Effect of booster vaccination against Delta and Omicron SARS-CoV-2 variants in Iceland

Publisher Copyright: © 2022, The Author(s).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.Peer reviewe

HLA alleles, disease severity, and age associate with T-cell responses following infection with SARS-CoV-2

Funding Information: We thank all of the participants that contributed samples for this study for their invaluable contribution to the research. We also thank our research staff at the Patient Recruitment Center for their thorough work. Publisher Copyright: © 2022, The Author(s).Memory T-cell responses following SARS-CoV-2 infection have been extensively investigated but many studies have been small with a limited range of disease severity. Here we analyze SARS-CoV-2 reactive T-cell responses in 768 convalescent SARS-CoV-2-infected (cases) and 500 uninfected (controls) Icelanders. The T-cell responses are stable three to eight months after SARS-CoV-2 infection, irrespective of disease severity and even those with the mildest symptoms induce broad and persistent T-cell responses. Robust CD4+ T-cell responses are detected against all measured proteins (M, N, S and S1) while the N protein induces strongest CD8+ T-cell responses. CD4+ T-cell responses correlate with disease severity, humoral responses and age, whereas CD8+ T-cell responses correlate with age and functional antibodies. Further, CD8+ T-cell responses associate with several class I HLA alleles. Our results, provide new insight into HLA restriction of CD8+ T-cell immunity and other factors contributing to heterogeneity of T-cell responses following SARS-CoV-2 infection.Peer reviewe

Eighty-eight variants highlight the role of T cell regulation and airway remodeling in asthma pathogenesis

Publisher's version (útgefin grein)Asthma is one of the most common chronic diseases affecting both children and adults. We report a genome-wide association meta-analysis of 69,189 cases and 702,199 controls from Iceland and UK biobank. We find 88 asthma risk variants at 56 loci, 19 previously unreported, and evaluate their effect on other asthma and allergic phenotypes. Of special interest are two low frequency variants associated with protection against asthma; a missense variant in TNFRSF8 and 3‘ UTR variant in TGFBR1. Functional studies show that the TNFRSF8 variant reduces TNFRSF8 expression both on cell surface and in soluble form, acting as loss of function. eQTL analysis suggests that the TGFBR1 variant acts through gain of function and together with an intronic variant in a downstream gene, SMAD3, points to defective TGFβR1 signaling as one of the biological perturbations increasing asthma risk. Our results increase the number of asthma variants and implicate genes with known role in T cell regulation, inflammation and airway remodeling in asthma pathogenesis.We thank the individuals who participated in this study and the staff at the Icelandic Patient Recruitment Center and the deCODE genetics core facilities. Further to all our colleagues who contributed to the data collection and phenotypic characterization of clinical samples as well as to the genotyping and analysis of the whole-genome association data. This research has been conducted using the UK biobank Resource under Application Number ‘24711’.Peer Reviewe

A homozygous loss-of-function mutation leading to CYBC1 deficiency causes chronic granulomatous disease

Publisher's version (útgefin grein) Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.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 (gp91phox) 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 chipgenotyped 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.We wish to thank the family of the two probands, as well as all the other individuals who participated in the study and whose contribution made this work possible.Peer Reviewe

Tumor grading.

<p>Gleason grading score of the tumors for the samples used in Experiment 1 and Experiment 2. The sample on array 5 was used repeatedly on three arrays in Experiment 3.</p

The number of Monte Carlo simulations for which each region is chosen by the selection method using arrays with the same sample.

<p>The genomic location of the regions on 8q24 is on the x-axis. The proportion of Monte Carlo simulations for which the region was chosen is on the y-axis. The graph is shown with two different colourings, representing whether the region was among the previously experiment-wise selected regions (cyan) or not (pink). Those who were selected previously in Experiment 1 are shown at the top graph, Experiment 2 in the middle and Experiment 3 at the bottom. The simulations are done on the ten repeated spots for each probe for the three arrays in Experiment 3 that contained the same sample.</p

The number of Monte Carlo simulations for which each region is chosen by the selection method using arrays with different samples.

<p>The genomic location of the regions on 8q24 is on the x-axis. The proportion of Monte Carlo simulations for which the region was chosen is on the y-axis. The graph is shown with two different colourings, representing whether the region was among the previously experiment-wise selected regions (cyan) or not (pink). Those who were selected previously in Experiment 1 are shown at the top graph, Experiment 2 in the middle and Experiment 3 at the bottom. The simulations are done on the ten repeated spots for each probe for all nine arrays in Experiment 3.</p

Regions selected in first two experiments.

<p>The loci of the 20 regions selected in first and second experiments, according to hg18 and hg19 and the genes reported at these loci.</p

The proportion of regions that were selected in both Experiment 1 and Experiment 2.

<p>The underlying region was split up into equally sized regions and a fixed number of regions with the highest ratio of probes, within the region, expressed above the median, was selected. The proportion of regions that were selected in both Experiment 1 and Experiment 2 was calculated for varying length of each underlying region (y-axis) and the total number of regions to be selected (x-axis). The numbers within each cell show the exact proportions for the corresponding criteria.</p