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Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

Contains fulltext : 248704.pdf (Publisher’s version ) (Open Access) Innate immune cells are able to build memory characteristics via a process termed "trained immunity." Host factors that influence the magnitude of the individual trained immunity response remain largely unknown. Using an integrative genomics approach, our study aimed to prioritize and understand the role of specific genes in trained immunity responses. In vitro-induced trained immunity responses were assessed in two independent population-based cohorts of healthy individuals, the 300 Bacillus Calmette-Guérin (300BCG; n = 267) and 200 Functional Genomics (200FG; n = 110) cohorts from the Human Functional Genomics Project. Genetic loci that influence cytokine responses upon trained immunity were identified by conducting a meta-analysis of QTLs identified in the 300BCG and 200FG cohorts. From the identified QTL loci, we functionally validated the role of PI3K-Akt signaling pathway and two genes that belong to the family of Siglec receptors (Siglec-5 and Siglec-14). Furthermore, we identified the H3K9 histone demethylases of the KDM4 family as major regulators of trained immunity responses. These data pinpoint an important role of metabolic and epigenetic processes in the regulation of trained immunity responses, and these findings may open new avenues for vaccine design and therapeutic interventions.

Genetic variants identified through genome-wide association studies (GWAS) are typically non-coding and exert small regulatory effects on downstream genes, but which downstream genes are ultimately impacted and how they confer risk remains mostly unclear. Conversely, variants that cause rare Mendelian diseases are often coding and have a more direct impact on disease development. We demonstrate that common and rare genetic diseases can be linked by studying the gene regulatory networks impacted by common disease-associated variants. We implemented this in the ‘Downstreamer’ method and applied it to 44 GWAS traits and find that predicted downstream “key genes” are enriched with Mendelian disease genes, e.g. key genes for height are enriched for genes that cause skeletal abnormalities and Ehlers-Danlos syndromes. We find that 82% of these key genes are located outside of GWAS loci, suggesting that they result from complex trans regulation rather than being impacted by disease-associated variants in cis. Finally, we discuss the challenges in reconstructing gene regulatory networks and provide a roadmap to improve identification of these highly connected genes for common traits and diseases.

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

Gaining insight into the downstream consequences of non-coding variants is an essential step towards the identification of therapeutic targets from genome-wide association study (GWAS) findings. Here we have harmonized and integrated 8,727 RNA-seq samples with accompanying genotype data from multiple brain-regions from 14 datasets. This sample size enabled us to perform both cis- and trans-expression quantitative locus (eQTL) mapping. Upon comparing the brain cortex cis-eQTLs (for 12,307 unique genes at FDRcis-eQTL analysis (n=31,684 samples), we observed that brain eQTLs are more tissue specific than previously assumed.We inferred the brain cell type for 1,515 cis-eQTLs by using cell type proportion information. We conducted Mendelian Randomization on 31 brain-related traits using cis-eQTLs as instruments and found 159 significant findings that also passed colocalization. Furthermore, two multiple sclerosis (MS) findings had cell type specific signals, a neuron-specific cis-eQTL for CYP24A1 and a macrophage specific cis-eQTL for CLECL1.To further interpret GWAS hits, we performed trans-eQTL analysis. We identified 2,589 trans-eQTLs (at FDRWe also generated a brain-specific gene-coregulation network that we used to predict which genes have brain-specific functions, and to perform a novel network analysis of Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS) and Parkinson’s disease (PD) GWAS data. This resulted in the identification of distinct sets of genes that show significantly enriched co-regulation with genes inside the associated GWAS loci, and which might reflect drivers of these diseases.

PurposeThe Lifelines COVID-19 cohort was set up to assess the psychological and societal impacts of the COVID-19 pandemic and investigate potential risk factors for COVID-19 within the Lifelines prospective population cohort.ParticipantsParticipants were recruited from the 140 000 eligible participants of Lifelines and the Lifelines NEXT birth cohort, who are all residents of the three northern provinces of the Netherlands. Participants filled out detailed questionnaires about their physical and mental health and experiences on a weekly basis starting in late March 2020, and the cohort consists of everyone who filled in at least one questionnaire in the first 8 weeks of the project.Findings to date>71 000 unique participants responded to the questionnaires at least once during the first 8 weeks, with >22 000 participants responding to seven questionnaires. Compiled questionnaire results are continuously updated and shared with the public through the Corona Barometer website. Early results included a clear signal that younger people living alone were experiencing greater levels of loneliness due to lockdown, and subsequent results showed the easing of anxiety as lockdown was eased in June 2020.Future plansQuestionnaires were sent on a (bi)weekly basis starting in March 2020 and on a monthly basis starting July 2020, with plans for new questionnaire rounds to continue through 2020 and early 2021. Questionnaire frequency can be increased again for subsequent waves of infections. Cohort data will be used to address how the COVID-19 pandemic developed in the northern provinces of the Netherlands, which environmental and genetic risk factors predict disease susceptibility and severity and the psychological and societal impacts of the crisis. Cohort data are linked to the extensive health, lifestyle and sociodemographic data held for these participants by Lifelines, a 30-year project that started in 2006, and to data about participants held in national databases.

Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ∼200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenicFMR1premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

As our ancestors migrated throughout the different continents, natural selection increased the presence of alleles advantageous in the new environments. Heritable variations that alter the susceptibility to diseases vary with the historical period, the virulence of the infections, and their geographical spread. In this study we built polygenic scores for heritable traits influencing the genetic adaptation in the production of cytokines and immune-mediated disorders, including infectious, inflammatory, and autoimmune diseases, and applied them to the genomes of several ancient European populations. We observed that the advent of the Neolithic was a turning point for immune-mediated traits in Europeans, favoring those alleles linked with the development of tolerance against intracellular pathogens and promoting inflammatory responses against extracellular microbes. These evolutionary patterns are also associated with an increased presence of traits related to inflammatory and auto-immune diseases.

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).

Candida bloodstream infection, i.e. candidemia, is the most frequently encountered life-threatening fungal infection worldwide, with mortality rates up to almost 50%. In the majority of candidemia cases, Candida albicans is responsible. Worryingly, a global increase in the number of patients who are susceptible to infection (e.g. immunocompromised patients), has led to a rise in the incidence of candidemia in the last few decades. Therefore, a better understanding of the anti-Candida host response is essential to overcome this poor prognosis and to lower disease incidence. Here, we integrated genome-wide association studies with bulk and single-cell transcriptomic analyses of immune cells stimulated with Candida albicans to further our understanding of the anti-Candida host response. We show that differential expression analysis upon Candida stimulation in single-cell expression data can reveal the important cell types involved in the host response against Candida. This confirmed the known major role of monocytes, but more interestingly, also uncovered an important role for NK cells. Moreover, combining the power of bulk RNA-seq with the high resolution of single-cell RNA-seq data led to the identification of 27 Candida-response QTLs and revealed the cell types potentially involved herein. Integration of these response QTLs with a GWAS on candidemia susceptibility uncovered a potential new role for LY86 in candidemia susceptibility. Finally, experimental follow-up confirmed that LY86 knockdown results in reduced monocyte migration towards the chemokine MCP-1, thereby implying that this reduced migration may underlie the increased susceptibility to candidemia. Altogether, our integrative systems genetics approach identifies previously unknown mechanisms underlying the immune response to Candida infection., Author summary Candida albicans is a fungus that can cause a life-threatening infection in individuals with an impaired immune system. To improve the prognosis and treatment of patients with such an infection, a better understanding of an individual’s immune response against Candida is required. However, small patient group sizes have limited our ability to gain such understanding. Here we show that integrating many different data layers can improve the sensitivity to detect the effects of genetics on the response to Candida infection and the roles different immune cell types have herein. Using this approach, we were able to prioritize genes that are associated with an increased risk of developing systemic Candida infections. We expand on the gene with the strongest risk association, LY86, and describe a potential mechanism through which this gene affects the immune response against Candida infection. Through experimental follow-up, we provided additional insights into how this gene is associated with an increased risk to develop a Candida infection. We expect that our approach can be generalized to other infectious diseases for which small patient group sizes have restricted our ability to unravel the disease mechanism in more detail. This will provide new opportunities to identify treatment targets in the future.

Here, we assessed whether 41 SNPs within steroid hormone genes associated with erosive disease. The most relevant finding was the rheumatoid factor (RF)-specific effect of the CYP1B1, CYP2C9, ESR2, FcγR3A, and SHBG SNPs to modulate the risk of bone erosions (P = 0.004, 0.0007, 0.0002, 0.013 and 0.015) that was confirmed through meta-analysis of our data with those from the DREAM registry (P = 0.000081, 0.0022, 0.00074, 0.0067 and 0.0087, respectively). Mechanistically, we also found a gender-specific correlation of the CYP2C9rs1799853T/T genotype with serum vitamin D3 levels (P = 0.00085) and a modest effect on IL1β levels after stimulation of PBMCs or blood with LPS and PHA (P = 0.0057 and P = 0.0058). An overall haplotype analysis also showed an association of 3 ESR1 haplotypes with a reduced risk of erosive arthritis (P = 0.009, P = 0.002, and P = 0.002). Furthermore, we observed that the ESR2, ESR1 and FcγR3A SNPs influenced the immune response after stimulation of PBMCs or macrophages with LPS or Pam3Cys (P = 0.002, 0.0008, 0.0011 and 1.97•10−7). Finally, we found that a model built with steroid hormone-related SNPs significantly improved the prediction of erosive disease in seropositive patients (PRF+ = 2.46•10−8) whereas no prediction was detected in seronegative patients (PRF− = 0.36). Although the predictive ability of the model was substantially lower in the replication population (PRF+ = 0.014), we could confirm that CYP1B1 and CYP2C9 SNPs help to predict erosive disease in seropositive patients. These results are the first to suggest a RF-specific association of steroid hormone-related polymorphisms with erosive disease.

Contains fulltext : 193382.pdf (Publisher’s version ) (Closed access) The immune response to pathogens varies substantially among people. Whereas both genetic and nongenetic factors contribute to interperson variation, their relative contributions and potential predictive power have remained largely unknown. By systematically correlating host factors in 534 healthy volunteers, including baseline immunological parameters and molecular profiles (genome, metabolome and gut microbiome), with cytokine production after stimulation with 20 pathogens, we identified distinct patterns of co-regulation. Among the 91 different cytokine-stimulus pairs, 11 categories of host factors together explained up to 67% of interindividual variation in cytokine production induced by stimulation. A computational model based on genetic data predicted the genetic component of stimulus-induced cytokine production (correlation 0.28-0.89), and nongenetic factors influenced cytokine production as well.

IP injection in rats of 2-acetylaminofluorene (AAF) or N-hydroxy-2-acetylaminofluorene (N-OH-AAF) resulted in a transient increase of hepatic ornithine decarboxylase (ODC) and tyrosine aminotransferase (TAT) activity. Maximal activity of ODC was observed 4 hr and of TAT 3 hr after administration of either AAF or N-OH-AAF. A lag-time of 2 hr preceded the increase of ODC and TAT activity. N-OH-AAF dependent ODC induction displayed an almost linear dose-response in the dose range up to 94.1 mumol/kg bw (body weight) when the ODC activity was measured at its maximum 4 hr after administration. Elevation of the dose N-OH-AAF to 126 mol/kg bw resulted in a lower ODC induction. Administration of doses AAF to 31.4 mumol did not change ODC activity. At doses up to 126 mumol/kg bw ODC induction increased linear. TAT induction increased linear in the dose range 15.7-94.1 mumol N-OH-AAF and 31.4-94.1 mumol AAF/kg. Lowering the dose of AAF did not result in a lower ODC or TAT activity. Judged by the effects of actinomycin D or cycloheximide administered 1 hr prior to AAF or N-OH-AAF, the in vivo induction of rat liver ODC activity by AAF and N-OH-AAF appeared to be under transcriptional control, whereas augmentation of TAT activity under influence of AAF or N-OH-AAF appeared the result of (post) translational events. Induction of ODC by AAF or N-OH-AAF was not significantly changed by indomethacin, was slightly increased by pentachlorophenol (PCP) and was synergistically enhanced by retinylacetate (RA). The increase of TAT activity was stimulated by PCP and RA. The effect of PCP indicates that N-sulfonoxy-2-acetylaminofluorene is most probably not involved in the induction of ODC. AAF appeared more effective hepatic ODC inducer in females than males and moreover more effective than N-OH-AAF in females. N-OH-AAF had stronger ODC inducing capacity in males than females. Similar observations were made with respect to TAT activity. When induction of ODC is indicative for a tumor promoting property then the data presented here suggest that tumor promotion of the complete carcinogens AAF and N-OH-AAF is not mediated by N-O-sulfation; this might be due to other metabolic conversions.