS summary statistic files. Often, these files can be difficult to acquire either as a result of unshared or incomplete data. To date, bioinformatics tools which focus on restoring missing columns containing identification and association data are limited, which has the potential to increase the number of usable GWAS summary statistics files.

Results

SumStatsRehab was able to restore rsID, effect/other alleles, chromosome, base pair position, effect allele frequencies, beta, standard error, and p-values to a better extent than any other currently available tool, with minimal loss.

Conclusions

SumStatsRehab offers a unique tool utilizing both functional programming and pipeline-like architecture, allowing users to generate accurate data restorations for incomplete summary statistics files. This in turn, increases the number of usable GWAS summary statistics files, which may be invaluable for less researched health traits.

Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits

A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.

Alzheimer's disease-related transcriptional sex differences in myeloid cells

Sex differences have been identified in many diseases associated with dysregulated immune responses, including Alzheimer's disease (AD), for which approximately two-thirds of patients are women. An accumulating body of research indicates that microglia may play a causal role in the pathogenesis of this disease. We hypothesised that sex differences in the transcriptome of human myeloid cells may contribute to the sex difference observed in AD prevalence. To explore this, we assessed bulk and single-nuclear RNA sequencing data sets generated from four human derived myeloid cell populations: post-mortem microglial nuclei, peripheral monocytes, monocyte-derived macrophages (MDMs) and induced pluripotent stem cell derived microglial-like cells (MGLs). We found that expression of AD risk genes, gene signatures associated with the inflammatory response in AD, and genes related to proinflammatory immune responses were enriched in microglial nuclei isolated from aged female donors without ante-mortem neurological disease, relative to those from males. In addition, these inflammation-associated gene sets were found to be enriched in peripheral monocytes isolated from postmenopausal women and in MDMs obtained from premenopausal individuals relative to age-matched males. Expression of these gene sets did not differ in MDMs derived from women whose blood was sampled across the menstrual cycle or in MGLs cultured with 17β-oestradiol. This suggests that the observed gene set enrichments in myeloid cells from women were not being driven by acute hormonal influences. Together, these data support the hypothesis that the increased prevalence of AD in women may be partly explained by a myeloid cell phenotype biased towards expression of biological processes relevant to AD.

Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms

Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.