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High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project 1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people 2 , for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity. Comparisons of phenotypic and genetic association with protein levels from Icelandic and UK Biobank cohorts show that using multiple analysis platforms and stratifying populations by ancestry improves the detection of associations and allows the refinement of their location within the genome.

Mutations in genes encoding subunits of the phagocyte NADPH oxidase complex are recognized to cause chronic granulomatous disease (CGD), a severe primary immunodeficiency. Here we describe how deficiency of CYBC1, a previously uncharacterized protein in humans (C17orf62), leads to reduced expression of NADPH oxidase’s main subunit (gp91 phox ) and results in CGD. Analyzing two brothers diagnosed with CGD we identify a homozygous loss-of-function mutation, p.Tyr2Ter, in CYBC1 . Imputation of p.Tyr2Ter into 155K chip-genotyped Icelanders reveals six additional homozygotes, all with signs of CGD, manifesting as colitis, rare infections, or a severely impaired PMA-induced neutrophil oxidative burst. Homozygosity for p.Tyr2Ter consequently associates with inflammatory bowel disease (IBD) in Iceland ( P   =  8.3 × 10 −8 ; OR = 67.6), as well as reduced height ( P   =  3.3 × 10 −4 ; −8.5 cm). Overall, we find that CYBC1 deficiency results in CGD characterized by colitis and a distinct profile of infections indicative of macrophage dysfunction. Mutations in genes encoding NAPDH oxidase subunits are known to be causative for the primary immunodeficiency chronic granulomatous disease (CGD). Here, the authors identify CYBC1 mutations in patients with CGD and show that CYBC1 is important for formation of the NADPH complex and respiratory burst.

Gallstones are responsible for one of the most common diseases in the Western world and are commonly treated with cholecystectomy. We perform a meta-analysis of two genome-wide association studies of gallstone disease in Iceland and the UK, totaling 27,174 cases and 736,838 controls, uncovering 21 novel gallstone-associated variants at 20 loci. Two distinct low frequency missense variants in SLC10A2 , encoding the apical sodium-dependent bile acid transporter (ASBT), associate with an increased risk of gallstone disease (Pro290Ser: OR = 1.36 [1.25–1.49], P  = 2.1 × 10 –12 , MAF = 1%; Val98Ile: OR = 1.15 [1.10–1.20], P  = 1.8 × 10 –10 , MAF = 4%). We demonstrate that lower bile acid transport by ASBT is accompanied by greater risk of gallstone disease and highlight the role of the intestinal compartment of the enterohepatic circulation of bile acids in gallstone disease susceptibility. Additionally, two low frequency missense variants in SERPINA1 and HNF4A and 17 common variants represent novel associations with gallstone disease. Genome-wide association studies have so far identified eight risk loci for gallstone disease. Here, the authors perform meta-analysis in cohorts from Iceland and the UK which reveals further 21 common and low-frequency risk variants that highlight the role of bile acid homeostasis in gallstone disease.

Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci ( SMARCD3 , WAC , ELL2 , CDCA7L , CEP120 , and PREX1 ). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy. The causality and functional roles of disease-associated variants revealed by genome-wide association studies (GWAS) are mostly unexplored. Here the authors identify putative causal variants in multiple myeloma and find their association with gene expression and chromatin accessibility.

By the end of July 2021, the majority of the Icelandic population had received vaccination against COVID-19. In mid-July a wave of SARS-CoV-2 infections, dominated by the Delta variant, spread through the population, followed by an Omicron wave in December. A booster vaccination campaign was initiated to curb the spread of the virus. We estimate the risk of infection for different vaccine combinations using vaccination data from 276,028 persons and 963,557 qPCR tests for 277,687 persons. We measure anti-Spike-RBD antibody levels and ACE2-Spike binding inhibitory activity in 371 persons who received one of four recommended vaccination schedules with or without an mRNA vaccine booster. Overall, we find different antibody levels and inhibitory activity in recommended vaccination schedules, reflected in the observed risk of SARS-CoV-2 infections. We observe an increased protection following mRNA boosters, against both Omicron and Delta variant infections, although BNT162b2 boosters provide greater protection against Omicron than mRNA-1273 boosters. Iceland has used four different SARS-CoV-2 vaccines in various combinations. Here, the authors describe differences in the immune responses elicited by different initial/booster vaccine combinations, and then use population-level data to assess the effects of booster doses against Delta and Omicron infection.

Despite timely implementation of testing for SARS-CoV-2 virus, a contact-tracing scheme, and social-distancing measures, infection has spread in Iceland. However, there was no detected increase in the proportion of infected persons between March 13 and April 4, 2020.

The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF) < 1%). We tested plasma protein levels for association with 373 diseases and other traits and identified 257,490 associations. We integrated pQTL and genetic associations with diseases and other traits and found that 12% of 45,334 lead associations in the GWAS Catalog are with variants in high linkage disequilibrium with pQTL. We identified 938 genes encoding potential drug targets with variants that influence levels of possible biomarkers. Combining proteomics, genomics and transcriptomics, we provide a valuable resource that can be used to improve understanding of disease pathogenesis and to assist with drug discovery and development. A genome-wide association study of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders highlights links with over 370 disease endpoints and other traits.

Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM , underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options. Genome-wide analyses identify loci associated with nonalcoholic fatty liver disease, including rare, protective loss-of-function variants in MTARC1 and GPAM . Plasma proteomic analyses provide insight into proteins involved in disease pathogenesis.

Predicting all-cause mortality risk is challenging and requires extensive medical data. Recently, large-scale proteomics datasets have proven useful for predicting health-related outcomes. Here, we use measurements of levels of 4,684 plasma proteins in 22,913 Icelanders to develop all-cause mortality predictors both for short- and long-term risk. The participants were 18-101 years old with a mean follow up of 13.7 (sd. 4.7) years. During the study period, 7,061 participants died. Our proposed predictor outperformed, in survival prediction, a predictor based on conventional mortality risk factors. We could identify the 5% at highest risk in a group of 60-80 years old, where 88% died within ten years and 5% at the lowest risk where only 1% died. Furthermore, the predicted risk of death correlates with measures of frailty in an independent dataset. Our results show that the plasma proteome can be used to assess general health and estimate the risk of death.Eiriksdottir et al. use a temporal proteomic dataset from over 22,000 Icelandic individuals to identify predictors and predict all-cause mortality. Their findings suggest that the plasma proteome may be of value in general health screening for risk of death.