Baptiste Couvy-Duchesne

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen’s d effect sizes: −0.10 to −0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: −0.26 to −0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

Head Motion and Inattention/Hyperactivity Share Common Genetic Influences: Implications for fMRI Studies of ADHD

Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity.

Genetic effects influencing risk for major depressive disorder in China and Europe

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Subcortical brain structure and suicidal behaviour in major depressive disorder: a meta-analysis from the ENIGMA-MDD working group

The aetiology of suicidal behaviour is complex, and knowledge about its neurobiological mechanisms is limited. Neuroimaging methods provide a noninvasive approach to explore the neural correlates of suicide vulnerability in vivo. The ENIGMA-MDD Working Group is an international collaboration evaluating neuroimaging and clinical data from thousands of individuals collected by research groups from around the world. Here we present analyses in a subset sample (n=3097) for whom suicidality data were available. Prevalence of suicidal symptoms among major depressive disorder (MDD) cases ranged between 29 and 69% across cohorts. We compared mean subcortical grey matter volumes, lateral ventricle volumes and total intracranial volume (ICV) in MDD patients with suicidal symptoms (N=451) vs healthy controls (N=1996) or MDD patients with no suicidal symptoms (N=650). MDD patients reporting suicidal plans or attempts showed a smaller ICV (P=4.12 × 10−3) or a 2.87% smaller volume compared with controls (Cohen’s d=−0.284). In addition, we observed a nonsignificant trend in which MDD cases with suicidal symptoms had smaller subcortical volumes and larger ventricular volumes compared with controls. Finally, no significant differences (P=0.28–0.97) were found between MDD patients with and those without suicidal symptoms for any of the brain volume measures. This is by far the largest neuroimaging meta-analysis of suicidal behaviour in MDD to date. Our results did not replicate previous reports of association between subcortical brain structure and suicidality and highlight the need for collecting better-powered imaging samples and using improved suicidality assessment instruments.

Hair Cortisol in Twins: Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.

Association Between Population Density and Genetic Risk for Schizophrenia

Importance Urban life has been proposed as an environmental risk factor accounting for the increased prevalence of schizophrenia in urban areas. An alternative hypothesis is that individuals with increased genetic risk tend to live in urban/dense areas. Objective To assess whether adults with higher genetic risk for schizophrenia have an increased probability to live in more populated areas than those with lower risk. Design, Setting, and Participants Four large, cross-sectional samples of genotyped individuals of European ancestry older than 18 years with known addresses in Australia, the United Kingdom, and the Netherlands were included in the analysis. Data were based on the postcode of residence at the time of last contact with the participants. Community-based samples who took part in studies conducted by the Queensland Institute for Medical Research Berghofer Medical Research Institute (QIMR), UK Biobank (UKB), Netherlands Twin Register (NTR), or QSkin Sun and Health Study (QSKIN) were included. Genome-wide association analysis and mendelian randomization (MR) were included. The study was conducted between 2016 and 2018. Exposures Polygenic risk scores for schizophrenia derived from genetic data (genetic risk is independently measured from the occurrence of the disease). Socioeconomic status of the area was included as a moderator in some of the models. Main Outcomes and Measures Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested. Results The QIMR participants (15 544; 10 197 [65.6%] women; mean [SD] age, 54.4 [13.2] years) living in more densely populated areas (people per square kilometer) had a higher genetic loading for schizophrenia (r2 = 0.12%; P = 5.69 × 10−5), a result that was replicated across all 3 other cohorts (UKB: 345 246; 187 469 [54.3%] women; age, 65.7 [8.0] years; NTR: 11 212; 6727 [60.0%] women; age, 48.6 [17.5] years; and QSKIN: 15 726; 8602 [54.7%] women; age, 57.0 [7.9] years). This genetic association could account for 1.7% (95% CI, 0.8%-3.2%) of the schizophrenia risk. Estimates from MR analyses performed in the UKB sample were significant (b = 0.049; P = 3.7 × 10−7 using GSMR), suggesting that the genetic liability to schizophrenia may have a causal association with the tendency to live in urbanized locations. Conclusions and Relevance The results of this study appear to support the hypothesis that individuals with increased genetic risk tend to live in urban/dense areas and suggest the need to refine the social stress model for schizophrenia by including genetics as well as possible gene-environment interactions.

Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness

&NA; Quantifying the genetic architecture of the cerebral cortex is necessary for understanding disease and changes to the brain across the lifespan. Prior work shows that both surface area (SA) and cortical thickness (CT) are heritable. However, we do not yet understand the extent to which region‐specific genetic factors (i.e., independent of global effects) play a dominant role in the regional patterning or inter‐regional associations across the cortex. Using a population sample of young adult twins (N = 923), we show that the heritability of SA and CT varies widely across regions, generally independent of measurement error. When global effects are controlled for, we detected a complex pattern of genetically mediated clusters of inter‐regional associations, which varied between hemispheres. There were generally weak associations between the SA of different regions, except within the occipital lobe, whereas CT was positively correlated within lobar divisions and negatively correlated across lobes, mostly due to genetic covariation. These findings were replicated in an independent sample of twins and siblings (N = 698) from the Human Connectome Project. The different genetic contributions to SA and CT across regions reveal the value of quantifying sources of covariation to appreciate the genetic complexity of cortical structures.

Nineteen and Up study (19Up): understanding pathways to mental health disorders in young Australian twins

Purpose The Nineteen and Up study (19Up) assessed a range of mental health and behavioural problems and associated risk factors in a genetically informative Australian cohort of young adult twins and their non-twin siblings. As such, 19Up enables detailed investigation of genetic and environmental pathways to mental illness and substance misuse within the Brisbane Longitudinal Twin Sample (BLTS). Participants Twins and their non-twin siblings from Queensland, Australia; mostly from European ancestry. Data were collected between 2009 and 2016 on 2773 participants (age range 18–38, 57.8% female, 372 complete monozygotic pairs, 493 dizygotic pairs, 640 non-twin siblings, 403 singleton twins). Findings to date A structured clinical assessment (Composite International Diagnostic Interview) was used to collect lifetime prevalence of diagnostic statistical manual (4th edition) (DSM-IV) diagnoses of major depressive disorder, (hypo)mania, social anxiety, cannabis use disorder, alcohol use disorder, panic disorder and psychotic symptoms. Here, we further describe the comorbidities and ages of onset for these mental disorders. Notably, two-thirds of the sample reported one or more lifetime mental disorder. In addition, the 19Up study assessed general health, drug use, work activity, education level, personality, migraine/headaches, suicidal thoughts, attention deficit hyperactivity disorder (ADHD) symptomatology, sleep–wake patterns, romantic preferences, friendships, familial environment, stress, anorexia and bulimia as well as baldness, acne, asthma, endometriosis, joint flexibility and internet use. The overlap with previous waves of the BLTS means that 84% of the 19Up participants are genotyped, 36% imaged using multimodal MRI and most have been assessed for psychological symptoms at up to four time points. Furthermore, IQ is available for 57%, parental report of ADHD symptomatology for 100% and electroencephalography for 30%. Future plans The 19Up study complements a phenotypically rich, longitudinal collection of environmental and psychological risk factors. Future publications will explore hypotheses related to disease onset and development across the waves of the cohort. A follow-up study at 25+years is ongoing.

Higher Genetic Risk For Schizophrenia Is Associated With Living In Urban And Populated Areas

Background The prevalence of schizophrenia is higher in urban areas than in rural areas. The association between urbanization and schizophrenia has been reported before in relation to place of birth, place of upbringing and place of residence. Two major hypotheses have been proposed to explain this phenomenon: (1) the causation hypothesis, where the stress of city life and undefined factors in the urban environment would increase the risk of this disease, and (2) the selection hypothesis, where individuals with genetic liability for schizophrenia would move into urban areas. On the other hand, genetic factors have been shown to have a higher impact on the country v.s city living as people grow older (>40y), while the impact of family background decreases. Heritability estimates reported for full ACE models were 12.7%, 22% and 41.2% for those under 20, 20-40 and over 40, respectively. Our aim was to test the alternative hypothesis that adults with higher genetic risk for schizophrenia are more likely to move to and live in urbanized and populated areas than those with lower risk. Methods Our sample was comprised of 15,253 participants in 7,007 families (63.4% women) over 40 years old (M = 54.43, SD = 10.86) living in Australia. The participants reported their postcode as part of the protocols of several studies on health and wellbeing conducted from QIMR. Participants were genotyped genome-wide and imputed to 1000G v.3. We used three measures of urbanicity; (i) subjects’ zip code were categorized into urban, suburban or rural zones; we also computed (ii) distance to the closest city centre and (iii) the population density of the postcode district. Polygenic risk scores (PRS) for schizophrenia based on summary statistics from the Psychiatric Genomics Consortium (PGC-2) were computed with PLINK 1.90 (version 3) for eight different P-value thresholds. We used linear mixed models to predict the three urbanicity measures from the schizophrenia PRS, controlling for age, sex, genetic principal components, GWAS chip and genetic relationship matrix. Predictions were calculated using GCTA (Genome-wide Complex Trait Analysis, version 1.22). Results Genetic risk for schizophrenia was associated with the place where the participants lived in the expected direction, with increased effects as the risk scores included more SNPs. P-values for PRS at thresholds Discussion Our results suggest that people with a higher genetic risk for schizophrenia may prefer to live in more urban and populated areas. Importantly, this study does not use a case-control sample but a non-selected sample where the genetic risk for schizophrenia was estimated. This study proposes that greater genetic predisposition to schizophrenia is at least one mechanism explaining why this illness is more prevalent in city environments. Future research should test if this effect is replicated in other countries. Financial Support: NHMRC Grant 1103603