Biomedical subjects

Kari Stefansson

Publications and source records attributed to Kari Stefansson.

5 recordsLinked to original sources

PubMed2026

Robust inference and correlates from genetic associations with personality.

Personality traits describe stable differences in how people think, feel and behave, and how they interact with and experience their social and physical environments1,2. Many questions remain unanswered about associations between DNA and personality traits, such as their robustness, their generalizability and the biological and social pathways through which they act. Here we meta-analyse data across 46 cohorts comprising 611,037 to 1.14 million participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience), and data from up to 50,725 participants for within-family GWAS. We identify 1,260 lead genetic variants associated with personality, including 824 novel variants3. Common genetic variants explain a moderate 4.8-9.3% of the variance in measures of each trait, and 9.3-13.3% among instruments with typical measurement reliability. Genetic associations with personality are highly consistent but not identical across geography, reporter (self versus close other), age group and measurement instrument, and we find minimal spousal assortment for personality in recent history. In contrast to many other social and behavioural traits4,5, within-family GWAS and polygenic index analyses indicate that genetic associations with personality are minimally confounded by the shared family environment. Polygenic prediction, genetic correlation and Mendelian randomization analyses indicate that personality traits have widespread, potentially causal associations with consequential behaviours and life outcomes. Overall, we find that the genetic architecture of personality is robustly generalizable, minimally confounded and widely relevant to human experience.

Journal Article↗

PubMed2026

Genomic analyses implicate hormonal and metabolic dysregulation in polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plasma proteins. Many risk-increasing loci were associated with later age at menopause, underscoring the reproductive longevity related to an increased oocyte number and/or availability across the lifespan. Hormonal regulation in the etiology of this condition, through metabolic and reproductive features, was emphasized. The proteomic analysis highlighted metabolic biology known to be related to PCOS. A polygenic risk score (PRS) was associated with adverse cardiometabolic outcomes, with differing relevance of testosterone and body mass index in women and men. Finally, while oligo-anovulation and anovulatory infertility are features of PCOS, we observed no impact of PCOS susceptibility on childlessness. We suggest that PCOS susceptibility confers balanced pleiotropic influences on fertility in women, and life-long adverse metabolic consequences in both sexes.

Humans↗

PubMed2025

The genetic architecture of fibromyalgia across 2.5 million individuals.

Fibromyalgia is a common and debilitating chronic pain syndrome of poorly understood etiology. Here, we conduct a multi-ancestry genome-wide association study meta-analysis across 2,563,755 individuals (54,629 cases and 2,509,126 controls) from 11 cohorts, identifying the first 26 risk loci for fibromyalgia. The strongest association was with a coding variant in HTT, the causal gene for Huntington's disease. Gene prioritization implicated the HTT regulator GPR52, as well as diverse genes with neural roles, including CAMKV, DCC, DRD2/NCAM1, MDGA2, and CELF4. Fibromyalgia heritability was exclusively enriched within brain tissues and neural cell types. Fibromyalgia showed strong, positive genetic correlation with a wide range of chronic pain, psychiatric, and somatic disorders, including genetic correlations above 0.7 with low back pain, post-traumatic stress disorder and irritable bowel syndrome. Despite large sex differences in fibromyalgia prevalence, the genetic architecture of fibromyalgia was nearly identical between males and females. This work provides the first robust genetic evidence defining fibromyalgia as a central nervous system disorder, thereby establishing a biological framework for its complex pathophysiology and extensive clinical comorbidities.

Journal Article↗

PubMed2024

Genome-Wide Association Study of Accessory Atrioventricular Pathways.

IMPORTANCE: Understanding of the genetics of accessory atrioventricular pathways (APs) and affiliated arrhythmias is limited. OBJECTIVE: To investigate the genetics of APs and affiliated arrhythmias. DESIGN, SETTING, AND PARTICIPANTS: This was a genome-wide association study (GWAS) of APs, defined by International Classification of Diseases (ICD) codes and/or confirmed by electrophysiology (EP) study. Genome-wide significant AP variants were tested for association with AP-affiliated arrhythmias: paroxysmal supraventricular tachycardia (PSVT), atrial fibrillation (AF), ventricular tachycardia, and cardiac arrest. AP variants were also tested in data on other heart diseases and measures of cardiac physiology. Individuals with APs and control individuals from Iceland (deCODE Genetics), Denmark (Copenhagen Hospital Biobank, Danish Blood Donor Study, and SupraGen/the Danish General Suburban Population Study [GESUS]), the US (Intermountain Healthcare), and the United Kingdom (UK Biobank) were included. Time of phenotype data collection ranged from January 1983 to December 2022. Data were analyzed from August 2022 to January 2024. EXPOSURES: Sequence variants. MAIN OUTCOMES AND MEASURES: Genome-wide significant association of sequence variants with APs. RESULTS: The GWAS included 2310 individuals with APs (median [IQR] age, 43 [28-57] years; 1252 [54.2%] male and 1058 [45.8%] female) and 1 206 977 control individuals (median [IQR] year of birth, 1955 [1945-1970]; 632 888 [52.4%] female and 574 089 [47.6%] male). Of the individuals with APs, 909 had been confirmed in EP study. Three common missense variants were associated with APs, in the genes CCDC141 (p.Arg935Trp: adjusted odds ratio [aOR], 1.37; 95% CI, 1.24-1.52, and p.Ala141Val: aOR, 1.55; 95% CI 1.34-1.80) and SCN10A (p.Ala1073Val: OR, 1.22; 95% CI, 1.15-1.30). The 3 variants associated with PSVT and the SCN10A variant associated with AF, supporting an effect on AP-affiliated arrhythmias. All 3 AP risk alleles were associated with higher heart rate and shorter PR interval, and have reported associations with chronotropic response. CONCLUSIONS AND RELEVANCE: Associations were found between sequence variants and APs that were also associated with risk of PSVT, and thus likely atrioventricular reentrant tachycardia, but had allele-specific associations with AF and conduction disorders. Genetic variation in the modulation of heart rate, chronotropic response, and atrial or atrioventricular node conduction velocity may play a role in the risk of AP-affiliated arrhythmias. Further research into CCDC141 could provide insights for antiarrhythmic therapeutic targeting in the presence of an AP.

Humans↗

PubMed2016

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas.

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

Atlases as Topic↗