Circulatory Inflammatory Proteins as Early Diagnostic Biomarkers for Invasive Aspergillosis in Patients with Hematologic Malignancies-an Exploratory Study.

OBJECTIVES: Invasive aspergillosis (IA) is a major cause of mortality in immunocompromised patients and it is difficult to diagnose because of the lack of reliable highly sensitive diagnostics. We aimed to identify circulating immunological markers that could be useful for an early diagnosis of IA. METHODS: We collected longitudinally serum samples from 33 cases with probable/proven IA and two matched control cohorts without IA (one with microbiological and clinical evidence of bacterial or viral non-fungal pneumonia and one without evidence of infection, all matched for neutropenia, primary underlying disease, and receipt of corticosteroids/other immunosuppressants) at a tertiary university hospital. In addition, samples from an independent cohort (n = 20 cases of proven/probable IA and 20 matched controls without infection) were obtained. A panel of 92 circulating proteins involved in inflammation was measured by proximity extension assay. A random forest model was used to predict the development of IA using biomarkers measured before diagnosis. RESULTS: While no significant differences were observed between IA cases and infected controls, concentrations of 30 inflammatory biomarkers were different between cases and non-infected controls, of which nine were independently replicated: PD-L1, MMP-10, Interleukin(IL)-10, IL-15RA, IL-18, IL-18R1, CDCP1, CCL19 and IL-17C. From the differential abundance analysis of serum samples collected more than 10 days before diagnosis and at diagnosis, increased IL-17C concentrations in IA patients were replicated in the independent cohort. CONCLUSIONS: An increased circulating concentration of IL-17C was detected both in the discovery and independent cohort, both at the time of diagnosis and in samples 10 days before the diagnosis of IA, suggesting it should be evaluated further as potential (early) biomarker of infection.

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes.

BACKGROUND: The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort. METHODS: We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups. RESULTS: We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease. CONCLUSIONS: These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations. TRIAL REGISTRATION: NCT04357366.

The impact of ADRB2 polymorphisms on immune responses and norepinephrine-induced immunosuppression.

RATIONALE: To evaluate whether common nonsynonymous variants [single-nucleotide polymorphisms (SNPs) or SNP haplotypes] in the ß2-adrenergic receptor render subjects more susceptible to norepinephrine-induced immunosuppression and whether they are associated with dysregulated ex vivo and in vivo inflammatory responses. METHODS: Peripheral blood mononuclear cells from healthy volunteers (main cohort: n = 106, secondary cohort: n = 408) were ex vivo stimulated with various stimuli and production of cytokines was assessed. Additionally, ex vivo modulation of cytokine production by norepinephrine was evaluated in the main cohort. Volunteers from the main cohort also underwent experimental endotoxemia (administration of 1 ng/kg lipopolysaccharide), during which in vivo plasma cytokine concentrations and clinical inflammatory parameters were measured. Subjects were genotyped, common SNPs in the ADRB2 gene were extracted (rs1042711, rs1042713, and rs1042714), and the presence of haplotypes was identified (CysGlyGln, CysArgGln, and ArgGlyGlu). RESULTS: In both cohorts, presence of ADRB2 SNPs or haplotypes was not associated with altered ex vivo cytokine responses. Norepinephrine attenuated production of the proinflammatory cytokines TNF and IL-6 [-26% (-22% to -30%) and -14% (-9% to -18%), respectively, both P < 0.0001] and enhanced release of the anti-inflammatory IL-10 [+9% (+3% to +15%), P = 0.003]. These effects were not modulated by the presence of ADRB2 SNPs or haplotypes (all P values >0.37). In addition, no influence of SNPs or haplotypes on in vivo cytokine concentrations or clinical inflammatory parameters was observed (P values >0.14). CONCLUSIONS: Common nonsynonymous variants in the ADRB2 gene influence neither ex vivo cytokine production or norepinephrine-mediated immunosuppression nor the systemic in vivo inflammatory response induced by lipopolysaccharide administration in healthy volunteers.

Characterization of sepsis inflammatory endotypes using circulatory proteins in patients with severe infection: a prospective cohort study.

BACKGROUND: Sepsis is a heterogeneous syndrome due to a variable range of dysregulated processes in the host immune response. Efforts are made to stratify patients for personalized immune-based treatments and better prognostic prediction. Using gene expression data, different inflammatory profiles have been identified. However, it remains unknown whether these endotypes mirror inflammatory proteome profiling, which would be more feasible to assess in clinical practice. We aim to identify different inflammatory endotypes based on circulating proteins in a cohort of moderately ill patients with severe infection (Sepsis-2 criteria). METHODS: In this prospective study, 92 inflammatory plasma markers were profiled using a targeted proteome platform and compared between patients with severe infection (Sepsis-2 criteria) and healthy controls. To identify endotypes with different inflammatory profiles, we performed hierarchical clustering of patients based on the differentially expressed proteins, followed by clinical and demographic characterization of the observed endotypes. RESULTS: In a cohort of 167 patients with severe infection and 192 healthy individuals, we found 62 differentially expressed proteins. Inflammatory proteins such as TNFSF14, OSM, CCL23, IL-6, and HGF were upregulated, while TRANCE, DNER and SCF were downregulated in patients. Unsupervised clustering identified two different inflammatory profiles. One endotype showed significantly higher inflammatory protein abundance, and patients with this endotype were older and showed lower lymphocyte counts compared to the low inflammatory endotype. CONCLUSIONS: By identifying endotypes based on inflammatory proteins in moderately ill patients with severe infection, our study suggests that inflammatory proteome profiling can be useful for patient stratification.

A systematic review of analytical methods used in genetic association analysis of the X-chromosome.

Genetic association studies have been very successful at elucidating the genetic background of many complex diseases/traits. However, the X-chromosome is often neglected in these studies because of technical difficulties and the fact that most tools only utilize genetic data from autosomes. In this review, we aim to provide an overview of different practical approaches that are followed to incorporate the X-chromosome in association analysis, such as Genome-Wide Association Studies and Expression Quantitative Trait Loci Analysis. In general, the choice of which test statistics is most appropriate will depend on three main criteria: (1) the underlying X-inactivation model, (2) if Hardy-Weinberg equilibrium holds and sex-specific allele frequencies are expected and (3) whether adjustment for confounding variables is required. All in all, it is recommended that a combination of different association tests should be used for the analysis of X-chromosome.

Impact of Human Genetic Variation on C-Reactive Protein Concentrations and Acute Appendicitis.

Background: Acute appendicitis is one of the most common abdominal emergencies worldwide. Both environmental and genetic factors contribute to the disease. C-reactive protein (CRP) is an important biomarker in the diagnosis of acute appendicitis. CRP concentrations are significantly affected by genetic variation. However, whether such genetic variation is causally related to appendicitis risk remains unclear. In this study, the causal relationship between single-nucleotide polymorphisms (SNPs) associated with circulating CRP concentrations and the risk and severity of acute appendicitis was investigated. Methods: CRP concentrations in serum of appendicitis patients (n = 325) were measured. Appendicitis was categorized as complicated/uncomplicated and gangrenous/non-gangrenous. Imputed SNP data (n = 287) were generated. A genome-wide association study (GWAS) on CRP concentrations and appendicitis severity was performed. Intersection and colocalization of the GWAS results were performed with appendicitis and CRP-associated loci from the Pan-UKBB cohort. A functional-genomics approach to prioritize genes was employed. Results: Thirteen percent of significant CRP quantitative trait loci (QTLs) that were previously identified in a large cohort of healthy individuals were replicated in our small patient cohort. Significant enrichment of CRP-QTLs in association with appendicitis was observed. Among these shared loci, the two top loci at chromosomes 1q41 and 8p23.1 were characterized. The top SNP at chromosome 1q41 is located within the promoter of H2.0 Like Homeobox (HLX) gene, which is involved in blood cell differentiation, and liver and gut organogeneses. The expression of HLX is increased in the appendix of appendicitis patients compared to controls. The locus at 8p23.1 contains multiple genes, including cathepsin B (CTSB), which is overexpressed in appendix tissue from appendicitis patients. The risk allele of the top SNP in this locus also increases CTSB expression in the sigmoid colon of healthy individuals. CTSB is involved in collagen degradation, MHC class II antigen presentation, and neutrophil degranulation. Conclusions: The results of this study prioritize HLX and CTSB as potential causal genes for appendicitis and suggest a shared genetic mechanism between appendicitis and CRP concentrations.

The role of the X chromosome in infectious diseases.

Many infectious diseases in humans present with a sex bias. This bias arises from a combination of environmental factors, hormones and genetics. In this study, we review the contribution of the X chromosome to the genetic factor associated with infectious diseases. First, we give an overview of the X-linked genes that have been described in the context of infectious diseases and group them in four main pathways that seem to be dysregulated in infectious diseases: nuclear factor kappa-B, interleukin 2 and interferon γ cascade, toll-like receptors and programmed death ligand 1. Then, we review the infectious disease associations in existing genome-wide association studies (GWAS) from the GWAS Catalog and the Pan-UK Biobank, describing the main associations and their possible implications for the disease. Finally, we highlight the importance of including the X chromosome in GWAS analysis and the importance of sex-specific analysis.

Deconvolution of bulk blood eQTL effects into immune cell subpopulations.

BACKGROUND: Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). RESULTS: The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96-100%) and chromatin mark QTL (≥87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. CONCLUSIONS: Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).

Systematic Prioritization of Candidate Genes in Disease Loci Identifies TRAFD1 as a Master Regulator of IFNγ Signaling in Celiac Disease.

Celiac disease (CeD) is a complex T cell-mediated enteropathy induced by gluten. Although genome-wide association studies have identified numerous genomic regions associated with CeD, it is difficult to accurately pinpoint which genes in these loci are most likely to cause CeD. We used four different in silico approaches-Mendelian randomization inverse variance weighting, COLOC, LD overlap, and DEPICT-to integrate information gathered from a large transcriptomics dataset. This identified 118 prioritized genes across 50 CeD-associated regions. Co-expression and pathway analysis of these genes indicated an association with adaptive and innate cytokine signaling and T cell activation pathways. Fifty-one of these genes are targets of known drug compounds or likely druggable genes, suggesting that our methods can be used to pinpoint potential therapeutic targets. In addition, we detected 172 gene combinations that were affected by our CeD-prioritized genes in trans. Notably, 41 of these trans-mediated genes appear to be under control of one master regulator, TRAF-type zinc finger domain containing 1 (TRAFD1), and were found to be involved in interferon (IFN)γ signaling and MHC I antigen processing/presentation. Finally, we performed in vitro experiments in a human monocytic cell line that validated the role of TRAFD1 as an immune regulator acting in trans. Our strategy confirmed the role of adaptive immunity in CeD and revealed a genetic link between CeD and IFNγ signaling as well as with MHC I antigen processing, both major players of immune activation and CeD pathogenesis.

Immunochip meta-analysis in European and Argentinian populations identifies two novel genetic loci associated with celiac disease.

Celiac disease (CeD) is a common immune-mediated disease of the small intestine that is triggered by exposure to dietary gluten. While the HLA locus plays a major role in disease susceptibility, 39 non-HLA loci were also identified in a study of 24,269 individuals. We now build on this earlier study by adding 4125 additional Caucasian samples including an Argentinian cohort. In doing so, we not only confirm the previous associations, we also identify two novel independent genome-wide significant associations at loci: 12p13.31 and 22q13.1. By applying a genomics approach and differential expression analysis in CeD intestinal biopsies, we prioritize potential causal genes at these novel loci, including LTBR, CYTH4, and RAC2. Nineteen prioritized causal genes are overlapping known drug targets. Pathway enrichment analysis and expression of these genes in CeD biopsies suggest that they have roles in regulating multiple pathways such as the tumor necrosis factor (TNF) mediated signaling pathway and positive regulation of I-κB kinase/NF-κB signaling.

snpEnrichR: analyzing co-localization of SNPs and their proxies in genomic regions.

Motivation: Co-localization of trait associated SNPs for specific transcription-factor binding sites or regulatory regions in the genome can yield profound insight into underlying causal mechanisms. Analysis is complicated because the truly causal SNPs are generally unknown and can be either SNPs reported in GWAS studies or other proxy SNPs in their linkage disequilibrium. Hence, a comprehensive pipeline for SNP co-localization analysis that utilizes all relevant information about both the genotyped SNPs and their proxies is needed. Results: We developed an R package snpEnrichR for SNP co-localization analysis. The software integrates different tools for random SNP generation and genome co-localization analysis to automatize and help users to create custom SNP co-localization analysis. We show via an example that including proxy SNPs in SNP co-localization analysis enhances the sensitivity of co-localization detection. Availability and implementation: The software is available at https://github.com/kartiek/snpEnrichR.

A locus at 7p14.3 predisposes to refractory celiac disease progression from celiac disease.

BACKGROUND: Approximately 5% of patients with celiac disease (CeD) do not respond to a gluten-free diet and progress to refractory celiac disease (RCD), a severe progression that is characterized by infiltration of intraepithelial T lymphocytes. Patients with RCD type II (RCDII) show clonal expansions of intraepithelial T lymphocytes that result in a poor prognosis and a high mortality rate through development of aggressive enteropathy-associated T-cell lymphoma. It is not known whether genetic variations play a role in severe progression of CeD to RCDII. PATIENTS AND METHODS: We performed the first genome-wide association study to identify the causal genes for RCDII and the molecular pathways perturbed in RCDII. The genome-wide association study was performed in 38 Dutch patients with RCDII, and the 15 independent top-associated single nucleotide polymorphism (SNP) variants (P<5×10) were replicated in 56 independent French and Dutch patients with RCDII. RESULTS: After replication, SNP rs2041570 on chromosome 7 was significantly associated with progression to RCDII (P=2.37×10, odds ratio=2.36) but not with CeD susceptibility. SNP rs2041570 risk allele A was associated with lower levels of FAM188B expression in blood and small intestinal biopsies. Stratification of RCDII biopsies based on rs2041570 genotype showed differential expression of innate immune and antibacterial genes that are expressed in Paneth cells. CONCLUSION: We have identified a novel SNP associated with the severe progression of CeD to RCDII. Our data suggest that genetic susceptibility to CeD might be distinct from the progression to RCDII and suggest a role for Paneth cells in RCDII progression.

Cerebral tryptophan metabolism and outcome of tuberculous meningitis: an observational cohort study.

BACKGROUND: Immunopathology contributes to the high mortality of tuberculous meningitis, but the biological pathways involved are mostly unknown. We aimed to compare cerebrospinal fluid (CSF) and serum metabolomes of patients with tuberculous meningitis with that of controls without tuberculous meningitis, and assess the link between metabolite concentrations and mortality. METHODS: In this observational cohort study at the Hasan Sadikin Hospital (Bandung, Indonesia) we measured 425 metabolites using liquid chromatography-mass spectrometry in CSF and serum from 33 HIV-negative Indonesian patients with confirmed or probable tuberculous meningitis and 22 control participants with complete clinical data between March 12, 2009, and Oct 27, 2013. Associations of metabolite concentrations with survival were validated in a second cohort of 101 patients from the same centre. Genome-wide single nucleotide polymorphism typing was used to identify tryptophan quantitative trait loci, which were used for survival analysis in a third cohort of 285 patients. FINDINGS: Concentrations of 250 (70%) of 351 metabolites detected in CSF were higher in patients with tuberculous meningitis than in controls, especially in those who died during follow-up. Only five (1%) of the 390 metobolites detected in serum differed between patients with tuberculous meningitis and controls. CSF tryptophan concentrations showed a pattern different from most other CSF metabolites; concentrations were lower in patients who survived compared with patients who died (9-times) and to controls (31-times). The association of low CSF tryptophan with patient survival was confirmed in the validation cohort (hazard ratio 0·73; 95% CI 0·64-0·83; p<0·0001; per each halving). 11 genetic loci predictive for CSF tryptophan concentrations in tuberculous meningitis were identified (p<0·00001). These quantitative trait loci predicted survival in a third cohort of 285 HIV-negative patients in a prognostic index including age and sex, also after correction for possible confounders (p=0·0083). INTERPRETATION: Cerebral tryptophan metabolism, which is known to affect Mycobacterium tuberculosis growth and CNS inflammation, is important for the outcome of tuberculous meningitis. CSF tryptophan concentrations in tuberculous meningitis are under strong genetic influence, probably contributing to the variable outcomes of tuberculous meningitis. Interventions targeting tryptophan metabolism could improve outcomes of tuberculous meningitis. FUNDING: Royal Dutch Academy of Arts and Sciences; Netherlands Foundation for Scientific Research; Radboud University; National Academy of Sciences; Ministry of Research, Technology, and Higher Education, Indonesia; European Research Council; and PEER-Health.

An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.

Candidaemia is a bloodstream infection caused by Candida species that primarily affects specific groups of at-risk patients. Because only small candidaemia patient cohorts are available, classical genome wide association cannot be used to identify Candida susceptibility genes. Therefore, we have applied an integrative genomics approach to identify novel susceptibility genes and pathways for candidaemia. Candida-induced transcriptome changes in human primary leukocytes were assessed by RNA sequencing. Genetic susceptibility to candidaemia was assessed using the Illumina immunochip platform for genotyping of a cohort of 217 patients. We then integrated genetics data with gene-expression profiles, Candida-induced cytokine production capacity, and circulating concentrations of cytokines. Based on the intersection of transcriptome pathways and genomic data, we prioritized 31 candidate genes for candidaemia susceptibility. This group of genes was enriched with genes involved in inflammation, innate immunity, complement, and hemostasis. We then validated the role of MAP3K8 in cytokine regulation in response to Candida stimulation. Here, we present a new framework for the identification of susceptibility genes for infectious diseases that uses an unbiased, hypothesis-free, systems genetics approach. By applying this approach to candidaemia, we identified novel susceptibility genes and pathways for candidaemia, and future studies should assess their potential as therapeutic targets.

Genome-wide Analysis of STAT3-Mediated Transcription during Early Human Th17 Cell Differentiation.

The development of therapeutic strategies to combat immune-associated diseases requires the molecular mechanisms of human Th17 cell differentiation to be fully identified and understood. To investigate transcriptional control of Th17 cell differentiation, we used primary human CD4+ T cells in small interfering RNA (siRNA)-mediated gene silencing and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq) to identify both the early direct and indirect targets of STAT3. The integrated dataset presented in this study confirms that STAT3 is critical for transcriptional regulation of early human Th17 cell differentiation. Additionally, we found that a number of SNPs from loci associated with immune-mediated disorders were located at sites where STAT3 binds to induce Th17 cell specification. Importantly, introduction of such SNPs alters STAT3 binding in DNA affinity precipitation assays. Overall, our study provides important insights for modulating Th17-mediated pathogenic immune responses in humans.

No association between gluten sensitivity and amyotrophic lateral sclerosis.

To examine evidence for a role of gluten sensitivity (GS) or celiac disease (CD) in ALS etiology, we included participants from a population-based case-control study in The Netherlands between January 2006 and December 2015. We compared levels and seroprevalence of IgA antibodies to tissue transglutaminase 6 (TG6) in 359 ALS patients and 359 controls, and to transglutaminase 2 (TG2) and endomysium (EMA) in 199 ALS patients and 199 controls. Questionnaire data on 1829 ALS patients and 3920 controls were examined for CD or gluten-free diets (GFD). Genetic correlation and HLA allele frequencies were analyzed using two genome-wide association studies: one on ALS (12,577 cases, 23,475 controls), and one on CD (4533 cases, 10,750 controls). We found one patient with TG6, TG2 and EMA antibodies who had typical ALS and no symptoms of GS. TG6 antibody concentrations and positivity, CD prevalence and adherence to a GFD were similar in patients and controls (p > 0.66) and in these patients disease progression was compatible with typical ALS. CD and ALS were not found to be genetically correlated (p > 0.37). CD-associated HLA allele frequencies were similar in patients and controls (p > 0.28). In conclusion, we found no serological evidence for involvement of gluten-related antibodies in ALS etiology nor did we observe an association between CD and ALS in medical history or genetic data, indicating that there is no evidence in our data for an association between the two diseases. Hence, a role for a GFD in the ALS treatment seems unlikely.

A Functional Genomics Approach to Understand Variation in Cytokine Production in Humans.

As part of the Human Functional Genomics Project, which aims to understand the factors that determine the variability of immune responses, we investigated genetic variants affecting cytokine production in response to ex vivo stimulation in two independent cohorts of 500 and 200 healthy individuals. We demonstrate a strong impact of genetic heritability on cytokine production capacity after challenge with bacterial, fungal, viral, and non-microbial stimuli. In addition to 17 novel genome-wide significant cytokine QTLs (cQTLs), our study provides a comprehensive picture of the genetic variants that influence six different cytokines in whole blood, blood mononuclear cells, and macrophages. Important biological pathways that contain cytokine QTLs map to pattern recognition receptors (TLR1-6-10 cluster), cytokine and complement inhibitors, and the kallikrein system. The cytokine QTLs show enrichment for monocyte-specific enhancers, are more often located in regions under positive selection, and are significantly enriched among SNPs associated with infections and immune-mediated diseases. PAPERCLIP.

Inter-individual variability and genetic influences on cytokine responses to bacteria and fungi.

Little is known about the inter-individual variation of cytokine responses to different pathogens in healthy individuals. To systematically describe cytokine responses elicited by distinct pathogens and to determine the effect of genetic variation on cytokine production, we profiled cytokines produced by peripheral blood mononuclear cells from 197 individuals of European origin from the 200 Functional Genomics (200FG) cohort in the Human Functional Genomics Project (http://www.humanfunctionalgenomics.org), obtained over three different years. We compared bacteria- and fungi-induced cytokine profiles and found that most cytokine responses were organized around a physiological response to specific pathogens, rather than around a particular immune pathway or cytokine. We then correlated genome-wide single-nucleotide polymorphism (SNP) genotypes with cytokine abundance and identified six cytokine quantitative trait loci (QTLs). Among them, a cytokine QTL at the NAA35-GOLM1 locus markedly modulated interleukin (IL)-6 production in response to multiple pathogens and was associated with susceptibility to candidemia. Furthermore, the cytokine QTLs that we identified were enriched among SNPs previously associated with infectious diseases and heart diseases. These data reveal and begin to explain the variability in cytokine production by human immune cells in response to pathogens.

Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non-coding RNAs.

Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases.