Genome-Wide Association Study of Loneliness Demonstrates a Role for Common Variation

Complete Loss of Natural Teeth and Loneliness: A Fixed-Effect Analysis

Psychosocial properties of oral health have been reported. The present study aimed to investigate the causal effect of complete loss of natural teeth on loneliness by using fixed-effects analysis to control for confounding factors, including unmeasured time-invariant factors. Data from older adults participating in at least 2 consecutive waves of the English Longitudinal Study of Ageing in waves 3 (2006/2007), 5 (2010/2011), and 7 (2014/2015) were analyzed (N = 18,682 observations from 7,298 individuals). The association between complete loss of natural teeth and loneliness score (ranging from 3 to 9) was examined using fixed-effect linear regression analysis adjusting for time-varying confounders, including sociodemographic and health characteristics. The prevalence of complete tooth loss was 12.7%, 12.8%, and 10.6% in waves 3, 5, and 7, respectively. Individuals who transitioned to complete tooth loss during any 2 consecutive waves had an increase in loneliness score by 0.27 (95% confidence interval [CI] 0.03, 0.52), which was greater than those who maintained natural teeth (-0.03; 95% CI -0.05, -0.01). Fixed-effects analysis adjusting for time-varying confounders revealed a significant association between complete loss of natural teeth and an increase in loneliness score by 0.31 (95% CI 0.17, 0.46). Complete loss of natural teeth among older adults in England was associated with loneliness, even after accounting for measured time-varying and (un)measured time-invariant confounders. Retaining natural teeth may reduce the risk of loneliness.

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning

OBJECTIVE

Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.

METHODS

Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556-1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.

RESULTS

All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.

CONCLUSIONS

These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.

Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank

Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum. We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders. We included 33 k-380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3-5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01-0.02% variance explained to the corresponding additive model. PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.

A Genetically Informed Study of the Association Between Perceived Stress and Loneliness

Although research shows a strong positive association between perceived stress and loneliness, the genetic and environmental etiology underlying their association remains unknown. People with a genetic predisposition to perceived stress, for example, may be more prone to feeling lonely and vice versa. Conversely, unique factors in people's lives may explain differences in perceived stress levels that, in turn, affect feelings of loneliness. We tested whether genetic factors, environmental factors, or both account for the association between perceived stress and loneliness. Participants were 3,066 individual twins (nFemale = 2,154, 70.3%) from the Washington State Twin Registry who completed a survey during April-May, 2020. Structural equation modeling was used to analyze the item-level perceived stress and loneliness measures. The correlation between latent perceived stress and latent loneliness was .68. Genetic and nonshared environmental variance components underlying perceived stress accounted for 3.71% and 23.26% of the total variance in loneliness, respectively. The genetic correlation between loneliness and perceived stress was .45 and did not differ significantly between men and women. The nonshared environmental correlation was .54 and also did not differ between men and women. Findings suggest that holding constant the strong genetic association between perceived stress and loneliness, unique life experiences underlying people's perceived stress account for individual differences in loneliness.

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

Neurogenetics and Epigenetics of Loneliness

Loneliness, an established risk factor for both, mental and physical morbidity, is a mounting public health concern. However, the neurobiological mechanisms underlying loneliness-related morbidity are not yet well defined. Here we examined the role of genes and associated DNA risk polymorphic variants that are implicated in loneliness via genetic and epigenetic mechanisms and may thus point to specific therapeutic targets. Searches were conducted on PubMed, Medline, and EMBASE databases using specific Medical Subject Headings terms such as loneliness and genes, neuro- and epigenetics, addiction, affective disorders, alcohol, anti-reward, anxiety, depression, dopamine, cancer, cardiovascular, cognitive, hypodopaminergia, medical, motivation, (neuro)psychopathology, social isolation, and reward deficiency. The narrative literature review yielded recursive collections of scientific and clinical evidence, which were subsequently condensed and summarized in the following key areas: (1) Genetic Antecedents: Exploration of multiple genes mediating reward, stress, immunity and other important vital functions; (2) Genes and Mental Health: Examination of genes linked to personality traits and mental illnesses providing insights into the intricate network of interaction converging on the experience of loneliness; (3) Epigenetic Effects: Inquiry into instances of loneliness and social isolation that are driven by epigenetic methylations associated with negative childhood experiences; and (4) Neural Correlates: Analysis of loneliness-related affective states and cognitions with a focus on hypodopaminergic reward deficiency arising in the context of early life stress, eg, maternal separation, underscoring the importance of parental support early in life. Identification of the individual contributions by various (epi)genetic factors presents opportunities for the creation of innovative preventive, diagnostic, and therapeutic approaches for individuals who cope with persistent feelings of loneliness. The clinical facets and therapeutic prospects associated with the current understanding of loneliness, are discussed emphasizing the relevance of genes and DNA risk polymorphic variants in the context of loneliness-related morbidity.

Loneliness during the Covid-19 pandemic in Germany: Impact of social factors and polygenic risk scores on interpersonal differences in loneliness and mental health

OBJECTIVES

The outbreak of Covid-19 negatively affected mental health and increased loneliness. The subjective feeling of loneliness is influenced by genetic and social factors and has a negative impact on mental health.

METHODS

From March 2020 to June 2021 loneliness was investigated in N = 517 individuals using monthly acquired questionnaire data and Latent Growth Curve Analysis. Associations of social factors and polygenic risk scores (PRSs, n = 361) with class membership were investigated.

RESULTS

Three classes ("average", 40%; "not lonely", 38%; "elevated loneliness", 22%) were identified, that differ significantly regarding loneliness, mental dysfunction, and response to the lockdown phases. Individuals with a high PRS for neuroticism are more likely to belong to the "elevated loneliness" class, living with another person is a protective factor.

CONCLUSION

As the "elevated loneliness" class was at the highest risk of mental dysfunction, our findings underscore the importance of identifying those individuals to implement counteractive measures.

Frailty trajectory predicts subsequent cognitive decline: A 26-year population-based longitudinal cohort study

Frailty refers to a decline in the physiological functioning of one or more organ systems. It remained unclear whether variations in the trajectory of frailty over time were associated with subsequent cognitive change. The aim of the current study was to investigate the association between frailty trajectories and subsequent cognitive decline based on the Health and Retirement Study (HRS). A total of 15,454 participants were included. The frailty trajectory was assessed using the Paulson-Lichtenberg Frailty Index, while the cognitive function was evaluated using the Langa-Weir Classification. Results showed that severe frailty was significantly associated with the subsequent decline in cognitive function (β [95% CI] = -0.21 [-0.40, -0.03], p = 0.03). In the five identified frailty trajectories, participants with mild frailty (inverted U-shaped, β [95% CI] = -0.22 [-0.43, -0.02], p = 0.04), mild frailty (U-shaped, β [95% CI] = -0.22 [-0.39, -0.06], p = 0.01), and frailty (β [95% CI] = -0.34 [-0.62, -0.07], p = 0.01) were all significantly associated with the subsequent cognition decline in the elderly. The current study suggested that monitoring and addressing frailty trajectories in older adults may be a critical approach in preventing or mitigating cognitive decline, which had significant implications for healthcare.

Identifying novel proteins underlying loneliness by integrating GWAS summary data with human brain proteomes

Enduring loneliness is associated with mental disorders and physical diseases. Although genome-wide association studies (GWAS) have identified risk loci associated with loneliness, how these loci confer the risk remains largely unknown. In the current study, we aimed to investigate key proteins underlying loneliness in the brain by integrating human brain proteomes and transcriptomes with loneliness GWAS to perform a discovery proteome-wide association study (PWAS), followed by a confirmatory PWAS, transcriptome-wide association analysis (TWAS), Mendelian randomization (MR), Steigering filtering analysis and Bayesian colocalization analysis. Moreover, given the fact that loneliness is associated with mental disorders, we explored the shared genetic architecture between loneliness and mental disorders. Totally, we identified 18 genes to be associated with loneliness via their cis-regulated brain protein abundance. Eleven of the 18 genes (61.1%) were replicated in the confirmatory PWAS, and mRNA levels of 4 genes were further validated to be associated with loneliness.MR and genetic colocalization analysis further confirmed that the increased protein abundance of ALDH2 and ICA1L was protective against loneliness, while the increased protein abundance of GPX1 was a risk for developing loneliness. Furthermore, we found genetic correlations, bidirectional causal associations and overlapping phenotype-associated protein profiles between loneliness and mental disorders including major depression and schizophrenia. In summary, our findings provided clues about the brain-related molecular basis underlying loneliness, which warrants further investigation.

Loneliness, Depression, and Genetics in the Elderly: Prognostic Factors of a Worse Health Condition?

Loneliness is considered a prognostic factor for poorer health status in the elderly. It is proposed to analyze the role of loneliness in health status in terms of various factors. A total of 1747 individuals from the pilot survey of the Aging in Spain Longitudinal Study (ELES-PS) were reviewed. ELES is a cross-sectional study for collecting health variables, food habits, socioeconomic data, and cognitive and functional capacities, which was carried out on a Spanish representative sample of noninstitutionalized persons of 50 years of age or older. Moreover, since telomere shortening is associated with cellular senescence, 35 telomere-related SNPs and cognitive impairments were analyzed. The results characterize the "solos" as males of 50-60 years, who were overweight and had lower levels of hemoglobin and neutrophils. There is also an association between five SNPs related to telomere length and BDNF. A group of people with loneliness and depression was identified with poorer health and cognitive status, poorer perception of their quality of life, poorer quality of sleep, and lower physical activity. Therefore, it follows that telomeres and BDNF play a role as intermediaries between loneliness and depression and their relationship with a worse state of health.

The oxytocin signalling gene pathway contributes to the association between loneliness and cardiometabolic health

Increasing evidence has shown adverse effects of loneliness on cardiometabolic health. The neuromodulator and hormone oxytocin has traditionally been linked with social cognition and behaviour. However, recent implications of the oxytocin system in energy metabolism and the overrepresentation of metabolic issues in psychiatric illness suggests that oxytocin may represent a mechanism bridging mental and somatic traits. To clarify the role of the oxytocin signalling system in the link between cardiometabolic risk factors and loneliness, we calculated the contribution of single nucleotide polymorphisms (SNPs) in the oxytocin signalling pathway gene-set (154 genes) to the polygenic architecture of loneliness and body mass index (BMI). We investigated the associations of these oxytocin signalling pathway polygenic scores with body composition measured using body magnetic resonance imaging (MRI), bone mineral density (BMD), haematological markers, and blood pressure in a sample of just under half a million adults from the UK Biobank (BMD subsample n = 274,457; body MRI subsample n = 9796). Our analysis revealed significant associations of the oxytocin signalling pathway polygenic score for BMI with abdominal subcutaneous fat tissue, HDL cholesterol, lipoprotein(a), triglycerides, and BMD. We also found an association between the oxytocin signalling pathway polygenic score for loneliness and apolipoprotein A1, the major protein component of HDL. Altogether, these results provide additional evidence for the oxytocin signalling pathway's role in energy metabolism, lipid homoeostasis, and bone density, and support oxytocin's complex pleiotropic effects.

What next for eating disorder genetics? Replacing myths with facts to sharpen our understanding

Substantial progress has been made in the understanding of anorexia nervosa (AN) and eating disorder (ED) genetics through the efforts of large-scale collaborative consortia, yielding the first genome-wide significant loci, AN-associated genes, and insights into metabo-psychiatric underpinnings of the disorders. However, the translatability, generalizability, and reach of these insights are hampered by an overly narrow focus in our research. In particular, stereotypes, myths, assumptions and misconceptions have resulted in incomplete or incorrect understandings of ED presentations and trajectories, and exclusion of certain patient groups from our studies. In this review, we aim to counteract these historical imbalances. Taking as our starting point the Academy for Eating Disorders (AED) Truth #5 "Eating disorders affect people of all genders, ages, races, ethnicities, body shapes and weights, sexual orientations, and socioeconomic statuses", we discuss what we do and do not know about the genetic underpinnings of EDs among people in each of these groups, and suggest strategies to design more inclusive studies. In the second half of our review, we outline broad strategic goals whereby ED researchers can expand the diversity, insights, and clinical translatability of their studies.

Single nucleus multi-omics identifies human cortical cell regulatory genome diversity

Single-cell technologies measure unique cellular signatures but are typically limited to a single modality. Computational approaches allow the fusion of diverse single-cell data types, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells, we devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq) and applied it to postmortem human frontal cortex tissue. We developed a cross-validation approach using multi-modal information to validate fine-grained cell types and assessed the effectiveness of computational data fusion methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility, and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling the prediction of cell types that are associated with diseases.

Lacking Social Support is Associated With Structural Divergences in Hippocampus-Default Network Co-Variation Patterns

Elaborate social interaction is a pivotal asset of the human species. The complexity of people’s social lives may constitute the dominating factor in the vibrancy of many individuals’ environment. The neural substrates linked to social cognition thus appear especially susceptible when people endure periods of social isolation: here, we zoom in on the systematic inter-relationships between two such neural substrates, the allocortical hippocampus (HC) and the neocortical default network (DN). Previous human social neuroscience studies have focused on the DN, while HC subfields have been studied in most detail in rodents and monkeys. To bring into contact these two separate research streams, we directly quantified how DN subregions are coherently co-expressed with specific HC subfields in the context of social isolation. A two-pronged decomposition of structural brain scans from ∼40 000 UK Biobank participants linked lack of social support to mostly lateral subregions in the DN patterns. This lateral DN association co-occurred with HC patterns that implicated especially subiculum, presubiculum, CA2, CA3 and dentate gyrus. Overall, the subregion divergences within spatially overlapping signatures of HC–DN co-variation followed a clear segregation into the left and right brain hemispheres. Separable regimes of structural HC–DN co-variation also showed distinct associations with the genetic predisposition for lacking social support at the population level.

Polygenic contribution to the relationship of loneliness and social isolation with schizophrenia

Previous research suggests an association of loneliness and social isolation (LNL-ISO) with schizophrenia. Here, we demonstrate a LNL-ISO polygenic score contribution to schizophrenia risk in an independent case-control sample (N = 3,488). We then subset schizophrenia predisposing variation based on its effect on LNL-ISO. We find that genetic variation with concordant effects in both phenotypes shows significant SNP-based heritability enrichment, higher polygenic contribution in females, and positive covariance with mental disorders such as depression, anxiety, attention-deficit hyperactivity disorder, alcohol dependence, and autism. Conversely, genetic variation with discordant effects only contributes to schizophrenia risk in males and is negatively correlated with those disorders. Mendelian randomization analyses demonstrate a plausible bi-directional causal relationship between LNL-ISO and schizophrenia, with a greater effect of LNL-ISO liability on schizophrenia than vice versa. These results illustrate the genetic footprint of LNL-ISO on schizophrenia.

THE INVESTIGATION OF THE PSYCHOLOGICAL BURDEN OF PATIENTS AFTER HOSPITALIZATION FOR COVID 19

OBJECTIVE

The aim: The current Cross-Sectional study investigated the psychosocial effects on recovered Covid 19 patients in a General Hospital in Greece. It was investigated the impact of Covid 19 on levels of social support, loneliness, resilience & PTSD. Furthermore, the correlation between all the above factors was studied.

PATIENTS AND METHODS

Materials and methods: 107 adult patients participated. The questionnaire was fulfilled after signature of consensus form. This happened after their discharge from the hospital, without exclusion of infected on previous time. The questionnaire included 5 particular sections: a) Socio-demographic characteristics, b) social support scale, c) IES Covid 19 scale, d) UCLA scale e) CD-Risc scale. In terms of statistical analysis, the comparison between two groups of quantitative variables was conducted through Student's t-test. Related to examination of relationship between two quantitative variables was used Pearson's correlation coefficient (r). The Statistical analysis package used was SPSS 22.

RESULTS

Results: The 55,1% of sample were women, married (57,9 %) and (39,3%) university graduates. Moreover, the rate of overweight was significant (39,3%). Related to psychosocial factors, observed high level of resilience (70,6), moderate level of loneliness (39,1) and 57,9% of participants showed moderate social support. At last, PTSD level as a result of Covid 19 was moderate (33,5). A strong correlation was observed between higher mental resilience and lower feelings of loneliness.

CONCLUSION

Conclusions: The levels of determining factors of negative psychological effects, reveal the need for a preparation of political improvement policies in relation to mental health of rehabilitated persons, as well as the promotion of actions that would contribute to the development of a more effective supportive framework.

The P-factor and its genomic and neural equivalents: an integrated perspective

Different psychiatric disorders and symptoms are highly correlated in the general population. A general psychopathology factor (or "P-factor") has been proposed to efficiently describe this covariance of psychopathology. Recently, genetic and neuroimaging studies also derived general dimensions that reflect densely correlated genomic and neural effects on behaviour and psychopathology. While these three types of general dimensions show striking parallels, it is unknown how they are conceptually related. Here, we provide an overview of these three general dimensions, and suggest a unified interpretation of their nature and underlying mechanisms. We propose that the general dimensions reflect, in part, a combination of heritable 'environmental' factors, driven by a dense web of gene-environment correlations. This perspective calls for an update of the traditional endophenotype framework, and encourages methodological innovations to improve models of gene-brain-environment relationships in all their complexity. We propose concrete approaches, which by taking advantage of the richness of current large databases will help to better disentangle the complex nature of causal factors underlying psychopathology.

Loneliness is linked to specific subregional alterations in hippocampus-default network covariation

Social interaction complexity makes humans unique. But in times of social deprivation, this strength risks exposure of important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically covary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By codecomposition using structural brain scans of ∼40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex patterns coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN covariation had distinct associations with the genetic predisposition for loneliness at the population level.

NEW & NOTEWORTHY The hippocampus and default network have been implicated in rich social interaction. Yet, these allocortical and neocortical neural systems have been interrogated in mostly separate literatures. Here, we conjointly investigate the hippocampus and default network at a subregion level, by capitalizing structural brain scans from ∼40,000 participants. We thus reveal unique insights on the nature of the “lonely brain” by estimating the regimes of covariation between the hippocampus and default network at population scale.

Loneliness: An Immunometabolic Syndrome

Loneliness has been defined as an agonizing encounter, experienced when the need for human intimacy is not met adequately, or when a person’s social network does not match their preference, either in number or attributes. This definition helps us realize that the cause of loneliness is not merely being alone, but rather not being in the company we desire. With loneliness being introduced as a measurable, distinct psychological experience, it has been found to be associated with poor health behaviors, heightened stress response, and inadequate physiological repairing activity. With these three major pathways of pathogenesis, loneliness can do much harm; as it impacts both immune and metabolic regulation, altering the levels of inflammatory cytokines, growth factors, acute-phase reactants, chemokines, immunoglobulins, antibody response against viruses and vaccines, and immune cell activity; and affecting stress circuitry, glycemic control, lipid metabolism, body composition, metabolic syndrome, cardiovascular function, cognitive function and mental health, respectively. Taken together, there are too many immunologic and metabolic manifestations associated with the construct of loneliness, and with previous literature showcasing loneliness as a distinct psychological experience and a health determinant, we propose that loneliness, in and of itself, is not just a psychosocial phenomenon. It is also an all-encompassing complex of systemic alterations that occur with it, expanding it into a syndrome of events, linked through a shared network of immunometabolic pathology. This review aims to portray a detailed picture of loneliness as an “immunometabolic syndrome”, with its multifaceted pathology.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Genome-wide association study of suicidal behaviour severity in mood disorders

OBJECTIVE

Suicide is a major public health problem and it has a prominent genetic component. We performed a genome-wide association study (GWAS) of suicidal behaviour severity.

METHODS

Suicide behaviour severity was assessed within the Schedules for Clinical Assessment in Neuropsychiatry in our mood disorder sample (n = 3506) for the GWAS. We also performed polygenic risk score analyses to explore genetic sharing between suicidal behaviour severity and a number of phenotypes, including bipolar disorder, major depressive disorder, alcoholism, post-traumatic stress disorder, impulsivity, insomnia, educational attainment, loneliness, maltreatment, and amygdala volume.

RESULTS

We did not detect genome-wide significant findings at the single-marker or gene level. We report a number of suggestive single-marker and gene-based findings. Our polygenic risk score analyses did not yield significant findings with these phenotypes.

CONCLUSIONS

Larger sample sizes are required to detect moderate effects.

Genetic underpinnings of sociability in the general population

Levels of sociability are continuously distributed in the general population, and decreased sociability represents an early manifestation of several brain disorders. Here, we investigated the genetic underpinnings of sociability in the population. We performed a genome-wide association study (GWAS) of a sociability score based on four social functioning-related self-report questions from 342,461 adults in the UK Biobank. Subsequently we performed gene-wide and functional follow-up analyses. Robustness analyses were performed in the form of GWAS split-half validation analyses, as well as analyses excluding neuropsychiatric cases. Using genetic correlation analyses as well as polygenic risk score analyses we investigated genetic links of our sociability score to brain disorders and social behavior outcomes. Individuals with autism spectrum disorders, bipolar disorder, depression, and schizophrenia had a lower sociability score. The score was significantly heritable (SNP h2 of 6%). We identified 18 independent loci and 56 gene-wide significant genes, including genes like ARNTL, DRD2, and ELAVL2. Many associated variants are thought to have deleterious effects on gene products and our results were robust. The sociability score showed negative genetic correlations with autism spectrum, disorders, depression, schizophrenia, and two sociability-related traits-loneliness and social anxiety-but not with bipolar disorder or Alzheimer's disease. Polygenic risk scores of our sociability GWAS were associated with social behavior outcomes within individuals with bipolar disorder and with major depressive disorder. Variation in population sociability scores has a genetic component, which is relevant to several psychiatric disorders. Our findings provide clues towards biological pathways underlying sociability.

Identification of pleiotropy at the gene level between psychiatric disorders and related traits

Major mental disorders are highly prevalent and make a substantial contribution to the global disease burden. It is known that mental disorders share clinical characteristics, and genome-wide association studies (GWASs) have recently provided evidence for shared genetic factors as well. Genetic overlaps are usually identified at the single-marker level. Here, we aimed to identify genetic overlaps at the gene level between 7 mental disorders (schizophrenia, autism spectrum disorder, major depressive disorder, anorexia nervosa, ADHD, bipolar disorder and anxiety), 8 brain morphometric traits, 2 cognitive traits (educational attainment and general cognitive function) and 9 personality traits (subjective well-being, depressive symptoms, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness, children's aggressive behaviour, loneliness) based on publicly available GWASs. We performed systematic conditional regression analyses to identify independent signals and select loci associated with more than one trait. We identified 48 genes containing independent markers associated with several traits (pleiotropy at the gene level). We also report 9 genes with different markers that show independent associations with single traits (allelic heterogeneity). This study demonstrates that mental disorders and related traits do show pleiotropy at the gene level as well as the single-marker level. The identification of these genes might be important for prioritizing further deep genotyping, functional studies, or drug targeting.

Genetic underpinnings of affective temperaments: a pilot GWAS investigation identifies a new genome-wide significant SNP for anxious temperament in ADGRB3 gene

Although recently a large-sample GWASs identified significant loci in the background of depression, the heterogeneity of the depressive phenotype and the lack of accurate phenotyping hinders applicability of findings. We carried out a pilot GWAS with in-depth phenotyping of affective temperaments, considered as subclinical manifestations and high-risk states for affective disorders, in a general population sample of European origin. Affective temperaments were measured by TEMPS-A. SNP-level association was assessed by linear regression models, assuming an additive genetic effect, using PLINK1.9. Gender, age, the first ten principal components (PCs) and the other four temperaments were included in the regression models as covariates. SNP-level relevances (p-values) were aggregated to gene level using the PEGASUS method¹. In SNP-based tests, a Bonferroni-corrected significance threshold of p ≤ 5.0 × 10^-8 and a suggestive significance threshold of p ≤ 1.0 × 10^-5, whereas in gene-based tests a Bonferroni-corrected significance of 2.0 × 10^-6 and a suggestive significance of p ≤ 4.0 × 10^-4 was established. To explore known functional effects of the most significant SNPs, FUMA v1.3.5 was used. We identified 1 significant and 21 suggestively significant SNPs in ADGRB3, expressed in the brain, for anxious temperament. Several other brain-relevant SNPs and genes emerged at suggestive significance for the other temperaments. Functional analyses reflecting effect on gene expression and participation in chromatin interactions also pointed to several genes expressed in the brain with potentially relevant phenotypes regulated by our top SNPs. Our findings need to be tested in larger GWA studies and candidate gene analyses in well-phenotyped samples in relation to affective disorders and related phenotypes.

Causal influences of neuroticism on mental health and cardiovascular disease

We investigated the relationship between neuroticism and 16 mental and 18 physical traits using summary results of genome-wide association studies for these traits. LD score regression was used to investigate genetic correlations between neuroticism and the 34 health outcomes. Mendelian randomization was performed to investigate mutual causal relationships between neuroticism and the 34 health outcomes. Neuroticism genetically correlates with a majority of health-related traits and confers causal effects on 12 mental traits (major depressive disorder (MDD), insomnia, subjective well-being (SWB, negatively), schizophrenia, attention-deficit/hyperactivity disorder, alcohol dependence, loneliness, anorexia nervosa, anxiety disorder, bipolar disorder, obsessive-compulsive disorder, and psychiatric disorders) and two physical diseases (cardiovascular disease and hypertensive disease). Conversely, MDD, SWB, and insomnia have a causal effect on neuroticism. We highlighted key genes contributing to the causal associations between neuroticism and MDD, including RBFOX1, RERE, SOX5, and TCF4, and those contributing to the causal associations between neuroticism and cardiovascular diseases, including MAD1L1, ARNTL, RERE, and SOX6. The present study indicates that genetic variation mediates the causal influences of neuroticism on mental health and cardiovascular diseases.

Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex

Viral genetic tools that target specific brain cell types could transform basic neuroscience and targeted gene therapy. Here, we use comparative open chromatin analysis to identify thousands of human-neocortical-subclass-specific putative enhancers from across the genome to control gene expression in adeno-associated virus (AAV) vectors. The cellular specificity of reporter expression from enhancer-AAVs is established by molecular profiling after systemic AAV delivery in mouse. Over 30% of enhancer-AAVs produce specific expression in the targeted subclass, including both excitatory and inhibitory subclasses. We present a collection of Parvalbumin (PVALB) enhancer-AAVs that show highly enriched expression not only in cortical PVALB cells but also in some subcortical PVALB populations. Five vectors maintain PVALB-enriched expression in primate neocortex. These results demonstrate how genome-wide open chromatin data mining and cross-species AAV validation can be used to create the next generation of non-species-restricted viral genetic tools.

Genetics of OCD and Related Disorders; Searching for Shared Factors

Obsessive compulsive disorder (OCD) and several other obsessive-compulsive related disorders (OCRDs) including hoarding disorder, body dysmorphic disorder (BDD), skin picking disorder, trichotillomania and the newly arising public health conditions of online gaming and gambling disorders, under the umbrella of Problematic Usage of the Internet (PUI), not only share some common phenotypes, but there is evidence to suggest share some genetic risk factors. The simple fact that these disorders segregate within families points to this notion. However, the current data are still scarce. This chapter focuses on identifying the shared genetic factors. To address this question, a systematic review of the literature investigating genetic findings in OCD and OCRDs including PUI was conducted, with a focus on their genetic similarities. Greater knowledge of the specific genetic risks shared among OCRDs would be expected to open new avenues in the understanding of the biological mechanisms causing the development of these phenotypes, as well as provide opportunities to develop new animal and cellular models testing new therapy avenues.

Oxytocin Pathway Gene (CD38, OXTR) Variants Are Not Related to Psychosocial Characteristics Defined by Strengths and Difficulties Questionnaire in Adolescents: A Field School-Based Study

Background: CD38 is a transmembrane glycoprotein that regulates oxytocin (OT) production and influences social interactions. The oxytocin receptor (OXTR) has been studied intensively regarding its association with human psychosocial functions. Many studies have demonstrated a link between CD38 rs3796863 and OXTR rs53576 polymorphic regions and psychosocial characteristics as well as various psychiatric disorders in adolescents. Some studies, however, have reported null findings. Methods: The Strengths and Difficulties Questionnaire (SDQ) is a brief psychopathologic screening tool recommended for detecting psychosocial problems and psychiatric disorders in adolescents. The current field school-based study, conducted among urban Siberian adolescents (n = 298 aged 12-18), explored the SDQ scales in relation to polymorphisms of the CD38 and the OXTR genes (rs3796863 and rs53576, respectively). Results: None of the studied genotypes were associated with the SDQ results for the complete sample with presumed statistical power as 0.80 to detect a medium-size effect (Cramer's V = 0.3) at α = 0.0083. Post-hoc analysis in subgroups showed that OT pathway high activity may cause some negative consequences, such as emotional instability in older (aged 15-18) adolescent boys who are carriers of the rs53576 GG variant. Conclusion: Variations at the CD38 rs3796863 and OXTR rs53576 loci were not associated with psychosocial characteristics of adolescents assessed with the SDQ. In studies with a similar design, we recommend replication with larger samples and greater power to detect small effects, especially in age-sex subgroups of adolescents.

Shared transethnic genetic basis of panic disorder and psychiatric and related intermediate phenotypes

Panic disorder (PD), a common anxiety disorder, is modestly heritable. The genetic basis of anxiety disorders overlaps with that of other psychiatric disorders and their intermediate phenotypes in individuals of European ancestry. Here, we investigated the transethnic polygenetic features shared between Japanese PD patients and European patients with psychiatric disorders and their intermediate phenotypes by conducting polygenic risk score (PRS) analyses. Large-scale European genome-wide association study (GWAS) datasets (n = 7,556-1,131,881) for ten psychiatric disorders and seven intermediate phenotypes were utilized as discovery samples. PRSs derived from these GWASs were calculated for Japanese target subjects [718 PD patients and 1,717 healthy controls (HCs)]. The effects of these PRSs from European GWASs on the risk of PD in Japanese patients were investigated. The PRSs from European studies of anxiety disorders were marginally higher in Japanese PD patients than in HCs (p = 0.013). Regarding other psychiatric disorders, the PRSs for depression in European patients were significantly higher in Japanese PD patients than in HCs (p = 2.31×10^-4), while the PRSs for attention-deficit/hyperactivity disorder in European patients were nominally lower in Japanese PD patients than in HCs (p = 0.024). Regarding health-related, personality-based and cognitive intermediate phenotypes, the PRSs for loneliness (especially isolation) in European individuals were significantly higher in Japanese PD patients than in HCs (p = 9.02×10^-4). Furthermore, Japanese PD patients scored nominally higher than HCs in PRSs for neuroticism in European people (p = 3.37×10^-3), while Japanese PD patients scored nominally lower than HCs in PRSs for tiredness (p = 0.025), educational attainment (p = 0.035) and cognitive function (p = 9.63×10^-3). Our findings suggest that PD shares transethnic genetic etiologies with other psychiatric disorders and related intermediate phenotypes.

Long-Term Impact of Social Isolation and Molecular Underpinnings

Prolonged periods of social isolation can have detrimental effects on the physiology and behavior of exposed individuals in humans and animal models. This involves complex molecular mechanisms across tissues in the body which remain partly identified. This review discusses the biology of social isolation and describes the acute and lasting effects of prolonged periods of social isolation with a focus on the molecular events leading to behavioral alterations. We highlight the role of epigenetic mechanisms and non-coding RNA in the control of gene expression as a response to social isolation, and the consequences for behavior. Considering the use of strict quarantine during epidemics, like currently with COVID-19, we provide a cautionary tale on the indiscriminate implementation of such form of social isolation and its potential damaging and lasting effects in mental health.

Testing structural models of psychopathology at the genomic level

Genome-wide association studies (GWAS) have revealed hundreds of genetic loci associated with the vulnerability to major psychiatric disorders, and post-GWAS analyses have shown substantial genetic correlations among these disorders. This evidence supports the existence of a higher-order structure of psychopathology at both the genetic and phenotypic levels. Despite recent efforts by collaborative consortia such as the Hierarchical Taxonomy of Psychopathology (HiTOP), this structure remains unclear. In this study, we tested multiple alternative structural models of psychopathology at the genomic level, using the genetic correlations among fourteen psychiatric disorders and related psychological traits estimated from GWAS summary statistics. The best-fitting model included four correlated higher-order factors - externalizing, internalizing, thought problems, and neurodevelopmental disorders - which showed distinct patterns of genetic correlations with external validity variables and accounted for substantial genetic variance in their constituent disorders. A bifactor model including a general factor of psychopathology as well as the four specific factors fit worse than the above model. Several model modifications were tested to explore the placement of some disorders - such as bipolar disorder, obsessive-compulsive disorder, and eating disorders - within the broader psychopathology structure. The best-fitting model indicated that eating disorders and obsessive-compulsive disorder, on the one hand, and bipolar disorder and schizophrenia, on the other, load together on the same thought problems factor. These findings provide support for several of the HiTOP higher-order dimensions and suggest a similar structure of psychopathology at the genomic and phenotypic levels.

Diverse phenotypic measurements of wellbeing: Heritability, temporal stability and the variance explained by polygenic scores

Wellbeing, a key aspect of mental health, is moderately heritable with varying estimates reported from independent studies employing a variety of instruments. Recent genome-wide association studies (GWAS) have enabled the construction of polygenic scores (PGS) for wellbeing, providing the opportunity for direct comparisons of the variance explained by PGS for different instruments commonly employed in the field. Nine wellbeing measurements (multi-item and single-item), two personality domains (NEO-FFI neuroticism and extraversion), plus the depression domain of the DASS-42 were drawn from a larger self-report battery applied to the TWIN-E study-an Australian longitudinal twin cohort (N = 1660). Heritability was estimated using univariate twin modeling and 12-month test-retest reliability was estimated using intra-class correlation. PGS were constructed using wellbeing GWAS summary-statistics from Baselmans et al. (Nat Genet. 2019), and the variance explained estimated using linear models. Last, a GWAS was performed using COMPAS-W, a quantitative composite wellbeing measure, to explore its utility in genomic studies. Heritability estimates ranged from 23% to 47% across instruments, and multi-item measures showed higher heritability and test-retest reliability than single-item measures. The variance explained by PGS was ~0.5% to 1.5%, with considerable variation between measures, and within each measure over 12 months. Five loci with suggestive association (p < 1 × 10^-5 ) were identified from this initial COMPAS-W wellbeing GWAS. This work highlights the variability across measures currently employed in wellbeing research, with multi-item and composite measures favored over single-item measures. While wellbeing PGS are useful in a research setting, they explain little of the phenotypic variance, highlighting gaps for improved gene discovery.

Understanding loneliness in the twenty-first century: an update on correlates, risk factors, and potential solutions

PURPOSE

Loneliness is increasingly recognised as the next critical public health issue. A plausible reason for this concern may be related to emerging societal trends affecting the way we relate, communicate, and function in our social environment. In 2006, a prominent review of the clinical significance of loneliness was published. However, there has not been a comprehensive update on known and emerging risk factors and correlates of loneliness since then. Furthermore, there is no conceptual model that has been developed to better account for the complexity of loneliness and to inform the development of evidence-based solutions as we challenge the issues of the twenty-first century.

METHODS

We reviewed the current literature to identify either known or emerging risk factors and correlates of loneliness since 2006. This includes new or known evidence on: (1) demography; (2) health, including physical health; mental health; cognitive health; brain, biology, and genetics; and (3) socio-environmental factors including digital communication and the workplace.

RESULTS

We synthesized the literature according to a new proposed conceptual model of loneliness which showed the interplay between known and emerging correlates and risk factors from demography, health, to socio-environmental factors. In the conceptual model of loneliness, we illustrated how solutions can be delivered and tailored to an individual based on their life circumstances and preferences.

CONCLUSION

We concluded by making specific recommendations in advancing our scientific understanding of loneliness. Our knowledge can only be deepened if we increase scientific rigour via accounting for confounding variables and using longitudinal, multi-disciplinary, and multiple methodologies in research. We also call for the rigorous evaluation of programs targeting loneliness.

Genome-wide association study of shared liability to anxiety disorders in Army STARRS

Anxiety disorders (ANX), namely generalized anxiety, panic disorder, and phobias, are common, etiologically complex syndromes that show increasing prevalence and comorbidity throughout adolescence and beyond. Few genome-wide association studies (GWAS) examining ANX risk have been published and almost exclusively in individuals of European ancestry. In this study, we phenotyped participants from the Army Study To Assess Risk and Resilience in Servicemembers (STARRS) to approximate DSM-based ANX diagnoses. We factor-analyzed those to create a single dimensional anxiety score for each subject. GWAS were conducted using that score within each of three ancestral groups (EUR, AFR, LAT) and then meta-analyzed across ancestries (NTotal = 16,510). We sought to (a) replicate prior ANX GWAS findings in ANGST; (b) determine whether results extended to other ancestry groups; and (c) meta-analyze with ANGST for increased power to identify novel susceptibility loci. No reliable genome-wide significant SNP associations were detected in STARRS. However, SNPs within the CAMKMT gene located in region 2p21 associated with shared ANX risk in ANGST were replicated in EUR soldiers but not other ancestry groups. Combining EUR STARRS and ANGST (N = 28,950) yielded a more robust 2p21 association signal (p = 9.08x10-11 ). Gene-based analyses supported three genes within 2p21 and LBX1 on chromosome 10. More powerful ANX genetic studies will be required to identify further loci.

Emerging phenotyping strategies will advance our understanding of psychiatric genetics

Over the last decade, genome-wide association studies of psychiatric disorders have identified numerous significant loci. Whereas these studies initially depended on cohorts ascertained for specific disorders, there has been a gradual shift in the ascertainment strategy toward population-based cohorts for which both genotype and heterogeneous phenotypic information are available. One of the advantages of population-based cohorts is that, in addition to clinical diagnoses and various proxies for diagnoses ('minimal phenotyping'), many of them also provide non-clinical phenotypes, including putative endophenotypes, that can be used to study domains of normal function in addition to, or instead of, clinical diagnoses. By studying endophenotypes it is possible to both dissect psychiatric disorders ('splitting') and to combine multiple phenotypes ('clumping'), which can either reinforce or challenge traditional diagnostic categories. Such endophenotypes may also permit a deeper exploration of the neurobiology of psychiatric disorders. A coordinated effort to fully exploit the potential of endophenotypes is overdue.

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes

BACKGROUND

Psychiatric disorders and related intermediate phenotypes are highly heritable and have a complex, overlapping polygenic architecture. A large-scale genome-wide association study (GWAS) of anxiety disorders identified genetic variants that are significant on a genome-wide. The current study investigated the genetic etiological overlaps between anxiety disorders and frequently cooccurring psychiatric disorders and intermediate phenotypes.

METHODS

Using case-control and factor score models, we investigated the genetic correlations of anxiety disorders with eight psychiatric disorders and intermediate phenotypes [the volumes of seven subcortical brain regions, childhood cognition, general cognitive ability and personality traits (subjective well-being, loneliness, neuroticism and extraversion)] from large-scale GWASs (n = 7556-298 420) by linkage disequilibrium score regression.

RESULTS

Among psychiatric disorders, the risk of anxiety disorders was positively genetically correlated with the risks of major depressive disorder (MDD) (rg ± standard error = 0.83 ± 0.16, p = 1.97 × 10-7), schizophrenia (SCZ) (0.28 ± 0.09, p = 1.10 × 10-3) and attention-deficit/hyperactivity disorder (ADHD) (0.34 ± 0.13, p = 8.40 × 10-3). Among intermediate phenotypes, significant genetic correlations existed between the risk of anxiety disorders and neuroticism (0.81 ± 0.17, p = 1.30 × 10-6), subjective well-being (-0.73 ± 0.18, p = 4.89 × 10-5), general cognitive ability (-0.23 ± 0.08, p = 4.70 × 10-3) and putamen volume (-0.50 ± 0.18, p = 5.00 × 10-3). No other significant genetic correlations between anxiety disorders and psychiatric or intermediate phenotypes were observed (p > 0.05). The case-control model yielded stronger genetic effect sizes than the factor score model.

CONCLUSIONS

Our findings suggest that common genetic variants underlying the risk of anxiety disorders contribute to elevated risks of MDD, SCZ, ADHD and neuroticism and reduced quality of life, putamen volume and cognitive performance. We suggest that the comorbidity of anxiety disorders is partly explained by common genetic variants.

A SNP, Gene, and Polygenic Risk Score Approach of Oxytocin-Vasopressin Genes in Adolescents' Loneliness

Not much is known regarding underlying biological pathways to adolescents' loneliness. Insight in underlying molecular mechanisms could inform intervention efforts aimed at reducing loneliness. Using latent growth curve modeling, baseline levels and development of loneliness were studied in two longitudinal adolescent samples. Genes (OXTR, OXT, AVPR1A, AVPR1B) were examined using SNP-based, gene-based, and polygenic risk score (PRS) approaches. In both samples, SNP- and gene-based tests showed involvement of the OXTR gene in development of loneliness, though, significance levels did not survive correction for multiple testing. The PRS approach provided no evidence for relations with loneliness. We recommend alternative phenotyping methods, including environmental factors, to consider epigenetic studies, and to examine possible endophenotypes in relation to adolescents' loneliness.

Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health

BACKGROUND

Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits.

METHODS

Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression.

RESULTS

We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity.

CONCLUSIONS

Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Genome-wide association analysis of autism identified multiple loci that have been reported as strong signals for neuropsychiatric disorders

Autism is a common neurodevelopmental disorder with a moderate to a high degree of heritability, but only a few common genetic variants that explain the heritability have been associated. We performed a genome-wide transmission disequilibrium test analysis of a newly genotyped autism case-parent triad samples (127 trios) in Han Chinese, identified top association signals at multiple single nucleotide polymorphisms (SNPs), including rs9839376 (OR = 2.59, P = 1.27 × 10^-05 ) at KCNMB2, rs6044680 (OR = 0.319, P = 4.82 × 10^-05 ) and rs7274133 (OR = 0.313, P = 3.22 × 10^-05 ) at PCSK2, and rs310619 (OR = 2.40, P = 7.44 × 10^-05 ) at EEF1A2. Furthermore, a genome-wide combined P-value of individual SNPs in two independent case-parent triad samples (total 402 triads, n = 1,206) identified SNPs at EGFLAM, ZDHHC2, AGBL1, and SNX29 as additional association signals for autism. While none of these signals achieved a genome-wide significance in the two samples of our study, they have been reported in a previous genome-wide association study of neuropsychiatric disorders, and the majority of these SNP have a significant cis-regulatory association with mRNA in human tissues (false discovery rate (FDR) < 0.05). Our study warrants further study or replication with additional sample for association with autism and other neuropsychiatric disorders. Autism Res 2020, 13: 382-396. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism is a common neurodevelopmental disorder, heritable, but only a few common genetic variants that explain the heritability have been associated. We conducted a genome-wide association study with two cohorts of autism case-parent triad samples in Han Chinese and identified multiple single nucleotide polymorphisms that were reported as strong association signals in a previous genome-wide association study of other neuropsychiatric disorders or related traits. Our study provides evidence for shared genetic variants among autism and other neuropsychiatric disorders.

Polygenic Score of Subjective Well-Being Is Associated with the Brain Morphology in Superior Temporal Gyrus and Insula

Subjective well-being (SWB) is closely related to our physical and mental health. Existing studies show that neural or genetic basis underpins individual difference in SWB. Moreover, researchers have found high enrichment of SWB-related mutations in the central nervous system, but the relationship between the genetic architecture of SWB and brain morphology has not been explored. Considering the polygenic nature of SWB, in this study, we aim to establish a measure of additive genetic effect on SWB and explore its relationship to the brain anatomical structure. Based on the results of genome-wide association study (GWAS) on SWB, the polygenic scores (PGSs) of SWB at eight different thresholds were calculated in a large Chinese sample (N = 585). Then, we analyzed the associations between the PGSs of SWB and cortical thickness (CT) or gray matter volume (GMV) measured from 3.0-T structural imaging data. In whole-brain analyses, we found that a higher PGS was significantly associated with increased CT in the right superior temporal gyrus (STG) and GMV in the right insula, both of which are involved in social cognition and emotional processing. More importantly, these findings were repeatable at some different thresholds. The results may suggest that the brain morphology of right STG and insula is partly regulated by SWB-related genetic factors.

Genetic Contributions to Loneliness and Their Relevance to the Evolutionary Theory of Loneliness

Loneliness is a negative and distressing emotional state that arises from a discrepancy between one's desired and achieved levels of social connectedness. The evolutionary theory of loneliness (ETL) posits that experiencing loneliness is an inherited adaptation that signals that salutary social relations are endangered or damaged and prompts people to reconnect to significant others. The basic tenets of the ETL has led researchers to examine the genetic underpinnings of loneliness. The current review provides an updated overview of genetic studies on loneliness and discusses the importance of genetic research for the ETL. The most recent studies suggest that the many genes that contribute to a small degree to differences in loneliness partially overlap with genes that contribute to neuroticism, but not with depression. In addition, the genetic studies discussed in this review show that genes are unlikely to have a direct effect on loneliness. Instead, environmental factors determine in a dynamic fashion how genes that contribute to loneliness are expressed. Future research on epigenetic processes, such as DNA methylation, can further elucidate the dynamic interplay between genes and the environment and how this interplay contributes to loneliness.

A Genetic Investigation of the Well-Being Spectrum

The interrelations among well-being, neuroticism, and depression can be captured in a so-called well-being spectrum (3-phenotype well-being spectrum, 3-WBS). Several other human traits are likely linked to the 3-WBS. In the present study, we investigate how the 3-WBS can be expanded. First, we constructed polygenic risk scores for the 3-WBS and used this score to predict a series of traits that have been associated with well-being in the literature. We included information on loneliness, big five personality traits, self-rated health, and flourishing. The 3-WBS polygenic score predicted all the original 3-WBS traits and additionally loneliness, self-rated health, and extraversion (R² between 0.62% and 1.58%). Next, using LD score regression, we calculated genetic correlations between the 3-WBS and the traits of interest. From all candidate traits, loneliness and self-rated health were found to have the strongest genetic correlations (r_g = - 0.79, and r_g= 0.64, respectively) with the 3-WBS. Lastly, we use Genomic SEM to investigate the factor structure of the proposed spectrum. The best model fit was obtained for a two-factor model including the 5-WBS traits, with two highly correlated factors representing the negative- and positive end of the spectrum. Based on these analyses we propose to include loneliness and self-rated health in the WBS and use a 5-phenotype well-being spectrum in future studies to gain more insight into the determinants of human well-being.

Genetic risk for neuroticism predicts emotional health depending on childhood adversity

BACKGROUND

Existing evidence for gene × environment interaction (G × E) in neuroticism largely relies on candidate gene studies, although neuroticism is highly polygenic. This study aimed to investigate the long-term associations between polygenic risk scores for neuroticism (PRSN), objective childhood adversity and their interplay on emotional health aspects such as neuroticism itself, depressive symptoms, anxiety symptoms, loneliness and life satisfaction.

METHODS

The sample consisted of reared-apart (TRA) and reared-together (TRT) middle- and old age twins (N = 699; median age at separation = 2). PRSN were created under nine p value cut-off thresholds (pT-s) and the pT with the highest degree of neuroticism variance explained was chosen for subsequent analyses. Linear regressions were used to assess the associations between PRSN, childhood adversity (being reared apart) and emotional health. G × E was further investigated using a discordant twin design.

RESULTS

PRSN explained up to 1.7% (pT &lt; 0.01) of phenotypic neuroticism in the total sample. Analyses across two separation groups revealed substantial heterogeneity in the variance explained by PRSN; 4.3% was explained in TRT, but almost no effect was observed in TRA. Similarly, PRSN explained 4% and 1.7% of the variance in depressive symptoms and loneliness, respectively, only in TRT. A significant G × E interaction was identified for depressive symptoms.

CONCLUSIONS

By taking advantage of a unique sample of adopted twins, we demonstrated the presence of G × E in neuroticism and emotional health using PRSN and childhood adversity. Our results may indicate that genome-wide association studies are detecting genetic main effects associated with neuroticism, but not those susceptible to early environmental influences.

Sociogenomics in the 21st Century: An Introduction to the History and Potential of Genetically-informed Social Science

This article reviews research at the intersection of genetics and sociology and provides an introduction to the current data, methods, and theories used in sociogenomic research. To accomplish this, I review behavioral genetics models, candidate gene analysis, genome-wide complex trait analysis, and the use of polygenic scores (sometimes referred to as polygenic risk scores) in the study of complex human behaviors and traits. The information provided is meant to equip readers with the necessary tools to: (1) understand the methodology employed by each type of analysis, (2) intelligently interpret findings from sociogenomic research, and (3) understand the importance of sociologists in the ever-growing field of sociogenomics. To unify these three tasks, I rely on various examples from recent sociogenomic analyses of educational attainment focusing on social stratification and inequality.

Loneliness and Diurnal Salivary Cortisol in Emerging Adults

This study aimed to examine the relationship between trait loneliness and diurnal rhythms of salivary cortisol. Fifty-One Chinese undergraduates provided six saliva samples on a weekday at immediately, 0.5, 3, 6, and 12 h after waking, and at bedtime. Saliva collection times were monitored using electronic devices (MEMS TrackCaps). Participants were also administered a questionnaire consisting of scales measuring, trait loneliness, depression, and demographics. Relationships between loneliness and the cortisol awakening response (CAR), diurnal slope (DS), and area under the curve with respect to ground (AUC_G) were examined using multiple regression analyses. Results showed that a higher loneliness score was associated with an attenuated CAR, a large AUC_G, and a steeper DS, with the effects of compliance, waking time, and depression being controlled. As a blunted CAR and a higher diurnal cortisol level have been shown to be associated with poorer health in prior studies, increased attention to the mechanisms translating loneliness into disease endpoints via elevated cortisol is warranted.

Elucidating the genetic basis of social interaction and isolation

The negative impacts of social isolation and loneliness on health are well documented. However, little is known about their possible biological determinants. In up to 452,302 UK Biobank study participants, we perform genome-wide association study analyses for loneliness and regular participation in social activities. We identify 15 genomic loci (P < 5 × 10⁻⁸) for loneliness, and demonstrate a likely causal association between adiposity and increased susceptibility to loneliness and depressive symptoms. Further loci were identified for regular attendance at a sports club or gym (N = 6 loci), pub or social club (N = 13) or religious group (N = 18). Across these traits there was strong enrichment for genes expressed in brain regions that control emotional expression and behaviour. We demonstrate aetiological mechanisms specific to each trait, in addition to identifying loci that are pleiotropic across multiple complex traits. Further study of these traits may identify novel modifiable risk factors associated with social withdrawal and isolation.

Little is known about the genetic determinants of social isolation and loneliness despite their well-established importance for health. Here, using multi-trait GWAS, Day et al. identify 15 genomic loci for loneliness and further show a bidirectional causal relationship between BMI and loneliness by MR.