Shared and specific genetic risk factors for lifetime major depression, depressive symptoms and neuroticism in three population-based twin samples

On the Selection of Item Scores or Composite Scores for Clinical Prediction

Recent shifts to prioritize prediction, rather than explanation, in psychological science have increased applications of predictive modeling methods. However, composite predictors, such as sum scores, are still commonly used in practice. The motivations behind composite test scores are largely intertwined with reducing the influence of measurement error in answering explanatory questions. But this may be detrimental for predictive aims. The present paper examines the impact of utilizing composite or item-level predictors in linear regression. A mathematical examination of the bias-variance decomposition of prediction error in the presence of measurement error is provided. It is shown that prediction bias, which may be exacerbated by composite scoring, drives prediction error for linear regression. This may be particularly salient when composite scores are comprised of heterogeneous items such as in clinical scales where items correspond to symptoms. With sufficiently large training samples, the increased prediction variance associated with item scores becomes negligible even when composite scores are sufficient. Practical implications of predictor scoring are examined in an empirical example predicting suicidal ideation from various depression scales. Results show that item scores can markedly improve prediction particularly for symptom-based scales. Cross-validation methods can be used to empirically justify predictor scoring decisions.

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.

The 'discontinuity hypothesis' of depression in later life-clinical and research implications

The term depression is overused as an umbrella term for a variety of conditions, including depressed mood and various psychiatric disorders. According to psychiatric diagnostic criteria, depressive disorders impact nearly all aspects of human life and are a leading cause of disability worldwide. The widespread assumption that different types of depression lie on a continuum of severity has stimulated important research on subthreshold depression in later life. This view assumes that depressed mood is a precursor of a depressive disorder. The present narrative review argues why in later life depressed mood might either (i) lie on a continuum with depressive disorders among people vulnerable for a depressive disorder or (ii) be an ageing-related epiphenomenon of underlying physical illnesses in people who are resilient to depressive disorders ('discontinuity hypothesis'). Three arguments are discussed. First, the course of depressed mood and depressive disorders differs across the life span. Second, screening instruments for depression have low predictive value for depressive disorders in later life. Third, a dose-response relationship has not been consistently found across different types of depression and detrimental health outcomes. Using the umbrella term depression may partly explain why pharmacological treatment is less effective with increasing age, and negative health-related outcomes might be overestimated. The discontinuity hypothesis may prevent pharmacological overtreatment of milder subtypes of depression and may stimulate comprehensive multidisciplinary assessment as well as the development of separate treatment algorithms for depressed mood and depressive disorders.

Symptoms of depression and internalizing problems in early adulthood - associated factors from birth to adolescence

PURPOSE

Even though the mechanisms behind the development of depression and internalizing problems remains unknown, many different factors have been shown to increase the risk. Longitudinal studies enable the investigation of exposure during different developmental periods during childhood. This study aims to examine factors associated with depressive and internalizing problems at age 20 in terms of sociodemographic factors, previous mental health problems and stressful life events during childhood, adolescence, and early adulthood.

METHODS

A birth cohort of 1723 children were followed to age 20. At the 20-year follow-up, n = 731 (44%) participated. Standardized instruments were filled out at baseline and the 3-,12- and 20-year follow-ups.

RESULTS

Depressive problems at age 20 were associated with female gender, experience of interpersonal life events reported at age 20, bullying victimization and reports on paternal mental health problems. Participants with depressive problems were also less likely to have experienced adolescence as happy and to report that their father had been a good father. Internalizing problems at age 20 were, in addition, associated with internalizing problems at age 12 and reports on maternal mental health problems. Internalizing problems were associated with a lower likelihood of experiencing adolescence as happy in the final model.

CONCLUSION

Recent events (i.e. interpersonal life events and bullying) seemed to be the most influential factors on the development of internalizing and depressive problems. Internalizing problems during childhood increased the risk for internalizing problems in early adulthood, emphasizing the importance of early intervention. Fewer factors were found to increase the risk for depressive problems compared to internalizing problems.

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

The effects of adverse childhood experiences on depression and suicidal behaviors are partially mediated by neuroticism: A subclinical manifestation of major depression

Introduction

Neuroticism, a personality trait, can predict major depressive disorder (MDD). The current study aims to determine whether a) neuroticism is a feature of the acute state of MDD, including suicidal behaviors (SB); and b) adverse childhood experiences (ACEs) are associated with neuroticism in MDD.

Methods

This study included 133 participants, 67 healthy controls and 66 MDD patients, and assessed the Big 5 Inventory (BFI), ACEs using the ACE Questionnaire, and the phenome of depression using the Hamilton Depression Rating Scale (HAM-D), Beck Depression Inventory (BDI), The State-Trait Anxiety Inventory (STAI) and Columbia Suicide Severity Rating Scale (C-SSRS) scores to assess current SB.

Results

Neuroticism was significantly higher in MDD than controls, and it explained 64.9% of the variance in the depression phenome (a latent vector extracted from HAM-D, BDI, STAI, and current SB scores). The other BFI domains had much less (extraversion, agreeableness) or no effect (openness, conscientiousness). One latent vector could be extracted from the phenome, lifetime dysthymia, lifetime anxiety disorders and neuroticism scores. Neglect (physical and emotional) and abuse (physical, neglect and sexual) account for approximately 30% of the variance in this latent vector. Partial Least Squares analysis showed that the effects of neglect on the phenome were partially mediated by neuroticism, whereas the effects of abuse were completely mediated by neuroticism.

Discussion

Neuroticism (trait) and the MDD phenome (state) are both manifestations of the same latent core, with neuroticism being a subclinical manifestation of MDD.

Prevalence of internalizing disorders, symptoms, and traits across age using advanced nonlinear models

BACKGROUND

Most epidemiological studies show a decrease of internalizing disorders at older ages, but it is unclear how the prevalence exactly changes with age, and whether there are different patterns for internalizing symptoms and traits, and for men and women. This study investigates the impact of age and sex on the point prevalence across different mood and anxiety disorders, internalizing symptoms, and neuroticism.

METHODS

We used cross-sectional data on 146 315 subjects, aged 18-80 years, from the Lifelines Cohort Study, a Dutch general population sample. Between 2012 and 2016, five current internalizing disorders - major depression, dysthymia, generalized anxiety disorder, social phobia, and panic disorder - were assessed according to DSM-IV criteria. Depressive symptoms, anxiety symptoms, neuroticism, and negative affect (NA) were also measured. Generalized additive models were used to identify nonlinear patterns across age, and to investigate sex differences.

RESULTS

The point prevalence of internalizing disorders generally increased between the ages of 18 and 30 years, stabilized between 30 and 50, and decreased after age 50. The patterns of internalizing symptoms and traits were different. NA and neuroticism gradually decreased after age 18. Women reported more internalizing disorders than men, but the relative difference remained stable across age (relative risk ~1.7).

CONCLUSIONS

The point prevalence of internalizing disorders was typically highest between age 30 and 50, but there were differences between the disorders, which could indicate differences in etiology. The relative gap between the sexes remained similar across age, suggesting that changes in sex hormones around the menopause do not significantly influence women's risk of internalizing disorders.

Understanding the genetics of peripartum depression: Research challenges, strategies, and opportunities

Peripartum depression (PD) is a common mood disorder associated with negative outcomes for mother and child. PD is an understudied disorder in psychiatric genetics, and progress characterizing its genetic architecture has been limited by a lack of disorder-specific research, heterogeneous and evolving phenotypic definitions, inadequate representation of global populations, low-powered studies, and insufficient data amenable to large meta-analyses. The increasing availability of large-scale, population-level efforts, like biobanks, have the potential to accelerate scientific discovery and translational research by leveraging clinical, molecular, and self-report data from hundreds of thousands of individuals. Although these efforts will not fully equip researchers to confront every challenge posed by systemic issues in data collection, such as the reliance on minimal phenotyping strategies, the field is in a position to learn from other successful psychiatric genetic investigations. This review summarizes the current state of PD genetics research and highlights research challenges, including the impact of phenotype depth, measurement, and definition on the replicability and interpretability of genomic research. Recommendations for advancing health equity and improving the collection, analysis, discussion, and reporting of measures for PD research are provided.

Symptom-level modelling unravels the shared genetic architecture of anxiety and depression

Depression and anxiety are highly prevalent and comorbid psychiatric traits that cause considerable burden worldwide. Here we use factor analysis and genomic structural equation modelling to investigate the genetic factor structure underlying 28 items assessing depression, anxiety and neuroticism, a closely related personality trait. Symptoms of depression and anxiety loaded on two distinct, although highly genetically correlated factors, and neuroticism items were partitioned between them. We used this factor structure to conduct genome-wide association analyses on latent factors of depressive symptoms (89 independent variants, 61 genomic loci) and anxiety symptoms (102 variants, 73 loci) in the UK Biobank. Of these associated variants, 72% and 78%, respectively, replicated in an independent cohort of approximately 1.9 million individuals with self-reported diagnosis of depression and anxiety. We use these results to characterize shared and trait-specific genetic associations. Our findings provide insight into the genetic architecture of depression and anxiety and comorbidity between them.

ADHD and depression: investigating a causal explanation

BACKGROUND

Attention-deficit hyperactivity disorder (ADHD) is associated with later depression and there is considerable genetic overlap between them. This study investigated if ADHD and ADHD genetic liability are causally related to depression using two different methods.

METHODS

First, a longitudinal population cohort design was used to assess the association between childhood ADHD (age 7 years) and recurrent depression in young-adulthood (age 18-25 years) in N = 8310 individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC). Second, two-sample Mendelian randomization (MR) analyses examined relationships between genetic liability for ADHD and depression utilising published Genome-Wide Association Study (GWAS) data.

RESULTS

Childhood ADHD was associated with an increased risk of recurrent depression in young-adulthood (OR 1.35, 95% CI 1.05-1.73). MR analyses suggested a causal effect of ADHD genetic liability on major depression (OR 1.21, 95% CI 1.12-1.31). MR findings using a broader definition of depression differed, showing a weak influence on depression (OR 1.07, 95% CI 1.02-1.13).

CONCLUSIONS

Our findings suggest that ADHD increases the risk of depression later in life and are consistent with a causal effect of ADHD genetic liability on subsequent major depression. However, findings were different for more broadly defined depression.

Etiological pathways of depressive and anxiety symptoms linked to personality traits: A genetically-informative longitudinal study

BACKGROUND

The comorbidity of depression and anxiety is associated with an increased risk of prolonged adverse mental health status. However, little is currently known about their genetic and environmental influences that help to explain both the comorbidity and distinctiveness. Using longitudinal twin data, the present study investigated both the overlapping and distinct relationships between depression and anxiety viewed from the perspective of Gray's Reinforcement Sensitivity Theory (RST): two personality traits of the Behavioral Inhibition and Activation Systems (BIS and BAS).

METHODS

A total of 422 twin pairs (298 monozygotic and 124 dizygotic pairs) participated by completing a personality questionnaire at wave 1, and mood symptoms questionnaires at wave 2. The waves were on average 2.23 years apart.

RESULTS

Multivariate Cholesky decomposition indicated that the genetic variance of the personality traits (BIS and BAS) explained all of the genetic variance in depressive and anxiety symptoms. Additionally, genetic factors related to the BIS positively explained depressive and anxiety symptoms, whereas genetic factors related to the BAS negatively explained only depressive symptoms.

LIMITATIONS

Limitations include shorter time interval and the reliance on self-reported data.

CONCLUSIONS

The present study provided evidence explaining the overlap and differentiation of depressive and anxiety symptoms by using data on personality traits in a longitudinal, genetically-informative design. The findings suggested the personality traits from Gray's RST model played an important role in the prediction, and clarified the description, of both depressive and anxiety symptoms.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Five Factor Model Personality Traits and Subjective Cognitive Failures

Momentary lapses in memory, perception, or action, known as cognitive failures, are relatively common. These lapses may reflect, in part, aspects of psychological functioning, such as personality traits. The present research addresses how Five Factor Model personality traits and facets are associated with cognitive failures, and whether these associations are accounted for by depressed affect. Participants (N=5,133; 50% female) who ranged in age from 18 to 91 completed an online survey that assessed their personality traits, cognitive failures, and depressed affect. Higher neuroticism was associated with more cognitive failures, whereas Conscientiousness and Agreeableness were associated with fewer failures, controlling for sociodemographic characteristics. Controlling for depressed affect reduced the associations in most cases by about 50%, but most relations were still apparent. Facet-level analyses provided a more detailed picture of how the traits are associated with cognitive failures. Subjective perceptions of lapses in cognition are associated with basic personality traits and may reflect, in part, processes related to those traits beyond depressed affect.

Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

INTRODUCTION

Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relationship in the etiology and development of MDD remains unclear. Under such situation, a systems biology approach focusing on the function correlation and interaction of the candidate genes in the context of MDD will provide useful information on exploring the molecular mechanisms underlying the disease.

METHODS

We collected genes potentially related to MDD by screening the human genetic studies deposited in PubMed (https://www.ncbi.nlm.nih.gov/pubmed). The main biological themes within the genes were explored by function and pathway enrichment analysis. Then, the interaction of genes was analyzed in the context of protein-protein interaction network and a MDD-specific network was built by Steiner minimal tree algorithm.

RESULTS

We collected 255 candidate genes reported to be associated with MDD from available publications. Functional analysis revealed that biological processes and biochemical pathways related to neuronal development, endocrine, cell growth and/or survivals, and immunology were enriched in these genes. The pathways could be largely grouped into three modules involved in biological procedures related to nervous system, the immune system, and the endocrine system, respectively. From the MDD-specific network, 35 novel genes potentially associated with the disease were identified.

CONCLUSION

By means of network- and pathway-based methods, we explored the molecular mechanism underlying the pathogenesis of MDD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular features of MDD.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

BACKGROUND

Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.

RESULTS

Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression.

CONCLUSIONS

Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

Psychological theories of depressive relapse and recurrence: A systematic review and meta-analysis of prospective studies

Psychological factors hypothesized to account for relapse of major depressive disorder (MDD) roughly originate from five main theories: Cognitive, diathesis-stress, behavioural, psychodynamic, and personality-based. In a meta-analysis we investigated prospective, longitudinal evidence for these leading psychological theories and their factors in relation to depressive relapse. Included studies needed to establish history of MDD and prospective depressive relapse through a clinical interview, have a longitudinal and prospective design, and measure at least one theory-derived factor before relapse. We identified 66 eligible articles out of 43,586 records published up to November 2018. Pooled odds ratios (OR) indicated a significant relationship between the cognitive, behavioural, and personality-based theories and depressive relapse (cognitive: k = 17, OR = 1.24, 95% CI = 1.10-1.40; behavioural, k = 8, OR = 1.15, 95% CI = 1.05-1.25; personality: k = 12, OR = 1.26, 95% CI = 1.02-1.54), but not for the psychodynamic theories (k = 4, OR = 1.29, 95% CI = 0.83-1.99). Pooled hazard ratios of the theories were not significant. There were no articles identified for the diathesis-stress theories. To conclude, there is a restricted number of prospective studies, and some evidence that the cognitive, behavioural, and personality-based theories indeed partially account for depressive relapse.

Dispositional negativity, cognition, and anxiety disorders: An integrative translational neuroscience framework

When extreme, anxiety can become debilitating. Anxiety disorders, which often first emerge early in development, are common and challenging to treat, yet the underlying mechanisms have only recently begun to come into focus. Here, we review new insights into the nature and biological bases of dispositional negativity, a fundamental dimension of childhood temperament and adult personality and a prominent risk factor for the development of pediatric and adult anxiety disorders. Converging lines of epidemiological, neurobiological, and mechanistic evidence suggest that dispositional negativity increases the likelihood of psychopathology via specific neurocognitive mechanisms, including attentional biases to threat and deficits in executive control. Collectively, these observations provide an integrative translational framework for understanding the development and maintenance of anxiety disorders in adults and youth and set the stage for developing improved intervention strategies.

DNA methylation studies of depression with onset in the peripartum: A critical systematic review

OBJECTIVE

Major depression with peripartum onset (MDP) has been associated with multiple adverse offspring health outcomes. The biological mechanisms underlying this relationship remain unclear, but DNA methylation (DNAm) represents a plausible mechanism for mediating MDP exposures and changes in offspring development, behavior, and health. Advances in DNAm research necessitate reevaluating the MDP-DNAm literature to determine how well past studies conform with current best practices.

METHOD

Five databases were searched to identify studies of prenatal-onset MDP and DNAm. Quality scores were assigned to each article independently by two raters using a novel scale specific for MDP-DNAm research.

RESULTS

Nineteen studies met inclusion criteria. Quality scores ranged from 10 to 17 out of 24 points (M = 12.8; SD = 1.9), with higher scores indicating increased study rigor. Poor covariate reporting was the most significant contributor to lower scores.

CONCLUSION

No longitudinal MDP-DNAm studies exist. Earlier MDP-DNAm studies should be interpreted with caution, and future research must commit to sharing methodology and data to facilitate cross-study comparisons and maximize dataset utility.