Biomedical subjects

Jaakko Kaprio

Publications and source records attributed to Jaakko Kaprio.

4 recordsLinked to original sources

PubMed2026

Genome-wide association meta-analysis of eating behavior traits revealed one susceptibility locus for emotional eating.

In order to identify new and genome-wide significant loci for eating behavior traits (cognitive restraint, uncontrolled eating and emotional eating), we conducted a meta-GWAS with seven studies of European ancestry (n = 11,250). Eating behavior was assessed using the Three-Factor Eating Questionnaire. Genotype effects of single studies were estimated using additive models adjusting for age, sex, BMI, and principal components and single study results were combined by fixed-effect meta-analysis.For cognitive restraint and uncontrolled eating, no genome-wide significant association could be detected. For emotional eating, one genomic region on chromosome 5 comprising two polymorphisms attained genome-wide significance (P = 4.0×10-8 for rs6877636 and P = 3.2×10-8 for rs6897090). The minor alleles were associated with higher emotional eating scores (β=0.093 ± 0.017), with a similar direction of effect in each study. Both SNPs, in near perfect linkage disequilibrium, mapped to RP11-24P24.1, a processed pseudogene of ornithine decarboxylase 1 (ODC1). Enrichment analysis revealed a significant overlap between genome-wide BMI-associated variants and nominal emotional eating variants, supporting the hypothesis that shared genetic factors may influence both eating behavior traits and obesity risk. Finally, we observed a number of interesting associations reaching suggestive significance (P < 10-6) involving BMI candidate genes, including a suggestive association between FTO variants and cognitive restraint (rs9922708, β = 0.069, P = 5.9×10-7).In conclusion, our meta-GWAS identified for the first time a robust chromosomal region associated with emotional eating in seven studies. Given that emotional eating strongly influences body weight but is often stigmatized, recognizing genetic susceptibility to certain eating behaviors may help reduce stigma and alleviate guilt.

Journal Article↗

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

Evaluating a Genome-Wide Polygenic Score for Handgrip Strength and Its Interplay with Leisure-Time Physical Activity Across the IGEMS Twin Cohorts.

PURPOSE: Polygenic scores (PGSs) may help assess genetic predisposition to multifactorial traits. We examined whether age, sex, and leisure-time physical activity (LTPA) modify the association between a PGS for handgrip strength (HGS) and measured HGS in older adults. METHODS: PGS for HGS (PGS hgs) , based on Pan-UK Biobank genome-wide association study data, was calculated for 5103 participants (aged 40-96; 44% women) from eight twin cohorts in Denmark, Sweden, Australia, the United States, and Finland within the IGEMS consortium. Sex-standardized HGS and self-reported LTPA were assessed cross-sectionally. Linear mixed models estimated associations between PGS hgs and HGS, including interactions with age, country, and LTPA, as well as an association between PGS hgs and LTPA. Fixed-effect within-pair models were conducted to assess environmental contributions. RESULTS: Higher PGS hgs was associated with greater HGS (β = 2.14, SE = 0.15, P < 0.001), explaining 4.6% of HGS variance overall, with modest variation across countries. In sex-stratified models, PGS hgs explained 5.2% of the variance in females and 4.3% in males. No statistically significant interaction with age was found. A significant PGS hgs × LTPA interaction (β = -0.034, P = 0.013) indicated that the association between LTPA and HGS was more pronounced among individuals with lower PGS hgs . The within-pair models offered limited support for the independent environmental impact of LTPA. CONCLUSIONS: The PGS hgs was associated with measured HGS in the meta-analysis, highlighting the potential of PGSs to capture individual differences in strength-related traits across populations. The association of PGS hgs with HGS was moderated by LTPA, such that the beneficial impact of LTPA on HGS was greater among individuals with a lower genetic propensity for HGS.

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↗