Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

Genes and the environment contribute to variation in adult body mass index [BMI (in kg/m)], but factors modifying these variance components are poorly understood. We analyzed genetic and environmental variation in BMI between men and women from young adulthood to old age from the 1940s to the 2000s and between cultural-geographic regions representing high (North America and Australia), moderate (Europe), and low (East Asia) prevalence of obesity. We used genetic structural equation modeling to analyze BMI in twins ≥20 y of age from 40 cohorts representing 20 countries (140,379 complete twin pairs). The heritability of BMI decreased from 0.77 (95% CI: 0.77, 0.78) and 0.75 (95% CI: 0.74, 0.75) in men and women 20-29 y of age to 0.57 (95% CI: 0.54, 0.60) and 0.59 (95% CI: 0.53, 0.65) in men 70-79 y of age and women 80 y of age, respectively. The relative influence of unique environmental factors correspondingly increased. Differences in the sets of genes affecting BMI in men and women increased from 20-29 to 60-69 y of age. Mean BMI and variances in BMI increased from the 1940s to the 2000s and were greatest in North America and Australia, followed by Europe and East Asia. However, heritability estimates were largely similar over measurement years and between regions. There was no evidence of environmental factors shared by co-twins affecting BMI. The heritability of BMI decreased and differences in the sets of genes affecting BMI in men and women increased from young adulthood to old age. The heritability of BMI was largely similar between cultural-geographic regions and measurement years, despite large differences in mean BMI and variances in BMI. Our results show a strong influence of genetic factors on BMI, especially in early adulthood, regardless of the obesity level in the population.

For over one hundred years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically 1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and 2) to study the effects of birth related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects including both monozygotic and dizygotic twins using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.