Biomedical subjects

Martin Tesli

Publications and source records attributed to Martin Tesli.

4 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.

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PubMed2026

Family genetic designs in MoBa provide insights into health and functioning.

Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease1. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother-father-child trios2,3. However, samples of genotyped families are rare4-11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. 3), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children's height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

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PubMed2025

Genome-wide association study of adolescent-onset depression.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

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PubMed2025

Associations of Genetic Liability to Six Psychiatric Disorders With Cardiometabolic Diseases.

IMPORTANCE: Individuals with psychiatric disorders have increased risk of cardiometabolic diseases (CMDs). Evaluating how psychiatric genetic liability relates to CMD may clarify mechanisms. OBJECTIVE: Identify genetic overlap between psychiatric disorders and CMDs independent of cross-disorder pleiotropy, BMI, and smoking. DESIGN SETTING AND PARTICIPANTS: Three Northern European cohorts (the Swedish Twin Registry, the Estonian Biobank, and the Norwegian Mother, Father and Child Cohort Study [MoBa]) totaling 355,159 individuals. Associations with CMDs were estimated as adjusted odds ratios (AORs) from logistic models mutually adjusted for all psychiatric PRSs and in models additionally adjusting for body mass index (BMI) and smoking. Cohort-specific AORs were pooled by inverse-variance weighting. MAIN OUTCOMES AND MEASURES: Exposures were PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), anxiety disorder, posttraumatic stress disorder (PTSD), bipolar disorder, and schizophrenia. Outcomes were diagnoses of CMDs (hyperlipidemia, obesity, type 2 diabetes, hypertensive diseases, arteriosclerosis, ischemic heart disease, heart failure, thromboembolic disease, cerebrovascular disease, and arrhythmias), ascertained from electronic health records. RESULTS: The MDD PRS was associated with increased risk of all CMDs across analyses (AORs ranged from 1.13 [95% CI, 1.10-1.15] for heart failure to 1.02 [95% CI, 1.00-1.05] for arrhythmias). The ADHD PRS was associated with increased risk of all CMDs (AOR ranged from 1.11 [95% CI, 1.09-1.12] for obesity to 1.02 [95% CI, 1.01-1.03] for hyperlipidemia), however associations where attenuated when adjusting for BMI and smoking (lifestyle adjusted AOR for obesity: 1.03 [95% CI, 1.02-1.05]). When not mutually adjusting for all psychiatric PRSs, anxiety disorder and PTSD PRSs were associated with all CMDs; these associations diminished after adjustment. The bipolar and schizophrenia PRSs were inversely associated with most CMDs (AOR for schizophrenia PRS and obesity, 0.93 [95% CI, 0.92-0.94]). CONCLUSIONS AND RELEVANCE: Associations between psychiatric PRSs and CMDs diverged: ADHD, MDD, anxiety disorder, and PTSD PRSs were positively associated with CMDs, whereas bipolar and schizophrenia PRSs were inversely associated. Genetic liability to MDD showed robust associations with CMDs independent of cross-disorder pleiotropy, BMI, and smoking status, whereas associations between the ADHD PRS and CMDs were largely attenuated after adjustment for BMI and smoking.

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