ArticleNeuroImage2010
Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies.
Article in NeuroImage, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 672 papers, 13 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
672 citing papers in PubMed, 13 syntheses or guidelines pooled it, 1,199 citations in OpenAlex.
- The Genetic Architecture of the Human Corpus Callosum and its Subregions.Nature communications · 2025Pooled it
- Shared cortical characteristics in major depressive disorder, anxiety disorder, and chronic pain: a structural MRI meta-analysis study.Translational psychiatry · 2025Pooled it
- Shared neuroimaging and molecular profiles in type 2 diabetes mellitus and major depressive disorder: an integrative analysis of genetic, transcriptomic, and neuroimaging data.Translational psychiatry · 2025Pooled it
- Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study.The American journal of psychiatry · 2025Pooled it
- Convergent Neuroimaging and Molecular Signatures in Mild Cognitive Impairment and Alzheimer's Disease: A Data-Driven Meta-Analysis with N = 3,118.Neuroscience bulletin · 2024Pooled it
- Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder.BMC medicine · 2024Pooled it
- Effects of electroconvulsive therapy on cortical thickness in depression: a systematic review.Acta neuropsychiatrica · 2024Pooled it
- Cortical thickness abnormalities in autism spectrum disorder.European child & adolescent psychiatry · 2024Pooled it
- Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses.Molecular psychiatry · 2023Pooled it
- Country-level gender inequality is associated with structural differences in the brains of women and men.Proceedings of the National Academy of Sciences of the United States of America · 2023Pooled it
- Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders.Biological psychiatry · 2023Pooled it
- Brain Structure in Acutely Underweight and Partially Weight-Restored Individuals With Anorexia Nervosa: A Coordinated Analysis by the ENIGMA Eating Disorders Working Group.Biological psychiatry · 2022Pooled it
- Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings.Psychiatry and clinical neurosciences · 2022Pooled it
- Lifespan exposure to hormone therapies and structural brain morphometry in older women.NeuroImage · 2026Trial
- Culture, prefrontal volume, and memory.PloS one · 2024Trial
- Trial
- Brain Structure Measurements Predict Individualized Treatment Outcome of 12-Week Antipsychotic Monotherapies in First-episode Schizophrenia.Schizophrenia bulletin · 2023Trial
- Structural connectivity of auditory-linguistic brain networks predicts success in speech categorization and listening in noise.Neuroscience · 2026Article
- Greater temporo-occipital gray matter volume and frontoparietal cortical thickness in post-menopausal women: a UK Biobank study.Brain structure & function · 2026Article
- Detailed Analysis of Intraretinal Layers and Their Correlation to Brain Structures in Normal Healthy Aging.Translational vision science & technology · 2026Article
612 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies is unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.