İlhan E. Acar

Abstract Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism 1–7 . This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases 8–11 . Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

Abstract In the past decade, single-cell transcriptomics has helped to uncover new cell types and states and led to the construction of a cellular compendium of health and disease. Despite this progress, some difficult-to-sequence cells remain absent from tissue atlases. Eosinophils—elusive granulocytes that are implicated in a plethora of human pathologies 1–5 —are among these uncharted cell types. The heterogeneity of eosinophils and the gene programs that underpin their pleiotropic functions remain poorly understood. Here we provide a comprehensive single-cell transcriptomic profiling of mouse eosinophils. We identify an active and a basal population of intestinal eosinophils, which differ in their transcriptome, surface proteome and spatial localization. By means of a genome-wide CRISPR inhibition screen and functional assays, we reveal a mechanism by which interleukin-33 (IL-33) and interferon-γ (IFNγ) induce the accumulation of active eosinophils in the inflamed colon. Active eosinophils are endowed with bactericidal and T cell regulatory activity, and express the co-stimulatory molecules CD80 and PD-L1. Notably, active eosinophils are enriched in the lamina propria of a small cohort of patients with inflammatory bowel disease, and are closely associated with CD4 + T cells. Our findings provide insights into the biology of eosinophils and highlight the crucial contribution of this cell type to intestinal homeostasis, immune regulation and host defence. Furthermore, we lay a framework for the characterization of eosinophils in human gastrointestinal diseases.

Abstract Age-related macular degeneration (AMD) is a leading cause of blindness. Genetic variants at the chromosome 1q31.3 encompassing the complement factor H ( CFH , FH) and CFH related genes ( CFHR1-5 ) are major determinants of AMD susceptibility, but their molecular consequences remain unclear. Here we demonstrate that FHR-4 plays a prominent role in AMD pathogenesis. We show that systemic FHR-4 levels are elevated in AMD ( P -value = 7.1 × 10 −6 ), whereas no difference is seen for FH. Furthermore, FHR-4 accumulates in the choriocapillaris, Bruch’s membrane and drusen, and can compete with FH/FHL-1 for C3b binding, preventing FI-mediated C3b cleavage. Critically, the protective allele of the strongest AMD-associated CFH locus variant rs10922109 has the highest association with reduced FHR-4 levels ( P -value = 2.2 × 10 −56 ), independently of the AMD-protective CFHR1–3 deletion, and even in those individuals that carry the high-risk allele of rs1061170 (Y402H). Our findings identify FHR-4 as a key molecular player contributing to complement dysregulation in AMD.

PurposeThe current study aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date, as well as aiming to determine the effect of AMD-associated genetic variants on metabolite levels and investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways.DesignCase-control association analysis of metabolomics data.ParticipantsFive European cohorts consisting of 2267 AMD patients and 4266 control participants.MethodsMetabolomics was performed using a high-throughput proton nuclear magnetic resonance metabolomics platform, which allows quantification of 146 metabolite measurements and 79 derivative values. Metabolome–AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d-to-C3 ratio) were investigated using linear regression.Main Outcome MeasuresMetabolites associated with AMD.ResultsWe identified 60 metabolites that were associated significantly with AMD, including increased levels of large and extra-large high-density lipoprotein (HDL) subclasses and decreased levels of very low-density lipoprotein (VLDL), amino acids, and citrate. Of 52 AMD-associated genetic variants, 7 variants were associated significantly with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, and LIPC) with metabolites belonging to the large and extra-large HDL subclasses. Also, 57 of 60 metabolites were associated significantly with complement activation levels, independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation.ConclusionsLipoprotein levels were associated with AMD-associated genetic variants, whereas decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD. The current study aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date, as well as aiming to determine the effect of AMD-associated genetic variants on metabolite levels and investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways. Case-control association analysis of metabolomics data. Five European cohorts consisting of 2267 AMD patients and 4266 control participants. Metabolomics was performed using a high-throughput proton nuclear magnetic resonance metabolomics platform, which allows quantification of 146 metabolite measurements and 79 derivative values. Metabolome–AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d-to-C3 ratio) were investigated using linear regression. Metabolites associated with AMD. We identified 60 metabolites that were associated significantly with AMD, including increased levels of large and extra-large high-density lipoprotein (HDL) subclasses and decreased levels of very low-density lipoprotein (VLDL), amino acids, and citrate. Of 52 AMD-associated genetic variants, 7 variants were associated significantly with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, and LIPC) with metabolites belonging to the large and extra-large HDL subclasses. Also, 57 of 60 metabolites were associated significantly with complement activation levels, independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation. Lipoprotein levels were associated with AMD-associated genetic variants, whereas decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD.

PURPOSE: To develop a genotype assay to assess associations with common and rare age-related macular degeneration (AMD) risk variants, to calculate an overall genetic risk score (GRS), and to identify potential misdiagnoses with inherited macular dystrophies that mimic AMD. DESIGN: Case-control study. PARTICIPANTS: Individuals (n = 4740) from 5 European cohorts. METHODS: We designed single-molecule molecular inversion probes for target selection and used next generation sequencing to sequence 87 single nucleotide polymorphisms (SNPs), coding and splice-site regions of 10 AMD-(related) genes (ARMS2, C3, C9, CD46, CFB, CFH, CFI, HTRA1, TIMP3, and SLC16A8), and 3 genes that cause inherited macular dystrophies (ABCA4, CTNNA1, and PRPH2). Genetic risk scores for common AMD risk variants were calculated based on effect size and genotype of 52 AMD-associated variants. Frequency of rare variants was compared between late AMD patients and control individuals with logistic regression analysis. MAIN OUTCOME MEASURES: Genetic risk score, association of genetic variants with AMD, and genotype-phenotype correlations. RESULTS: We observed high concordance rates between our platform and other genotyping platforms for the 69 successfully genotyped SNPs (>96%) and for the rare variants (>99%). We observed a higher GRS for patients with late AMD compared with patients with early/intermediate AMD (P < 0.001) and individuals without AMD (P < 0.001). A higher proportion of pathogenic variants in the CFH (odds ratio [OR] = 2.88; P = 0.006), CFI (OR = 4.45; P = 0.005), and C3 (OR = 6.56; P = 0.0003) genes was observed in late AMD patients compared with control individuals. In 9 patients, we identified pathogenic variants in the PRPH2, ABCA4, and CTNNA1 genes, which allowed reclassification of these patients as having inherited macular dystrophy. CONCLUSIONS: This study reports a genotype assay for common and rare AMD genetic variants, which can identify individuals at intermediate to high genetic risk of late AMD and enables differential diagnosis of AMD-mimicking dystrophies. Our study supports sequencing of CFH, CFI, and C3 genes because they harbor rare high-risk variants. Carriers of these variants could be amendable for new treatments for AMD that currently are under development.