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Feelings of well-being and happiness fluctuate over time and contexts. Ecological Momentary Assessment (EMA) studies can capture fluctuations in momentary behavior, and experiences by assessing these multiple times per day. Traditionally, EMA was performed using pen and paper. Recently, due to technological advances EMA studies can be conducted more easily with smartphones, a device ubiquitous in our society. The goal of this review was to evaluate the literature on smartphone-based EMA in well-being research in healthy subjects. The systematic review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Searching PubMed and Web of Science, we identified 53 studies using smartphone-based EMA of well-being. Studies were heterogeneous in designs, context, and measures. The average study duration was 12.8 days, with well-being assessed 2–12 times per day. Half of the studies included objective data (e.g. location). Only 47.2% reported compliance, indicating a mean of 71.6%. Well-being fluctuated daily and weekly, with higher well-being in evenings and weekends. These fluctuations disappeared when location and activity were accounted for. On average, being in nature and physical activity relates to higher well-being. Working relates to lower well-being, but workplace and company do influence well-being. The important advantages of using smartphones instead of other devices to collect EMAs are the easier data collection and flexible designs. Smartphone-based EMA reach far larger maximum sample sizes and more easily add objective data to their designs than palm-top/PDA studies. Smartphone-based EMA research is feasible to gain insight in well-being fluctuations and its determinants and offers the opportunity for parallel objective data collection. Most studies currently focus on group comparisons, while studies on individual differences in well-being patterns and fluctuations are lacking. We provide recommendations for future smartphone-based EMA research regarding measures, objective data and analyses.

We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the added value of our multivariate methods relative to univariate GWAMA. We applied the novel methods to life satisfaction, positive affect, neuroticism, and depressive symptoms, collectively referred to as the well-being spectrum ( N obs  = 2,370,390), and found 304 significant independent signals. Our multivariate approaches resulted in a 26% increase in the number of independent signals relative to the four univariate GWAMAs and in an ~57% increase in the predictive power of polygenic risk scores. Supporting transcriptome- and methylome-wide analyses (TWAS and MWAS, respectively) uncovered an additional 17 and 75 independent loci, respectively. Bioinformatic analyses, based on gene expression in brain tissues and cells, showed that genes differentially expressed in the subiculum and GABAergic interneurons are enriched in their effect on the well-being spectrum. New methods for multivariate genome-wide-association meta-analysis (GWAMA) applied to four well-being spectrum traits identifies 304 association loci, representing a 26% increase in the number of signals, as compared with four univariate analyses.

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10−7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3–82%) of the aggression–methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.

BackgroundIdentifying modifiable factors associated with well-being is of increased interest for public policy guidance. Developments in record linkage make it possible to identify what contributes to well-being from a myriad of factors. To this end, we link two large-scale data resources; the Geoscience and Health Cohort Consortium, a collection of geo-data, and the Netherlands Twin Register, which holds population-based well-being data.ObjectiveWe perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to well-being.MethodsFirst, we performed a generalized estimation equation regression (N = 11,975) to test for the effects of environmental exposures on well-being. Second, to account for multicollinearity amongst exposures, we performed principal component regression. Finally, using a genetically informative design, we examined whether environmental exposure is driven by genetic predisposition for well-being.ResultsWe identified 21 environmental factors that were associated with well-being in the domains: housing stock, income, core neighbourhood characteristics, livability, and socioeconomic status. Of these associations, socioeconomic status and safety are indicated as the most important factors to explain differences in well-being. No evidence of gene-environment correlation was found.SignificanceThese observed associations, especially neighbourhood safety, could be informative for policy makers and provide public policy guidance to improve well-being. Our results show that linking databases is a fruitful exercise to identify determinants of mental health that would remain unknown by a more unilateral approach.

The adult self report (ASR) is a well-validated instrument with multiple scales relating to adult psychopathology. Recently, an 18-item version has been introduced, the brief problem monitor (BPM) to measure Internalizing behavior (INT), Externalizing behavior (EXT), and attention problems (ATT). The present study compared the BPM and ASR and investigated how well the BPM can serve as a supplement or an alternative for the ASR for specific clinical and scientific purposes. In a large sample of adult twins (N = 9.835) from the Netherlands Twin Register (NTR), we compared the internal consistency, clinical classification concordance, means, and variances of the ASR and BPM. Using the classical twin design, we investigated the genetic covariance structure. For external validation, the associations between subjective well-being and different subscales of the ASR and BPM were compared. The internal consistency of the BPM scales (around α = 0.75) was somewhat lower than the ASR (α ~ 0.85). The BPM Externalizing scale showed the lowest internal consistency (α = 0.63). ASR and BPM scores showed good clinical classification concordance (0.61–0.80) and high correlations (r > 0.88). A small reversed sex difference in the BPM Externalizing scale appeared (women > men). Genetic (0.34–0.54) and environmental components (0.46–0.66) explained the variance to a similar extent for the ASR and BPM. The phenotypic and genetic associations with well-being were comparable. In situations where sum scores are sufficient, the BPM performs as well as the longer ASR. Depending on the situation and goal, it is worth considering the BPM as an alternative for the ASR to reduce the participant burden.

Ever since twin-family studies found that a substantial amount (± 40%) of the variation in well-being can be explained by genetic variation, several candidate genes have been proposed explaining this variation. However, these candidate gene and candidate gene-by-environment interaction studies have been surrounded by controversy regarding the validity and replication of their results. In the present study, we review the existing candidate gene literature for well-being. First, we perform a systematic literature search that results in the inclusion of 41 studies. After describing the results of the included studies, we evaluated the included candidate polymorphisms by (1) looking up the results for the studied candidate SNPs in a large well-being genome-wide association study, (2) performing association analyses in UK biobank (UKB) data for the candidate variable number tandem repeats (VNTR) and the APOE ε4 allele, and (3) studying possible candidate interactions with positive and negative environmental moderators using UKB data. We find no support for any of the candidate genes or candidate gene-environment interactions for well-being, with the exception of two SNPs that were chosen based on genome-wide evidence. While the generalizability of our findings is limited by our phenotype and environment definitions, we strongly advise well-being researchers to abandon the candidate gene approach in the field of well-being and move toward genome-wide approaches.

The tendency to conceive spontaneous dizygotic (DZ) twins is a complex trait with important contributions from both environmental factors and genetic disposition. In earlier work, we identified the first two genes as maternal susceptibility loci for DZ twinning. The aim of this study was to identify genetic variants influencing multiple births and to genetically correlate the findings across a broad range of traits. We performed a genome-wide association study (GWAS) in 8962 participants with Caucasian ancestry from UK Biobank who reported being part of a multiple birth, and 409,591 singleton controls. We replicated the association between FSHB, SMAD3 and twinning in the gene-based (but not SNP-based) test, which had been established in previous genome-wide association analyses in mothers with dizygotic twin offspring. Additionally, we report a novel genetic variant associated with multiple birth, rs428022 at 15q23 (p = 2.84 × 10−8) close to two genes: PIAS1 and SKOR1. Finally, we identified meaningful genetic correlations between being part of a multiple birth and other phenotypes (anthropometric traits, health-related traits, and fertility-related measures). The outcomes of this study provide important new insights into the genetic aetiology of multiple births and fertility, and open up novel directions for fertility and reproduction research.

Daniel Benjamin, Meike Bartels, Philipp Koellinger and colleagues report a genome-wide association meta-analysis of subjective well-being, depressive symptoms and neuroticism. The study leverages a large sample size together with genetic correlations between the phenotypes to identify, with high confidence, loci associated with each phenotype. Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being ( n = 298,420), depressive symptoms ( n = 161,460), and neuroticism ( n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (| ρ ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.

Several occurrences of the word ‘schizophrenia’ have been re-worded as ‘liability to schizophrenia’ or ‘schizophrenia risk’, including in the title, which should have been “GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability,” as well as in Supplementary Figures 1–10 and Supplementary Tables 7–10, to more accurately reflect the findings of the work.

Wellbeing (WB) is a major topic of research across several scientific disciplines, partly driven by its strong association with psychological and mental health. Twin-family studies have found that both genotype and environment play an important role in explaining the variance in WB. Epigenetic mechanisms, such as DNA methylation, regulate gene expression, and may mediate genetic and environmental effects on WB. Here, for the first time, we apply an epigenome-wide association study (EWAS) approach to identify differentially methylated sites associated with individual differences in WB. Subjects were part of the longitudinal survey studies of the Netherlands Twin Register (NTR) and participated in the NTR biobank project between 2002 and 2011. WB was assessed by a short inventory that measures satisfaction with life (SAT). DNA methylation was measured in whole blood by the Illumina Infinium HumanMethylation450 BeadChip (HM450k array) and the association between WB and DNA methylation level was tested at 411,169 autosomal sites. Two sites (cg10845147, p = 1.51 * 10−8 and cg01940273, p = 2.34 * 10−8) reached genome-wide significance following Bonferonni correction. Four more sites (cg03329539, p = 2.76* 10−7; cg09716613, p = 3.23 * 10−7; cg04387347, p = 3.95 * 10−7; and cg02290168, p = 5.23 * 10−7) were considered to be genome-wide significant when applying the widely used criterion of a FDR q value < 0.05. Gene ontology (GO) analysis highlighted enrichment of several central nervous system categories among higher-ranking methylation sites. Overall, these results provide a first insight into the epigenetic mechanisms associated with WB and lay the foundations for future work aiming to unravel the biological mechanisms underlying a complex trait like WB.