Paul Thompson

Paul Thompson
University of Southern California | USC · Department of Neurology

About

2,004
Publications
287,238
Reads
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114,593
Citations
Introduction
Paul Thompson's team co-leads the "ENIGMA Consortium" (http://enigma.ini.usc.edu), now performing the largest brain imaging studies in the world. The effort involves 340 institutions and >2,000 scientists, analyzing brain scans and genomic data from >53,000 people. ENIGMA's working groups are supported by Dr. Thompson's team and 65 leading scientists across Europe and Asia, in large scale projects on depression, schizophrenia, bipolar illness, autism, ADHD, HIV, 22q deletion syndrome, and OCD.
Additional affiliations
September 1993 - September 2013
University of California, Los Angeles
Position
  • Professor (Full)

Publications

Publications (2,004)
Preprint
Full-text available
Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and brain diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization meth...
Article
Objective: The variety of instruments used to assess posttraumatic stress disorder (PTSD) allows for flexibility, but also creates challenges for data synthesis. The objective of this work was to use a multisite mega analysis to derive quantitative recommendations for equating scores across measures of PTSD severity. Method: Empirical Bayes harm...
Article
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Changes in the levels of circulating proteins are associated with Alzheimer’s disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33–ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological ch...
Preprint
Mechanisms underpinning neurotypical age-related variations in cortical thickness in the human brain remain insufficiently specified. Here we used cell-specific marker genes, followed by gene ontology and enrichment analyses, to quantify the association between gene-expression levels and inter-regional age-related variations in neurotypical cortica...
Article
Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer’s Disease Neuroimagin...
Preprint
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MRI-based modeling of brain networks has been widely used to understand functional and structural interactions and connections among brain regions, and factors that affect them, such as brain development and disease. Graph mining on brain networks may facilitate the discovery of novel biomarkers for clinical phenotypes and neurodegenerative disease...
Preprint
Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate...
Preprint
Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily exa...
Article
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The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we ai...
Article
Importance: Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease. Objective: To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort o...
Preprint
Full-text available
Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to structural covariance patterns across brain regions and individuals. We present a mega-analysis of structural covariance with magnetic resonance imaging of 50,699 healthy and diseased individuals (12 studies, 130 sites, and 12 countries)...
Article
Full-text available
Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomo...
Article
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Hemispheric lateralization constitutes a core architectural principle of human brain organization underlying cognition, often argued to represent a stable, trait-like feature. However, emerging evidence underlines the inherently dynamic nature of brain networks, in which time-resolved alterations in functional lateralization remain uncharted. Integ...
Preprint
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morp...
Article
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The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has...
Chapter
Diffusion MRI-derived brain structural connectomes or brain networks are widely used in the brain research. However, constructing brain networks is highly dependent on various tractography algorithms, which leads to difficulties in deciding the optimal view concerning the downstream analysis. In this paper, we propose to learn a unified representat...
Preprint
Hemispheric lateralization constitutes a core architectural principle of human brain organization underlying cognition, often argued to represent a stable, trait-like feature. However, emerging evidence underlines the inherently dynamic nature of brain networks, in which time-resolved alterations in functional lateralization remain uncharted. Integ...
Article
Full-text available
DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neur...
Article
Visually identifying effective bio-markers from human brain networks poses non-trivial challenges to the field of data visualization and analysis. Existing methods in the literature and neuroscience practice are generally limited to the study of individual connectivity features in the brain (e.g., the strength of neural connection among brain regio...
Presentation
Full-text available
Introduction Chronic pain (CP) has a severe impact on quality of life, and is the leading cause of disability and disease burden globally. The central nervous system plays a key role in the development and maintenance of CP, but pain remains self-reported and there are no clear biomarkers to assess CP. Large highly-powered studies are needed. We ai...
Article
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Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive–compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and t...
Article
We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chron...
Preprint
Full-text available
Hyperbolic geometry has been successfully applied in modeling brain cortical and subcortical surfaces with general topological structures. However such approaches, similar to other surface based brain morphology analysis methods, usually generate high dimensional features. It limits their statistical power in cognitive decline prediction research,...
Preprint
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The amount of biomedical data continues to grow rapidly. However, the ability to analyze these data is limited due to privacy and regulatory concerns. Machine learning approaches that require data to be copied to a single location are hampered by the challenges of data sharing. Federated Learning is a promising approach to learn a joint model over...
Preprint
Deep Learning for neuroimaging data is a promising but challenging direction. The high dimensionality of 3D MRI scans makes this endeavor compute and data-intensive. Most conventional 3D neuroimaging methods use 3D-CNN-based architectures with a large number of parameters and require more time and data to train. Recently, 2D-slice-based models have...
Article
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Abstract This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci as...
Article
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22q11.2 deletion syndrome (22q11DS)—a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22—is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but sma...
Preprint
Full-text available
We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronol...
Article
Full-text available
No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface are...
Article
Full-text available
First‐degree relatives of patients diagnosed with schizophrenia (SZ‐FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First‐degree relatives of patients diagnosed with bipolar disorder (BD‐FDRs) show divergent patterns; on average, intracranial volume is larger compared to co...
Article
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The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans f...
Chapter
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology, for an individual brain, mining a discriminative network representation from the multimodal brain networks is non-trivial. The recent success of deep learning technique...
Article
Full-text available
Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individua...
Article
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Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal app...
Preprint
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Sex differences are found in the incidence and expression of psychiatric and neurodegenerative conditions, and many studies suggest these differences are influenced by innate biological differences between males and females and risk factors that interact with these differences. However, few studies have used neuroimaging to examine brain signatures...
Article
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The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion...
Preprint
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology, for an individual brain, mining a discriminative network representation from the multimodal brain networks is non-trivial. The recent success of deep learning technique...
Article
Full-text available
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...
Article
Full-text available
Post-traumatic stress disorder (PTSD) is a highly disabling condition, increasingly recognized as both a disorder of mental health and social burden, but also as an anxiety disorder characterized by fear, stress, and negative alterations in mood. PTSD is associated with structural, metabolic, and molecular changes in several brain regions and the n...
Preprint
Pooled imaging data from multiple sources is subject to bias from each source. Studies that do not correct for these scanner/site biases at best lose statistical power, and at worst leave spurious correlations in their data. Estimation of the bias effects is non-trivial due to the paucity of data with correspondence across sites, so called "traveli...
Article
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Estimating the polygenicity (proportion of causally associated single nucleotide polymorphisms (SNPs)) and discoverability (effect size variance) of causal SNPs for human traits is currently of considerable interest. SNP-heritability is proportional to the product of these quantities. We present a basic model, using detailed linkage disequilibrium...
Article
Full-text available
Left–right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures a...
Article
Full-text available
Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods...
Article
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Background Schizophrenia (SZ) and bipolar disorder (BD) are both associated with generally lower IQ test results and show overlapping structural brain abnormalities, albeit with lower effect sizes in BD. In contrast, our recent ENIGMA-Relatives meta-analysis showed that patients’ first-degree relatives (FDRs) have divergent patterns of global brain...
Article
Full-text available
Background Cortical neuroanatomical abnormalities have been reported along a continuum between individuals with chronic schizophrenia, first-episode psychosis, clinical high risk for psychosis, and healthy individuals self-reporting subclinical psychotic-like experiences (or schizotypy). Recently, the Schizophrenia Working Group within the ENIGMA (...
Article
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Background Negative symptoms can be seen to represent a continuum from subclinical manifestations in the general population to severe symptoms in schizophrenia. Neuroanatomical studies show evidence of fronto-striatal structural abnormalities linked to negative symptoms in patients with schizophrenia (Walton et al. 2018). However, it remains an ope...
Preprint
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Background: Suicidal behavior is highly heterogeneous and complex. A better understanding of its biological substrates and mechanisms could inform the design of more effective suicide prevention and intervention strategies. Neuroimaging studies of suicidality have so far been conducted in small samples, prone to biases and false-positive associatio...
Preprint
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Objective: The coronavirus disease 2019 (COVID-19) - a novel and highly infectious pneumonia - has now spread across China and beyond for over four months. However, its psychological impact on patients is unclear. We aim to examine the prevalence and associated risk factors for psychological morbidities and fatigue in patients with confirmed COVID-...
Article
Background: Disease progression prediction based on neuroimaging biomarkers is vital in Alzheimer's disease (AD) research. Convolutional neural networks (CNN) have been proved to be powerful for various computer vision research by refining reliable and high-level feature maps from image patches. Objective: A key challenge in applying CNN to neur...
Preprint
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Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1,021 adults with epilepsy compared to 1,564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy co-l...
Preprint
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Cortisol is considered the most fundamental stress hormone and is elevated in stress and multiple neuropsychiatric conditions. Prior studies have shown associations of plasma cortisol levels with total cerebral and hippocampal volumes and less consistently with the amygdala. Here, we extend our hypothesis to test associations of plasma cortisol wit...
Preprint
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Background: Brain structure abnormalities throughout the course of Parkinson's Disease (PD) have yet to be fully elucidated. Inconsistent findings across studies may be partly due to small sample sizes and heterogeneous analysis methods. Using a multicenter approach and harmonized analysis methods, we aimed to overcome these limitations and shed li...
Article
Full-text available
Losing an only child is a devastating life event that a parent can experience and may lead to post-traumatic stress disorder (PTSD). Social support could buffer against the negative influence of this trauma, but the neural mechanism underlying this alleviation effect remains poorly understood. In this study, voxel-based morphometry was conducted on...
Article
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Deviations in neurodevelopment may underlie the association between lower childhood socioeconomic status and difficulties in cognitive and socioemotional domains. Most previous investigations of the association between childhood socioeconomic status and brain morphology have used cross-sectional designs with samples that span wide age ranges, occlu...