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Andrew M. McIntosh
University of Edinburgh
PsychiatryPsychologyBipolar disorderSchizophreniaBiology
624Publications
75H-index
25.6kCitations
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Publications 690
Newest
#2Futao ZhangH-Index: 12
Last. Riccardo E. MarioniH-Index: 40
view all 22 authors...
Availability of Data and Material According to the terms of consent for GS participants, access to individual-level data (omics and phenotypes) must be reviewed by the GS Access Committee. Applications should be made to access@generationscotland.org. Full summary statistics for the analyses presented are publicly available online at https://doi.org/10.7488/ds/2709. Funding GS received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the S...
2 CitationsSource
#1Azmeraw T. Amare (University of Adelaide)H-Index: 40
#2Ahmad Vaez (IUMS: Isfahan University of Medical Sciences)H-Index: 11
Last. Catharina A. HartmanH-Index: 52
view all 11 authors...
Although a genetic basis of depression has been well established in twin studies, identification of genome-wide significant loci has been difficult. We hypothesized that bivariate analyses of findings from a meta-analysis of genome-wide association studies (meta-GWASs) of the broad depression phenotype with those from meta-GWASs of self-reported and recurrent major depressive disorder (MDD), bipolar disorder and schizophrenia would enhance statistical power to identify novel genetic loci for dep...
14 CitationsSource
#1Laura S. van Velzen (University of Melbourne)H-Index: 8
#2Sinead Kelly (Brigham and Women's Hospital)H-Index: 14
Last. Lianne Schmaal (University of Melbourne)H-Index: 22
view all 71 authors...
Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12–88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Worki...
7 CitationsSource
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#1Aleks Stolicyn (Royal Edinburgh Hospital)
#2Mathew A. Harris (Royal Edinburgh Hospital)
Last. Stephen M. Lawrie (Royal Edinburgh Hospital)H-Index: 55
view all 13 authors...
Major depressive disorder (MDD) has been the subject of many neuroimaging case-control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically-ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well-phenotyped community-based group of current MDD cases with clinical interview-based diagnose...
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#1Alex S. F. Kwong (UoB: University of Bristol)H-Index: 2
#2Rebecca M. Pearson (UoB: University of Bristol)H-Index: 21
Last. Stan Zammit (Cardiff University)H-Index: 5
view all 24 authors...
Background: The impact of COVID-19 on mental health is unclear. Evidence from longitudinal studies with pre pandemic data are needed to address (1) how mental health has changed from pre-pandemic levels to during the COVID-19 pandemic and (2), whether there are groups at greater risk of poorer mental health during the pandemic? Methods: We used data from COVID-19 surveys (completed through April/May 2020), nested within two large longitudinal population cohorts with harmonised measures of mental...
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#1Miruna C. Barbu (Edin.: University of Edinburgh)H-Index: 5
#2Xueyi Shen (Edin.: University of Edinburgh)H-Index: 7
Last. Yanni Zeng (SYSU: Sun Yat-sen University)H-Index: 4
view all 13 authors...
Variation in DNA methylation (DNAm) is associated with lifestyle factors such as smoking and body mass index (BMI) but there has been little research exploring its ability to identify individuals with major depressive disorder (MDD). Using penalised regression on genome-wide CpG methylation, we tested whether DNAm risk scores (MRS), trained on 1223 MDD cases and 1824 controls, could discriminate between cases (n = 363) and controls (n = 1417) in an independent sample, comparing their predictive ...
1 CitationsSource
#1Daniel Trejo Banos (UNIL: University of Lausanne)
#2Daniel L. McCartney (Edin.: University of Edinburgh)H-Index: 5
Last. Archie Campbell (Edin.: University of Edinburgh)H-Index: 24
view all 23 authors...
Linking epigenetic marks to clinical outcomes improves insight into molecular processes, disease prediction, and therapeutic target identification. Here, a statistical approach is presented to infer the epigenetic architecture of complex disease, determine the variation captured by epigenetic effects, and estimate phenotype-epigenetic probe associations jointly. Implicitly adjusting for probe correlations, data structure (cell-count or relatedness), and single-nucleotide polymorphism (SNP) marke...
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#1Samuel Rupprechter (Edin.: University of Edinburgh)H-Index: 1
#2Liana Romaniuk (Edin.: University of Edinburgh)H-Index: 16
Last. Mathew A. Harris (Edin.: University of Edinburgh)H-Index: 9
view all 19 authors...
Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex an...
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#1Lianne SchmaalH-Index: 22
#2Elena PozziH-Index: 2
Last. Dick J. VeltmanH-Index: 69
view all 78 authors...
A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging ...
3 CitationsSource
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