Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders.

Psychological medicine - 1 Jul 2024

Zheng Junjie, Zong Xiaofen, Tang Lili, Guo Huiling, Zhao Pengfei, Womer Fay Y, Zhang Xizhe, Tang Yanqing, Wang Fei

Abstract excerpt

BACKGROUND: Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine. METHODS: We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Bipolar Disorder
Share to Brain

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Case-Control Studies

Share to Gray Matter

Share to Magnetic Resonance Imaging

Share to Major Depressive Disorder

Share to Mood Disorders

Share to Neuroimaging

Source

Identifiers

PMID: 38804091
DOI: 10.1017/S0033291724000886

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders.PMID 38804091Read ↗

Normative modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in major depressive disorderSemantic proximity Read ↗

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk.Semantic proximity Read ↗

Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and symptom severitySemantic proximity Read ↗

Mapping generalizable brain-based depression subtypes across clinical, cognitive, and neurotransmitter dimensionsSemantic proximity Read ↗

Separating Clinical and Subclinical Depression by Big Data Informed Structural Vulnerability Index and Its impact on Cognition: ENIGMA Dot ProductSemantic proximity Read ↗

Profound and reproducible patterns of reduced regional gray matter characterize major depressive disorderSemantic proximity Read ↗

Gray matter volumetric correlates of the polygenic risk of depression: A study of the Human Connectome Project data.Semantic proximity Read ↗

Association between polygenic risk for Major Depression and brain structure in a mega-analysis of 50,975 participants across 11 studies.Semantic proximity Read ↗

Parsing clinical and neurobiological sources of heterogeneity in depressionSemantic proximity Read ↗

Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortalitySemantic proximity Read ↗

Biotypes of deeply phenotyped depressed patients reflect signatures of adverse childhood experience and depressive cognitive biases.Semantic proximity Read ↗

Age-dependent acceleration of structural brain aging in medication-free major depressive disorder linked to neuroanatomical phenotype findings from COORDINATE-MDD consortiumSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.