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Heritability and genetic covariance/correlation quantify the marginal and shared genetic effects across traits. They offer insights on the genetic architecture of complex traits and diseases. To explore how genetic variations contribute to brain function variations, we estimated heritability and genetic correlation across cortical thickness, surface area, and volume of 33 anatomically predefined regions in left and right hemispheres, using summary statistics of genome-wide association analyses of 31,968 participants in the UK Biobank. To characterize the relationships between these regions of interest, we constructed a genetic network for these regions using recursive two-way cut-offs in similarity matrices defined by genetic correlations. The inferred genetic network matches the brain lobe mapping more closely than the network inferred from phenotypic similarities. We further studied the associations between the genetic network for brain regions and 30 complex traits through a novel composite-linkage disequilibrium score regression method. We identified seven significant pairs, which offer insights on the genetic basis for regions of interest mediated by cortical measures.
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http://dx.doi.org/10.1016/j.neuroimage.2024.120739 | DOI Listing |
Genome Biol
September 2025
Institute of Translational Medicine, Zhejiang University School of Medicine, Zhejiang, Hangzhou, 310029, China.
Metagenomic analyses of microbial communities have unveiled a substantial level of interspecies and intraspecies genetic diversity by reconstructing metagenome-assembled genomes (MAGs). The MAG database (MAGdb) boasts an impressive collection of 74 representative research papers, spanning clinical, environmental, and animal categories and comprising 13,702 paired-end run accessions of metagenomic sequencing and 99,672 high quality MAGs with manually curated metadata. MAGdb provides a user-friendly interface that users can browse, search, and download MAGs and their corresponding metadata information.
View Article and Find Full Text PDFBJOG
September 2025
Department of Obstetrics and Gynaecology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Objective: To estimate the effect on healthcare resource use after introducing the World Health Organization diagnostic criteria (WHO-2013) for gestational diabetes mellitus (GDM) compared to former criteria in Sweden (SWE-GDM).
Design: A cost-analysis alongside the Changing Diagnostic Criteria for Gestational Diabetes (CDC4G) randomised controlled trial.
Setting: Sweden, with risk-factor based screening for GDM.
Genome Biol
September 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.
Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.
Clin Genet
September 2025
Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
LONP1 encodes a mitochondrial protease essential for protein quality control and metabolism. Variants in LONP1 are associated with a diverse and expanding spectrum of disorders, including Cerebral, Ocular, Dental, Auricular, and Skeletal anomalies syndrome (CODAS), congenital diaphragmatic hernia (CDH), and neurodevelopmental disorders (NDD), with some individuals exhibiting features of mitochondrial encephalopathy. We report 16 novel LONP1 variants identified in 16 individuals (11 with NDD, 5 with CDH), further expanding the clinical spectrum.
View Article and Find Full Text PDFStem Cell Rev Rep
September 2025
Department of Medical Genetics and Prenatal Diagnostics, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
The emergence of organoid models has significantly bridged the gap between traditional cell cultures/animal models and authentic human disease states, particularly for genetic disorders, where their inherent genetic fidelity enables more biologically relevant research directions and enhances translational validity. This review systematically analyzes established organoid models of genetic diseases across organs (e.g.
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