ArticleScientific reports2020
Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer's Disease.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification of 16 novel Alzheimer's disease loci using multi-ancestry meta-analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Pooled it
- An exploratory exome-wide machine learning analysis identifies candidate host gene signatures associated with Long COVID in a large admixed Brazilian cohort.Frontiers in medicine · 2026Article
- White matter microstructure changes across the lifespan: a meta-analysis of longitudinal diffusion MRI studies.bioRxiv : the preprint server for biology · 2025Article
- Identifying genetic variants for brain connectivity using Ball Covariance Ranking and Aggregation.Journal of the American Statistical Association · 2025Article
- White-Matter Structural Connectivity and Alzheimer's Disease: A Mendelian Randomization Study.Brain and behavior · 2025Article
- Bayesian mixed model inference for genetic association under related samples with brain network phenotype.Biostatistics (Oxford, England) · 2024Article
- Identification of 16 novel Alzheimer's disease susceptibility loci using multi-ancestry meta-analyses of clinical Alzheimer's disease and AD-by-proxy cases from four whole genome sequencing datasets.medRxiv : the preprint server for health sciences · 2024Article
- Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS.BMC genomics · 2024Article
- Rare variant analyses validate known ALS genes in a multi-ethnic population and identifiesResearch square · 2023Article
- Identification and verification of genes associated with hypoxia microenvironment in Alzheimer's disease.Scientific reports · 2023Article
- Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease.Communications biology · 2023Article
- Lost in traffic: consequences of altered palmitoylation in neurodegeneration.Frontiers in physiology · 2023Review
- Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population.Frontiers in aging neuroscience · 2023Article
- Genetic underpinnings of brain structural connectome for young adults.Journal of the American Statistical Association · 2023Article
- Co-expression network analysis of frontal cortex during the progression of Alzheimer's disease.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Estimating the X chromosome-mediated risk for developing Alzheimer's disease.Journal of neurology · 2022Article
- Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models.Neurobiology of disease · 2021Review
- The human connectome in Alzheimer disease - relationship to biomarkers and genetics.Nature reviews. Neurology · 2021Review
- Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts.Frontiers in genetics · 2021Article
- Relating Global and Local Connectome Changes to Dementia and Targeted Gene Expression in Alzheimer's Disease.Frontiers in human neuroscience · 2021Article
Corrections and comments
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4 authors.
Funding
Abstract
Variations in the human genome have been found to be an essential factor that affects susceptibility to Alzheimer's disease. Genome-wide association studies (GWAS) have identified genetic loci that significantly contribute to the risk of Alzheimers. The availability of genetic data, coupled with brain imaging technologies have opened the door for further discoveries, by using data integration methodologies and new study designs. Although methods have been proposed for integrating image characteristics and genetic information for studying Alzheimers, the measurement of disease is often taken at a single time point, therefore, not allowing the disease progression to be taken into consideration. In longitudinal settings, we analyzed neuroimaging and single nucleotide polymorphism datasets obtained from the Alzheimer's Disease Neuroimaging Initiative for three clinical stages of the disease, including healthy control, early mild cognitive impairment and Alzheimer's disease subjects. We conducted a GWAS regressing the absolute change of global connectivity metrics on the genetic variants, and used the GWAS summary statistics to compute the gene and pathway scores. We observed significant associations between the change in structural brain connectivity defined by tractography and genes, which have previously been reported to biologically manipulate the risk and progression of certain neurodegenerative disorders, including Alzheimer's disease.
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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.