A Multidisciplinary Perspective on Person-Environment Fit: Relevance, Measurement, and Future Directions

Environments shape people, and at the same time, people are attracted to environments that fit their characteristics because fit facilitates the achievement of people’s desired life outcomes, such as relationship satisfaction, work success, and well-being. In this article, we outline how persons and environments can fit, the relevance of fit and misfit for different life outcomes, and the benefits and pitfalls of different (mis)fit measures. We propose three directions for future research: (a) the use of both subjective and objective (mis)fit measures; (b) the consideration of complex dynamics between person and environment characteristics via pathways through multiple biological, experiential, behavioral, and social layers across the life span; and (c) the integration of insights from different disciplines, including psychology, sociology, neuroscience, and genetics, to move the field forward

Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders

GLRB allelic variation associated with agoraphobic cognitions, increased startle response and fear network activation : a potential neurogenetic pathway to panic disorder

The molecular genetics of panic disorder (PD) with and without agoraphobia (AG) are still largely unknown and progress is hampered by small sample sizes. We therefore performed a genome-wide association study with a dimensional, PD/AG - related anxiety phenotype based on the Agoraphobia Cognition Questionnaire (ACQ) in a sample of 1,370 healthy German volunteers of the CRC TRR58 MEGA study wave 1. A genome-wide significant association was found between ACQ and single non-coding nucleotide variants of the GLRB gene (rs78726293, p=3.3x10-8; rs191260602, p=3.9x10-8). We followed up on this finding in a larger dimensional ACQ sample (N=2,547) and in independent samples with a dichotomous AG phenotype based on the Symptoms Checklist (SCL-90; N=3,845) and a case control sample with the categorical phenotype PD/AG (Ncombined =1,012) obtaining highly significant p-values also for GLRB single nucleotide variants rs17035816 (p=3.8x10-4) and rs7688285 (p=7.6x10-5). GLRB gene expression was found to be modulated by rs7688285 in brain tissue as well as cell culture. Analyses of intermediate PD/AG phenotypes demonstrated increased startle reflex and increased fear network as well as general sensory activation by GLRB risk gene variants rs78726293, rs191260602, rs17035816 and rs7688285. Partial Glrb knockout-mice demonstrated an agoraphobic phenotype. In conjunction withthe clinical observation that rare coding GLRB gene mutations are associated with the neurological disorder hyperekplexia characterized by a generalized startle reaction and agoraphobic behavior, our data provide evidence that non-coding, though functional GLRB gene polymorphisms may predispose to PD by increasing startle response and agoraphobic cognitions.PostprintPeer reviewe

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders

Genome-wide association study of borderline personality disorder reveals genetic overlap with the bipolar disorder, schizophrenia and major depression

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of Bipolar Disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was: (i) to detect genes and gene-sets involved in BOR; and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, Major Depression (MDD) and Schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests,and gene-set-analyses were performed in 998 BOR patients and 1,545 controls. LD score regression was used to detect genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Genebased analysis yielded two significant genes: DPYD (p=4.42x10-7) and PKP4 (p=8.67x10-7); and gene-set-analysis yielded a significant finding for exocytosis (GO:0006887, pFDR=0.019). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [p=2.99x10-3]), SCZ (rg=0.34 [p=4.37x10-5]), and MDD (rg=0.57 [p=1.04x10-3]). Our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies

Common variants at 2q11.2, 8q21.3, and 11q13.2 are associated with major mood disorders

Bipolar disorder (BPD) and major depressive disorder (MDD) are primary major mood disorders. Recent studies suggest that they share certain psychopathological features and common risk genes, but unraveling the full genetic architecture underlying the risk of major mood disorders remains an important scientific task. The public genome-wide association study (GWAS) data sets offer the opportunity to examine this topic by utilizing large amounts of combined genetic data, which should ultimately allow a better understanding of the onset and development of these illnesses. Genome-wide meta-analysis was performed by combining two GWAS data sets on BPD and MDD (19,637 cases and 18,083 controls), followed by replication analyses for the loci of interest in independent 12,364 cases and 76,633 controls from additional samples that were not included in the two GWAS data sets. The single-nucleotide polymorphism (SNP) rs10791889 at 11q13.2 was significant in both discovery and replication samples. When combining all samples, this SNP and multiple other SNPs at 2q11.2 (rs717454), 8q21.3 (rs10103191), and 11q13.2 (rs2167457) exhibited genome-wide significant association with major mood disorders. The SNPs in 2q11.2 and 8q21.3 were novel risk SNPs that were not previously reported, and SNPs at 11q13.2 were in high LD with potential BPD risk SNPs implicated in a previous GWAS. The genome-wide significant loci at 2q11.2 and 11q13.2 exhibited strong effects on the mRNA expression of certain nearby genes in cerebellum. In conclusion, we have identified several novel loci associated with major mood disorders, adding further support for shared genetic risk between BPD and MDD. Our study highlights the necessity and importance of mining public data sets to explore risk genes for complex diseases such as mood disorders

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Response to Therapeutic Sleep Deprivation: A Naturalistic Study of Clinical and Genetic Factors and Post-treatment Depressive Symptom Trajectory

Research has shown that therapeutic sleep deprivation (SD) has rapid antidepressant effects in the majority of depressed patients. Investigation of factors preceding and accompanying these effects may facilitate the identification of the underlying biological mechanisms. This exploratory study aimed to examine clinical and genetic factors predicting response to SD and determine the impact of SD on illness course. Mood during SD was also assessed via visual analogue scale. Depressed inpatients (n = 78) and healthy controls (n = 15) underwent ~36 h of SD. Response to SD was defined as a score of ≤ 2 on the Clinical Global Impression Scale for Global Improvement. Depressive symptom trajectories were evaluated for up to a month using self/expert ratings. Impact of genetic burden was calculated using polygenic risk scores for major depressive disorder. In total, 72% of patients responded to SD. Responders and non-responders did not differ in baseline self/expert depression symptom ratings, but mood differed. Response was associated with lower age (p = 0.007) and later age at life-time disease onset (p = 0.003). Higher genetic burden of depression was observed in non-responders than healthy controls. Up to a month post SD, depressive symptoms decreased in both patients groups, but more in responders, in whom effects were sustained. The present findings suggest that re-examining SD with a greater focus on biological mechanisms will lead to better understanding of mechanisms of depression