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Gudbjartsson, D. F.

Publications and source records attributed to Gudbjartsson, D. F..

13 recordsLinked to original sources
bioRxiv2026

BloodVariome: a high-resolution atlas of inherited genetic effects in human immune cells

Genome-wide association studies have linked thousands of sequence variants to immune-mediated diseases, yet their cellular mechanisms remain largely unresolved. Here we present BloodVariome, a high-resolution atlas of genetic effects across the human immune cell hierarchy. Combining deep immunophenotyping with automated pattern-recognition, we quantified 1,533 traits across 127 immune cell populations in 11,983 individuals. We identified 259 significant associations, the vast majority of which are not captured by conventional bulk blood trait studies. Most associations were restricted to single immune lineages or cell populations, revealing a fine-grained genetic compartmentalization of the immune system. By linking known disease risk alleles to specific immune cell phenotypes, BloodVariome illuminates cellular mechanisms underlying autoimmunity, immunodeficiency, and hematologic malignancy. Moreover, we implicate novel regulators of human immune cell development and function. By bridging the gap between cohort size and phenotypic depth, BloodVariome establishes a high-resolution framework for interpreting how genetic variation shapes cellular immunity at population-scale.

genomics↗
bioRxiv2026

Population-scale immunoglobulin genetics resolves the human B-cell system

Immunoglobulins (Ig) mediate adaptive humoral immunity, yet the regulation of B-cell responses in vivo in humans remains inaccessible to direct experimentation. Here we use population-scale Ig genetics to resolve molecular regulation of the human B-cell system. Analysis of circulating IgA, IgG, IgM, and six composite Ig traits in 114,697 individuals identifies 504 genetic associations. Integration with regulatory genomics, plasma proteomics, and immunophenotyping maps these effects across the B-cell hierarchy, recovering known regulators and revealing previously unrecognized genes in humoral immunity. At key control nodes - including Fc{gamma} receptors, the immunoglobulin heavy-chain locus and the TACI-APRIL signaling axis - variants form allelic series generating graded perturbations of antibody output. Ig-associated loci show extensive overlap with autoimmunity, immunodeficiency and B-cell malignancy. These findings demonstrate that Ig traits, analyzed at population scale, encode fine-grained information about the regulation of the human B-cell system and link natural variation in humoral immunity to immune-mediated disease.

genomics↗
bioRxiv2021

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWAS) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations, and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels, and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. Two prioritized genes, CREBRF and RRBP1, show convergent evidence across functional datasets supporting their roles in lipid biology.

genomics↗
bioRxiv2019

Long read sequencing of 1,817 Icelanders provides insight into the role of structural variants in human disease

Long-read sequencing (LRS) promises to improve characterization of structural variants (SVs), a major source of genetic diversity. We generated LRS data on 3,622 Icelanders using Oxford Nanopore Technologies, and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions), spanning a median of 10 Mb per haploid genome. We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association with a rare (AF = 0.037%) deletion of the first exon of PCSK9. Carriers of this deletion have 0.93 mmol/L (1.31 SD) lower LDL cholesterol levels than the population average (p-value = 7.0{middle dot}10-20). We also discovered an association with a multi-allelic SV inside a large repeat region, contained within single long reads, in an exon of ACAN. Within this repeat region we found 11 alleles that differ in the number of a 57 bp-motif repeat, and observed a linear relationship (0.016 SD per motif inserted, p = 6.2{middle dot}10-18) between the number of repeats carried and height. These results show that SVs can be accurately characterized at population scale using long read sequence data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.

genetics↗
bioRxiv2019

Deep learning based brain age prediction uncovers associated sequence variants

Machine learning algorithms trained to recognize age-related structural changes in magnetic resonance images (MRIs) of healthy individuals can be used to predict biological brain age in independent samples. The difference between predicted and chronological age, predicted age difference (PAD), is a phenotype holding promise for the study of normal brain ageing and brain diseases, and genetic discovery via genome-wide association studies (GWASs). Here, we present a new deep learning approach to predict brain age from a T1-weighted MRI. The method was trained on a dataset of healthy Icelanders (N = 1264) and tested on two datasets, the IXI (N = 544) and UK Biobank (N = 12395) datasets, utilizing transfer learning to improve accuracy on new sites. A GWAS of PAD in the UK Biobank data (discovery set: N=12395, replication set: N=4453) yielded two sequence variants, rs1452628-T ({beta}=-0.08, P = 1.15 {middle dot} 10-9) and rs2435204-G ({beta}=0.102, P = 9.73 {middle dot} 10-12). The former is near KCNK2 and correlates with reduced sulcal width, whereas the latter correlates with reduced white matter surface area and tags a well-known inversion at 17q21.31 (H2). The genetic association analysis was also confined to variants known to associate with brain structure, yielding three additional sequence variants associating with PAD.

neuroscience↗
bioRxiv2018

Genome-wide association meta-analysis of PR interval identifies 47 novel loci associated with atrial and atrioventricular electrical activity

Electrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.

genetics↗
bioRxiv2017

Recurrence of de novo mutations in families

De novo mutations (DNMs) cause a large fraction of severe rare diseases of childhood. DNMs that occur in early embryos may result in mosaicism of both somatic and germ cells. Such early mutations may be transmitted to more than one offspring and cause recurrence of serious disease. We scanned 1,007 sibling pairs from 251 families and identified 885 DNMs shared by siblings (ssDNMs) at 451 genomic sites. We estimated the probability of DNM recurrence based on presence in the blood of the parent, sharing by other siblings, parent-of-origin, mutation type, and genomic position. We detected 52.1% of ssDNMs in the parental blood. The probability of a DNM being shared goes down by 2.28% per year for paternal DNMs and 1.82% for maternal DNMs. Shared paternal DNMs are more likely to be T>C mutations than maternal ones, but less likely to be C>T mutations. Depending on DNM properties, the probability of recurrence in a younger sibling ranges from 0.013% to 29.6%. We have launched an online DNM recurrence probability calculator, to use in genetic counselling in cases of rare genetic diseases.

genomics↗
bioRxiv2017

Mutations in RPL3L and MYZAP increase risk of atrial fibrillation

We performed a meta-analysis of genome-wide association studies on atrial fibrillation (AF) among 14,710 cases and 373,897 controls from Iceland and 14,792 cases and 393,863 controls from the UK Biobank, focusing on low frequency coding and splice mutations, with follow-up in samples from Norway and the US. We observed associations with two missense (OR=1.19 for both) and one splice-donor mutation (OR=1.52) in RPL3L, encoding a ribosomal protein primarily expressed in skeletal muscle and heart. Analysis of 167 RNA samples from the right atrium revealed that the splice donor mutation in RPL3L results in exon skipping. AF is the first disease associated with RPL3L and RPL3L is the first ribosomal gene implicated in AF. This finding is consistent with tissue specialization of ribosomal function. We also found an association with a missense variant in MYZAP (OR=1.37), encoding a component of the intercalated discs of cardiomyocytes, the organelle harbouring most of the mutated proteins involved in arrhythmogenic right ventricular cardiomyopathy. Both discoveries emphasize the close relationship between the mechanical and electrical function of the heart.

genetics↗
bioRxiv2017

Estimating heritability without environmental bias

Heritability measures the proportion of trait variation that is due to genetic inheritance. Measurement of heritability is of importance to the nature-versus-nurture debate. However, existing estimates of heritability could be biased by environmental effects. Here we introduce relatedness disequilibrium regression (RDR), a novel method for estimating heritability. RDR removes environmental bias by exploiting variation in relatedness due to random segregation. We use a sample of 54,888 Icelanders with both parents genotyped to estimate the heritability of 14 traits, including height (55.4%, S.E. 4.4%) and educational attainment (17.0%, S.E. 9.4%). Our results suggest that some other estimates of heritability could be inflated by environmental effects.

genetics↗
bioRxiv2017

The nature of nurture: effects of parental genotypes

Sequence variants in the parental genomes that are not transmitted to a child/proband are often ignored in genetic studies. Here we show that non-transmitted alleles can impact a child through their effects on the parents and other relatives, a phenomenon we call genetic nurture. Using results from a meta-analysis of educational attainment, the polygenic score computed for the non-transmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P = 1.6x10-14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition/heath related traits.\n\nOne Sentence SummaryNurture has a genetic component, i.e. alleles in the parents affect the parents phenotypes and through that influence the outcomes of the child.

genetics↗
bioRxiv2017

A rare missense mutation in MYH6 confers high risk of coarctation of the aorta

Coarctation of the aorta (CoA) accounts for 4-8% of congenital heart defects (CHDs) and carries substantial morbidity despite treatment1. We performed a genome-wide association study (GWAS) of CoA among 120 Icelandic cases and 355,166 controls and found association with a rare (frequency = 0.34%) missense mutation p.Arg721Trp in MYH6 (odds ratio (OR) = 44.2, P = 5.0x10-22), encoding an essential sarcomere protein. Approximately 20% of CoA cases in Iceland carry p.Arg721Trp. This is the first mutation associated with non-familial or sporadic CoA at a population level. P.Arg721Trp also associates with risk of bicuspid aortic valve (BAV) and other CHDs and has been reported to have a broad effect on cardiac electrical function and to associate strongly with sick sinus syndrome (SSS) and atrial fibrillation (AF)2. These findings suggest that p.Arg721Trp in MYH6 causes a cardiac syndrome with highly variable expressivity, and emphasize the major importance of sarcomere integrity for cardiac development and function.

genetics↗
bioRxiv2017

Graphtyper: Population-scale genotyping using pangenome graphs

A fundamental requisite for genetic studies is an accurate determination of sequence variation. While human genome sequence diversity is increasingly well characterized, there is a need for efficient ways to utilize this knowledge in sequence analysis. Here we present Graphtyper, a publicly available novel algorithm and software for discovering and genotyping sequence variants. Graphtyper realigns short-read sequence data to a pangenome, a variation-aware graph structure that encodes sequence variation within a population by representing possible haplotypes as graph paths. Our results show that Graphtyper is fast, highly scalable, and provides sensitive and accurate genotype calls. Graphtyper genotyped 89.4 million sequence variants in whole-genomes of 28,075 Icelanders using less than 100,000 CPU days, including detailed genotyping of six human leukocyte antigen (HLA) genes. We show that Graphtyper is a valuable tool in characterizing sequence variation in population-scale sequencing studies.

bioinformatics↗