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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.

Stacy Steinberg, Hreinn Stefansson, Thorlakur Jonsson and colleagues found that rare variants predicted to alter the function of ABCA7 are associated with risk of Alzheimer's disease. The association was found in Iceland and replicated in northern Europe and the United States. We conducted a search for rare, functional variants altering susceptibility to Alzheimer's disease that exploited knowledge of common variants associated with the same disease. We found that loss-of-function variants in ABCA7 confer risk of Alzheimer's disease in Icelanders (odds ratio (OR) = 2.12, P = 2.2 × 10 −13 ) and discovered that the association replicated in study groups from Europe and the United States (combined OR = 2.03, P = 6.8 × 10 −15 ).

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.

Despite significant research efforts aimed at understanding the neurobiological underpinnings of psychiatric disorders, the diagnosis and the evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms. Therefore, biological markers which could improve the current classification of psychiatry disorders, and in perspective stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. In order to identify novel candidate biological markers for major depression and schizophrenia, we have applied a focused proteomic approach using plasma samples from a large case-control collection. Patients were diagnosed according to DSM criteria using structured interviews and a number of additional clinical variables and demographic information were assessed. Plasma samples from 245 depressed patients, 229 schizophrenic patients and 254 controls were submitted to multi analyte profiling allowing the evaluation of up to 79 proteins, including a series of cytokines, chemokines and neurotrophins previously suggested to be involved in the pathophysiology of depression and schizophrenia. Univariate data analysis showed more significant p-values than would be expected by chance and highlighted several proteins belonging to pathways or mechanisms previously suspected to be involved in the pathophysiology of major depression or schizophrenia, such as insulin and MMP-9 for depression, and BDNF, EGF and a number of chemokines for schizophrenia. Multivariate analysis was carried out to improve the differentiation of cases from controls and identify the most informative panel of markers. The results illustrate the potential of plasma biomarker profiling for psychiatric disorders, when conducted in large collections. The study highlighted a set of analytes as candidate biomarker signatures for depression and schizophrenia, warranting further investigation in independent collections.

The atypical antipsychotic clozapine is the only effective medication for treatment-resistant schizophrenia. However, it can also induce serious adverse drug reactions, including agranulocytosis and neutropenia. The mechanism by which it does so is largely unknown, but there is evidence for contributing genetic factors. Several studies identified HLA-DQB1 variants and especially a polymorphism located in HLA-DQB1 (6672G>C, rs113332494) as associated with clozapine-induced agranulocytosis and neutropenia. We analysed the risk allele distribution of SNP rs113332494 in a sample of 1396 controls and 178 neutropenia cases of which 60 developed agranulocytosis. Absolute neutrophil counts of 500/mm3 and 1500/mm3 were used for defining agranulocytosis and neutropenia cases, respectively. We also performed association analyses and analysed local ancestry patterns in individuals of European ancestry, seeking replication and extension of earlier findings. HLA-DQB1 (6672G>C, rs113332494) was associated with neutropenia (OR = 6.20, P = 2.20E−06) and agranulocytosis (OR = 10.49, P = 1.83E−06) in individuals of European ancestry. The association signal strengthened after including local ancestry estimates (neutropenia: OR = 10.38, P = 6.05E−08; agranulocytosis: OR = 16.31, P = 1.39E−06), with effect sizes being considerably larger for agranulocytosis. Using local ancestry estimates for prediction, the sensitivity of rs113332494 increased from 11.28 to 55.64% for neutropenia and from 16.67 to 53.70% for agranulocytosis. Our study further strengthens the evidence implicating HLA-DQB1 in agranulocytosis and neutropenia, suggesting components of the immune system as contributing to this serious adverse drug reaction. Using local ancestry estimates might help in identifying risk variants and improve prediction of haematological adverse effects.

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater \"load\" of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

Downbeat nystagmus (DBN) is a frequent form of acquired persisting central fixation nystagmus, often associated with other cerebellar ocular signs, such as saccadic smooth pursuit or gaze-holding deficits. Despite its distinct clinical features, the underlying etiology of DBN often remains unclear. Therefore, a genome-wide association study (GWAS) was conducted in 106 patients and 2609 healthy controls of European ancestry to identify genetic variants associated with DBN. A genome-wide significant association (p < 5 × 10−8) with DBN was found for a variation on chromosome 13 located within the fibroblast growth factor 14 gene (FGF14). FGF14 is expressed in Purkinje cells (PCs) and a reduction leads to a decreased spontaneous firing rate and excitability of PCs, compatible with the pathophysiology of DBN. In addition, mutations in the FGF14 gene cause spinocerebellar ataxia type 27. Suggestive associations (p < 1 × 10−05) could be detected for 15 additional LD-independent loci, one of which is also located in the FGF14 gene. An association of a region containing the dihydrofolate reductase (DHFR) and MutS Homolog 3 (MSH3) genes on chromosome 5 was slightly below the genome-wide significance threshold. DHFR is relevant for neuronal regulation, and a dysfunction is known to induce cerebellar damage. Among the remaining twelve suggestive associations, four genes (MAST4, TPPP, FTMT, and IDS) seem to be involved in cerebral pathological processes. Thus, this GWAS analysis has identified a potential genetic contribution to idiopathic DBN, including suggestive associations to several genes involved in postulated pathological mechanisms of DBN (i.e., impaired function of cerebellar PCs).

Polymorphisms in a primate-specific isoform of K + channel KCNH2 are associated with schizophrenia. This isoform induces a rapidly deactivating K + current and high-frequency neuronal firing pattern. The disease-associated alleles predict lower intelligence quotient scores, lower speed of cognitive processing and altered memory. This channel isoform represents a potential new drug target for psychotherapy pages 488–490 . Organized neuronal firing is crucial for cortical processing and is disrupted in schizophrenia. Using rapid amplification of 5′ complementary DNA ends in human brain, we identified a primate-specific isoform (3.1) of the ether-a-go-go–related K + channel KCNH2 that modulates neuronal firing. KCNH2 -3.1 messenger RNA levels are comparable to full-length KCNH2 (1A) levels in brain but three orders of magnitude lower in heart. In hippocampus from individuals with schizophrenia, KCNH2 -3.1 expression is 2.5-fold greater than KCNH2 -1A expression. A meta-analysis of five clinical data sets (367 families, 1,158 unrelated cases and 1,704 controls) shows association of single nucleotide polymorphisms in KCNH2 with schizophrenia. Risk-associated alleles predict lower intelligence quotient scores and speed of cognitive processing, altered memory-linked functional magnetic resonance imaging signals and increased KCNH2 - 3.1 mRNA levels in postmortem hippocampus. KCNH2-3.1 lacks a domain that is crucial for slow channel deactivation. Overexpression of KCNH2 - 3.1 in primary cortical neurons induces a rapidly deactivating K + current and a high-frequency, nonadapting firing pattern. These results identify a previously undescribed KCNH2 channel isoform involved in cortical physiology, cognition and psychosis, providing a potential new therapeutic drug target.

Both environmental (e.g. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/features in the general population indicate that genetic factors underlying these symptoms/features are shared in part with the personality traits of the Five Factor Model (FFM) of personality—the “Big Five”. In the present study, the genetic overlap of BPD with the Big Five -Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism- was assessed. Linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD ( N  = 2543) and GWAS on the Big Five ( N  = 76,551–122,886, Neuroticism N  = 390,278). Polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status. Significant positive genetic correlations of BPD were found with Neuroticism ( rg  = 0.34, p  = 6.3*10 −5 ) and Openness ( rg  = 0.24, p  = 0.036), but not with the other personality traits (all |  rg  | <0.14, all p  > 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters “Depressed Affect” and “Worry”, and with a broad range of Neuroticism items ( N  = 348,219–376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk. The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the “Big Five” are needed to further explore the role of personality traits in the etiology of BPD.

In the present study, an integrated hierarchical approach was applied to: (1) identify pathways associated with susceptibility to schizophrenia; (2) detect genes that may be potentially affected in these pathways since they contain an associated polymorphism; and (3) annotate the functional consequences of such single-nucleotide polymorphisms (SNPs) in the affected genes or their regulatory regions. The Global Test was applied to detect schizophrenia-associated pathways using discovery and replication datasets comprising 5,040 and 5,082 individuals of European ancestry, respectively. Information concerning functional gene-sets was retrieved from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and the Molecular Signatures Database. Fourteen of the gene-sets or pathways identified in the discovery dataset were confirmed in the replication dataset. These include functional processes involved in transcriptional regulation and gene expression, synapse organization, cell adhesion, and apoptosis. For two genes, i.e. CTCF and CACNB2, evidence for association with schizophrenia was available (at the gene-level) in both the discovery study and published data from the Psychiatric Genomics Consortium schizophrenia study. Furthermore, these genes mapped to four of the 14 presently identified pathways. Several of the SNPs assigned to CTCF and CACNB2 have potential functional consequences, and a gene in close proximity to CACNB2, i.e. ARL5B, was identified as a potential gene of interest. Application of the present hierarchical approach thus allowed: (1) identification of novel biological gene-sets or pathways with potential involvement in the etiology of schizophrenia, as well as replication of these findings in an independent cohort; (2) detection of genes of interest for future follow-up studies; and (3) the highlighting of novel genes in previously reported candidate regions for schizophrenia.