Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1,2,3,4,5,6,7. This detailed knowledge of the genetic... Show moreGenome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1,2,3,4,5,6,7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8,9,10,11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases. Show less
BackgroundChildhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood... Show moreBackgroundChildhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood experiences. As first step toward a more refined analysis of the impact of CM, our objective is to revisit the relation of abuse and neglect, major subtypes of CM, with symptoms across disorders.MethodsThree longitudinal studies of major depressive disorder (MDD, N = 1240), bipolar disorder (BD, N = 1339), and schizophrenia (SCZ, N = 577), each including controls (N = 881), were analyzed. Multivariate regression models were used to examine the relation between exposure to abuse, neglect, or their combination to the odds for MDD, BD, SCZ, and symptoms across disorders. Bidirectional Mendelian randomization (MR) was used to probe causality, using genetic instruments of abuse and neglect derived from UK Biobank data (N = 143 473).ResultsAbuse was the stronger risk factor for SCZ (OR 3.51, 95% CI 2.17–5.67) and neglect for BD (OR 2.69, 95% CI 2.09–3.46). Combined CM was related to increased risk exceeding additive effects of abuse and neglect for MDD (RERI = 1.4) and BD (RERI = 1.1). Across disorders, abuse was associated with hallucinations (OR 2.16, 95% CI 1.55–3.01) and suicide attempts (OR 2.16, 95% CI 1.55–3.01) whereas neglect was associated with agitation (OR 1.24, 95% CI 1.02–1.51) and reduced need for sleep (OR 1.64, 95% CI 1.08–2.48). MR analyses were consistent with a bidirectional causal effect of abuse with SCZ (IVWforward = 0.13, 95% CI 0.01–0.24).ConclusionsChildhood abuse and neglect are associated with different risks to psychiatric symptoms and disorders. Unraveling the origin of these differences may advance understanding of disease etiology and ultimately facilitate development of improved personalized treatment strategies. Show less
Kivelä, L.M.M.; Antypa N.; Fried, E.I.; Schoevers, R.; Hemert, A.M. van; Penninx, B.W.J.H.; Does, A.J.W. van der 2023
BackgroundChildhood trauma (CT) has been cross-sectionally associated with metabolic syndrome (MetS), a group of biological risk factors for cardiometabolic disease. Longitudinal studies, while... Show moreBackgroundChildhood trauma (CT) has been cross-sectionally associated with metabolic syndrome (MetS), a group of biological risk factors for cardiometabolic disease. Longitudinal studies, while rare, would clarify the development of cardiometabolic dysregulations over time. Therefore, we longitudinally investigated the association of CT with the 9-year course of MetS components.MethodsParticipants (N = 2958) from the Netherlands Study of Depression and Anxiety were assessed four times across 9 years. The CT interview retrospectively assessed childhood emotional neglect and physical, emotional, and sexual abuse. Metabolic outcomes encompassed continuous MetS components (waist circumference, triglycerides, high-density lipoprotein [HDL] cholesterol, blood pressure [BP], and glucose) and count of clinically elevated MetS components. Mixed-effects models estimated sociodemographic- and lifestyle-adjusted longitudinal associations of CT with metabolic outcomes over time. Time interactions evaluated change in these associations.ResultsCT was reported by 49% of participants. CT was consistently associated with increased waist (b = 0.32, s.e. = 0.10, p = 0.001), glucose (b = 0.02, s.e. = 0.01, p < 0.001), and count of MetS components (b = 0.04, s.e. = 0.01, p < 0.001); and decreased HDL cholesterol (b = −0.01, s.e.<0.01, p = .020) and systolic BP (b = −0.33, s.e. = 0.13, p = 0.010). These associations were mainly driven by severe CT and unaffected by lifestyle. Only systolic BP showed a CT-by-time interaction, where CT was associated with lower systolic BP initially and with higher systolic BP at the last follow-up.ConclusionsOver time, adults with CT have overall persistent poorer metabolic outcomes than their non-maltreated peers. Individuals with CT have an increased risk for cardiometabolic disease and may benefit from monitoring and early interventions targeting metabolism. Show less
Kivelae, L.M.M.; Antypa, N.; Fried, E.I.; Schoevers, R.; Hemert, A.M. van; Penninx, B.W.J.H.; Does, A.J.W. van der 2023
BackgroundDepression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across... Show moreBackgroundDepression is a highly recurrent disorder, with more than 50% of those affected experiencing a subsequent episode. Although there is relatively little stability in symptoms across episodes, some evidence indicates that suicidal ideation may be an exception. However, these findings warrant replication, especially over longer periods and across multiple episodes.AimsTo assess the relative stability of suicidal ideation in comparison with other non-core depressive symptoms across episodes.MethodWe examined 490 individuals with current major depressive disorder (MDD) at baseline and at least one subsequent episode during 9-year follow-up within the Netherlands Study of Depression and Anxiety (NESDA). The Inventory of Depressive Symptomatology (IDS) was used to assess DSM-5 non-core MDD symptoms (fatigue, appetite/weight change, sleep disturbance, psychomotor disturbance, concentration difficulties, worthlessness/guilt, suicidal ideation) at baseline and 2-, 4-, 6- and 9-year follow-up. We examined consistency in symptom presentation (i.e. whether the symptom met the diagnostic threshold, based on a binary categorisation of the IDS) using kappa (κ) and percentage agreement, and stability in symptom severity using Spearman correlation, based on the continuous IDS scores.ResultsOut of all non-core depressive symptoms, insomnia appeared the most stable across episodes (r = 0.55–0.69, κ = 0.31–0.47) and weight decrease the least stable (r = 0.03–0.33, κ = 0.06–0.19). For suicidal ideation, correlations across episodes ranged from r = 0.36 to r = 0.55 and consistency ranged from κ = 0.28 to κ = 0.49.ConclusionsSuicidal ideation is moderately stable in recurrent depression over 9 years. Contrary to prior reports, however, it does not exhibit substantially more stability than most other non-core symptoms of depression. Show less
BackgroundThe ability to predict the disease course of individuals with major depressive disorder (MDD) is essential for optimal treatment planning. Here, we used a data-driven machine learning... Show moreBackgroundThe ability to predict the disease course of individuals with major depressive disorder (MDD) is essential for optimal treatment planning. Here, we used a data-driven machine learning approach to assess the predictive value of different sets of biological data (whole-blood proteomics, lipid metabolomics, transcriptomics, genetics), both separately and added to clinical baseline variables, for the longitudinal prediction of 2-year remission status in MDD at the individual-subject level.MethodsPrediction models were trained and cross-validated in a sample of 643 patients with current MDD (2-year remission n = 325) and subsequently tested for performance in 161 individuals with MDD (2-year remission n = 82).ResultsProteomics data showed the best unimodal data predictions (area under the receiver operating characteristic curve = 0.68). Adding proteomic to clinical data at baseline significantly improved 2-year MDD remission predictions (area under the receiver operating characteristic curve = 0.63 vs. 0.78, p = .013), while the addition of other omics data to clinical data did not yield significantly improved model performance. Feature importance and enrichment analysis revealed that proteomic analytes were involved in inflammatory response and lipid metabolism, with fibrinogen levels showing the highest variable importance, followed by symptom severity. Machine learning models outperformed psychiatrists’ ability to predict 2-year remission status (balanced accuracy = 71% vs. 55%).ConclusionsThis study showed the added predictive value of combining proteomic data, but not other omics data, with clinical data for the prediction of 2-year remission status in MDD. Our results reveal a novel multimodal signature of 2-year MDD remission status that shows clinical potential for individual MDD disease course predictions from baseline measurements. Show less
Maran, P.L.; Klokgieters, S.S.; Giltay, E.J.; Oppen, P. van; Jörg, F.; Eikelenboom, M.; ... ; Kok, A.A.L. 2023
BackgroundDespite growing concerns about mental health during the COVID-19 pandemic, particularly in people with pre-existing mental health disorders, research has shown that symptoms of depression... Show moreBackgroundDespite growing concerns about mental health during the COVID-19 pandemic, particularly in people with pre-existing mental health disorders, research has shown that symptoms of depression and anxiety were generally quite stable, with modest changes in certain subgroups. However, individual differences in cumulative exposure to COVID-19 stressors have not been yet considered.AimsWe aimed to quantify and investigate the impact of individual-level cumulative exposure to COVID-19-pandemic-related adversity on changes in depressive and anxiety symptoms and loneliness. In addition, we examined whether the impact differed among individuals with various levels of pre-pandemic chronicity of mental health disorders.MethodBetween April 2020 and July 2021, 15 successive online questionnaires were distributed among three psychiatric case–control cohorts that started in the 2000s (N = 1377). Outcomes included depressive and anxiety symptoms and loneliness. We developed a COVID-19 Adversity Index (CAI) summarising up to 15 repeated measures of COVID-19-pandemic-related exposures (e.g. exposure to COVID-19 infection, negative economic impact and quarantine). We used linear mixed linear models to estimate the effects of COVID-19-related adversity on mental health and its interaction with pre-pandemic chronicity of mental health disorders and CAI.ResultsHigher CAI scores were positively associated with higher increases in depressive symptoms, anxiety symptoms and loneliness. Associations were not statistically significantly different between groups with and without (chronic) pre-pandemic mental health disorders.ConclusionsIndividual differences in cumulative exposure to COVID-19-pandemic-related adversity are important predictors of mental health, but we found no evidence for higher vulnerability among people with (chronic) pre-pandemic mental health disorders. Show less
The genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher... Show moreThe genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher genetically predicted RHR decreases risk of atrial fibrillation and ischemic stroke.Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development. Show less
BackgroundChildhood trauma (CT) is associated with severe sequelae, including stress-related mental health disorders that can perpetuate long into adulthood. A key mechanism in this relationship... Show moreBackgroundChildhood trauma (CT) is associated with severe sequelae, including stress-related mental health disorders that can perpetuate long into adulthood. A key mechanism in this relationship seems to be emotion regulation. We aimed to investigate (1) whether childhood trauma is associated with anger in adulthood, and, if so, (2) to explore which types of childhood trauma predominate in the prediction of anger in a cohort that included participants with and without current affective disorders.MethodsIn the Netherlands Study of Depression and Anxiety (NESDA), childhood trauma was assessed with a semi-structured Childhood Trauma Interview (CTI) at baseline, and analyzed in relation to anger as measured at a 4-year follow-up with the Spielberger Trait Anger Subscale (STAS), the Anger Attacks Questionnaire, and cluster B personality traits (i.e., borderline, antisocial) of the Personality Disorder Questionnaire 4 (PDQ-4), using analysis of covariance (ANCOVA) and multivariable logistic regression analyses. Post hoc analyses comprised cross-sectional regression analyses, using the Childhood Trauma Questionnaire-Short Form (CTQ-SF) also obtained at a 4-year follow-up.ResultsParticipants (n = 2271) were on average 42.1 years (SD = 13.1), and 66.2% were female. Childhood trauma showed a dose–response association with all anger constructs. All types of childhood trauma were significantly associated with borderline personality traits, independently of depression and anxiety. Additionally, all types of childhood trauma except for sexual abuse were associated with higher levels of trait anger, and a higher prevalence of anger attacks and antisocial personality traits in adulthood. Cross-sectionally, the effect sizes were larger compared with the analyses with the childhood trauma measured 4 years prior to the anger measures.ConclusionsChildhood trauma is linked with anger in adulthood, which could be of particular interest in the context of psychopathology. Focus on childhood traumatic experiences and adulthood anger may help to enhance the effectiveness of treatment for patients with depressive and anxiety disorders. Trauma-focused interventions should be implemented when appropriate. Show less
BackgroundAffective (i.e. depressive and anxiety) disorders often co-occur with immunometabolic diseases and related biological pathways. Although many large population-based and meta-analytic... Show moreBackgroundAffective (i.e. depressive and anxiety) disorders often co-occur with immunometabolic diseases and related biological pathways. Although many large population-based and meta-analytic studies have confirmed this link in community and clinical samples, studies in at-risk samples of siblings of persons with affective disorders are lacking. Furthermore, this somatic-mental co-occurrence may be partially explained by familial clustering of the conditions. First, we examined whether the association between a wide range of immunometabolic diseases and related biomarker based risk-profiles with psychological symptoms replicates in at-risk siblings of probands with affective disorders. Second, leveraging on a sibling-pair design, we disentangled and quantified the effect of probands’ immunometabolic health on siblings’ psychological symptoms and on the association between immunometabolic health and these symptoms in siblings.MethodsThe sample included 636 participants (Mage = 49.7; 62.4% female) from 256 families, each including a proband with lifetime depressive and/or anxiety disorders and at least one of their sibling(s) (N = 380 proband-sibling pairs). Immunometabolic health included cardiometabolic and inflammatory diseases, body mass index (BMI), and composite metabolic (based on the five metabolic syndrome components) and inflammatory (based on interleukin-6 and C-reactive protein) biomarker indices. Overall affective symptoms and specific atypical, energy-related depressive symptoms were derived from self-report questionnaires. Mixed-effects analyses were used to model familial clustering.ResultsIn siblings, inflammatory disease (γ = 0.25, p = 0.013), higher BMI (γ = 0.10, p = 0.033) and metabolic index (γ = 0.28, p < 0.001) were associated with higher affective symptoms, with stronger associations for atypical, energy-related depressive symptoms (additionally associated with cardiometabolic disease; γ = 0.56, p = 0.048). Immunometabolic health in probands was not independently associated with psychological symptoms in siblings nor did it moderate the association between immunometabolic health and psychological symptoms estimated in siblings.ConclusionsOur findings demonstrate that the link between later life immunometabolic health and psychological symptoms is consistently present also in adult siblings at high risk for affective disorders. Familial clustering did not appear to have a substantial impact on this association. Instead, individual lifestyle, rather than familial factors, may have a relatively higher impact in the clustering of later life immunometabolic conditions with psychological symptoms in at-risk adult individuals. Furthermore, results highlighted the importance of focusing on specific depression profiles when investigating the overlap with immunometabolic health. Show less
Kluiver, H. de; Jansen, R.; Penninx, B.W.J.H.; Giltay, E.J.; Schoevers, R.A.; Milaneschi, Y. 2023
Depression shows a metabolomic signature overlapping with that of cardiometabolic conditions. Whether this signature is linked to specific depression profiles remains undetermined. Previous... Show moreDepression shows a metabolomic signature overlapping with that of cardiometabolic conditions. Whether this signature is linked to specific depression profiles remains undetermined. Previous research suggested that metabolic alterations cluster more consistently with depressive symptoms of the atypical spectrum related to energy alterations, such as hyperphagia, weight gain, hypersomnia, fatigue and leaden paralysis. We characterized the metabolomic signature of an “atypical/energy-related” symptom (AES) profile and evaluated its specificity and consistency. Fifty-one metabolites measured using the Nightingale platform in 2876 participants from the Netherlands Study of Depression and Anxiety were analyzed. An ‘AES profile’ score was based on five items of the Inventory of Depressive Symptomatology (IDS) questionnaire. The AES profile was significantly associated with 31 metabolites including higher glycoprotein acetyls (β = 0.13, p = 1.35*10-12), isoleucine (β = 0.13, p = 1.45*10-10), very-low-density lipoproteins cholesterol (β = 0.11, p = 6.19*10-9) and saturated fatty acid levels (β = 0.09, p = 3.68*10-10), and lower high-density lipoproteins cholesterol (β = −0.07, p = 1.14*10-4). The metabolites were not significantly associated with a summary score of all other IDS items not included in the AES profile. Twenty-five AES-metabolites associations were internally replicated using data from the same subjects (N = 2015) collected at 6-year follow-up. We identified a specific metabolomic signature—commonly linked to cardiometabolic disorders—associated with a depression profile characterized by atypical, energy-related symptoms. The specific clustering of a metabolomic signature with a clinical profile identifies a more homogenous subgroup of depressed patients at higher cardiometabolic risk, and may represent a valuable target for interventions aiming at reducing depression’s detrimental impact on health. Show less
Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree... Show moreCoronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74–2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways. Show less
BackgroundMajor depressive disorder (MDD) is a heterogeneous psychiatric disorder. Childhood trauma (CT, emotional/physical/sexual abuse or neglect before the age of 18) is one of the largest and... Show moreBackgroundMajor depressive disorder (MDD) is a heterogeneous psychiatric disorder. Childhood trauma (CT, emotional/physical/sexual abuse or neglect before the age of 18) is one of the largest and most consistent risk factors for development and poor course of MDD. Overactivity of the HPA-axis and the stress hormone cortisol is thought to play a role in the vulnerability for MDD following exposure to CT. Rodent experiments showed that antagonism of the glucocorticoid receptor (GR) at adult age reversed the effects of early life stress. Similarly, we aim to target MDD in individuals with CT exposure using the GR antagonist mifepristone.MethodsThe RESET-medication study is a placebo-controlled double-blind randomized controlled trial (RCT) which aims to include 158 adults with MDD and CT. Participants will be randomized (1:1) to a 7-day treatment arm of mifepristone (1200 mg/day) or a control arm (placebo). Participants are allowed to receive usual care for MDD including antidepressants. Measurements include three face-to-face meetings at baseline (T0), day 8 (T1), week 6 (T2), and two online follow-up meetings at 12 weeks (T3) and 6 months (T4). A subgroup of participants (N = 80) are included in a fMRI sub-study (T0, T2). The main study outcome will be depressive symptom severity as measured with the Inventory of Depressive Symptomatology—Self Rated (IDS-SR) at T2. Secondary outcomes include, among others, depressive symptom severity at other time points, disability, anxiety, sleep and subjective stress. To address underlying mechanisms mifepristone plasma levels, cortisol, inflammation, epigenetic regulation and fMRI measurements are obtained.DiscussionThe RESET-medication study will provide clinical evidence whether GR antagonism is a disease-modifying treatment for MDD in individuals exposed to CT. If effective, this hypothesis-driven approach may extend to other psychiatric disorders where CT plays an important role. Show less
BackgroundDepression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network... Show moreBackgroundDepression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models.MethodsWe used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later.ResultsThe network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave.ConclusionsThe somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles. Show less
BackgroundChildhood maltreatment is associated with depression and cardiometabolic disease in adulthood. However, the relationships with these two diseases have so far only been evaluated in... Show moreBackgroundChildhood maltreatment is associated with depression and cardiometabolic disease in adulthood. However, the relationships with these two diseases have so far only been evaluated in different samples and with different methodology. Thus, it remains unknown how the effect sizes magnitudes for depression and cardiometabolic disease compare with each other and whether childhood maltreatment is especially associated with the co-occurrence (“comorbidity”) of depression and cardiometabolic disease. This pooled analysis examined the association of childhood maltreatment with depression, cardiometabolic disease, and their comorbidity in adulthood.MethodsWe carried out an individual participant data meta-analysis on 13 international observational studies (N = 217,929). Childhood maltreatment comprised self-reports of physical, emotional, and/or sexual abuse before 18 years. Presence of depression was established with clinical interviews or validated symptom scales and presence of cardiometabolic disease with self-reported diagnoses. In included studies, binomial and multinomial logistic regressions estimated sociodemographic-adjusted associations of childhood maltreatment with depression, cardiometabolic disease, and their comorbidity. We then additionally adjusted these associations for lifestyle factors (smoking status, alcohol consumption, and physical activity). Finally, random-effects models were used to pool these estimates across studies and examined differences in associations across sex and maltreatment types.ResultsChildhood maltreatment was associated with progressively higher odds of cardiometabolic disease without depression (OR [95% CI] = 1.27 [1.18; 1.37]), depression without cardiometabolic disease (OR [95% CI] = 2.68 [2.39; 3.00]), and comorbidity between both conditions (OR [95% CI] = 3.04 [2.51; 3.68]) in adulthood. Post hoc analyses showed that the association with comorbidity was stronger than with either disease alone, and the association with depression was stronger than with cardiometabolic disease. Associations remained significant after additionally adjusting for lifestyle factors, and were present in both males and females, and for all maltreatment types.ConclusionsThis meta-analysis revealed that adults with a history of childhood maltreatment suffer more often from depression and cardiometabolic disease than their non-exposed peers. These adults are also three times more likely to have comorbid depression and cardiometabolic disease. Childhood maltreatment may therefore be a clinically relevant indicator connecting poor mental and somatic health. Future research should investigate the potential benefits of early intervention in individuals with a history of maltreatment on their distal mental and somatic health (PROSPERO CRD42021239288). Show less
Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of... Show moreIdentifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.Mathieson et al. carried out a genome-wide association study of reproductive success (number of children born) in humans, revealing the importance of diverse neuro-endocrine and behavioural factors. Show less
PurposeSiblings of probands with depressive and anxiety disorders are at increased risk for psychopathology, but little is known about how risk factors operate within families to increase... Show morePurposeSiblings of probands with depressive and anxiety disorders are at increased risk for psychopathology, but little is known about how risk factors operate within families to increase psychopathology for siblings. We examined the additional impact of psychosocial risk factors in probands—on top of or in combination with those in siblings—on depressive/anxious psychopathology in siblings.MethodsThe sample included 636 participants (Mage = 49.7; 62.4% female) from 256 families, each including a proband with lifetime depressive and/or anxiety disorders and their sibling(s) (N = 380 proband-sibling pairs). Sixteen psychosocial risk factors were tested. In siblings, depressive and anxiety disorders were determined with standardized psychiatric interviews; symptom severity was measured using self-report questionnaires. Analyses were performed with mixed-effects models accounting for familial structure.ResultsIn siblings, various psychosocial risk factors (female gender, low income, childhood trauma, poor parental bonding, being single, smoking, hazardous alcohol use) were associated with higher symptomatology and likelihood of disorder. The presence of the same risk factor in probands was independently associated (low income, being single) with higher symptomatology in siblings or moderated (low education, childhood trauma, hazardous alcohol use)—by reducing its strength—the association between the risk factor and symptomatology in siblings. There was no additional impact of risk factors in probands on likelihood of disorder in siblings.ConclusionOur findings demonstrate the importance of weighing psychosocial risk factors within a family context, as it may provide relevant information on the risk of affective psychopathology for individuals. Show less
