AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.
It is revealed that the genetically predisposed higher risk of diabetic maculopathy was associated with increased salience network connectivity, shedding light on the neural drivers of diabetic pathologies.
The results support a prioritized genomic map with substantial instrument- and model-specific uncertainty, and disease-to-clock signals were richer than clock-to-disease signals, GrimAA shared polygenic architecture with osteoarthritis, and selected loci showed strong shared-variant evidence.
Background Phenotypic age acceleration (PhenoAgeAccel), derived from PhenoAge, and MetaboHealth are composite exposures of biological ageing and metabolic health associated with dementia-related outcomes. Whether these associations are causal and reflect the exposures, constituent biomarkers, or both remains unclear. Methods This study included UK Biobank participants of White British genetic ancestry. MetaboHealth was derived from nuclear magnetic resonance (NMR) metabolomics and PhenoAgeAccel from clinical biomarkers and chronological age. Genome-wide association studies (GWAS) were conducted for MetaboHealth (n=272,568) and PhenoAgeAccel (n=274,077). Independent genome-wide significant variants were used as genetic instruments in two-sample Mendelian randomisation (MR) with FinnGen all-cause dementia summary statistics. Inverse-variance weighting was the primary MR method. Causal network analysis estimated relationships among constituent biomarkers and dementia. Findings GWAS identified 126 and 141 independent genome-wide significant variants for MetaboHealth and PhenoAgeAccel, of which 109 and 141 were retained as genetic instruments. MR found no evidence of a causal effect of genetically predicted MetaboHealth (per unit: OR 0.83, 95% CI 0.49-1.42; p=0.51) or PhenoAgeAccel (per year: OR 0.99, 95% CI 0.95-1.02; p=0.44) on all-cause dementia, with consistent findings across sensitivity analyses and robust MR methods. Lower lymphocyte percentage and higher NMR-derived glucose had direct relationships with dementia in the joint constituent-biomarker network. Interpretation MR provided no evidence that either composite exposure causally influenced dementia. The network prioritised lymphocyte percentage and NMR-derived glucose, supporting examination of composite exposures alongside their constituent biomarkers. Funding NIHR, UKRI, MRC, UK Dementia Research Institute, Innovate UK, and European Union. Full funding details are provided in the acknowledgements.
Objective This study used two-sample Mendelian Randomization to investigate the causal link between multiple biological aging indicators and vascular disease. Methods Summary genetic data was obtained from genome-wide association studies (GWAS) focusing on aging-related exposures and various vascular disease outcomes. The exposures included granulocyte proportions, PAI-1 (plasminogen activator inhibitor-1), telomere lengths, and the Frailty Index. The primary analysis employed the Inverse Variance Weighted (IVW) method to estimate causal relationships, supported by MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran’s Q test, MR-Egger regression, leave-one-out test, and the MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) test, were conducted to evaluate heterogeneity and pleiotropy. Results The analysis revealed distinct pathways after sensitivity adjustments. A higher genetically predicted Frailty Index was associated with an increased risk of abdominal aortic aneurysm (OR=2.5935, 95% CI: 1.3936–4.8268, P=0.0026, false discovery rate (FDR)=0.0475), atherosclerosis excluding cerebral and coronary sclerosis (OR=2.0262, 95% CI:1.5179–2.705, P=1.66×10-6, FDR=1×10-4), and arterial thromboembolic events (OR = 4.0306, 95% CI: 1.7133–9.4818, P = 0.0014, FDR = 0.0337). Conversely, longer telomere length demonstrated a strong, specific protective effect against abdominal aortic aneurysm (OR=0.5008, 95% CI:0.4111–0.6100, P=6.42×10-12, FDR=9.25×10-10), indicating that shorter telomere length is associated with an increased risk of AAA. Furthermore, a lower granulocyte proportion was causally linked to an increased risk of thoracic aortic aneurysm (OR=0.0181, 95% CI: 0.0014–0.2376, P=0.0023, FDR=0.0465). Conclusion This study identifies three genetic pathways linking biological aging to vascular disease, offering new molecular targets for its prevention and treatment.
These findings provide a hypothesis-generating reframing of the traditional comorbidity model, suggesting that divergent molecular programs may converge on shared pathways and offer a preliminary foundation for exploring therapeutic strategies at the mood–metabolism interface.
Type 2 diabetes (T2D) and dementia frequently co-occur, yet the biological mechanisms underlying this comorbidity remain incompletely understood. Here, we systematically investigate shared genetic signals between T2D and three forms of neurodegenerative dementia (Alzheimer's disease, Lewy body dementia, and sporadic frontotemporal dementia) using large-scale genome-wide association studies of clinically diagnosed cases. We identify five genomic regions harbouring shared association signals between T2D and at least one dementia subtype. Among these, the APOE locus was common to all dementia subtypes, whereas the remaining four loci (GBA, CRY2/PEX16/MAPK8IP1, INO80E, and NSF) were each shared exclusively between T2D and one dementia subtype. Integrating multi-omics data across several disease-relevant tissues and orthogonal lines of functional evidence, we prioritize 26 candidate genes, through which these shared genetic loci potentially mediate their effect. Pathway enrichment highlights lipid and lipoprotein regulatory biology as a central shared axis. Mendelian randomization analyses using genetically regulated gene expression in relevant tissues indicate pleiotropic mechanisms with divergent phenotypic consequences. Our findings identify shared genetic loci between T2D and neurodegenerative dementia, revealing systemic metabolic-neurodegenerative trade-offs and highlighting key genes that underpin the comorbidity, providing a framework for improved understanding of age-related multimorbidity.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.