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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.

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.

People living with human immunodeficiency virus (PLHIV) are at high risk of developing non-HIV related comorbidities, particularly at older ages. In a retrospective claims database analysis, we compared PLHIV to a matched, non-HIV cohort to assess the prevalence of comorbidities and healthcare costs in PLHIV and the general non-HIV population in Germany. In total, 2,132 adult patients with HIV were identified in the InGef research database with HIV ICD-10 diagnosis within each year from 2011 to 2014. Of these, 1,969 could be matched to a control cohort of 3,938 individuals (1:2 ratio). Matching criteria included age, gender and socio-economic variables. The prevalence of acute renal disease (0.5% vs. 0.2%, p = 0.045), bone fractures due to osteoporosis (6.4% vs. 2.1%, p<0.001), chronic renal disease (4.3% vs. 2.4%, p<0.001), cardiovascular disease (12.8% vs. 10.4%, p = 0.006), Hepatitis B (5.9% vs. 0.3%, p<0.001) and Hepatitis C infection (8.8% vs. 0.3%, p<0.001) was significantly higher in PLHIV compared to the matched non-HIV cohort. Mean costs excluding costs for antiretroviral therapy (ART) were significantly higher in the HIV cohort (8,049€ vs. 3,658€, p<0.05). On average, PLHIV incurred excess costs of 16,441€ for ART, 2,747€ for pharmaceuticals excluding ART (p<0.05), 1,441€ for outpatient care (p<0.05) and 321€ for inpatient care (p<0.05). Devices and remedies' costs were significantly higher in the control cohort with excess costs of 113€ (p<0.05). Considering mean total costs, excluding ART, excess costs for PLHIV amounted to 8,049€ (p<0.05). This analysis demonstrated an increased comorbidity and economic burden of PLHIV compared to matched controls. Our findings suggest that HIV remains an area of high unmet medical need. To improve patient outcomes, adequate HIV management including regular monitoring, screening for comorbidities and optimal ART selection throughout the life course of PLHIV are of key importance., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: SC has received honoraria and/or travel grants for consulting or speaking at educational events from Abbvie, Gilead, Indivior, Janssen-Cilag, MSD and ViiV. EW has received honoraria and/or travel grants for consulting or speaking at educational events from AbbVie, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, Hexal, Janssen-Cilag, MSD SHARP & DOHME, Roche, and ViiV Healthcare. MUC Research has received support for clinical research from AbbVie, Gilead Sciences, MSD Sharp and Dohme, Pfizer und ViiV Healthcare. JA is an employee of Xcenda GmbH, a company which received funding from Gilead Sciences Europe Ltd for developing and conducting this study. HDC is a Gilead Sciences Europe Ltd employee.