ImmVar project: Insights and design considerations for future studies of "healthy" immune variation

Environmental chemical-wide associations with immune biomarkers in US adults: A cross-sectional analysis

Environmental chemical exposures influence immune system functions, and humans are exposed to a wide range of chemicals, termed the chemical "exposome". A comprehensive, discovery analysis of the associations of multiple chemical families with immune biomarkers is needed. In this study, we tested the associations between environmental chemical concentrations and immune biomarkers. We analyzed the United States cross-sectional National Health and Nutrition Examination Survey (NHANES, 1999-2018). Chemical biomarker concentrations were measured in blood or urine (196 chemicals, 17 chemical families). Immune biomarkers included counts of lymphocytes, neutrophils, monocytes, basophils, eosinophils, red blood cells, white blood cells, and mean corpuscular volume. We conducted separate survey-weighted, multivariable linear regressions of each log2-transformed chemical and immune measure, adjusted for relevant covariates. We accounted for multiple comparisons using a false discovery rate (FDR). Among 45,528 adult participants, the mean age was 45.7 years, 51.4% were female, and 69.3% were Non-Hispanic White. 71 (36.2%) chemicals were associated with at least one of the eight immune biomarkers. The most chemical associations (FDR<0.05) were observed with mean corpuscular volume (36 chemicals) and red blood cell counts (35 chemicals). For example, a doubling in the concentration of cotinine was associated with 0.16 fL (95% CI: 0.15, 0.17; FDR<0.001) increased mean corpuscular volume, and a doubling in the concentration of blood lead was associated with 61,736 increased red blood cells per μL (95% CI: 54,335, 69,138; FDR<0.001). A wide variety of chemicals, such as metals and smoking-related compounds, were highly associated with immune system biomarkers. This environmental chemical-wide association study identified chemicals from multiple families for further toxicological, immunologic, and epidemiological investigation.

Variation in the basal immune state and implications for disease

Analysis of pre-existing immunity and its effects on acute infection often focus on memory responses associated with a prior infectious exposure. However, memory responses occur in the context of the overall immune state and leukocytes must interact with their microenvironment and other immune cells. Thus, it is important to also consider non-antigen-specific factors which shape the composite basal state and functional capacity of the immune system, termed here as I0 ('I naught'). In this review, we discuss the determinants of I0. Utilizing influenza virus as a model, we then consider the effect of I0 on susceptibility to infection and disease severity. Lastly, we outline a mathematical framework and demonstrate how researchers can build and tailor models to specific needs. Understanding how diverse factors uniquely and collectively impact immune competence will provide valuable insights into mechanisms of immune variation, aid in screening for high-risk populations, and promote the development of broadly applicable prophylactic and therapeutic treatments.

The human microglia responsome: a resource to better understand microglia states in health and disease

Microglia, the immune cells of the brain, are increasingly implicated in neurodegenerative disorders through genetic studies. However, how genetic risk factors for these diseases are related to microglial gene expression, microglial function, and ultimately disease, is still largely unknown. Microglia change rapidly in response to alterations in their cellular environment, which is regulated through changes in transcriptional programs, which are as yet poorly understood. Here, we compared the effects of a set of inflammatory and restorative stimuli (lipopolysaccharide, interferon-gamma, resiquimod, tumor necrosis factor-alpha, adenosine triphosphate, dexamethasone, and interleukin-4) on human microglial cells from 67 different donors (N = 398 samples) at the gene and transcript level. We show that microglia from different anatomical brain regions show distinct responses to inflammatory stimuli. We observed a greater overlap between human stimulated microglia and human monocytes than with mouse microglia. We define specific microglial signatures across conditions which are highly relevant for a wide range of biological functions and complex human diseases. Finally, we used our stimulation signatures to interpret associations from Alzheimer's disease (AD) genetic studies and microglia by integrating our inflammatory gene expression profiles with common genetic variants to map cis -expression QTLs (eQTLs). Together, we provide the most comprehensive transcriptomic database of the human microglia responsome.

Highlights

RNA-sequencing of 398 human microglial samples exposed to six different triggers.Microglia from different anatomical regions show distinct stimulation responses.Responses in human microglia show a greater overlap with human monocytes than murine microglia.Mapping of response Quantitative Trait Loci identifies interactions between genotype and effect of stimulation on gene expression.Our atlas provides a reference map for interpreting microglia signatures in health and disease.

Single-cell genomics meets human genetics

Single-cell genomic technologies are revealing the cellular composition, identities and states in tissues at unprecedented resolution. They have now scaled to the point that it is possible to query samples at the population level, across thousands of individuals. Combining single-cell information with genotype data at this scale provides opportunities to link genetic variation to the cellular processes underpinning key aspects of human biology and disease. This strategy has potential implications for disease diagnosis, risk prediction and development of therapeutic solutions. But, effectively integrating large-scale single-cell genomic data, genetic variation and additional phenotypic data will require advances in data generation and analysis methods. As single-cell genetics begins to emerge as a field in its own right, we review its current state and the challenges and opportunities ahead.

Differential impact of environmental factors on systemic and localized autoimmunity

The influence of environmental factors on the development of autoimmune disease is being broadly investigated to better understand the multifactorial nature of autoimmune pathogenesis and to identify potential areas of intervention. Areas of particular interest include the influence of lifestyle, nutrition, and vitamin deficiencies on autoimmunity and chronic inflammation. In this review, we discuss how particular lifestyles and dietary patterns may contribute to or modulate autoimmunity. We explored this concept through a spectrum of several autoimmune diseases including Multiple Sclerosis (MS), Systemic Lupus Erythematosus (SLE) and Alopecia Areata (AA) affecting the central nervous system, whole body, and the hair follicles, respectively. A clear commonality between the autoimmune conditions of interest here is low Vitamin D, a well-researched hormone in the context of autoimmunity with pleiotropic immunomodulatory and anti-inflammatory effects. While low levels are often correlated with disease activity and progression in MS and AA, the relationship is less clear in SLE. Despite strong associations with autoimmunity, we lack conclusive evidence which elucidates its role in contributing to pathogenesis or simply as a result of chronic inflammation. In a similar vein, other vitamins impacting the development and course of these diseases are explored in this review, and overall diet and lifestyle. Recent work exploring the effects of dietary interventions on MS showed that a balanced diet was linked to improvement in clinical parameters, comorbid conditions, and overall quality of life for patients. In patients with MS, SLE and AA, certain diets and supplements are linked to lower incidence and improved symptoms. Conversely, obesity during adolescence was linked with higher incidence of MS while in SLE it was associated with organ damage. Autoimmunity is thought to emerge from the complex interplay between environmental factors and genetic background. Although the scope of this review focuses on environmental factors, it is imperative to elaborate the interaction between genetic susceptibility and environment due to the multifactorial origin of these disease. Here, we offer a comprehensive review about the influence of recent environmental and lifestyle factors on these autoimmune diseases and potential translation into therapeutic interventions.

Genetic heterogeneity: Challenges, impacts, and methods through an associative lens

Genetic heterogeneity describes the occurrence of the same or similar phenotypes through different genetic mechanisms in different individuals. Robustly characterizing and accounting for genetic heterogeneity is crucial to pursuing the goals of precision medicine, for discovering novel disease biomarkers, and for identifying targets for treatments. Failure to account for genetic heterogeneity may lead to missed associations and incorrect inferences. Thus, it is critical to review the impact of genetic heterogeneity on the design and analysis of population level genetic studies, aspects that are often overlooked in the literature. In this review, we first contextualize our approach to genetic heterogeneity by proposing a high-level categorization of heterogeneity into "feature," "outcome," and "associative" heterogeneity, drawing on perspectives from epidemiology and machine learning to illustrate distinctions between them. We highlight the unique nature of genetic heterogeneity as a heterogeneous pattern of association that warrants specific methodological considerations. We then focus on the challenges that preclude effective detection and characterization of genetic heterogeneity across a variety of epidemiological contexts. Finally, we discuss systems heterogeneity as an integrated approach to using genetic and other high-dimensional multi-omic data in complex disease research.

A guide to systems-level immunomics

The immune system is highly complex and distributed throughout an organism, with hundreds to thousands of cell states existing in parallel with diverse molecular pathways interacting in a highly dynamic and coordinated fashion. Although the characterization of individual genes and molecules is of the utmost importance for understanding immune-system function, high-throughput, high-resolution omics technologies combined with sophisticated computational modeling and machine-learning approaches are creating opportunities to complement standard immunological methods with new insights into immune-system dynamics. Like systems immunology itself, immunology researchers must take advantage of these technologies and form their own diverse networks, connecting with researchers from other disciplines. This Review is an introduction and 'how-to guide' for immunologists with no particular experience in the field of omics but with the intention to learn about and apply these systems-level approaches, and for immunologists who want to make the most of interdisciplinary networks.

Emerging roles for endogenous retroviruses in immune epigenetic regulation

In recent years, there has been significant progress toward understanding the transcriptional networks underlying mammalian immune responses, fueled by advances in regulatory genomic technologies. Epigenomic studies profiling immune cells have generated detailed genome-wide maps of regulatory elements that will be key to deciphering the regulatory networks underlying cellular immune responses and autoimmune disorders. Unbiased analyses of these genomic maps have uncovered endogenous retroviruses as an unexpected ally in the regulation of human immune systems. Despite their parasitic origins, studies are finding an increasing number of examples of retroviral sequences having been co-opted for beneficial immune function and regulation by the host cell. Here, we review how endogenous retroviruses have given rise to numerous regulatory elements that shape the epigenetic landscape of host immune responses. We will discuss the implications of these elements on the function, dysfunction, and evolution of innate immunity.

Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome

Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4⁺ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.

Using functional genomics to advance the understanding of psoriatic arthritis

Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.

No detectable alloreactive transcriptional responses under standard sample preparation conditions during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures.

RESULTS

Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets.

CONCLUSIONS

We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments.

scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets

BACKGROUND

Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell.

RESULTS

Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci.

CONCLUSION

ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset.

AVAILABILITY

https://github.com/HorvathLab/NGS/tree/master/scReQTL.

Single cell profiling of capillary blood enables out of clinic human immunity studies

An individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.

CRELD1 modulates homeostasis of the immune system in mice and humans

CRELD1 is a pivotal factor for heart development, the function of which is unknown in adult life. We here provide evidence that CRELD1 is an important gatekeeper of immune system homeostasis. Exploiting expression variance in large human cohorts contrasting individuals with the lowest and highest CRELD1 expression levels revealed strong phenotypic, functional and transcriptional differences, including reduced CD4⁺ T cell numbers. These findings were validated in T cell-specific Creld1-deficient mice. Loss of Creld1 was associated with simultaneous overactivation and increased apoptosis, resulting in a net loss of T cells with age. Creld1 was transcriptionally and functionally linked to Wnt signaling. Collectively, gene expression variance in large human cohorts combined with murine genetic models, transcriptomics and functional testing defines CRELD1 as an important modulator of immune homeostasis.

Strategic Outlook toward 2030: Japan's research for allergy and immunology - Secondary publication

Strategic Outlook toward 2030: Japan's Research for Allergy and Immunology (Strategy 2030) is the national research strategy based on Japan's Basic Law on Measures Against Allergic Diseases, a first of its kind worldwide. This strategy was established by a multi-disciplinary committee consisting of administrators of the Ministry of Health, Labour and Welfare of Japan, young and senior experts from various research societies and associations, and representatives of patient and public groups. Whereas the issues of transition, integration, and international collaboration have yet to be solved in this research realm in Japan, identification of unmet needs, digitization of information and transparent procedures, and strategic planning for complex problems (a process dubbed MIERUKA by the Toyota Way) are crucial to share and tackle the same vision and goals. The committee developed three specific actions focusing on preemptive treatment, interdisciplinarity and internationality, and life stage. The real success of Strategy 2030 is made by the spontaneous contributions of doctors, dentists, veterinarians, and other medical professionals; basic and clinical research scientists, research supporters, and pharmaceutical/medical device companies; manufacturers of food, healthcare, and home appliances; and patients, their families, and the public. The hope is to establish a stable society in which people can live long, healthy lives, as free as possible from allergic and immunological diseases, at each individual life stage. This article is based on a Japanese review first reported in Arerugi, introduces the developmental process and details of Strategy 2030.

The impact of human single nucleotide polymorphisms on Bacillus Calmette-Guérin responses

The influence of genetic variability on human immune responses has major implications for the understanding of disease mechanisms and host-pathogen interactions. Bacillus Calmette-Guérin (BCG) vaccine, which is given globally to protect against tuberculosis, has high variability in its protective efficacy against mycobacteria and its beneficial off-target (heterologous) effects. Single nucleotide polymorphisms (SNPs) are major cause of genetic variation and have been strongly associated with susceptibility to tuberculosis and outcomes following BCG immunotherapy for cancer. This review discusses the contribution of SNPs to the variability in mycobacterial-specific and off-target BCG responses, and the implications for this on development of novel TB vaccines and strategies to harness the beneficial off-target effects of BCG.

The Enigma of Low COVID-19 Fatality Rate in India

Coronavirus disease 2019 (COVID-19), an acute onset pneumonia caused by a novel Betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly evolved into a pandemic. Though its origin has been linked to the Wuhan City of China's Hubei Province in December 2019, recent reports claim that the original animal-to-human transmission of the virus probably happened sometime between September and October 2019 in Guangdong Province, rather than Hubei. As of July 3, 2020, India has reported a case positivity rate of 6.5% and a fatality rate of 2.8%, which are among the lowest in the world. Also, the severity of the disease is much less among Indians as evidenced by the low rate of ICU admission (15.3%) and the need for mechanical ventilation (4.16%). As per the World Health Organization (WHO) situation report 165 on July 3, 2020, India has one of the lowest deaths per 100,000 population (1.32 deaths against a global average of 6.04). Several factors related to the pathogen, host and environment might have some role in reducing the susceptibility of Indians to COVID-19. These include some ongoing mutations that can alter the virulence of the circulating SARS-CoV-2 strains, host factors like innate immunity, genetic diversity in immune responses, epigenetic factors, genetic polymorphisms of ACE2 receptors, micro RNAs and universal BCG vaccination, and environmental factors like high temperature and humidity which may alter the viability and transmissibility of the strain. This perspective -highlights the potential factors that might be responsible for the observed low COVID-19 fatality rate in Indian population. It puts forward several hypotheses which can be a ground for future studies determining individual and population susceptibility to COVID-19 and thus, may offer a new dimension to our current understanding of the disease.

Multiple sclerosis risk variants regulate gene expression in innate and adaptive immune cells

At least 200 single-nucleotide polymorphisms (SNPs) are associated with multiple sclerosis (MS) risk. A key function that could mediate SNP-encoded MS risk is their regulatory effects on gene expression. We performed microarrays using RNA extracted from purified immune cell types from 73 untreated MS cases and 97 healthy controls and then performed Cis expression quantitative trait loci mapping studies using additive linear models. We describe MS risk expression quantitative trait loci associations for 129 distinct genes. By extending these models to include an interaction term between genotype and phenotype, we identify MS risk SNPs with opposing effects on gene expression in cases compared with controls, namely, rs2256814 MYT1 in CD4 cells (q = 0.05) and rs12087340 RF00136 in monocyte cells (q = 0.04). The rs703842 SNP was also associated with a differential effect size on the expression of the METTL21B gene in CD8 cells of MS cases relative to controls (q = 0.03). Our study provides a detailed map of MS risk loci that function by regulating gene expression in cell types relevant to MS.

An analysis of genetically regulated gene expression across multiple tissues implicates novel gene candidates in Alzheimer's disease

Introduction

Genome-wide association studies (GWAS) have successfully identified multiple independent genetic loci that harbour variants associated with Alzheimer’s disease, but the exact causal genes and biological pathways are largely unknown.

Methods

To prioritise likely causal genes associated with Alzheimer’s disease, we used S-PrediXcan to integrate expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression (GTEx) study and CommonMind Consortium (CMC) with Alzheimer’s disease GWAS summary statistics. We meta-analysed the GTEx results using S-MultiXcan, prioritised disease-implicated loci using a computational fine-mapping approach, and performed a biological pathway analysis on the gene-based results.

Results

We identified 126 tissue-specific gene-based associations across 48 GTEx tissues, targeting 50 unique genes. Meta-analysis of the tissue-specific associations identified 73 genes whose expression was associated with Alzheimer’s disease. Additional analyses in the dorsolateral prefrontal cortex from the CMC identified 12 significant associations, 8 of which also had a significant association in GTEx tissues. Fine-mapping of causal gene sets prioritised gene candidates in 10 Alzheimer’s disease loci with strong evidence for causality. Biological pathway analyses of the meta-analysed GTEx data and CMC data identified a significant enrichment of Alzheimer’s disease association signals in plasma lipoprotein clearance, in addition to multiple immune-related pathways.

Conclusions

Gene expression data from brain and peripheral tissues can improve power to detect regulatory variation underlying Alzheimer’s disease. However, the associations in peripheral tissues may reflect tissue-shared regulatory variation for a gene. Therefore, future functional studies should be performed to validate the biological meaning of these associations and whether they represent new pathogenic tissues.

Infection History Determines Susceptibility to Unrelated Diseases

Epidemiological data suggest that previous infections can alter an individual's susceptibility to unrelated diseases. Nevertheless, the underlying mechanisms are not completely understood. Substantial research efforts have expanded the classical concept of immune memory to also include long-lasting changes in innate immunity and antigen-independent reactivation of adaptive immunity. Collectively, these processes provide possible explanations on how acute infections might induce long-term changes that also affect immunity to unrelated diseases. Here, we review lasting changes the immune compartment undergoes upon infection and how infection experience alters the responsiveness of immune cells towards universal signals. This heightened state of alert enhances the ability of the immune system to combat even unrelated infections but may also increase susceptibility to autoimmunity. At the same time, infection-induced changes in the regulatory compartment may dampen subsequent immune responses and promote pathogen persistence. The concepts presented here outline how infection-induced changes in the immune system may affect human health.

Mitochondrial genetics cooperate with nuclear genetics to selectively alter immune cell development/trafficking

The nuclear genome drives differences in immune cell populations and differentiation potentials, in part regulated by changes in metabolism. Despite this connection, the role of mitochondrial DNA (mtDNA) polymorphisms (SNP) in this process has not been examined. Using mitochondrial nuclear exchange (MNX) mice, we and others have shown that mtDNA strongly influences varying aspects of cell biology and disease. Based upon an established connection between mitochondria and immune cell polarization, we hypothesized that mtDNA SNP alter immune cell development, trafficking, and/or differentiation. Innate and adaptive immune cell populations were isolated and characterizated from the peritoneum and spleen. While most differences between mouse strains are regulated by nuclear DNA (nDNA), there are selective changes that are mediated by mtDNA differences (e.g., macrophage (CD11c) differentiation), These findings highlight how nuclear-mitochondrial crosstalk may alter pathology and physiology via regulation of specific components of the immune system.

An Immunological Perspective to Non-syndromic Sensorineural Hearing Loss

Conventionally the etiology of congenital Non-Syndromic Hearing Loss has been attributed to mutations in the genes involved in ion homeostasis or the structural compartments of the inner ear. However, this contributes to only a part of the problem, as still the determinants for a large majority of the Non-Syndromic Hearing loss seems to be an enigma. Evidences indicate that pathogens like Rubella, Cytomegalovirus, and many other infections can also result in congenital hearing loss. Additionally, there are variety of factors other than the viral mediators, that can act as stressors to trigger an altered immune response, during the gestational period of the mother. It is also known that non-specific stimulation of the immune system can mimic an infection status. This indicates a strong role for environmental factors toward their contribution to the pathology, possibly by influencing the host immune response. These varieties of known or unknown environmental factors interact with the susceptible variants in immune response genes in defining the threshold for protection or infection in an individual. Considering this background we propose to present this perspective that threshold of the host immune response during the prenatal conditions, in response to environmental stimulus, might be determined by the susceptible variants in immune response genes. This in turn can directly or indirectly influence the genes involved in maintaining the structural components or ion homeostasis, resulting in hearing loss. The threshold of immune response alterations may be heavily dependent on the immunogenetic profile of the mother or the fetus.

A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

Identification of rheumatoid arthritis causal genes using functional genomics

Over the past decade, genome-wide association studies have contributed a wealth of knowledge to our understanding of polygenic disorders such as rheumatoid arthritis. As the size of sample cohorts has improved so too have the computational and experimental methods used to robustly define variants associated with disease susceptibility. The challenge now remains to translate these findings into improved understanding of disease aetiology and patient care. Whilst much of the focus of translating the findings of genome-wide association studies has been on global analysis of all variants identified, careful functional study of individual disease susceptibility loci will be required in order to refine our understanding of how individual variants contribute to disease risk. Here, we present the argument behind such an approach and describe some of the novel tools being used to investigate risk loci. This includes the use of chromosomal conformation capture techniques and modifications of the CRISPR-Cas9 system, with several examples of their implementation being described.

A Scalable Permutation Approach Reveals Replication and Preservation Patterns of Network Modules in Large Datasets

Network modules-topologically distinct groups of edges and nodes-that are preserved across datasets can reveal common features of organisms, tissues, cell types, and molecules. Many statistics to identify such modules have been developed, but testing their significance requires heuristics. Here, we demonstrate that current methods for assessing module preservation are systematically biased and produce skewed p values. We introduce NetRep, a rapid and computationally efficient method that uses a permutation approach to score module preservation without assuming data are normally distributed. NetRep produces unbiased p values and can distinguish between true and false positives during multiple hypothesis testing. We use NetRep to quantify preservation of gene coexpression modules across murine brain, liver, adipose, and muscle tissues. Complex patterns of multi-tissue preservation were revealed, including a liver-derived housekeeping module that displayed adipose- and muscle-specific association with body weight. Finally, we demonstrate the broader applicability of NetRep by quantifying preservation of bacterial networks in gut microbiota between men and women.

Approaches and advances in the genetic causes of autoimmune disease and their implications

Genome-wide association studies are transformative in revealing the polygenetic basis of common diseases, with autoimmune diseases leading the charge. Although the field is just over 10 years old, advances in understanding the underlying mechanistic pathways of these conditions, which result from a dense multifactorial blend of genetic, developmental and environmental factors, have already been informative, including insights into therapeutic possibilities. Nevertheless, the challenge of identifying the actual causal genes and pathways and their biological effects on altering disease risk remains for many identified susceptibility regions. It is this fundamental knowledge that will underpin the revolution in patient stratification, the discovery of therapeutic targets and clinical trial design in the next 20 years. Here we outline recent advances in analytical and phenotyping approaches and the emergence of large cohorts with standardized gene-expression data and other phenotypic data that are fueling a bounty of discovery and improved understanding of human physiology.

Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges

Identifying the drivers of the interindividual diversity of the human immune system is crucial to understand their consequences on immune-mediated diseases. By examining the transcriptional responses of 1,000 individuals to various microbial challenges, we show that age and sex influence the expression of many immune-related genes, but their effects are overall moderate, whereas genetic factors affect a smaller gene set but with a stronger effect. We identify numerous genetic variants that affect transcriptional variation on infection, many of which are associated with autoimmune or inflammatory disorders. These results enable additional exploration of the role of regulatory variants in the pathogenesis of immune-related diseases and improve our understanding of the respective effects of age, sex, and genetics on immune response variation.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8⁺ T cells for age and CD4⁺ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.

Biological function integrated prediction of severe radiographic progression in rheumatoid arthritis: a nested case control study

Background

Radiographic progression is reported to be highly heritable in rheumatoid arthritis (RA). However, previous study using genetic loci showed an insufficient accuracy of prediction for radiographic progression. The aim of this study is to identify a biologically relevant prediction model of radiographic progression in patients with RA using a genome-wide association study (GWAS) combined with bioinformatics analysis.

Methods

We obtained genome-wide single nucleotide polymorphism (SNP) data for 374 Korean patients with RA using Illumina HumanOmni2.5Exome-8 arrays. Radiographic progression was measured using the yearly Sharp/van der Heijde modified score rate, and categorized in no or severe progression. Significant SNPs for severe radiographic progression from GWAS were mapped on the functional genes and reprioritized by post-GWAS analysis. For robust prediction of radiographic progression, tenfold cross-validation using a support vector machine (SVM) classifier was conducted. Accuracy was used for selection of optimal SNPs set in the Hanyang Bae RA cohort. The performance of our final model was compared with that of other models based on GWAS results and SPOT (one of the post-GWAS analyses) using receiver operating characteristic (ROC) curves. The reliability of our model was confirmed using GWAS data of Caucasian patients with RA.

Results

A total of 36,091 significant SNPs with a p value <0.05 from GWAS were reprioritized using post-GWAS analysis and approximately 2700 were identified as SNPs related to RA biological features. The best average accuracy of ten groups was 0.6015 with 85 SNPs, and this increased to 0.7481 when combined with clinical information. In comparisons of the performance of the model, the 0.7872 area under the curve (AUC) in our model was superior to that obtained with GWAS (AUC 0.6586, p value 8.97 × 10^-5) or SPOT (AUC 0.7449, p value 0.0423). Our model strategy also showed superior prediction accuracy in Caucasian patients with RA compared with GWAS (p value 0.0049) and SPOT (p value 0.0151).

Conclusions

Using various biological functions of SNPs and repeated machine learning, our model could predict severe radiographic progression relevantly and robustly in patients with RA compared with models using only GWAS results or other post-GWAS tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-017-1414-x) contains supplementary material, which is available to authorized users.

Reconstructing the Molecular Function of Genetic Variation in Regulatory Networks

Over the past decade, genetic studies have recognized hundreds of polymorphic DNA loci called response QTLs (reQTLs) as potential contributors to interindividual variation in transcriptional responses to stimulations. Such reQTLs commonly affect the transduction of signals along the regulatory network that controls gene transcription. Identifying the pathways through which reQTLs perturb the underlying network has been a major challenge. Here, we present GEVIN ("Genome-wide Embedding of Variation In Networks"), a methodology that simultaneously identifies a reQTL and the particular pathway in which the reQTL affects downstream signal transduction along the network. Using synthetic data, we show that this algorithm outperforms existing pathway identification and reQTL identification methods. We applied GEVIN to the analysis of murine and human dendritic cells in response to pathogenic components. These analyses revealed significant reQTLs together with their perturbed Toll-like receptor signaling pathways. GEVIN thus offers a powerful framework that renders a comprehensive picture of disease-related DNA loci and their molecular functions within regulatory networks.

Continuous immunotypes describe human immune variation and predict diverse responses

The immune system consists of many specialized cell populations that communicate with each other to achieve systemic immune responses. Our analyses of various measured immune cell population frequencies in healthy humans and their responses to diverse stimuli show that human immune variation is continuous in nature, rather than characterized by discrete groups of similar individuals. We show that the same three key combinations of immune cell population frequencies can define an individual's immunotype and predict a diverse set of functional responses to cytokine stimulation. We find that, even though interindividual variations in specific cell population frequencies can be large, unrelated individuals of younger age have more homogeneous immunotypes than older individuals. Across age groups, cytomegalovirus seropositive individuals displayed immunotypes characteristic of older individuals. The conceptual framework for defining immunotypes suggested by our results could guide the development of better therapies that appropriately modulate collective immunotypes, rather than individual immune components.

Molecular and genetic inflammation networks in major human diseases

It has been well-recognized that inflammation alongside tissue repair and damage maintaining tissue homeostasis determines the initiation and progression of complex diseases. Albeit with the accomplishment of having captured the most critical inflammation-involved molecules, genetic susceptibilities, epigenetic factors, and environmental factors, our schemata on the role of inflammation in complex diseases remain largely patchy, in part due to the success of reductionism in terms of research methodology per se. Omics data alongside the advances in data integration technologies have enabled reconstruction of molecular and genetic inflammation networks which shed light on the underlying pathophysiology of complex diseases or clinical conditions. Given the proven beneficial role of anti-inflammation in coronary heart disease as well as other complex diseases and immunotherapy as a revolutionary transition in oncology, it becomes timely to review our current understanding of the molecular and genetic inflammation networks underlying major human diseases. In this review, we first briefly discuss the complexity of infectious diseases and then highlight recently uncovered molecular and genetic inflammation networks in other major human diseases including obesity, type II diabetes, coronary heart disease, late onset Alzheimer's disease, Parkinson's disease, and sporadic cancer. The commonality and specificity of these molecular networks are addressed in the context of genetics based on genome-wide association study (GWAS). The double-sword role of inflammation, such as how the aberrant type 1 and/or type 2 immunity leads to chronic and severe clinical conditions, remains open in terms of the inflammasome and the core inflammatome network features. Increasingly available large Omics and clinical data in tandem with systems biology approaches have offered an exciting yet challenging opportunity toward reconstruction of more comprehensive and dynamic molecular and genetic inflammation networks, which hold great promise in transiting network snapshots to video-style multi-scale interplays of disease mechanisms, in turn leading to effective clinical intervention.

Leukocyte diversity in resolving and nonresolving mechanisms of cardiac remodeling

In response to myocardial infarction (MI), time-dependent leukocyte infiltration is critical to program the acute inflammatory response. Post-MI leukocyte density, residence time in the infarcted area, and exit from the infarcted injury predict resolving or nonresolving inflammation. Overactive or unresolved inflammation is the primary determinant in heart failure pathology post-MI. Here, our review describes supporting evidence that the acute inflammatory response also guides the generation of healing and regenerative mediators after cardiac damage. Time-dependent leukocyte density and diversity and the magnitude of myocardial injury is responsible for the resolving and nonresolving pathway in myocardial healing. Post MI, the diversity of leukocytes, such as neutrophils, macrophages, and lymphocytes, has been explored that regulate the clearance of deceased cardiomyocytes by using the classic and reparative pathways. Among the innovative factors and intermediates that have been recognized as essential in acute the self-healing and clearance mechanism, we highlight specialized proresolving mediators as the emerging factor for post-MI reparative mechanisms-translational leukocyte modifiers, such as aging, the source of leukocytes, and the milieu around the leukocytes. In the clinical setting, it is possible that leukocyte diversity is more prominent as a result of risk factors, such as obesity, diabetes, and hypertension. Pharmacologic agents are critical modifiers of leukocyte diversity in healing mechanisms that may impair or stimulate the clearance mechanism. Future research is needed, with a focused approach to understand the molecular targets, cellular effectors, and receptors. A clear understanding of resolving and nonresolving inflammation in myocardial healing will help to develop novel targets with major emphasis on the resolution of inflammation in heart failure pathology.-Tourki, B., Halade, G. Leukocyte diversity in resolving and nonresolving mechanisms of cardiac remodeling.

Colonic transcriptional response to 1α,25(OH)2 vitamin D3 in African- and European-Americans

Colorectal cancer (CRC) is a significant health burden especially among African Americans (AA). Epidemiological studies have correlated low serum vitamin D with CRC risk, and, while hypovitaminosis D is more common and more severe in AA, the mechanisms by which vitamin D modulates CRC risk and how these differ by race are not well understood. Active vitamin D (1α,25(OH)₂D₃) has chemoprotective effects primarily through transcriptional regulation of target genes in the colon. We hypothesized that transcriptional response to 1α,25(OH)₂D₃ differs between AA and European Americans (EA) irrespective of serum vitamin D and that regulatory variants could impact transcriptional response. We treated ex vivo colon cultures from 34 healthy subjects (16 AA and 18 EA) with 0.1μM 1α,25(OH)₂D₃ or vehicle control for 6h and performed genome-wide transcriptional profiling. We found 8 genes with significant differences in transcriptional response to 1α,25(OH)₂D₃ between AA and EA with definitive replication of inter-ethnic differences for uridine phosphorylase 1 (UPP1) and zinc finger-SWIM containing 4 (ZSWIM4). We performed expression quantitative trait loci (eQTL) mapping and identified response cis-eQTLs for ZSWIM4 as well as for histone deacetylase 3 (HDAC3), the latter of which showed a trend toward significant inter-ethnic differences in transcriptional response. Allele frequency differences of eQTLs for ZSWIM4 and HDAC3 accounted for observed transcriptional differences between populations. Taken together, our results demonstrate that transcriptional response to 1α,25(OH)₂D₃ differs between AA and EA independent of serum 25(OH)D levels. We provide evidence in support of a genetic regulatory mechanism underlying transcriptional differences between populations for ZSWIM4 and HDAC3. Further work is needed to elucidate how response eQTLs modify vitamin D response and whether genotype and/or transcriptional response correlate with chemopreventive effects. Relevant biomarkers, such as tissue-specific 1α,25(OH)₂D₃ transcriptional response, could identify individuals likely to benefit from vitamin D for CRC prevention as well as elucidate basic mechanisms underlying CRC disparities.

Exploring the nexus of Alzheimer's disease and related dementias with cancer and cancer therapies: A convening of the Alzheimer's Association & Alzheimer's Drug Discovery Foundation

Recent population studies suggest an intriguing inverse relationship between several types of cancer and neurodegenerative diseases, including Alzheimer's disease. Understanding the intersection of the underlying biology for these two distinct families of diseases with one another may offer novel approaches to identify new therapeutic approaches and possible opportunities to repurpose existing drug candidates. The Alzheimer's Association and the Alzheimer's Drug Discovery Foundation convened a one-day workshop to delve into this discussion. Workshop participants outlined research focus areas, potential collaborations, and partnerships for future action.

Human immune system variation

The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.

Trans-pQTL study identifies immune crosstalk between Parkinson and Alzheimer loci

OBJECTIVE

Given evidence from genetic studies, we hypothesized that there may be a shared component to the role of myeloid function in Parkinson and Alzheimer disease (PD and AD) and assessed whether PD susceptibility variants influenced protein expression of well-established AD-associated myeloid genes in human monocytes.

METHODS

We repurposed data in which AD-related myeloid proteins CD33, TREM1, TREM2, TREML2, TYROBP, and PTK2B were measured by flow cytometry in monocytes from 176 participants of the PhenoGenetic Project (PGP) and Harvard Aging Brain Study. Linear regression was used to identify associations between 24 PD risk variants and protein expression. The 2 cohorts were meta-analyzed in a discovery analysis, and the 4 most strongly suggestive results were validated in an independent cohort of 50 PGP participants.

RESULTS

We discovered and validated an association between the PD risk allele rs12456492(G) in the RIT2 locus and increased CD33 expression (p joint = 3.50 × 10(-5)) and found strongly suggestive evidence that rs11060180(A) in the CCDC62/HIP1R locus decreased PTK2B expression (p joint = 1.12 × 10(-4)). Furthermore, in older individuals, increased CD33 expression on peripheral monocytes was associated with a greater burden of parkinsonism (p = 0.047), particularly bradykinesia (p = 6.64 × 10(-3)).

CONCLUSIONS

We find that the rs12456492 PD risk variant affects expression of AD-associated protein CD33 in peripheral monocytes, which suggests that genetic factors for these 2 diseases may converge to influence overlapping innate immune-mediated mechanisms that contribute to neurodegeneration. Furthermore, the effect of the rs12456492(G) PD risk allele on increased CD33 suggests that the inhibition of certain myeloid functions may contribute to PD susceptibility, as is the case for AD.

Genetics and immunity in the era of single-cell genomics

Recent developments in the field of single-cell genomics (SCG) are changing our understanding of how functional phenotypes of cell populations emerge from the behaviour of individual cells. Some of the applications of SCG include the discovery of new gene networks and novel cell subpopulations, fine mapping of transcription kinetics, and the relationships between cell clonality and their functional phenotypes. Immunology is one of the fields that is benefiting the most from such advancements, providing us with completely new insights into mammalian immunity. In this review, we start by covering new immunological insights originating from the use of single-cell genomic tools, specifically single-cell RNA-sequencing. Furthermore, we discuss how new genetic study designs are starting to explain inter-individual variation in the immune response. We conclude with a perspective on new multi-omics technologies capable of integrating several readouts from the same single cell and how such techniques might push our biological understanding of mammalian immunity to a new level.

Cryptic Genetic Variation in Evolutionary Developmental Genetics

Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes-processes that cannot be fully observed in continuously varying visible traits.

The cellular composition of the human immune system is shaped by age and cohabitation

Detailed population-level description of the human immune system has recently become achievable. We used a 'systems-level' approach to establish a resource of cellular immune profiles of 670 healthy individuals. We report a high level of interindividual variation, with low longitudinal variation, at the level of cellular subset composition of the immune system. Despite the profound effects of antigen exposure on individual antigen-specific clones, the cellular subset structure proved highly elastic, with transient vaccination-induced changes followed by a return to the individual's unique baseline. Notably, the largest influence on immunological variation identified was cohabitation, with 50% less immunological variation between individuals who share an environment (as parents) than between people in the wider population. These results identify local environmental conditions as a key factor in shaping the human immune system.

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

Genetics of autoimmune diseases: perspectives from genome-wide association studies

Genome-wide association studies (GWASs) for autoimmune diseases (ADs) have identified many risk loci and have provided insights into the etiology of each disease. Some of these loci, such asPTPN22,IL23RandSTAT4, are shared among different ADs, and the combination of risk loci may determine an individual's susceptibility for a disease. The majority of GWAS loci are expression quantitative trait loci (eQTLs), where disease-causing variants regulate expression of neighboring (or sometimes distant) genes. Because the eQTL effects are often cell type-specific, the incorporation of epigenetic data from disease-related cell types and tissues is expected to refine the identification of causal variants. The cumulative eQTL effects in multiple genes may influence the activity or fate of immune cells, which in turn may affect the function of the immune system in individuals. In this paper, I review the etiology of ADs by focusing on important immune cells (Th1 cells, Th17 cells and regulatory T cells), important pathways (antigen-receptor signaling and type I interferon signaling) and relevant genes identified in GWASs.