Lachlan T. Strike

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.

Genetic architecture of subcortical brain regions: common and region-specific genetic contributions

Understanding the aetiology of patterns of variation within and covariation across brain regions is key to advancing our understanding of the functional, anatomical and developmental networks of the brain. Here we applied multivariate twin modelling and principal component analysis (PCA) to investigate the genetic architecture of the size of seven subcortical regions (caudate nucleus, thalamus, putamen, pallidum, hippocampus, amygdala and nucleus accumbens) in a genetically informative sample of adolescents and young adults (N = 1038; mean age = 21.6 ± 3.2 years; including 148 monozygotic and 202 dizygotic twin pairs) from the Queensland Twin IMaging (QTIM) study. Our multivariate twin modelling identified a common genetic factor that accounts for all the heritability of intracranial volume (0.88) and a substantial proportion of the heritability of all subcortical structures, particularly those of the thalamus (0.71 out of 0.88), pallidum (0.52 out of 0.75) and putamen (0.43 out of 0.89). In addition, we also found substantial region‐specific genetic contributions to the heritability of the hippocampus (0.39 out of 0.79), caudate nucleus (0.46 out of 0.78), amygdala (0.25 out of 0.45) and nucleus accumbens (0.28 out of 0.52). This provides further insight into the extent and organization of subcortical genetic architecture, which includes developmental and general growth pathways, as well as the functional specialization and maturation trajectories that influence each subcortical region.

The effect of increased genetic risk for Alzheimer's disease on hippocampal and amygdala volume

Reduction in hippocampal and amygdala volume measured via structural magnetic resonance imaging is an early marker of Alzheimers disease (AD). Whether genetic risk factors for AD exert an effect on these subcortical structures independent of clinical status has not been fully investigated. We examine whether increased genetic risk for AD influences hippocampal and amygdala volumes in case-control and population cohorts at different ages, in 1674 older (aged >53 years; 17% AD, 39% mild cognitive impairment [MCI]) and 467 young (16-30 years) adults. An AD polygenic risk score combining common risk variants excluding apolipoprotein E (APOE), and a single nucleotide polymorphism in TREM2, were both associated with reduced hippocampal volume in healthy older adults and those with MCI. APOE ε4 was associated with hippocampal and amygdala volume in those with AD and MCI but was not associated in healthy older adults. No associations were found in young adults. Genetic risk for AD affects the hippocampus before the clinical symptoms of AD, reflecting a neurodegenerative effect before clinical manifestations in older adults.

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.

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.

Lingual Gyrus surface area is associated with anxiety-depression severity in young adults: a genetic clustering approach

Abstract Here we aimed to identify cortical endophenotypes for anxiety-depression. Our data-driven approach used vertex-wise genetic correlations (estimated from a twin sample: 157 monozygotic and 194 dizygotic twin pairs) to parcellate cortical thickness (CT) and surface area (SA) into genetically homogeneous regions (Chen et al., 2013). In an overlapping twin and sibling sample (n = 834; aged 15–29, 66% female), in those with anxiety-depression Somatic and Psychological Health Report (SPHERE) scores (Hickie et al., 2001) above median, we found a reduction of SA in an occipito-temporal cluster, which comprised part of the right lingual, fusiform and parahippocampal gyrii. A similar reduction was observed in the Human Connectome Project (HCP) sample (n = 890, age 22–37, 56.5% female) in those with Adult Self Report (ASR) DSM-oriented scores (Achenbach et al., 2005) in the 25–95% quantiles. A post hoc vertex-wise analysis identified the right lingual and, to a lesser extent the fusiform gyrus. Overall, the surface reduction explained by the anxiety-depression scores was modest (r = −0.10, 3rd order spline, and r = −0.040, 1st order spline in the HCP). The discordant results in the top 5% of the anxiety-depression scores may be explained by differences in recruitment between the studies. However, we could not conclude whether this cortical region was an endophenotype for anxiety-depression as the genetic correlations did not reach significance, which we attribute to the modest effect size (post hoc statistical power <10%).

Description of left and right CT and SA clusters used in the publication "Lingual Gyrus surface area is associated with anxiety-depression severity in young adults: a genetic clustering approach"

nData provided in. asc format, which allows opening in text editor and easy plotting un Freeview after converting to .mgh using the code: mris_convert -c ./input.asc /Applications/freesurfer/subjects/fsaverage4/surf/lh.orig ./input.mgh.

Association of anxiety-depression score with right lingual surface area: true association or false positive?

Individual illness severity may be measured by the degree of overall psychosocial functioning. We studied whether the presence of one or more copy number variants (CNVs) is associated with the level of psychosocial impairment measured by the Global Assessment of Functioning (GAF; DSMIV Axis V) scale in a sample of individuals with DSM-IV schizophrenia (SZ). The GAF score measures the overall functioning level of an individual from 1 (lowest) to 100 (highest). Using a genome-wide, high-quality CNV dataset, we assessed whether CNVs are related to GAF values collected for three points in time over the individual course of disease: before illness onset, the “worst ever” (during an illness episode) and the current (in remission) GAF score. Investigating GAF values adjusted for phenotypic predictors, our analysis revealed a trend towards lower psychosocial functioning at the “worst ever” GAF in individuals possessing one or more CNVs compared to individuals without CNVs. An exploratory analysis of CNVs present in the study sample found a protective effect on the current GAF score for a duplication on chromosome 10q26.3.Background: Alcohol and nicotine consumption are two of the most important preventable causes of morbidity and premature death worldwide. In western populations, alcohol and nicotine consumption are highly correlated which further increases medical costs as co-use is associated with even worse health outcomes than either of the substances used alone. In order to improve the efficacy of prevention and treatment strategies, we need a better understanding of risk factors contributing to harmful alcohol and nicotine consumption. Phenotypic correlations between alcohol and nicotine consumption are at least partly explained by overlap in genetic risk factors. Therefore, we aim to investigate the genetic architecture of multiple phenotypes associated with alcohol and nicotine consumption, including the number of alcoholic beverages, heavy vs. non heavy drinking, number of cigarettes smoked per day (CPD), age of smoking initiation, ever vs. never smoker, and heavy vs. non-heavy smoker. Methods: Phenotypes have been assessed in a general population sample including 16,000 subjects from the Netherlands. All subjects have been genotyped on the Illumina Human Exome BeadChip v1.1 that interrogates 250,000 nonsense, missense, and splice site variants with an allele frequency >=1% allowing us to evaluate the role of functional, rare variants. Genotyping and calling was conducted at a single laboratory according to uniform procedures which facilitates comparison of genotype frequencies between groups. Results: Preliminary analysis of a single phenotype (i.e., number of alcoholic drinks per week) in a subset of the total sample (N=1,491) revealed several promising findings (see Figure 1). Interestingly, the genetic variant most strongly associated with alcohol consumption (beta=0.11; p=4*10-6) was located at chromosome 11 in the tumor P53-Regulated Apoptosis-Inducing Protein 1 (TP53AIP1). Mutations in a gene from the same P53 gene family were previously found to be associated with alcohol consumption. In this relatively small pilot study, no findings were statistically significant, but power analysis of the top finding (minor allele frequency=0.20, p=0.11) shows that increasing the sample size to ~16,000 will provide enough statistical power (0.83) to detect this particular variant. Discussion: This work will be extended to the full sample and will focus on the detection of rare genetic variants involved in different alcohol and nicotine phenotypes. Since all phenotypes have been assessed in the same subjects, we will also be able to determine genetic variants that explain the phenotypic concordance across multiple traits using multivariate genetic analyses. Methodological challenges specific to population-based association analysis of rare variants and quantitative behavioral traits will be discussed.

Structural brain alterations in major depression: findings from the ENIGMA Major Depressive Disorder Working Group

Background: Patterns of structural brain alterations in major depressive disorder (MDD) remain 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. Therefore, we initiated the ENIGMA-MDD Working Group to identify robust imaging markers of MDD using coordinated standardized image processing and statistical analysis protocols. Here, we investigated subcortical volume alterations in MDD in the largest sample to date using an individual participant data (IPD) based metaanalysis approach.