Frontiers in molecular biosciences · 2026
Integrating causal human genetics and In vivo transcriptomics to uncover a shared lipid-centric architecture in metabolic and neurocognitive disease.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Li Yi, Ni Zhu, Xia Xiao-Yong, Cheng Na, Bo Yu, He Junwen, He Yang, Meng Xiang-Yu, Wang Xu, Xu Xuan
Аннотация
BACKGROUND: Metabolic disorders and neurocognitive diseases frequently co-occur, yet the specific mechanisms driving this comorbidity remain elusive. While epidemiological associations are well-documented, the causal links between these conditions are complex and incompletely understood, necessitating a systems-level investigation into their shared biological architecture.
METHODS: This study integrates large-scale human genetics with experimental in vivo transcriptomics and computational chemistry to elucidate these shared pathways. Specifically, an AD-like murine model was used to experimentally prioritize a core network of 13 dysregulated genes within a pathologically relevant context.
RESULTS: Network-informed Mendelian randomization identified bidirectional causalities, including a 14% elevated dementia risk from type 2 diabetes and protective effects of obesity against parental Alzheimer's disease (AD). The study identified a signature encompassing key lipid metabolism hubs APOE, CLU, and LDLR. This signature serves as a critical biological filter, anchoring human genetic associations by providing direct evidence of their dysregulation in a neurodegenerative environment. Subsequent chemical enrichment and molecular docking analyses indicated that these experimentally-prioritized targets are engaged by both therapeutic agents (e.g., valproic acid) and environmental toxins (e.g., benzo[a]pyrene).
CONCLUSION: This multi-modal investigation provides a robust framework that converges on a high-confidence, 13-gene signature of lipid dysregulation as a central mechanistic interface, offering a powerful set of prioritized targets for future functional validation and therapeutic development at the metabolic-neurocognitive nexus.
METHODS: This study integrates large-scale human genetics with experimental in vivo transcriptomics and computational chemistry to elucidate these shared pathways. Specifically, an AD-like murine model was used to experimentally prioritize a core network of 13 dysregulated genes within a pathologically relevant context.
RESULTS: Network-informed Mendelian randomization identified bidirectional causalities, including a 14% elevated dementia risk from type 2 diabetes and protective effects of obesity against parental Alzheimer's disease (AD). The study identified a signature encompassing key lipid metabolism hubs APOE, CLU, and LDLR. This signature serves as a critical biological filter, anchoring human genetic associations by providing direct evidence of their dysregulation in a neurodegenerative environment. Subsequent chemical enrichment and molecular docking analyses indicated that these experimentally-prioritized targets are engaged by both therapeutic agents (e.g., valproic acid) and environmental toxins (e.g., benzo[a]pyrene).
CONCLUSION: This multi-modal investigation provides a robust framework that converges on a high-confidence, 13-gene signature of lipid dysregulation as a central mechanistic interface, offering a powerful set of prioritized targets for future functional validation and therapeutic development at the metabolic-neurocognitive nexus.