Heritability estimates of the Big Five personality traits based on common genetic variants

According to twin studies, the Big Five personality traits have substantial heritable components explaining 40–60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527 469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e.=0.08, P=0.04) and openness (21%, s.e.=0.08, P<0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG=1.00, P <0.001), despite low phenotypic correlation (r=−0.09, P <0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.     

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13 835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case–Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.     

Genetic association of cyclic AMP signaling genes with bipolar disorder

The genetic basis for bipolar disorder (BPD) is complex with the involvement of multiple genes. As it is well established that cyclic adenosine monophosphate (cAMP) signaling regulates behavior, we tested variants in 29 genes that encode components of this signaling pathway for associations with BPD type I (BPD I) and BPD type II (BPD II). A total of 1172 individuals with BPD I, 516 individuals with BPD II and 1728 controls were analyzed. Single SNP (single-nucleotide polymorphism), haplotype and SNP × SNP interactions were examined for association with BPD. Several statistically significant single-SNP associations were observed between BPD I and variants in the PDE10A gene and between BPD II and variants in the DISC1 and GNAS genes. Haplotype analysis supported the conclusion that variation in these genes is associated with BPD. We followed-up PDE10A''s association with BPD I by sequencing a 23-kb region in 30 subjects homozygous for seven minor allele risk SNPs and discovered eight additional rare variants (minor allele frequency <1%). These single-nucleotide variants were genotyped in 999 BPD cases and 801 controls. We obtained a significant association for these variants in the combined sample using multiple methods for rare variant analysis. After using newly developed methods to account for potential bias from sequencing BPD cases only, the results remained significant. In addition, SNP × SNP interaction studies suggested that variants in several cAMP signaling pathway genes interact to increase the risk of BPD. This report is among the first to use multiple rare variant analysis methods following common tagSNPs associations with BPD.     

A whole genome association study of neuroticism using DNA pooling

We describe a multistage approach to identify single nucleotide polymorphisms (SNPs) associated with neuroticism, a personality trait that shares genetic determinants with major depression and anxiety disorders. Whole genome association with 452 574 SNPs was performed on DNA pools from approximately 2000 individuals selected on extremes of neuroticism scores from a cohort of 88 142 people from southwest England. The most significant SNPs were then genotyped on independent samples to replicate findings. We were able to replicate association of one SNP within the PDE4D gene in a second sample collected by our laboratory and in a family-based test in an independent sample; however, the SNP was not significantly associated with neuroticism in two other independent samples. We also observed an enrichment of low P-values in known regions of copy number variations. Simulation indicates that our study had approximately 80% power to identify neuroticism loci in the genome with odds ratio (OR)>2, and approximately 50% power to identify small effects (OR=1.5). Since we failed to find any loci accounting for more than 1% of the variance, the heritability of neuroticism probably arises from many loci each explaining much less than 1%. Our findings argue the need for much larger samples than anticipated in genetic association studies and that the biological basis of emotional disorders is extremely complex.     

Personality traits of agreeableness and extraversion are associated with ADH4 variation.

BACKGROUND: Personality traits are associated with substance dependence (SD); genetic factors may influence both. Strong associations between ADH4 variation and SD have been reported. We aimed to investigate the relationship between ADH4 variation and personality traits in the present study. METHODS: We assessed dimensions of the five-factor model of personality in 243 subjects with SD (175 European Americans [EAs] and 68 African Americans [AAs]) and 296 healthy control subjects (256 EAs and 40 AAs). We also genotyped 7 ADH4 markers (spanning the locus) and 38 unlinked ancestry-informative markers in these subjects. The relationships between the diplotypes, alleles, and genotypes at ADH4 and personality traits were examined using multivariate analysis of covariance (MANCOVA), controlling for potential confounders. RESULTS: Generally, SD patients, older individuals, and male subjects scored higher on neuroticism and lower on other personality factors. Personality factors were associated with the diplotypes. The allele A or genotype A/A of single nucleotide polymorphism (SNP)6 (rs1800759 at the gene promoter) was significantly associated with agreeableness scores. There were associations between extraversion and SNP1 (hcv2033010 at the 3' end) and SNP2 (rs1042364 in exon 9) in subjects with higher conscientiousness scores. CONCLUSIONS: The personality traits of agreeableness and extraversion are related to ADH4 polymorphism. Among the ADH4 markers that appear to predispose to certain personality traits, the functional variant rs1800759 (SNP6) in the promoter region is most important. We conclude that personality traits and SD have a partially overlapping genetic basis.     

Genome-wide association study of Alzheimer's disease

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer''s disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer''s disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples.     

Low extraversion and high neuroticism as indices of genetic and environmental risk for social phobia, agoraphobia, and animal phobia

OBJECTIVE: The authors examined the extent to which two major personality dimensions (extraversion and neuroticism) index the genetic and environmental risk for three phobias (social phobia, agoraphobia, and animal phobia) in twins ascertained from a large, population-based registry. METHOD: Lifetime phobias and personality traits were assessed through diagnostic interview and self-report questionnaire, respectively, in 7,800 twins from female-female, male-male, and opposite-sex pairs. Sex-limited trivariate Cholesky structural equation models were used to decompose the correlations among extraversion, neuroticism, and each phobia. RESULTS: In the best-fitting models, genetic correlations were moderate and negative between extraversion and both social phobia and agoraphobia, and that between extraversion and animal phobia was effectively zero. Genetic correlations were high and positive between neuroticism and both social phobia and agoraphobia, and that between neuroticism and animal phobia was moderate. All of the genetic risk factors for social phobia and agoraphobia were shared with those that influence extraversion and neuroticism; in contrast, only a small proportion of the genetic risk factors for animal phobia (16%) was shared with those that influence personality. Shared environmental experiences were not a source of correlations between personality traits and phobias, and unique environmental correlations were relatively modest. CONCLUSION: Genetic factors that influence individual variation in extraversion and neuroticism appear to account entirely for the genetic liability to social phobia and agoraphobia, but not animal phobia. These findings underline the importance of both introversion (low extraversion) and neuroticism in some psychiatric disorders.     

Glutamate Networks Implicate Cognitive Impairments in Schizophrenia: Genome-Wide Association Studies of 52 Cognitive Phenotypes

Cognitive impairments are a core feature in patients with schizophrenia. These deficits could serve as effective tools for understanding the genetic architecture of schizophrenia. This study investigated whether genetic variants associated with cognitive impairments aggregate in functional gene networks related to the pathogenesis of schizophrenia. Here, genome-wide association studies (GWAS) of a range of cognitive phenotypes relevant to schizophrenia were performed in 411 healthy subjects. We attempted to replicate the GWAS data using 257 patients with schizophrenia and performed a meta-analysis of the GWAS findings and the replicated results. Because gene networks, rather than a single gene or genetic variant, may be strongly associated with the susceptibility to schizophrenia and cognitive impairments, gene-network analysis for genes in close proximity to the replicated variants was performed. We observed nominal associations between 3054 variants and cognitive phenotypes at a threshold of P < 1.0 × 10^{− 4}. Of the 3054 variants, the associations of 191 variants were replicated in the replication samples (P < .05). However, no variants achieved genome-wide significance in a meta-analysis (P > 5.0 × 10^{− 8}). Additionally, 115 of 191 replicated single nucleotide polymorphisms (SNPs) have genes located within 10 kb of the SNPs (60.2%). These variants were moderately associated with cognitive phenotypes that ranged from P = 2.50 × 10^{− 5} to P = 9.40 × 10^{− 8}. The genes located within 10 kb from the replicated SNPs were significantly grouped in terms of glutamate receptor activity (false discovery rate (FDR) q = 4.49 × 10^{− 17}) and the immune system related to major histocompatibility complex class I (FDR q = 8.76 × 10^{− 11}) networks. Our findings demonstrate that genetic variants related to cognitive trait impairment in schizophrenia are involved in the N-methyl-d-aspartate glutamate network.Key words: schizophrenia, genome-wide association study, cognitive phenotypes, glutamate receptor activity, immune function, functional gene network     

TMPRSS9 and GRIN2B Are Associated with Neuroticism: a Genome-Wide Association Study in a European Sample

Major depression disorder (MDD) is a complex and chronic disease that ranks fourth as cause of disability worldwide. About 14 million adults in the USA are believed to have MDD, and an estimated 75 % attempt suicide making MDD a major public health problem. Neuroticism has been recognized as an endophenotype of MDD; however, few genome-wide association (GWA) analyses of neuroticism as a quantitative trait have been reported to date. The aim of this study is to identify genome-wide genetic variants affecting neuroticism using a European sample. A linear regression model was used to analyze the association with neuroticism as a continuous trait in the Netherlands Study of Depression and Anxiety and Netherlands Twin Registry population-based sample of 2,748 individuals with Perlegen 600K single nucleotide polymorphisms (SNPs). In addition, the neuroticism-associated genes/loci of the top 20 SNPs (p?<?10^?4) were examined with anti-social personality disorder (ASPD) in an Australian twin family study. Through GWA analysis, 32 neuroticism-associated SNPs (p?<?10^?4) were identified. The most significant association was observed with SNP rs4806846 within the TMPRSS9 gene (p?=?7.79?×?10^?6) at 19p13.3. The next best signal was in GRIN2B gene (rs220549, p?=?1.05?×?10^?5) at 12p12. In addition, several SNPs within GRIN2B showed borderline associations with ASPD in the Australian sample. In conclusion, these results provide a possible genetic basis for the association with neuroticism. Our findings provide a basis for replication in other populations to elucidate the potential role of these genetic variants in neuroticism and MDD along with a possible relationship between ASPD and neuroticism.     

Replication and characterisation of genetic variants in the fibrinogen gene cluster with plasma fibrinogen levels and haematological traits in the Third National Health and Nutrition Examination Survey

Previous genetic association studies of the fibrinogen gene cluster have identified associations with plasma fibrinogen levels. These studies are typically limited to plasma fibrinogen measured among European-descent populations. We sought to replicate previous well-known associations with fibrinogen variants and plasma fibrinogen. We then sought to identify and characterise novel associations with fibrinogen variants with plasma fibrinogen and several haematological traits in three racial/ethnic populations. We genotyped 25 single nucleotide polymorphisms (SNPs) in the fibrinogen gene cluster in 2,631 non-Hispanic whites, 2,108 non-Hispanic blacks, and 2,073 Mexican-Americans from the Third National Health and Nutrition Examination Survey (NHANES). We performed single SNP tests of association for plasma fibrinogen, mean platelet volume, platelet distribution width, platelet count, white blood cell count, and serum triglycerides. Five previously identified associations with plasma fibrinogen replicated in our study in non-Hispanic whites and blacks. We identified two novel associations between genetic variants and decreased plasma fibrinogen: rs2227395 (p=0.0007; non-Hispanic whites) and rs2070022 (p=0.001; Mexican-Americans). Several fibrinogen SNPs were also associated with haematological traits: rs6050 with decreased platelet distribution width in non-Hispanic whites; rs6050 and rs2066879 with decreased and increased platelet distribution width, respectively, in non-Hispanic whites;rs2227409 with increased mean platelet volume, rs2070017 with decreased platelet count, and rs6063 with increased platelet distribution width in non-Hispanic blacks; and rs4220 and rs2227395 with decreased white blood cell count, rs2227409 with increased platelet distribution width, rs2066860 and rs1800792 with increased and decreased triclyceride levels, respectively, and rs1800792 with decreased platelet counts in Mexican-Americans. We successfully replicated and identified novel associations with fibrinogen variants and plasma fibrinogen. These data confirm the importance of the fibrinogen gene cluster for plasma fibrinogen levels as well as suggest this gene cluster may have pleiotropic effects on haematological traits.     

Shared genetic influences on resting‐state functional networks of the brain

The amplitude of activation in brain resting state networks (RSNs), measured with resting‐state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome‐wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.     

Substantial SNP-based heritability estimates for working memory performance

Working memory (WM) is an important endophenotype in neuropsychiatric research and its use in genetic association studies is thought to be a promising approach to increase our understanding of psychiatric disease. As for any genetically complex trait, demonstration of sufficient heritability within the specific study context is a prerequisite for conducting genetic studies of that trait. Recently developed methods allow estimating trait heritability using sets of common genetic markers from genome-wide association study (GWAS) data in samples of unrelated individuals. Here we present single-nucleotide polymorphism (SNP)-based heritability estimates (h²_SNP) for a WM phenotype. A Caucasian sample comprising a total of N=2298 healthy and young individuals was subjected to an N-back WM task. We calculated the genetic relationship between all individuals on the basis of genome-wide SNP data and performed restricted maximum likelihood analyses for variance component estimation to derive the h²_SNP estimates. Heritability estimates for three 2-back derived WM performance measures based on all autosomal chromosomes ranged between 31 and 41%, indicating a substantial SNP-based heritability for WM traits. These results indicate that common genetic factors account for a prominent part of the phenotypic variation in WM performance. Hence, the application of GWAS on WM phenotypes is a valid method to identify the molecular underpinnings of WM.     

Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D

Affecting about 1 in 12 Americans annually, depression is a leading cause of the global disease burden. While a range of effective antidepressants are now available, failure and relapse rates remain substantial, with intolerable side effect burden the most commonly cited reason for discontinuation. Thus, understanding individual differences in susceptibility to antidepressant therapy side effects will be essential to optimize depression treatment. Here we perform genome-wide association studies (GWAS) to identify genetic variation influencing susceptibility to citalopram-induced side effects. The analysis sample consisted of 1762 depression patients, successfully genotyped for 421K single-nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR^*D) study. Outcomes included five indicators of citalopram side effects: general side effect burden, overall tolerability, sexual side effects, dizziness and vision/hearing side effects. Two SNPs met our genome-wide significance criterion (q<0.1), ensuring that, on average, only 10% of significant findings are false discoveries. In total, 12 additional SNPs demonstrated suggestive associations (q<0.5). The top finding was rs17135437, an intronic SNP within EMID2, mediating the effects of citalopram on vision/hearing side effects (P=3.27 × 10⁻⁸, q=0.026). The second genome-wide significant finding, representing a haplotype spanning ∼30 kb and eight genotyped SNPs in a gene desert on chromosome 13, was associated with general side effect burden (P=3.22 × 10⁻⁷, q=0.096). Suggestive findings were also found for SNPs at LAMA1, AOX2P, EGFLAM, FHIT and RTP2. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antidepressant medications.     

Genome-wide association studies establish that human intelligence is highly heritable and polygenic

General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan. Data from twin and family studies are consistent with a high heritability of intelligence, but this inference has been controversial. We conducted a genome-wide analysis of 3511 unrelated adults with data on 549,692 single nucleotide polymorphisms (SNPs) and detailed phenotypes on cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just SNP data we predicted ～1% of the variance of crystallized and fluid cognitive phenotypes in an independent sample (P=0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.     

How specific is second language-learning ability? A twin study exploring the contributions of first language achievement and intelligence to second language achievement

Learning a second language is crucially important in an increasingly global society, yet surprisingly little is known about why individuals differ so substantially in second language (SL) achievement. We used the twin design to assess the nature, nurture and mediators of individual differences in SL achievement. For 6263 twin pairs, we analyzed scores from age 16 UK-wide standardized tests, the General Certificate of Secondary Education (GCSE). We estimated genetic and environmental influences on the variance of SL for specific languages, the links between SL and English and the extent to which the links between SL and English are explained by intelligence. All SL measures showed substantial heritability, although heritability was nonsignificantly lower for German (36%) than the other languages (53–62%). Multivariate genetic analyses indicated that a third of genetic influence in SL is shared with intelligence, a third with English independent of intelligence and a further third is unique to SL.     

Endothelial SKCa and IKCa channels regulate brain parenchymal arteriolar diameter and cortical cerebral blood flow

Calcium-sensitive potassium (K_Ca) channels have been shown to modulate the diameter of cerebral pial arteries; however, little is known regarding their roles in controlling cerebral parenchymal arterioles (PAs). We explored the function and cellular distribution of small-conductance (SK_Ca) and intermediate-conductance (IK_Ca) K_Ca channels and large-conductance K_Ca (BK_Ca) channels in endothelial cells (ECs) and smooth muscle cells (SMCs) of PAs. Both SK_Ca and IK_Ca channels conducted the outward current in isolated PA ECs (current densities, ∼20 pA/pF and ∼28 pA/pF at +40 mV, respectively), but these currents were not detected in PA SMCs. In contrast, BK_Ca currents were prominent in PA SMCs (∼154 pA/pF), but were undetectable in PA ECs. Pressurized PAs constricted to inhibition of SK_Ca (∼16%) and IK_Ca (∼16%) channels, but were only modestly affected by inhibition of BK_Ca channels (∼5%). Blockade of SK_Ca and IK_Ca channels decreased resting cortical cerebral blood flow (CBF) by ∼15%. NS309 (6,7-dichloro-1H-indole-2,3-dione3-oxime), a SK_Ca/IK_Ca channel opener, hyperpolarized PA SMCs by ∼27 mV, maximally dilated pressurized PAs, and increased CBF by ∼40%. In conclusion, these data show that SK_Ca and IK_Ca channels in ECs profoundly modulate PA tone and CBF, whereas BK_Ca channels in SMCs only modestly influence PA diameter.     

Evaluating brain structure traits as endophenotypes using polygenicity and discoverability

Human brain structure traits have been hypothesized to be broad endophenotypes for neuropsychiatric disorders, implying that brain structure traits are comparatively “closer to the underlying biology.” Genome-wide association studies from large sample sizes allow for the comparison of common variant genetic architectures between traits to test the evidence supporting this claim. Endophenotypes, compared to neuropsychiatric disorders, are hypothesized to have less polygenicity, with greater effect size of each susceptible SNP, requiring smaller sample sizes to discover them. Here, we compare polygenicity and discoverability of brain structure traits, neuropsychiatric disorders, and other traits (91 in total) to directly test this hypothesis. We found reduced polygenicity (FDR = 0.01) and increased discoverability (FDR = 3.68 × 10^?9) of cortical brain structure traits, as compared to aggregated estimates of multiple neuropsychiatric disorders. We predict that ~8 M individuals will be required to explain the full heritability of cortical surface area by genome-wide significant SNPs, whereas sample sizes over 20 M will be required to explain the full heritability of depression. In conclusion, our findings are consistent with brain structure satisfying the higher power criterion of endophenotypes.     

The genetic background of the associations between sense of coherence and mental health,self-esteem and personality

Purpose

Sense of coherence (SOC) represents coping and can be considered an essential component of mental health. SOC correlates with mental health and personality, but the background of these associations is poorly understood. We analyzed the role of genetic factors behind the associations of SOC with mental health, self-esteem and personality using genetic twin modeling and polygenic scores (PGS).

Methods

Information on SOC (13-item Orientation of Life Questionnaire), four mental health indicators, self-esteem and personality (NEO Five Factor Inventory Questionnaire) was collected from 1295 Finnish twins at 20–27 years of age.

Results

In men and women, SOC correlated negatively with depression, alexithymia, schizotypal personality and overall mental health problems and positively with self-esteem. For personality factors, neuroticism was associated with weaker SOC and extraversion, agreeableness and conscientiousness with stronger SOC. All these psychological traits were influenced by genetic factors with heritability estimates ranging from 19 to 66%. Genetic and environmental factors explained these associations, but the genetic correlations were generally stronger. The PGS of major depressive disorder was associated with weaker, and the PGS of general risk tolerance with stronger SOC in men, whereas in women the PGS of subjective well-being was associated with stronger SOC and the PGSs of depression and neuroticism with weaker SOC.

Conclusion

Our results indicate that a substantial proportion of genetic variation in SOC is shared with mental health, self-esteem and personality indicators. This suggests that the correlations between these traits reflect a common neurobiological background rather than merely the influence of external stressors.

     

Characterization of cerebral glutamine uptake from blood in the mouse brain: implications for metabolic modeling of 13C NMR data

¹³C Nuclear Magnetic Resonance (NMR) studies of rodent and human brain using [1-¹³C]/[1,6-¹³C₂]glucose as labeled substrate have consistently found a lower enrichment (∼25% to 30%) of glutamine-C4 compared with glutamate-C4 at isotopic steady state. The source of this isotope dilution has not been established experimentally but may potentially arise either from blood/brain exchange of glutamine or from metabolism of unlabeled substrates in astrocytes, where glutamine synthesis occurs. In this study, the contribution of the former was evaluated ex vivo using ¹H-[¹³C]-NMR spectroscopy together with intravenous infusion of [U-¹³C₅]glutamine for 3, 15, 30, and 60 minutes in mice. ¹³C labeling of brain glutamine was found to be saturated at plasma glutamine levels >1.0 mmol/L. Fitting a blood–astrocyte–neuron metabolic model to the ¹³C enrichment time courses of glutamate and glutamine yielded the value of glutamine influx, V_Gln(in), 0.036±0.002 μmol/g per minute for plasma glutamine of 1.8 mmol/L. For physiologic plasma glutamine level (∼0.6 mmol/L), V_Gln(in) would be ∼0.010 μmol/g per minute, which corresponds to ∼6% of the glutamine synthesis rate and rises to ∼11% for saturating blood glutamine concentrations. Thus, glutamine influx from blood contributes at most ∼20% to the dilution of astroglial glutamine-C4 consistently seen in metabolic studies using [1-¹³C]glucose.     

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self‐reported relatedness or calculated empirically using genome‐wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self‐reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry. We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self‐reported and empirical CR methods Kinship‐based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole‐genome empirical CR were higher but remained significantly correlated (r ～0.9) with those obtained using self‐reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates. Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The chromosomal heritability patterns were correlated among traits from the same knowledge domains; among traits with significant genetic correlations; and among traits sharing biological processes, without being genetically related. The pedigree structures generated in our analyses are available online as a web‐based calculator ( www.solar-eclipse-genetics.org/HCP ).