Metabolic and Inflammatory Pathways of Midlife Neurocognitive Disparities

项目总结/摘要 健康不是在人群或空间中随机分布的：它跟踪一个社会经济 从个人到他们生活的地区的梯度。个人和地区一级 社会经济不利因素会给各种相互关联的物质环境带来风险， 和神经认知健康结果。这种风险在中年尤其明显， 神经认知老化的病理生理学轨迹可预测晚年痴呆的风险 开始加速。在这方面，我们提供了一些初步证据，表明个人- 和区域水平的社会经济劣势与皮质组织体积减少有关， 白色物质完整性，显示正常收缩和完整性的脑形态学方面 随着年龄的增长，认知能力下降。联系社会经济 加速神经认知老化的不利因素仍不清楚。最近的证据，包括 我们自己的研究表明，代谢因素可能发挥了作用。患有代谢性疾病的人 综合征、糖尿病前期或2型糖尿病患者加速 神经认知老化此外，我们最近的横截面研究结果表明，代谢 危险因素有助于区域水平的劣势与脑形态学的关联 在中年人中。在这里，我们的目标是通过纵向检查代谢来扩展这项工作。 将个人和地区水平的劣势与神经认知老化联系起来的途径 中年时期。为此，我们建议重新评估300个样本的认知 我们收集了正常中年人的社会经济参数的基线测量值， 9-10年前的代谢风险、脑形态和认知功能（随访时的平均年龄 = 52）。我们的主要目标是研究个人和地区一级的社会经济指标是否 劣势预测了大脑形态和认知功能的变化，这些变化会随着年龄的增长而下降 以及不利因素与神经认知老化的关联是否可以通过代谢来解释， 风险和相关炎症。我们预计，这项研究将有助于新的 认知老化差异的神经生物学知识。

Project Summary/Abstract Health is not randomly distributed across people or across space: it tracks a socioeconomic gradient that extends from individuals to the areas in which they live. Individual- and area-level attributes of socioeconomic disadvantage confer risk for a broad range of interrelated physical and neurocognitive health outcomes. This risk is especially apparent in midlife when pathophysiological trajectories of neurocognitive aging that predict risk for dementia in later life begin to accelerate. In this regard, we have provided some of the first evidence that individual- and area- level socioeconomic disadvantage associate with reduced cortical tissue volume and white matter integrity, aspects of brain morphology that show normative shrinkage and integrity loss with age in association with poorer cognitive outcomes. Pathways linking socioeconomic disadvantage to accelerated neurocognitive aging remain unclear. Recent evidence, including our own, suggests that metabolic factors may play a role. Individuals who develop metabolic syndrome, pre-diabetes or type 2 diabetes mellitus are at increased risk for accelerated neurocognitive aging. Furthermore, our recent cross-sectional findings suggest that metabolic risk factors contribute to the associations of area-level disadvantage with brain morphology among midlife adults. Here, we aim to extend this work by longitudinally examining metabolic pathways linking individual- and area-level disadvantage to neurocognitive aging across a 10 year period of midlife. For this purpose, we propose reassessing a sample of 300 cognitively normal midlife adults on whom we collected baseline measures of socioeconomic parameters, metabolic risk, brain morphology and cognitive function 9-10 years ago (mean age at follow-up = 52). Our primary aims examine whether individual- and area-level measures of socioeconomic disadvantage predict changes in brain morphology and cognitive function that decline with age and whether associations of disadvantage with neurocognitive aging are explained by metabolic risk and associated inflammation. We anticipate that this study will contribute to new knowledge to the neurobiology of disparities in cognitive aging.