Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

Investigating the Link between Psychological Well-Being and Early-Stage Age-Related Macular Degeneration: A Mendelian Randomization Analysis

PURPOSE

While some studies have started to focus on the link between psychological well-being and age-related macular degeneration (AMD), the relationship remains uncertain. Our research aims to provide new insights into this association, laying a foundation for future interventions and addressing existing knowledge gaps.

METHODS

We utilized the "TwoSampleMR" package in R for a bidirectional Mendelian randomization analysis of psychological well-being (subjective well-being, depression, neuroticism, and Sensitivity to Environmental Stress and Adversity) and early-stage AMD. Causal effects were estimated using the inverse-variance weighted method, and additional methods included weighted median and MR-Egger regression. Sensitivity analyses included Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO, and leave-one-out analysis.

RESULTS

The study found that the population with genetic predisposition to neuroticism had a 39.7% lower risk of early-stage AMD (OR = 0.603, 95% CI = 0.385-0.945, p = 0.027). Conversely, the population with genetic predisposition to subjective well-being had a 3.2% increased risk of early-stage AMD (OR = 1.032, 95% CI = 1.003-1.063, p = 0.029). No significant causal relationships were found from depression or Sensitivity to Environmental Stress and Adversity to early-stage AMD, nor from early-stage AMD to psychological well-being.

CONCLUSION

This study provides preliminary evidence that the relationship between psychological well-being and early-stage AMD may be complex and multifaceted. It suggests that moderate neuroticism levels might reduce early-stage AMD risk through health behaviors, pathophysiological mechanisms, and other factors, while high subjective well-being levels might increase this risk similarly. However, these findings are insufficient for preventive strategies due to a lack of substantial evidence and still require extensive experimental research for further validation.

The association between overweight and varying degrees of obesity with subjective well-being and depressive symptoms: A two sample Mendelian randomization study

OBJECTIVE

This study utilized the Mendelian randomization (MR) method to elucidate the causal relationship between genetically predicted overweight and various degrees of obesity with depressive symptoms and subjective well-being (SWB).

METHODS

Pooled genome-wide association studies (GWAS) data for overweight (BMI ≥ 25 kg/m2), class 1 obesity (BMI ≥ 30 kg/m2), and class 2 obesity (BMI ≥ 35 kg/m2) were used as exposures. Summary GWAS data for depressive symptoms and SWB were used as outcomes. Multiple MR methods, primarily inverse-variance weighted (IVW), were applied, and sensitivity analyses were conducted to assess heterogeneity and pleiotropy.

RESULTS

The MR analysis provided evidence that genetically predicted overweight(IVW β = 0.033; 95 %CI 0.008-0.057; P = 0.010) and class 1 obesity(IVW β = -0.033; 95 %CI -0.047 - -0.020; P < 0.001) were causally associated with increased depressive symptoms. Genetically predicted class 2 obesity(IVW β = 1.428; 95 %CI 1.193-1.710; P < 0.001) were associated with reduced SWB. There was no strong evidence of a causal association between genetically predicted overweight and class 1 obesity with SWB. Similarly, genetically predicted class 2 and class 3 obesity did not show strong evidence of a causal association with depressive symptoms. Sensitivity analysis revealed relationships of a similar magnitude.

CONCLUSION

This genetically informed MR study suggests that Overweight and class 1 obesity may causally increased depressive symptoms but not decrease SWB. In contrast, class 2 obesity may causally decrease SWB but not increase depressive symptoms.

Mendelian randomization analysis separated the independent impact of childhood obesity and adult obesity on socioeconomic status, psychological status, and substance use

Background

Obesity is linked to a variety of psychosocial and behavioral outcomes but the causalities remain unclear yet. Determining the causalities and distinguishing between the separate effects of childhood and adult obesity is critical to develop more targeted strategies to prevent adverse outcomes.

Methods

With single nucleotide polymorphisms (SNPs) used as genetic variables, we employed univariable Mendelian randomization (UVMR) to explore the causalities between childhood and adult body mass index (BMI) and socioeconomic status, psychological status, and substance use. Genetic data for childhood and adult BMI came respectively from 47,541 children aged 10 years and 339,224 adult participants. The outcome data were obtained from corresponding consortia. The direct impact of childhood BMI and adult BMI was then examined using a multivariable MR (MVMR).

Results

UVMR found that higher childhood BMI was linked causally to lower household income (β = -0.06, 95 % CI = -0.08 ∼ -0.03, P = 4.86 × 10-5), decreased subjective well-being (β = -0.07, 95 % CI = -0.12 ∼ -0.03, P = 1.74 × 10-3), and an increased tendency of smoking regularly (OR = 1.12, 95 % CI = 1.04-1.20, P = 1.52 × 10-3). Similar results were observed in adult BMI. MVMR further revealed that after adjusting with adult BMI, childhood BMI remained an isolated impact on household income. The impacts of adult BMI on the outcomes were diminished when adjusting with childhood BMI.

Conclusion

The findings indicate the impacts of childhood obesity on subjective well-being and smoking initiation are a result of higher BMI sustaining into adulthood, whereas the effect on household income is attributed to a lasting impact of obesity in early life. The results would help facilitate more targeted strategies for obesity management to prevent adverse outcomes.

A genome-wide association study of occupational creativity and its relations with well-being and career success

Creativity is one defining characteristic of human species. There have been mixed findings on how creativity relates to well-being, and little is known about its relationship with career success. We conduct a large-scale genome-wide association study to examine the genetic architecture of occupational creativity, and its genetic correlations with well-being and career success. The SNP-h2 estimates range from 0.08 (for managerial creativity) to 0.22 (for artistic creativity). We record positive genetic correlations between occupational creativity with autism, and positive traits and well-being variables (e.g., physical height, and low levels of neuroticism, BMI, and non-cancer illness). While creativity share positive genetic overlaps with indicators of high career success (i.e., income, occupational status, and job satisfaction), it also has a positive genetic correlation with age at first birth and a negative genetic correlation with number of children, indicating creativity-related genes may reduce reproductive success.

Executive Function and Impulsivity Predict Distinct Genetic Variance in Internalizing Problems, Externalizing Problems, Thought Disorders, and Compulsive Disorders: A Genomic Structural Equation Modeling Study

Individual differences in self-control predict many health and life outcomes. Building on twin literature, we used genomic structural equation modeling to test the hypothesis that genetic influences on executive function and impulsivity predict independent variance in mental health and other outcomes. The impulsivity factor (comprising urgency, lack of premeditation, and other facets) was only modestly genetically correlated with low executive function (rg =.13). Controlling for impulsivity, low executive function was genetically associated with increased internalizing (βg =.15), externalizing (βg =.13), thought disorders (βg =.38), compulsive disorders (βg =.22), and chronotype (βg =.11). Controlling for executive function, impulsivity was positively genetically associated with internalizing (βg =.36), externalizing (βg =.55), body mass index (βg =.26), and insomnia (βg =.35), and negatively genetically associated with compulsive disorders (βg = -.17). Executive function and impulsivity were both genetically correlated with general cognitive ability and educational attainment. This work suggests that executive function and impulsivity are genetically separable and show independent associations with mental health.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Pharmacogenomic scores in psychiatry: systematic review of current evidence

In the past two decades, significant progress has been made in the development of polygenic scores (PGSs). One specific application of PGSs is the development and potential use of pharmacogenomic- scores (PGx-scores) to identify patients who can benefit from a specific medication or are likely to experience side effects. This systematic review comprehensively evaluates published PGx-score studies in psychiatry and provides insights into their potential clinical use and avenues for future development. A systematic literature search was conducted across PubMed, EMBASE, and Web of Science databases until 22 August 2023. This review included fifty-three primary studies, of which the majority (69.8%) were conducted using samples of European ancestry. We found that over 90% of PGx-scores in psychiatry have been developed based on psychiatric and medical diagnoses or trait variants, rather than pharmacogenomic variants. Among these PGx-scores, the polygenic score for schizophrenia (PGSSCZ) has been most extensively studied in relation to its impact on treatment outcomes (32 publications). Twenty (62.5%) of these studies suggest that individuals with higher PGSSCZ have negative outcomes from psychotropic treatment - poorer treatment response, higher rates of treatment resistance, more antipsychotic-induced side effects, or more psychiatric hospitalizations, while the remaining studies did not find significant associations. Although PGx-scores alone accounted for at best 5.6% of the variance in treatment outcomes (in schizophrenia treatment resistance), together with clinical variables they explained up to 13.7% (in bipolar lithium response), suggesting that clinical translation might be achieved by including PGx-scores in multivariable models. In conclusion, our literature review found that there are still very few studies developing PGx-scores using pharmacogenomic variants. Research with larger and diverse populations is required to develop clinically relevant PGx-scores, using biology-informed and multi-phenotypic polygenic scoring approaches, as well as by integrating clinical variables with these scores to facilitate their translation to psychiatric practice.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR) = 1.24, p = 3.88 × 10-12; SZ OR = 1.09, p = 2.44 × 10-20). However, while the effect of mental distress (OR = 1.17, p = 1.02 × 10-4) and risk-taking (OR = 1.52, p = 0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

Causality between Sarcopenia and Depression: A Bidirectional Mendelian Randomization Study

BACKGROUND

Numerous observational studies have suggested a correlation between sarcopenia and depression, but the nature of this relationship requires further investigation.

METHODS

This study employed bidirectional Mendelian randomization to explore this connection. Data from genome-wide association studies were used, encompassing measures of sarcopenia and mental factors, including depression and emotional states. The initial analysis concentrated on the impact of depression on sarcopenia, and then it examined the reverse relationship. The same methodology was applied to emotional data for validation.

RESULTS

The results indicated a reciprocal causation between sarcopenia and depression, even when emotional state data were considered. Various emotions can impact sarcopenia, and in turn, sarcopenia can affect emotions, except subjective well-being. These findings highlight a cyclic deterioration between sarcopenia and depression, with a link to negative emotions and a partially ameliorative effect of subjective well-being on sarcopenia.

CONCLUSIONS

In summary, this study sheds light on the interplay between psychiatric factors and sarcopenia, offering insights into intervention and prevention strategies.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology

A family history of depression is a well-documented risk factor for offspring psychopathology. However, the genetic mechanisms underlying the intergenerational transmission of depression remain unclear. We used genetic, family history, and diagnostic data from 11,875 9-10 year-old children from the Adolescent Brain Cognitive Development study. We estimated and investigated the children's polygenic scores (PGSs) for 30 distinct traits and their association with a family history of depression (including grandparents and parents) and the children's overall psychopathology through logistic regression analyses. We assessed the role of polygenic risk for psychiatric disorders in mediating the transmission of depression from one generation to the next. Among 11,875 multi-ancestry children, 8,111 participants had matching phenotypic and genotypic data (3,832 female [47.2%]; mean (SD) age, 9.5 (0.5) years), including 6,151 [71.4%] of European ancestry). Greater PGSs for depression (estimate = 0.129, 95% CI = 0.070-0.187) and bipolar disorder (estimate = 0.109, 95% CI = 0.051-0.168) were significantly associated with higher family history of depression (Bonferroni-corrected P < .05). Depression PGS was the only PGS that significantly associated with both family risk and offspring's psychopathology, and robustly mediated the impact of family history of depression on several youth psychopathologies including anxiety disorders, suicidal ideation, and any psychiatric disorder (proportions mediated 1.39%-5.87% of the total effect on psychopathology; FDR-corrected P < .05). These findings suggest that increased polygenic risk for depression partially mediates the associations between family risk for depression and offspring psychopathology, showing a genetic basis for intergenerational transmission of depression. Future approaches that combine assessments of family risk with polygenic profiles may offer a more accurate method for identifying children at elevated risk.

Genetic Correlates of Treatment-Resistant Depression: Insights from Polygenic Scores Across Cognitive, Temperamental, and Sleep Traits in the All of US cohort

Background

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable economic and social burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits, and to explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us Research Program (AoU).

Methods

Data from 292,663 participants in the AoU were analyzed using a case-cohort design. Treatment resistant depression (TRD), treatment responsive Major Depressive Disorder (trMDD), and all others who have no formal diagnosis of Major Depressive Disorder (non-MDD) were identified through diagnostic codes and prescription patterns. Polygenic scores (PGS) for 61 unique traits from seven domains were used and logistic regressions were conducted to assess associations between PGS and TRD. Finally, Cox proportional hazard models were used to explore the predictive value of PGS for progression rate from the diagnostic event of Major Depressive Disorder (MDD) to TRD.

Results

In the discovery set (104128 non-MDD, 16640 trMDD, and 4177 TRD), 44 of 61 selected PGS were found to be significantly associated with MDD, regardless of treatment responsiveness. Eleven of them were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia and specific neuroticism traits were associated with increased TRD risk (OR range from 1.05 to 1.15), while higher education and intelligence scores were protective (ORs 0.88 and 0.91, respectively). These associations are consistent across two other independent sets within AoU (n = 104,388 and 63,330). Among 28,964 individuals tracked over time, 3,854 developed TRD within an average of 944 days (95% CI: 883 ~ 992 days) after MDD diagnosis. All eleven previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD. Thus, those having higher education PGS would experiencing slower conversion rates than those who have lower education PGS with hazard ratios in 0.79 (80th versus 20th percentile, 95% CI: 0.74 ~ 0.85). Those who had higher insomnia PGS experience faster conversion rates than those who had lower insomnia PGS, with hazard ratios in 1.21 (80th versus 20th percentile, 95% CI: 1.13 ~ 1.30).

Conclusions

Our results indicate that genetic predisposition related to neuroticism, cognitive function, and sleep patterns play a significant role in the development of TRD. These findings underscore the importance of considering genetic and psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance our understanding of pathways leading to treatment resistance.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis

AIM

To investigate the relationship and potential causality between biological ageing and periodontitis.

MATERIALS AND METHODS

We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis.

RESULTS

We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration.

CONCLUSIONS

Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches

The internalizing construct captures shared variance underlying risk for mood and anxiety disorders. Internalizing factors based on diagnoses (or symptoms) of major depressive disorder (MDD) and generalized anxiety disorder (GAD) are well established. Studies have also integrated self-reported measures of associated traits (e.g., questionnaires assessing neuroticism, worry, and rumination) onto these factors, despite having not tested the assumption that these measures truly capture the same sets of risk factors. This study examined the overlap among both sets of measures using converging approaches. First, using genomic structural equation modeling, we constructed internalizing factors based on genome-wide association studies (GWASs) of internalizing diagnoses (e.g., MDD) and traits associated with internalizing (neuroticism, loneliness, and reverse-scored subjective well-being). Results indicated the two factors were highly (rg = .79) but not perfectly genetically correlated (rg < 1.0, p < .001). Second, we constructed similar latent factors in a combined twin/adoption sample of adults from the Colorado Adoption/Twin Study of Lifespan Behavioral Development and Cognitive Aging. Again, both factors demonstrated strong overlap at the level of genetic (rg = .76, 95% confidence interval [CI] [0.40, 0.97]) and nonshared environmental influences (re = .80, 95% CI [0.53, 1.0]). Shared environmental influences were estimated near zero for both factors. Our findings are consistent with current frameworks of psychopathology, though they suggest there are some unique genetic influences captured by internalizing diagnosis compared to trait measures, with potentially more nonadditive genetic influences on trait measures. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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.

Current Update on Categorization of Migraine Subtypes on the Basis of Genetic Variation: a Systematic Review

Migraine is a complex neurovascular disorder that is characterized by severe behavioral, sensory, visual, and/or auditory symptoms. It has been labeled as one of the ten most disabling medical illnesses in the world by the World Health Organization (Aagaard et al Sci Transl Med 6(237):237ra65, 2014). According to a recent report by the American Migraine Foundation (Shoulson et al Ann Neurol 25(3):252-9, 1989), around 148 million people in the world currently suffer from migraine. On the basis of presence of aura, migraine is classified into two major subtypes: migraine with aura (Aagaard et al Sci Transl Med 6(237):237ra65, 2014) and migraine without aura. (Aagaard K et al Sci Transl Med 6(237):237ra65, 2014) Many complex genetic mechanisms have been proposed in the pathophysiology of migraine but specific pathways associated with the different subtypes of migraine have not yet been explored. Various approaches including candidate gene association studies (CGAS) and genome-wide association studies (Fan et al Headache: J Head Face Pain 54(4):709-715, 2014). have identified the genetic markers associated with migraine and its subtypes. Several single nucleotide polymorphisms (Kaur et al Egyp J Neurol, Psychiatry Neurosurg 55(1):1-7, 2019) within genes involved in ion homeostasis, solute transport, synaptic transmission, cortical excitability, and vascular function have been associated with the disorder. Currently, the diagnosis of migraine is majorly behavioral with no focus on the genetic markers and thereby the therapeutic intervention specific to subtypes. Therefore, there is a need to explore genetic variants significantly associated with MA and MO as susceptibility markers in the diagnosis and targets for therapeutic interventions in the specific subtypes of migraine. Although the proper characterization of pathways based on different subtypes is yet to be studied, this review aims to make a first attempt to compile the information available on various genetic variants and the molecular mechanisms involved with the development of MA and MO. An attempt has also been made to suggest novel candidate genes based on their function to be explored by future research.

Psychological distress and uterine fibroids: a bidirectional two-sample mendelian randomization study

BACKGROUND

Observational data indicates a connection between emotional discomfort, such as anxiety and depression, and uterine fibroids (UFs). However, additional investigation is required to establish the causal relationship between them. Hence, we assessed the reciprocal causality between four psychological disorders and UFs utilizing two-sample Mendelian randomization (MR).

METHODS

To evaluate the causal relationship between four types of psychological distress (depressive symptoms, severe depression, anxiety or panic attacks, mood swings) and UFs, bidirectional two-sample MR was employed, utilizing single nucleotide polymorphisms (SNPs) associated with these conditions. Both univariate MR (UVMR) and multivariate MR (MVMR) primarily applied inverse variance weighted (IVW) as the method for estimating potential causal effects. Complementary approaches such as MR Egger, weighted median, simple mode, and weighted mode were utilized to validate the findings. To assess the robustness of our MR results, we conducted sensitivity analyses using Cochran's Q-test and the MR Egger intercept test.

RESULTS

The results of our UVMR analysis suggest that genetic predispositions to depressive symptoms (Odds Ratio [OR] = 1.563, 95% Confidence Interval [CI] = 1.209-2.021, P = 0.001) and major depressive disorder (MDD) (OR = 1.176, 95% CI = 1.044-1.324, P = 0.007) are associated with an increased risk of UFs. Moreover, the IVW model showed a nominally significant positive correlation between mood swings (OR: 1.578; 95% CI: 1.062-2.345; P = 0.024) and UFs risk. However, our analysis did not establish a causal relationship between UFs and the four types of psychological distress. Even after adjusting for confounders like body mass index (BMI), smoking, alcohol consumption, and number of live births in the MVMR, the causal link between MDD and UFs remained significant (OR = 1.217, 95% CI = 1.039-1.425, P = 0.015).

CONCLUSIONS

Our study presents evidence supporting the causal relationship between genetic susceptibility to MDD and the incidence of UFs. These findings highlight the significance of addressing psychological health issues, particularly depression, in both the prevention and treatment of UFs.

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.

Genetic propensity to depression and the role of partnership status

Social relationships and genetic propensity are known to affect depression risk, but their joint effects are poorly understood. This study examined the association of a polygenic index for depression with time to antidepressant (AD) purchasing and the moderating role of partnership status. We analysed data from 30,192 Finnish individuals who participated in the FINRISK and Health 2000 and 2011 surveys and had register and medication data available. We measured genetic risk with a polygenic index (PGI) for depression. Depression was assessed through antidepressant purchases. We estimated an accelerated failure time model with partnership status as time-varying and different sets of confounder adjustments. The predicted cumulative hazard of antidepressant purchasing varied across PGI and partnership status. At follow-up year 10, being widowed was associated with the largest cumulative hazard of 0.34 (95%CI: 0.28-0.39) in the 80th and 0.20 (95%CI: 0.17-0.23) in the 20th PGI percentile, followed by divorced, single, married and cohabiting. Cohabiting was associated with a cumulative hazard of 0.19 (95%CI: 0.16-0.23) in the 80th and 0.11 (95%CI: 0.1-0.13) in the 20th PGI percentile. We found no evidence for an interaction between the PGI and partnership status. Results were robust to different model specifications, gender stratification, and the choice of PGI. Although antidepressant purchasing correlated with both PGI and partnership status, we found no evidence that partnership status could partially offset or amplify the association between the PGI for depression and antidepressant purchasing incidence.

Causal effects of childhood obesity on neuroticism and subjective well-being: A two-sample Mendelian randomization study

BACKGROUND

Childhood obesity is linked to both neuroticism and subjective wellbeing (SWB); however, the causal relations between them remain unclear.

METHODS

Two-sample Mendelian randomization (MR) analysis was applied to determine the causal effects of childhood BMI (n = 39,620) on neuroticism (n = 366,301) and SWB (n = 298,420) using summary statistics from large scale genome-wide association studies (GWASs). Inverse-variance weighting (IVW), weighted mode, weighted median, and MR-Egger approaches were used to estimate the causal effects. Sensitivity analyses including the Cochran's Q statistics, MR-Egger intercept test, MR-PRESSO global test, and the leave-one-out (LOO) analysis were used to assess potential heterogeneity and horizontal pleiotropy. Two-step MR mediation analysis was employed to explore the potential mediation effects of neuroticism on the causal relationship between childhood BMI and SWB.

RESULTS

Our study revealed that genetically predicted higher childhood BMI was causally associated with increased neuroticism (beta = 0.045, 95%CI = 0.013,0.077, p = 6.066e-03) and reduced SWB (beta = -0.059, 95%CI = -0.093,-0.024, p = 9.585e-04). Sensitivity analyses didn't detect any significant heterogeneity and horizontal pleiotropy (all p > 0.05). Additionally, the two-step MR mediation analysis indicated that the causal relationship between childhood BMI and SWB was partially mediated by neuroticism (proportion of mediation effects in total effects: 21.3 %, 95%CI: 5.4 % to 37.2, p = 0.0088).

CONCLUSION

Genetically proxy for higher childhood BMI was associated with increased neuroticism and reduced SWB. Further studies were warranted to investigate the underlying molecular mechanisms and potential use of weight management for improving personality and SWB.

Defining a vitamin A5/X specific deficiency - vitamin A5/X as a critical dietary factor for mental health

A healthy and balanced diet is an important factor to assure a good functioning of the central and peripheral nervous system. Retinoid X receptor (RXR)-mediated signaling was identified as an important mechanism of transmitting major diet-dependent physiological and nutritional signaling such as the control of myelination and dopamine signalling. Recently, vitamin A5/X, mainly present in vegetables as provitamin A5/X, was identified as a new concept of a vitamin which functions as the nutritional precursor for enabling RXR-mediated signaling. The active form of vitamin A5/X, 9-cis-13,14-dehydroretinoic acid (9CDHRA), induces RXR-activation, thereby acting as the central switch for enabling various heterodimer-RXR-signaling cascades involving various partner heterodimers like the fatty acid and eicosanoid receptors/peroxisome proliferator-activated receptors (PPARs), the cholesterol receptors/liver X receptors (LXRs), the vitamin D receptor (VDR), and the vitamin A(1) receptors/retinoic acid receptors (RARs). Thus, nutritional supply of vitamin A5/X might be a general nutritional-dependent switch for enabling this large cascade of hormonal signaling pathways and thus appears important to guarantee an overall organism homeostasis. RXR-mediated signaling was shown to be dependent on vitamin A5/X with direct effects for beneficial physiological and neuro-protective functions mediated systemically or directly in the brain. In summary, through control of dopamine signaling, amyloid β-clearance, neuro-protection and neuro-inflammation, the vitamin A5/X - RXR - RAR - vitamin A(1)-signaling might be "one of" or even "the" critical factor(s) necessary for good mental health, healthy brain aging, as well as for preventing drug addiction and prevention of a large array of nervous system diseases. Likewise, vitamin A5/X - RXR - non-RAR-dependent signaling relevant for myelination/re-myelination and phagocytosis/brain cleanup will contribute to such regulations too. In this review we discuss the basic scientific background, logical connections and nutritional/pharmacological expert recommendations for the nervous system especially considering the ageing brain.

Unraveling the complex role of MAPT-containing H1 and H2 haplotypes in neurodegenerative diseases

A ~ 1 Mb inversion polymorphism exists within the 17q21.31 locus of the human genome as direct (H1) and inverted (H2) haplotype clades. This inversion region demonstrates high linkage disequilibrium, but the frequency of each haplotype differs across ancestries. While the H1 haplotype exists in all populations and shows a normal pattern of genetic variability and recombination, the H2 haplotype is enriched in European ancestry populations, is less frequent in African ancestry populations, and nearly absent in East Asian ancestry populations. H1 is a known risk factor for several neurodegenerative diseases, and has been associated with many other traits, suggesting its importance in cellular phenotypes of the brain and entire body. Conversely, H2 is protective for these diseases, but is associated with predisposition to recurrent microdeletion syndromes and neurodevelopmental disorders such as autism. Many single nucleotide variants and copy number variants define H1/H2 haplotypes and sub-haplotypes, but identifying the causal variant(s) for specific diseases and phenotypes is complex due to the extended linkage equilibrium. In this review, we assess the current knowledge of this inversion region regarding genomic structure, gene expression, cellular phenotypes, and disease association. We discuss recent discoveries and challenges, evaluate gaps in knowledge, and highlight the importance of understanding the effect of the 17q21.31 haplotypes to promote advances in precision medicine and drug discovery for several diseases.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

Functional classes of SNPs related to psychiatric disorders and behavioral traits contrast with those related to neurological disorders

We investigated the functional classes of genomic regions containing SNPS contributing most to the SNP-heritability of important psychiatric and neurological disorders and behavioral traits, as determined from recent genome-wide association studies. We employed linkage-disequilibrium score regression with several brain-specific genomic annotations not previously utilized. The classes of genomic annotations conferring substantial SNP-heritability for the psychiatric disorders and behavioral traits differed systematically from the classes associated with neurological disorders, and both differed from the classes enriched for height, a biometric trait used here as a control outgroup. The SNPs implicated in these psychiatric disorders and behavioral traits were highly enriched in CTCF binding sites, in conserved regions likely to be enhancers, and in brain-specific promoters, regulatory sites likely to affect responses to experience. The SNPs relevant for neurological disorders were highly enriched in constitutive coding regions and splice regulatory sites.

An exploration into the causal relationships between educational attainment, intelligence, and wellbeing: an observational and two-sample Mendelian randomisation study

Educational attainment is associated with a range of positive outcomes, yet its impact on wellbeing is unclear, and complicated by high correlations with intelligence. We use genetic and observational data to investigate for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Results from our multivariable Mendelian randomisation demonstrated a positive causal impact of a genetic predisposition to higher educational attainment on wellbeing that remained after accounting for intelligence, and a negative impact of intelligence that was independent of educational attainment. Observational analyses suggested that these associations may be subject to sex differences, with benefits to wellbeing greater for females who attend higher education compared to males. For intelligence, males scoring more highly on measures related to happiness were those with lower intelligence. Our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities, with benefits likely to be greater for females compared to males.

Divergent gene expression patterns in alcohol and opioid use disorders lead to consistent alterations in functional networks within the Dorsolateral Prefrontal Cortex

Substance Use Disorders (SUDs) manifest as persistent drug-seeking behavior despite adverse consequences, with Alcohol Use Disorder (AUD) and Opioid Use Disorder (OUD) representing prevalent forms associated with significant mortality rates and economic burdens. The co-occurrence of AUD and OUD is common, necessitating a deeper comprehension of their intricate interactions. While the causal link between these disorders remains elusive, shared genetic factors are hypothesized. Leveraging public datasets, we employed genomic and transcriptomic analyses to explore conserved and distinct molecular pathways within the dorsolateral prefrontal cortex associated with AUD and OUD. Our findings unveil modest transcriptomic overlap at the gene level between the two disorders but substantial convergence on shared biological pathways. Notably, these pathways predominantly involve inflammatory processes, synaptic plasticity, and key intracellular signaling regulators. Integration of transcriptomic data with the latest genome-wide association studies (GWAS) for problematic alcohol use (PAU) and OUD not only corroborated our transcriptomic findings but also confirmed the limited shared heritability between the disorders. Overall, our study indicates that while alcohol and opioids induce diverse transcriptional alterations at the gene level, they converge on select biological pathways, offering promising avenues for novel therapeutic targets aimed at addressing both disorders simultaneously.

Mediating effect of depressive symptoms on the relationship of chronic pain and cardiovascular diseases among Chinese population: Evidence from the CHARLS

OBJECTIVE

Few studies have examined the direct or indirect effect of chronic pain on cardiovascular diseases (CVD) within Chinese population. The objective aimed to investigate the mediating role of depressive symptoms between chronic pain and CVD.

METHODS

6522 participants from China Health and Retirement Longitudinal Study were included in this retrospective cohort study. The main endpoint was the occurrence of CVD. Weighted multivariate logistic regression was used to assess the association between chronic pain and depressive symptoms. Distribution-of-product method was employed to examine the mediation effect of depressive symptoms. Subgroup analyses were performed.

RESULTS

219 developed CVD at the end of follow-up period. After adjusting all confounding variables, chronic pain was associated with increased risk of depressive symptoms in total population [odds ratio (OR) = 3.85, 95%confidence interval (CI): 3.35-4.42]. Among total population, there was a positive association of chronic pain and CVD [risk ratio (RR)a = 2.00, 95% CI: 1.33-3.00] (total effect). After further adjusting depressive symptoms, the association between chronic pain and CVD was significant (RRb = 1.67, 95% CI: 1.16-2.41) (direct effect). According to the distribution-of-product test, we observed a mediating effect of depressive symptoms on the relationship between chronic pain and CVD with the percentage of mediation of 32.8%. The mediating effect of depression was observed in individuals of aged45-65 years old, female participants, participants who never drinking and not have hypertension.

CONCLUSION

Chronic pain was positively associated with CVD for Chinese population, and depressive symptoms was considered to mediate the association between chronic pain and CVD.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

Family Resilience and Children's Subjective Well-Being: A Two-Wave Study

According to the Theory of Change, the resilience of the family unit plays a crucial role in shaping the developmental trajectory of children. Families exhibiting higher levels of family resilience are typically characterized by transparent and effective communication, optimistic outlooks on adversity, adept problem-solving skills, strong spiritual beliefs, and effective management of social and financial resources. While existing research has indicated that parental and familial characteristics can predict diverse outcomes for children, investigations concerning the association between family resilience and children's subjective well-being remains limited. Therefore, this study aims to examine whether different dimensions of family resilience can predict changes in children's subjective well-being, tested one year later. The sample includes 762 child-mother-father triads (intact families). Children aged 9-13 years (48% boys, age = 11.04, SD = 1.16) assessed their life satisfaction, positive and negative affect in two study waves, while mothers and fathers assessed family resilience in the first wave. A dyadic data common fate model was employed to create latent variables representing family resilience. Three latent variables were: family problem-solving, family spirituality, and utilization of social and economic resources. Findings from the structural equation model indicated a positive association between higher levels of family problem-solving and increased children's life satisfaction, alongside a negative relationship between higher family spirituality and negative affect. Parental assessments of social and economic resources utilization were not uniquely related to children's life satisfaction, positive, or negative affect.

The stability and change of wellbeing across the lifespan: a longitudinal twin-sibling study

BACKGROUND

Wellbeing is relatively stable over the life span. However, individuals differ in this stability and change. One explanation for these differences could be the influence of different genetic or environmental factors on wellbeing over time.

METHODS

To investigate causes of stability and change of wellbeing across the lifespan, we used cohort-sequential data on wellbeing from twins and their siblings of the Netherlands Twin Register (NTR) (total N = 46.885, 56% females). We organized wellbeing data in multiple age groups, from childhood (age 5), to adolescence, up to old age (age 61+). Applying a longitudinal genetic simplex model, we investigated the phenotypic stability of wellbeing and continuity and change in genetic and environmental influences.

RESULTS

Wellbeing peaked in childhood, decreased during adolescence, and stabilized during adulthood. In childhood and adolescence, around 40% of the individual differences was explained by genetic effects. The heritability decreased toward old adulthood (35-24%) and the contribution of unique environmental effects increased to 76%. Environmental innovation was found at every age, whereas genetic innovation was only observed during adolescence (10-18 years). In childhood and adulthood, the absence of genetic innovation indicates a stable underlying set of genes influencing wellbeing during these life phases.

CONCLUSION

These findings provide insights into the stability and change of wellbeing and the genetic and environmental influences across the lifespan. Genetic effects were mostly stable, except in adolescence, whereas the environmental innovation at every age suggests that changing environmental factors are a source of changes in individual differences in wellbeing over time.

Hemorrhoidal disease and its genetic association with depression, bipolar disorder, anxiety disorders, and schizophrenia: a bidirectional mendelian randomization study

BACKGROUND

Hemorrhoids and psychiatric disorders exhibit high prevalence rates and a tendency for relapse in epidemiological studies. Despite this, limited research has explored their correlation, and these studies are often subject to reverse causality and residual confounding. We conducted a Mendelian randomization (MR) analysis to comprehensively investigate the association between several mental illnesses and hemorrhoidal disease.

METHODS

Genetic associations for four psychiatric disorders and hemorrhoidal disease were obtained from large consortia, the FinnGen study, and the UK Biobank. Genetic variants associated with depression, bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease at the genome-wide significance level were selected as instrumental variables. Screening for potential confounders in genetic instrumental variables using PhenoScanner V2. Bidirectional MR estimates were employed to assess the effects of four psychiatric disorders on hemorrhoidal disease.

RESULTS

Our analysis revealed a significant association between genetically predicted depression and the risk of hemorrhoidal disease (IVW, OR=1.20,95% CI=1.09 to 1.33, P <0.001). We found no evidence of associations between bipolar disorder, anxiety disorders, schizophrenia, and hemorrhoidal disease. Inverse MR analysis provided evidence for a significant association between genetically predicted hemorrhoidal disease and depression (IVW, OR=1.07,95% CI=1.04 to 1.11, P <0.001).

CONCLUSIONS

This study offers MR evidence supporting a bidirectional causal relationship between depression and hemorrhoidal disease.

Examination of a novel expression-based gene-SNP annotation strategy to identify tissue-specific contributions to heritability in multiple traits

Complex traits show clear patterns of tissue-specific expression influenced by single nucleotide polymorphisms (SNPs), yet current strategies aggregate SNP effects to genes by employing simple physical proximity-based windows. Here, we examined whether incorporating SNPs with effects on tissue-specific cis-expression would improve our ability to detect trait-relevant tissues across 31 complex traits using stratified linkage disequilibrium score regression (S-LDSC). We found that a physical proximity annotation produced more significant tissue enrichments and larger S-LDSC regression coefficients, as compared to an expression-based annotation. Furthermore, we showed that our expression-based annotation did not outperform an annotation strategy in which an equal number of randomly chosen SNPs were annotated to genes within the same genomic window, suggesting extensive redundancy among SNP effect estimates due to linkage disequilibrium. That said, current sample sizes limit estimation of cis-genetic SNP effects; therefore, we recommend reexamination of the expression-based annotation when larger tissue-specific expression datasets become available. To examine the influence of sample size, we used a large whole blood eQTL reference panel (N = 31,684) applying a similar expression-based annotation strategy. We found that significant cis-expression QTLs in whole blood did not outperform the physical proximity annotation when estimating tissue-specific SNP heritability enrichment for either high- or low-density lipoprotein phenotypes but performed similarly for inflammatory bowel disease. Finally, we report new and updated tissue enrichment estimates across 31 complex traits, such as significant heritability enrichment of the frontal cortex for cognitive performance, educational attainment, and intelligence, providing further evidence of this structure's importance in higher cognitive function.

Genetic characterization of the ALFA study: Uncovering genetic profiles in the Alzheimer's continuum

INTRODUCTION

In 2013, the ALzheimer's and FAmilies (ALFA) project was established to investigate pathophysiological changes in preclinical Alzheimer's disease (AD), and to foster research on early detection and preventive interventions.

METHODS

We conducted a comprehensive genetic characterization of ALFA participants with respect to neurodegenerative/cerebrovascular diseases, AD biomarkers, brain endophenotypes, risk factors and aging biomarkers. We placed particular emphasis on amyloid/tau status and assessed gender differences. Multiple polygenic risk scores were computed to capture different aspects of genetic predisposition. We additionally compared AD risk in ALFA to that across the full disease spectrum from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

Results show that the ALFA project has been successful at establishing a cohort of cognitively unimpaired individuals at high genetic predisposition of AD.

DISCUSSION

It is, therefore, well-suited to study early pathophysiological changes in the preclinical AD continuum. Highlights Prevalence of ε4 carriers in ALzheimer and FAmilies (ALFA) is higher than in the general European population The ALFA study is highly enriched in Alzheimer's disease (AD) genetic risk factors beyond APOE AD genetic profiles in ALFA are similar to clinical groups along the continuum ALFA has succeeded in establishing a cohort of cognitively unimpaired individuals at high genetic AD risk ALFA is well suited to study pathogenic events/early pathophysiological changes in AD.

A concerted neuron-astrocyte program declines in ageing and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental disorders

BACKGROUND

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

METHODS

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

RESULTS

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

CONCLUSIONS

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Assessing the genetic contribution of cumulative behavioral factors associated with longitudinal type 2 diabetes risk highlights adiposity and the brain-metabolic axis

While genetic factors, behavior, and environmental exposures form a complex web of interrelated associations in type 2 diabetes (T2D), their interaction is poorly understood. Here, using data from ~500K participants of the UK Biobank, we identify the genetic determinants of a "polyexposure risk score" (PXS) a new risk factor that consists of an accumulation of 25 associated individual-level behaviors and environmental risk factors that predict longitudinal T2D incidence. PXS-T2D had a non-zero heritability (h2 = 0.18) extensive shared genetic architecture with established clinical and biological determinants of T2D, most prominently with body mass index (genetic correlation [rg] = 0.57) and Homeostatic Model Assessment for Insulin Resistance (rg = 0.51). Genetic loci associated with PXS-T2D were enriched for expression in the brain. Biobank scale data with genetic information illuminates how complex and cumulative exposures and behaviors as a whole impact T2D risk but whose biology have been elusive in genome-wide studies of T2D.

Genetic architecture distinguishes tinnitus from hearing loss

Tinnitus is a heritable, highly prevalent auditory disorder treated by multiple medical specialties. Previous GWAS indicated high genetic correlations between tinnitus and hearing loss, with little indication of differentiating signals. We present a GWAS meta-analysis, triple previous sample sizes, and expand to non-European ancestries. GWAS in 596,905 Million Veteran Program subjects identified 39 tinnitus loci, and identified genes related to neuronal synapses and cochlear structural support. Applying state-of-the-art analytic tools, we confirm a large number of shared variants, but also a distinct genetic architecture of tinnitus, with higher polygenicity and large proportion of variants not shared with hearing difficulty. Tissue-expression analysis for tinnitus infers broad enrichment across most brain tissues, in contrast to hearing difficulty. Finally, tinnitus is not only correlated with hearing loss, but also with a spectrum of psychiatric disorders, providing potential new avenues for treatment. This study establishes tinnitus as a distinct disorder separate from hearing difficulties.

Concerted neuron-astrocyte gene expression declines in aging and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron-and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.

Distinguishing happiness and meaning in life from depressive symptoms: A GWAS-by-subtraction study in the UK Biobank

Hedonic (happiness) and eudaimonic (meaning in life) well-being are negatively related to depressive symptoms. Genetic variants play a role in this association, reflected in substantial genetic correlations. We investigated the overlap and differences between well-being and depressive symptoms, using results of Genome-Wide Association studies (GWAS) in UK Biobank. Subtracting GWAS summary statistics of depressive symptoms from those of happiness and meaning in life, we obtained GWASs of respectively "pure" happiness (neffective  = 216,497) and "pure" meaning (neffective  = 102,300). For both, we identified one genome-wide significant SNP (rs1078141 and rs79520962, respectively). After subtraction, SNP heritability reduced from 6.3% to 3.3% for pure happiness and from 6.2% to 4.2% for pure meaning. The genetic correlation between the well-being measures reduced from 0.78 to 0.65. Pure happiness and pure meaning became genetically unrelated to traits strongly associated with depressive symptoms, including loneliness, and psychiatric disorders. For other traits, including ADHD, educational attainment, and smoking, the genetic correlations of well-being versus pure well-being changed substantially. GWAS-by-subtraction allowed us to investigate the genetic variance of well-being unrelated to depressive symptoms. Genetic correlations with different traits led to new insights about this unique part of well-being. Our results can be used as a starting point to test causal relationships with other variables, and design future well-being interventions.

Genome-Wide Meta-analysis Identifies Risk Loci and Improves Disease Prediction of Age-Related Macular Degeneration

PURPOSE

To identify age-related macular degeneration (AMD) risk loci and to establish a polygenic prediction model.

DESIGN

Genome-wide association study (GWAS) and polygenic risk score (PRS) construction.

PARTICIPANTS

We included 64 885 European patients with AMD and 568 740 control participants (with overlapped samples) in the UK Biobank, Genetic Epidemiology Research on Aging (GERA), International AMD Consortium, FinnGen, and published early AMD GWASs in meta-analyses, as well as 733 European patients with AMD and 20 487 control participants from the Canadian Longitudinal Study on Aging (CLSA) and non-Europeans from the UK Biobank and GERA for polygenic risk score validation.

METHODS

A multitrait meta-analysis of GWASs comprised 64 885 patients with AMD and 568 740 control participants; the multitrait approach accounted for sample overlap. We constructed a PRS for AMD based on both previously reported as well as unreported AMD loci. We applied the PRS to nonoverlapping data from the CLSA.

MAIN OUTCOME MEASURES

We identified several single nucleotide polymorphisms associated with AMD and established a PRS for AMD risk prediction.

RESULTS

We identified 63 AMD risk loci alongside the well-established AMD loci CFH and ARMS2, including 9 loci that were not reported in previous GWASs, some of which previously were linked to other eye diseases such as glaucoma (e.g., HIC1). We applied our PRS to nonoverlapping data from the CLSA. A new PRS was constructed using the PRS method, PRS-CS, and significantly improved the prediction accuracy of AMD risk compared with PRSs from previously published datasets. We further showed that even people who carry all the well-known AMD risk alleles at CFH and ARMS2 vary considerably in their AMD risk (ranging from close to 0 in individuals with low PRS to > 50% in individuals with high PRS). Although our PRS was derived in individuals of European ancestry, the PRS shows potential for predicting risk in people of East Asian, South Asian, and Latino ancestry.

CONCLUSIONS

Our findings improve the knowledge of the genetic architecture of AMD and help achieve better accuracy in AMD prediction.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Effects of physical activity and sedentary time on depression, anxiety and well-being: a bidirectional Mendelian randomisation study

BACKGROUND

Mental health conditions represent one of the major groups of non-transmissible diseases. Physical activity (PA) and sedentary time (ST) have been shown to affect mental health outcomes in opposite directions. In this study, we use accelerometery-derived measures of PA and ST from the UK Biobank (UKB) and depression, anxiety and well-being data from the UKB mental health questionnaire as well as published summary statistics to explore the causal associations between these phenotypes.

METHODS

We used MRlap to test if objectively measured PA and ST associate with mental health outcomes using UKB data and summary statistics from published genome-wide association studies. We also tested for bidirectional associations. We performed sex stratified as well as sensitivity analyses.

RESULTS

Genetically instrumented higher PA was associated with lower odds of depression (OR = 0.92; 95% CI: 0.88, 0.97) and depression severity (beta =  - 0.11; 95% CI: - 0.18, - 0.04), Genetically instrumented higher ST was associated higher odds of anxiety (OR = 2.59; 95% CI: 1.10, 4.60). PA was associated with higher well-being (beta = 0.11, 95% CI: 0.04; 0.18) and ST with lower well-being (beta =  - 0.18; 95% CI: - 0.32, - 0.03). Similar findings were observed when stratifying by sex. There was evidence for a bidirectional relationship, with higher genetic liability to depression associated with lower PA (beta =  - 0.25, 95% CI: - 0.42; - 0.08) and higher well-being associated with higher PA (beta = 0.15; 95% CI: 0.05, 0.25).

CONCLUSIONS

We have demonstrated the bidirectional effects of both PA and ST on a range of mental health outcomes using objectively measured predictors and MR methods for causal inference. Our findings support a causal role for PA and ST in the development of mental health problems and in affecting well-being.

Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder

Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.

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.

Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G)

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.

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.

Mendelian randomization studies of depression: evidence, opportunities, and challenges

BACKGROUND

Major depressive disorder (MDD) poses a significant social and economic burden worldwide. Identifying exposures, risk factors, and biological mechanisms that are causally connected to MDD can help build a scientific basis for disease prevention and development of novel therapeutic approaches.

METHODS

In this systematic review, we assessed the evidence for causal relationships between putative causal risk factors and MDD from Mendelian randomization (MR) studies, following PRISMA. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions.

RESULTS

We included methodological details and results from 52 articles. A causal link between lifestyle, metabolic, inflammatory biomarkers, particular pathological states and MDD is supported by MR investigations, although results for each category varied substantially.

CONCLUSIONS

While this review shows how MR can offer useful information for examining prospective treatment targets and better understanding the pathophysiology of MDD, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

Genetic and neural bases of the neuroticism general factor

We applied structural equation modeling to conduct a genome-wide association study (GWAS) of the general factor measured by a neuroticism questionnaire administered to ∼380,000 participants in the UK Biobank. We categorized significant genetic variants as acting either through the neuroticism general factor, through other factors measured by the questionnaire, or through paths independent of any factor. Regardless of this categorization, however, significant variants tended to show concordant associations with all items. Bioinformatic analysis showed that the variants associated with the neuroticism general factor disproportionately lie near or within genes expressed in the brain. Enriched gene sets pointed to an underlying biological basis associated with brain development, synaptic function, and behaviors in mice indicative of fear and anxiety. Psychologists have long asked whether psychometric common factors are merely a convenient summary of correlated variables or reflect coherent causal entities with a partial biological basis, and our results provide some support for the latter interpretation. Further research is needed to determine the extent to which causes resembling common factors operate alongside other mechanisms to generate the correlational structure of personality.

Is adjustment disorder genetically correlated with depression, anxiety, or risk-tolerant personality trait?

Adjustment disorder has three main subtypes: adjustment disorder with depressed mood, adjustment disorder with anxiety, and adjustment disorder with disturbance of conduct. The disorder is moderately heritable and has lifetime comorbidities with major depressive disorder (MDD), anxiety disorders, or risk-tolerant personality. However, it remains unclear whether the degrees of genetic correlations between adjustment disorder and other psychiatric disorders and intermediate phenotypes are similar or different to those between MDD, anxiety disorders or risk-tolerant personality and these other psychiatric disorders and intermediate phenotypes. To compare patterns of genetic correlations, we utilized large-scale genome-wide association study summary statistics for adjustment disorder-related disorders and personality trait, eleven other psychiatric disorders and fifteen intermediate phenotypes. Adjustment disorder had highly positive genetic correlations with MDD, anxiety disorders, and risk-tolerant personality. Among other psychiatric disorders, adjustment disorder, MDD, anxiety disorders and risk-tolerant personality were positively correlated with risks for schizophrenia (SCZ), bipolar disorder (BD), SCZ + BD, attention-deficit/hyperactivity disorder, and cross disorders. In contrast, adjustment disorder was not significantly correlated with risks for obsessive-compulsive disorder, Tourette syndrome, or posttraumatic stress disorder despite significant genetic correlations of MDD or anxiety disorders with these disorders. Among intermediate phenotypes, adjustment disorder, MDD, anxiety disorders, and risk-tolerant personality commonly had a younger age at first sexual intercourse, first birth, and menopause, lower cognitive ability, and higher rate of smoking initiation. Adjustment disorder was not genetically correlated with extraversion, although the related disorder and personality were correlated with extraversion. Only adjustment disorder was correlated with a higher smoking quantity. These findings suggest that adjustment disorder could share a genetic etiology with MDD, anxiety disorders and risk-tolerant personality trait, as well as have a disorder-specific genetic etiology.