Polygenic overlap and shared genetic loci between loneliness, severe mental disorders, and cardiovascular disease risk factors suggest shared molecular mechanisms

A translational neuroscience perspective on loneliness: Narrative review focusing on social interaction, illness and oxytocin

This review addresses key findings on loneliness from the social, neurobiological and clinical fields. From a translational perspective, results from studies in humans and animals are included, with a focus on social interaction, mental and physical illness and the role of oxytocin in loneliness. In terms of social interactions, lonely individuals tend to exhibit a range of abnormal behaviors based on dysfunctional social cognitions that make it difficult for them to form meaningful relationships. Neurobiologically, a link has been established between loneliness and the hypothalamic peptide hormone oxytocin. Since social interactions and especially social touch regulate oxytocin signaling, lonely individuals may have an oxytocin imbalance, which in turn affects their health and well-being. Clinically, loneliness is a predictor of physical and mental illness and leads to increased morbidity and mortality. There is evidence that psychopathology is both a cause and a consequence of loneliness. The final section of this review summarizes the findings from social, neurobiological and clinical perspectives to present a new model of the complex construct of loneliness.

Polygenic risk for schizophrenia and bipolar disorder in relation to cardiovascular biomarkers

Individuals with schizophrenia and bipolar disorder are at an increased risk of cardiovascular disease (CVD), and a range of biomarkers related to CVD risk have been found to be abnormal in these patients. Common genetic factors are a putative underlying mechanism, alongside lifestyle factors and antipsychotic medication. However, the extent to which the altered CVD biomarkers are related to genetic factors involved in schizophrenia and bipolar disorder is unknown. In a sample including 699 patients with schizophrenia, 391 with bipolar disorder, and 822 healthy controls, we evaluated 8 CVD risk biomarkers, including BMI, and fasting plasma levels of CVD biomarkers from a subsample. Polygenic risk scores (PGRS) were obtained from genome-wide associations studies (GWAS) of schizophrenia and bipolar disorder from the Psychiatric Genomics Consortium. The CVD biomarkers were used as outcome variables in linear regression models including schizophrenia and bipolar disorder PGRS as predictors, age, sex, diagnostic category, batch and 10 principal components as covariates, controlling for multiple testing by Bonferroni correction for the number of independent tests. Bipolar disorder PGRS was significantly (p = 0.03) negatively associated with BMI after multiple testing correction, and schizophrenia PGRS was nominally negatively associated with BMI. There were no other significant associations between bipolar or schizophrenia PGRS, and other investigated CVD biomarkers. Despite a range of abnormal CVD risk biomarkers in psychotic disorders, we only found a significant negative association between bipolar disorder PGRS and BMI. This has previously been shown for schizophrenia PGRS and BMI, and warrants further exploration.

A Potential Role for MAGI-1 in the Bi-Directional Relationship Between Major Depressive Disorder and Cardiovascular Disease

PURPOSE OF REVIEW

Major Depressive Disorder (MDD) is characterized by persistent symptoms such as fatigue, loss of interest in activities, feelings of sadness and worthlessness. MDD often coexist with cardiovascular disease (CVD), yet the precise link between these conditions remains unclear. This review explores factors underlying the development of MDD and CVD, including genetic, epigenetic, platelet activation, inflammation, hypothalamic-pituitary-adrenal (HPA) axis activation, endothelial cell (EC) dysfunction, and blood-brain barrier (BBB) disruption.

RECENT FINDINGS

Single nucleotide polymorphisms (SNPs) in the membrane-associated guanylate kinase WW and PDZ domain-containing protein 1 (MAGI-1) are associated with neuroticism and psychiatric disorders including MDD. SNPs in MAGI-1 are also linked to chronic inflammatory disorders such as spontaneous glomerulosclerosis, celiac disease, ulcerative colitis, and Crohn's disease. Increased MAGI-1 expression has been observed in colonic epithelial samples from Crohn's disease and ulcerative colitis patients. MAGI-1 also plays a role in regulating EC activation and atherogenesis in mice and is essential for Influenza A virus (IAV) infection, endoplasmic reticulum stress-induced EC apoptosis, and thrombin-induced EC permeability. Despite being understudied in human disease; evidence suggests that MAGI-1 may play a role in linking CVD and MDD. Therefore, further investigation of MAG-1 could be warranted to elucidate its potential involvement in these conditions.

The brain-heart axis: Integrative analysis of the shared genetic etiology between neuropsychiatric disorders and cardiovascular disease

BACKGROUND

Multiple observational studies have reported substantial comorbidity between neuropsychiatric disorders and cardiovascular disease (CVD), but the underlying mechanisms remain largely unknown.

METHODS

Using GWAS summary datasets of 8 neuropsychiatric disorders and 6 cardiovascular diseases, an integrative analysis incorporating linkage-disequilibrium-score-regression (LDSC), Mendelian randomization (MR), functional mapping and annotation (FUMA), and functional enrichment analysis, was conducted to investigate shared genetic etiology of the brain-heart axis from the whole genome level, single-nucleotide polymorphism (SNP) level, gene level, and biological pathway level.

RESULTS

In LDSC analysis, 18 pairwise traits between neuropsychiatric disorders and CVD were identified with significant genetic overlaps, revealing extensive genome-wide genetic correlations. In bidirectional MR analysis, 19 pairwise traits were identified with significant causal relationships. Genetic liabilities to neuropsychiatric disorders, particularly attention-deficit hyperactivity disorder and major depressive disorder, conferred extensive significant causal effects on the risk of CVD, while hypertension seemed to be a risk factor for multiple neuropsychiatric disorders, with no significant heterogeneity or pleiotropy. In FUMA analysis, 13 shared independent significant SNPs and 887 overlapping protein-coding genes were detected between neuropsychiatric disorders and CVD. With GO and KEEG functional enrichment analysis, biological pathways of the brain-heart axis were highly concentrated in neurotransmitter synaptic transmission, lipid metabolism, aldosterone synthesis and secretion, glutathione metabolism, and MAPK signaling pathway.

CONCLUSION

Extensive genetic correlations and genetic overlaps between neuropsychiatric disorders and CVD were identified in this study, which might provide some new insights into the brain-heart axis and the therapeutic targets in clinical practice.

Atypical dynamic network reconfiguration and genetic mechanisms in patients with major depressive disorder

BACKGROUND

Brain dynamics underlie complex forms of flexible cognition or the ability to shift between different mental modes. However, the precise dynamic reconfiguration based on multi-layer network analysis and the genetic mechanisms of major depressive disorder (MDD) remains unclear.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data were acquired from the REST-meta-MDD consortium, including 555 patients with MDD and 536 healthy controls (HC). A time-varying multi-layer network was constructed, and dynamic modular characteristics were used to investigate the network reconfiguration. Additionally, partial least squares regression analysis was performed using transcriptional data provided by the Allen Human Brain Atlas (AHBA) to identify genes associated with atypical dynamic network reconfiguration in MDD.

RESULTS

In comparison to HC, patients with MDD exhibited lower global and local recruitment coefficients. The local reduction was particularly evident in the salience and subcortical networks. Spatial transcriptome correlation analysis revealed an association between gene expression profiles and atypical dynamic network reconfiguration observed in MDD. Further functional enrichment analyses indicated that positively weighted reconfiguration-related genes were primarily associated with metabolic and biosynthetic pathways. Additionally, negatively enriched genes were predominantly related to programmed cell death-related terms.

CONCLUSIONS

Our findings offer robust evidence of the atypical dynamic reconfiguration in patients with MDD from a novel perspective. These results offer valuable insights for further exploration into the mechanisms underlying MDD.

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 and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies

Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world's population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.

How does loneliness "get under the skin" to become biologically embedded?

Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.

Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities

BACKGROUND

Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ.

STUDY DESIGN

GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects.

STUDY RESULTS

The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms.

CONCLUSIONS

Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.

An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value

INTRODUCTION

Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics.

AREAS COVERED

In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value.

EXPERT OPINION

A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.

Psychiatric disorders and subsequent risk of cardiovascular disease: a longitudinal matched cohort study across three countries

Background

Several psychiatric disorders have been associated with increased risk of cardiovascular disease (CVD), however, the role of familial factors and the main disease trajectories remain unknown.

Methods

In this longitudinal cohort study, we identified a cohort of 900,240 patients newly diagnosed with psychiatric disorders during January 1, 1987 and December 31, 2016, their 1,002,888 unaffected full siblings, and 1:10 age- and sex-matched reference population from nationwide medical records in Sweden, who had no prior diagnosis of CVD at enrolment. We used flexible parametric models to determine the time-varying association between first-onset psychiatric disorders and incident CVD and CVD death, comparing rates of CVD among patients with psychiatric disorders to the rates of unaffected siblings and matched reference population. We also used disease trajectory analysis to identify main disease trajectories linking psychiatric disorders to CVD. Identified associations and disease trajectories of the Swedish cohort were validated in a similar cohort from nationwide medical records in Denmark (N = 875,634 patients, same criteria during January 1, 1969 and December 31, 2016) and in Estonian cohorts from the Estonian Biobank (N = 30,656 patients, same criteria during January 1, 2006 and December 31, 2020), respectively.

Findings

During up to 30 years of follow-up of the Swedish cohort, the crude incidence rate of CVD was 9.7, 7.4 and 7.0 per 1000 person-years among patients with psychiatric disorders, their unaffected siblings, and the matched reference population. Compared with their siblings, patients with psychiatric disorders experienced higher rates of CVD during the first year after diagnosis (hazard ratio [HR], 1.88; 95% confidence interval [CI], 1.79-1.98) and thereafter (1.37; 95% CI, 1.34-1.39). Similar rate increases were noted when comparing with the matched reference population. These results were replicated in the Danish cohort. We identified several disease trajectories linking psychiatric disorders to CVD in the Swedish cohort, with or without mediating medical conditions, including a direct link between psychiatric disorders and hypertensive disorder, ischemic heart disease, venous thromboembolism, angina pectoris, and stroke. These trajectories were validated in the Estonian Biobank cohort.

Interpretation

Independent of familial factors, patients with psychiatric disorders are at an elevated risk of subsequent CVD, particularly during first year after diagnosis. Increased surveillance and treatment of CVDs and CVD risk factors should be considered as an integral part of clinical management, in order to reduce risk of CVD among patients with psychiatric disorders.

Funding

This research was supported by EU Horizon 2020 Research and Innovation Action Grant, European Research Council Consolidator grant, Icelandic Research fund, Swedish Research Council, US NIMH, the Outstanding Clinical Discipline Project of Shanghai Pudong, the Fundamental Research Funds for the Central Universities, and the European Union through the European Regional Development Fund; the Research Council of Norway; the South-East Regional Health Authority, the Stiftelsen Kristian Gerhard Jebsen, and the EEA-RO-NO-2018-0535.

Role of non-coding variants in cardiovascular disease

Cardiovascular diseases (CVDs) constitute one of the significant causes of death worldwide. Different pathological states are linked to CVDs, which despite interventions and treatments, still have poor prognoses. The genetic component, as a beneficial tool in the risk stratification of CVD development, plays a role in the pathogenesis of this group of diseases. The emergence of genome-wide association studies (GWAS) have led to the identification of non-coding parts associated with cardiovascular traits and disorders. Variants located in functional non-coding regions, including promoters/enhancers, introns, miRNAs and 5'/3' UTRs, account for 90% of all identified single-nucleotide polymorphisms associated with CVDs. Here, for the first time, we conducted a comprehensive review on the reported non-coding variants for different CVDs, including hypercholesterolemia, cardiomyopathies, congenital heart diseases, thoracic aortic aneurysms/dissections and coronary artery diseases. Additionally, we present the most commonly reported genes involved in each CVD. In total, 1469 non-coding variants constitute most reports on familial hypercholesterolemia, hypertrophic cardiomyopathy and dilated cardiomyopathy. The application and identification of non-coding variants are beneficial for the genetic diagnosis and better therapeutic management of CVDs.

Association of Deja Vu with Cardiovascular Diseases

Recent studies have suggested a link between déjà vu and cardiovascular diseases. While the mechanism for this association is not fully understood, one theory suggests that déjà vu may be a result of a disruption in the temporal lobe, which is also responsible for regulating blood pressure and heart rate. Another theory suggests that there may be a shared genetic factor between the two conditions, with certain individuals being predisposed to experiencing both. The APOE (Apolipoprotein E) gene, in particular, has been associated with memory processing, Alzheimer's disease, and an increased risk of cardiovascular disease. The protein encoded by this gene is involved in the metabolism of lipoproteins, including cholesterol and triglycerides, and is also involved in the development of atherosclerosis, which is a key risk factor for cardiovascular disease. Several hypotheses have been proposed to explain how the APOE4 isoform contributes to CVD, including impairing the clearance of lipoproteins, promoting inflammation, and causing endothelial dysfunction. Psychological factors such as stress may also contribute to the development of cardiovascular disease, and déjà vu may be associated with emotional arousal and stress. Further research is needed to fully understand the link between déjà vu and cardiovascular diseases and to explore potential treatment options for individuals who experience both conditions.

Exploring the genetic correlation of cardiovascular diseases and mood disorders in the UK Biobank

AIMS

Cardiovascular diseases (CVDs) are the leading cause of deaths globally. Mortality and incidence of CVDs are significantly higher in people with mood disorders. About 81.1% of CVD patients were reported with comorbidities in 2019, where the second most common comorbidity was due to major depressive disorder (MDD). This study, therefore, aimed to evaluate the genetic correlation between CVDs and mood disorders by using data from the UK Biobank towards understanding the influence of genetic factors on the comorbidity due to CVDs and mood disorders.

METHODS

The UK Biobank database provides genetic and health information from half a million adults, aged 40-69 years, recruited between 2006 and 2010. A total of 117,925 participants and 6,128,294 variants were included for analysis after applying exclusion criteria and quality control steps. This study focused on two CVD phenotypes, two mood disorders and 12 cardiometabolic-related traits to conduct association studies.

RESULTS

The results indicated a significant positive genetic correlation between CVDs and overall mood disorders and MDD specifically, showing substantial genetic overlap. Genetic correlation between CVDs and bipolar disorder was not significant. Furthermore, significant genetic correlation between mood disorders and cardiometabolic traits was also reported.

CONCLUSIONS

The results of this study can be used to understand that CVDs and mood disorders share a great deal of genetic liability in individuals of European ancestry.

Breaking the vicious cycle: The interplay between loneliness, metabolic illness, and mental health

Loneliness, or perceived social isolation, is a leading predictor of all-cause mortality and is increasingly considered a public health epidemic afflicting significant portions of the general population. Chronic loneliness is itself associated with two of the most pressing public health epidemics currently facing the globe: the rise of mental illness and metabolic health disorders. Here, we highlight the epidemiological associations between loneliness and mental and metabolic health disorders and argue that loneliness contributes to the etiology of these conditions by acting as a chronic stressor that leads to neuroendocrine dysregulation and downstream immunometabolic consequences that manifest in disease. Specifically, we describe how loneliness can lead to overactivation of the hypothalamic-pituitary-adrenal axis and ultimately cause mitochondrial dysfunction, which is implicated in mental and metabolic disease. These conditions can, in turn, lead to further social isolation and propel a vicious cycle of chronic illness. Finally, we outline interventions and policy recommendations that can reduce loneliness at both the individual and community levels. Given its role in the etiology of the most prevalent chronic diseases of our time, focusing resources on alleviating loneliness is a vitally important and cost-effective public health strategy.

Prenatal social support in low-risk pregnancy shapes placental epigenome

BACKGROUND

Poor social support during pregnancy has been linked to inflammation and adverse pregnancy and childhood health outcomes. Placental epigenetic alterations may underlie these links but are still unknown in humans.

METHODS

In a cohort of low-risk pregnant women (n = 301) from diverse ethnic backgrounds, social support was measured using the ENRICHD Social Support Inventory (ESSI) during the first trimester. Placental samples collected at delivery were analyzed for DNA methylation and gene expression using Illumina 450K Beadchip Array and RNA-seq, respectively. We examined association between maternal prenatal social support and DNA methylation in placenta. Associated cytosine-(phosphate)-guanine sites (CpGs) were further assessed for correlation with nearby gene expression in placenta.

RESULTS

The mean age (SD) of the women was 27.7 (5.3) years. The median (interquartile range) of ESSI scores was 24 (22-25). Prenatal social support was significantly associated with methylation level at seven CpGs (P_FDR < 0.05). The methylation levels at two of the seven CpGs correlated with placental expression of VGF and ILVBL (P_FDR < 0.05), genes known to be involved in neurodevelopment and energy metabolism. The genes annotated with the top 100 CpGs were enriched for pathways related to fetal growth, coagulation system, energy metabolism, and neurodevelopment. Sex-stratified analysis identified additional significant associations at nine CpGs in male-bearing pregnancies and 35 CpGs in female-bearing pregnancies.

CONCLUSIONS

The findings suggest that prenatal social support is linked to placental DNA methylation changes in a low-stress setting, including fetal sex-dependent epigenetic changes. Given the relevance of some of these changes in fetal neurodevelopmental outcomes, the findings signal important methylation targets for future research on molecular mechanisms of effect of the broader social environment on pregnancy and fetal outcomes.

TRIAL REGISTRATION

NCT00912132 ( ClinicalTrials.gov ).

Melancholic features and typical neurovegetative symptoms of major depressive disorder show specific polygenic patterns

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric condition characterised by a heterogeneous clinical presentation and an estimated twin-based heritability of ~40-50 %. Different clinical MDD subtypes might partly reflect distinctive underlying genetics. This study aims to investigate if polygenic risk scores (PRSs) for different psychiatric disorders, personality traits, and substance use-related traits may be associated with different clinical subtypes of MDD (i.e., MDD with melancholic or psychotic features), higher symptom severity, or different clusters of depressive symptoms (i.e., sadness symptoms, typical neurovegetative symptoms, detachment symptoms, and negative thoughts).

METHODS

The target sample included 1149 patients with MDD, recruited by the European Group for the Study of Resistant Depression. PRSs for 25 psychiatric disorders and traits were computed based on the most recent publicly available summary statistics of the largest genome-wide association studies. PRSs were then used as predictors in regression models, adjusting for age, sex, population stratification, and recruitment sites.

RESULTS

Patients with MDD having higher PRS for MDD and loneliness were more likely to exhibit melancholic features of MDD (p = 0.0009 and p = 0.005, respectively). Moreover, patients with higher PRS for alcohol intake and post-traumatic stress disorder were more likely to experience greater typical neurovegetative symptoms (p = 0.0012 and p = 0.0045, respectively).

LIMITATIONS

The proportion of phenotypic variance explained by the PRSs was limited.

CONCLUSIONS

This study suggests that melancholic features and typical neurovegetative symptoms of MDD may show distinctive underlying genetics. Our findings provide a new contribution to the understanding of the genetic heterogeneity of MDD.

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.

Cardiovascular disease and subsequent risk of psychiatric disorders: a nationwide sibling-controlled study

Background

The association between cardiovascular disease (CVD) and selected psychiatric disorders has frequently been suggested while the potential role of familial factors and comorbidities in such association has rarely been investigated.

Methods

We identified 869,056 patients newly diagnosed with CVD from 1987 to 2016 in Sweden with no history of psychiatric disorders, and 910,178 full siblings of these patients as well as 10 individually age- and sex-matched unrelated population controls (N = 8,690,560). Adjusting for multiple comorbid conditions, we used flexible parametric models and Cox models to estimate the association of CVD with risk of all subsequent psychiatric disorders, comparing rates of first incident psychiatric disorder among CVD patients with rates among unaffected full siblings and population controls.

Results

The median age at diagnosis was 60 years for patients with CVD and 59.2% were male. During up to 30 years of follow-up, the crude incidence rates of psychiatric disorder were 7.1, 4.6, and 4.0 per 1000 person-years for patients with CVD, their siblings and population controls. In the sibling comparison, we observed an increased risk of psychiatric disorder during the first year after CVD diagnosis (hazard ratio [HR], 2.74; 95% confidence interval [CI], 2.62-2.87) and thereafter (1.45; 95% CI, 1.42-1.48). Increased risks were observed for all types of psychiatric disorders and among all diagnoses of CVD. We observed similar associations in the population comparison. CVD patients who developed a comorbid psychiatric disorder during the first year after diagnosis were at elevated risk of subsequent CVD death compared to patients without such comorbidity (HR, 1.55; 95% CI, 1.44-1.67).

Conclusions

Patients diagnosed with CVD are at an elevated risk for subsequent psychiatric disorders independent of shared familial factors and comorbid conditions. Comorbid psychiatric disorders in patients with CVD are associated with higher risk of cardiovascular mortality suggesting that surveillance and treatment of psychiatric comorbidities should be considered as an integral part of clinical management of newly diagnosed CVD patients.

Funding

This work was supported by the EU Horizon 2020 Research and Innovation Action Grant (CoMorMent, grant no. 847776 to UV, PFS, and FF), Grant of Excellence, Icelandic Research Fund (grant no. 163362-051 to UV), ERC Consolidator Grant (StressGene, grant no. 726413 to UV), Swedish Research Council (grant no. D0886501 to PFS), and US NIMH R01 MH123724 (to PFS).

Positive moods are all alike? Differential affect amplification effects of 'elated' versus 'calm' mental imagery in young adults reporting hypomanic-like experiences

Positive mood amplification is a hallmark of the bipolar disorder spectrum (BPDS). We need better understanding of cognitive mechanisms contributing to such elevated mood. Generation of vivid, emotionally compelling mental imagery is proposed to act as an 'emotional amplifier' in BPDS. We used a positive mental imagery generation paradigm to manipulate affect in a subclinical BPDS-relevant sample reporting high (n = 31) vs. low (n = 30) hypomanic-like experiences on the Mood Disorder Questionnaire (MDQ). Participants were randomized to an 'elated' or 'calm' mental imagery condition, rating their momentary affect four times across the experimental session. We hypothesized greater affect increase in the high (vs. low) MDQ group assigned to the elated (vs. calm) imagery generation condition. We further hypothesized that affect increase in the high MDQ group would be particularly apparent in the types of affect typically associated with (hypo)mania, i.e., suggestive of high activity levels. Mixed model and time-series analysis showed that for the high MDQ group, affect increased steeply and in a sustained manner over time in the 'elated' imagery condition, and more shallowly in 'calm'. The low-MDQ group did not show this amplification effect. Analysis of affect clusters showed high-MDQ mood amplification in the 'elated' imagery condition was most pronounced for active affective states. This experimental model of BPDS-relevant mood amplification shows evidence that positive mental imagery drives changes in affect in the high MDQ group in a targeted manner. Findings inform cognitive mechanisms of mood amplification, and spotlight prevention strategies targeting elated imagery, while potentially retaining calm imagery to preserve adaptive positive emotionality.

Mental health status of healthcare workers assisted in Hubei during the initial outbreak of COVID-19 and their influencing factors: a prospective cohort study

OBJECTIVES

The COVID-19 outbreak beginning in late 2019 has resulted in negative emotions among the public. However, many healthcare workers risked their lives by voluntarily travelling to the worst-hit area, Hubei Province, to support antipandemic work. This study explored the mental health changes in these healthcare workers and tried to discover the influencing factors.

DESIGN

A longitudinal online survey was begun on 8 February 2020, using the snowball sampling method, and this first phase ended on 22 February 2020 (T1). The follow-up survey was conducted from 8 February to 22 February 2021 (T2).

SETTING

Healthcare workers from outside of the Hubei area who went to the province to provide medical assistance.

PARTICIPANTS

963 healthcare workers who completed both surveys.

MEASURES

Self-Rating Scale of Sleep (SRSS), Generalised Anxiety Scale (GAD-7) and 9-item Patient Health Questionnaire (PHQ-9).

RESULTS

There were no significant differences in the SRSS scores or in the GAD-7 scores between T1 and T2 (t=0.994, 0.288; p>0.05). However, the PHQ-9 score at T2 was significantly higher than the score at T1 (t=-10.812, p<0.001). Through multiple linear regression analysis, we found that the following traits could predict higher GAD-7 and PHQ-9 scores at T2: male sex, single marital status, occupation of nurse, lower professional technical titles, healthcare workers having a history of psychosis, treating seriously ill patients, having relatively poor self-perceived health, caring for patients who died and having family members who had been infected with COVID-19.

CONCLUSIONS

The results indicate that the depression levels of these special healthcare workers increased in the long term, and the initial demographics and experiences related to the pandemic played an important role in predicting their long-term poor mental health. In the future, more appropriate psychological decompression training should be provided for these special healthcare workers.

Cardiovascular disease risk in people with severe mental disorders: an update and call for action

PURPOSE OF REVIEW

Cardiovascular disease (CVD) is a major cause of premature death in people with severe mental disorders (SMDs). This review provides an update on the level of CVD mortality and morbidity, as well as the socioeconomic, psychosocial and genetic factors associated with the comorbidity, and offer directions for improved interventions to reduce CVD in SMDs.

RECENT FINDINGS

The level of CVD mortality and morbidity has sustained high in people with SMDs during the past decades, but the causal mechanism must be further elucidated. Psychosocial and socioeconomic challenges are frequent in SMDs as well as in CVD. Further, recent studies have revealed genetic variants jointly associated with SMDs, CVD risk and social factors. These findings highlight the need for more targeted interventions, prediction tools and psychosocial approaches to comorbid CVD in SMDs.

SUMMARY

The level of CVD comorbidity remains high in SMDs, indicating that most people with SMDs have not benefitted from recent medical advances. A complex interplay between genetic and social vulnerability to CVD, which differs across subgroups of patients, seems to be involved. Further research is required to meet the urgent need for earlier, more efficient intervention approaches and preventive strategies for comorbid CVD in SMD.

The impact of COVID-19-related quarantine on psychological outcomes in patients after cardiac intervention: a multicenter longitudinal study

Mandatory quarantine during the COVID-19 pandemic had substantial negative consequences on psychological health in the general population. Depression, anxiety, and insomnia were reported to increase the morbidity and mortality risk in cardiac patients after cardiac interventions. Nonetheless, a gap in the evidence appeared regarding the effects of COVID-19-related quarantine on psychological outcomes in patients after cardiac interventions. The present study aimed to longitudinally investigate the effects of quarantine on depressive, anxiety, and insomnia symptoms in a group of patients who underwent cardiac intervention. Seventy-three patients admitted for cardiac rehabilitation completed a psychological assessment before and a reassessment after the quarantine and were included in the quarantine group. The control group included 76 patients who completed both evaluations before the quarantine. Depressive (Beck Depression Inventory-II; BDI-II), anxiety (Beck Anxiety Inventory-II; BAI), and insomnia (Sleep Condition Indicator; SCI) symptoms were evaluated in both groups at one (assessment) and eight (reassessment) months after cardiac intervention. The statistical analyses revealed that at reassessment, the quarantine group showed higher global depressive, anxiety, and insomnia symptoms than the control group and increased cognitive symptoms of depression. A higher presence of clinically relevant depressed patients was seen in the quarantine group. The present results showed that the COVID-19-related mandatory quarantine negatively affected psychological outcomes in patients after cardiac intervention, increasing the probability for these patients to be depressed. This, in turn, could influence patients' health in a critical period for morbidity and mortality risk. This underlines the priority of integrating and improving targeted mental health support as the pandemic continues, especially for cardiac patients.

Joint associations of depression, genetic susceptibility and the area of residence for coronary heart disease incidence

BACKGROUND

Depression is a risk factor for coronary heart disease (CHD), but less is known whether genetic susceptibility to CHD or regional-level social indicators modify this association.

METHODS

Risk factors of CHD including a Polygenic Risk Score (PRS) were measured for 19 999 individuals residing in Finland in 1997, 2002, 2007 and 2012 (response rates 60%-75%). During the register-based follow-up until 2015, there were 1381 fatal and non-fatal incident CHD events. Unemployment rate, degree of urbanisation and crime rate of the municipality of residence were used as regional level social indicators. HRs were calculated using register-based antidepressant purchases as a non-reversible time-dependent covariate.

RESULTS

Those having depression and in the highest quartile of PRS had somewhat higher CHD risk than predicted only by the main effects of depression and PRS (HR for interaction 1.53, 95% CI 0.95 to 2.45). Depression was moderately associated with CHD in high crime (HR 1.51, 95% CI 1.20 to 1.90) and weakly in low crime regions (HR 1.07, 95% CI 0.86 to 1.33; p value of interaction=0.087). Otherwise, we did not found evidence for interactions.

CONCLUSIONS

Those having both depression and high genetic susceptibility need a special attention in healthcare for CHD.

The co-occurrence of multidimensional loneliness with depression, social anxiety and paranoia in non-clinical young adults: A latent profile analysis

INTRODUCTION

Loneliness is a negative experience arising from a mismatch between perceived and actual social relationships. Several dimensions of loneliness have been suggested, namely intimate, relational and collective loneliness. Loneliness has been linked to poorer mental health, with its co-occurrence with depression, social anxiety, and paranoia most widely reported. While expressions of these symptoms are heterogeneous across individuals in the non-clinical population, it remains unclear how these symptoms co-occur with one another and with various dimensions of loneliness. It is also of interest how trait factors such as core schemas about self/others may moderate these relationships between loneliness and co-occurring symptoms.

METHODS

A demographically diverse sample of young adults was recruited from multiple sources. The validated sample consisted of 2,089 participants (68.4% female), who completed an online survey consisting of questionnaires assessing levels of multidimensional loneliness, depression, social anxiety, paranoia, core schemas, and demographic characteristics. Latent profile analysis (LPA) was used to identify distinct profiles of loneliness and the three symptoms. Positive and negative core schemas about self and others were modeled as predictors of these profiles.

RESULTS

Five distinct profiles were identified. Profile 1 had low levels across all symptoms and dimensions of loneliness (n = 1,273, 60.9%). Profiles 2-5 were elevated on dimensions of loneliness, and were heightened in depression (n = 189, 9.0%), social anxiety (n = 206, 9.9%), paranoia (n = 198, 9.5%), and all symptoms (n = 223, 10.7%), respectively. Relative to Profile 1, the other four profiles scored higher on negative-self (adjusted ORs = 1.36-1.49, ps < 0.001) and negative-other schemas (adjusted ORs = 1.24-1.44, ps < 0.001), and lower on positive-self (adjusted ORs = 0.82-0.85, ps < 0.001) and positive-other schemas (adjusted ORs = 0.81-0.90, ps < 0.001).

CONCLUSION

More marked intimate, relational and collective loneliness were evident across profiles that had heightened depression, social anxiety and/or paranoia, suggesting that loneliness may serve as a general risk factor for these psychopathologies. Our findings shed light on the heterogeneity of the co-occurrence of loneliness and various mental health difficulties in non-clinical young adults. Core schemas are suggested to be putative psychological mechanisms underlying their co-occurrence and even development.

Prominent health problems, socioeconomic deprivation, and higher brain age in lonely and isolated individuals: A population-based study

Loneliness is linked to increased risk for Alzheimer's disease, but little is known about factors potentially contributing to adverse brain health in lonely individuals. In this study, we used data from 24,867 UK Biobank participants to investigate risk factors related to loneliness and estimated brain age based on neuroimaging data. The results showed that on average, individuals who self-reported loneliness on a single yes/no item scored higher on neuroticism, depression, social isolation, and socioeconomic deprivation, performed less physical activity, and had higher BMI compared to individuals who did not report loneliness. In line with studies pointing to a genetic overlap of loneliness with neuroticism and depression, permutation feature importance ranked these factors as the most important for classifying lonely vs. not lonely individuals (ROC AUC = 0.83). While strongly linked to loneliness, neuroticism and depression were not associated with brain age estimates. Conversely, objective social isolation showed a main effect on brain age, and individuals reporting both loneliness and social isolation showed higher brain age relative to controls - as part of a prominent risk profile with elevated scores on socioeconomic deprivation and unhealthy lifestyle behaviours, in addition to neuroticism and depression. While longitudinal studies are required to determine causality, this finding may indicate that the combination of social isolation and a genetic predisposition for loneliness involves a risk for adverse brain health. Importantly, the results underline the complexity in associations between loneliness and adverse health outcomes, where observed risks likely depend on a combination of interlinked variables including genetic as well as social, behavioural, physical, and socioeconomic factors.

Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes

Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208-795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20-22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.