Causal relationships involving brain imaging-derived phenotypes based on UKB imaging cohort: a review of Mendelian randomization studies

M Wang, Z Wang, Y Wang, Q Zhou… - Frontiers in Neuroscience, 2024 - frontiersin.org
The UK Biobank (UKB) has the largest adult brain imaging dataset, which encompasses
over 40,000 participants. A significant number of Mendelian randomization (MR) studies …

The genetic architecture of multimodal human brain age

J Wen, B Zhao, Z Yang, G Erus, I Skampardoni… - Nature …, 2024 - nature.com
The complex biological mechanisms underlying human brain aging remain incompletely
understood. This study investigated the genetic architecture of three brain age gaps (BAG) …

The Genetic Heterogeneity of Multimodal Human Brain Age

J Wen, B Zhao, Z Yang, G Erus, I Skampardoni… - bioRxiv, 2023 - biorxiv.org
The complex biological mechanisms underlying human brain aging remain incompletely
understood, involving multiple body organs and chronic diseases. In this study, we used …

[HTML][HTML] Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study

C Constantinides, V Baltramonaityte, D Caramaschi… - cortex, 2024 - Elsevier
Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting
that brain structure is often 'older'than expected at a given chronological age. Whether …

Dimensions of early life adversity are differentially associated with patterns of delayed and accelerated brain maturation

D Beck, L Whitmore, N MacSweeney, A Brieant, V Karl… - bioRxiv, 2024 - biorxiv.org
Background Different types of early-life adversity have been associated with children's brain
structure and function. However, understanding the disparate influence of distinct adversity …

Genome-wide analysis of brain age identifies 25 associated loci and unveils relationships with mental and physical health

P Jawinski, H Forstbach, H Kirsten, F Beyer, A Villringer… - medRxiv, 2023 - medrxiv.org
Neuroimaging and machine learning are opening up new opportunities in studying
biological aging mechanisms. In this field,'brain age gap'has emerged as promising MRI …