Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA.
Nat Neurosci. 2024 Nov;27(11):2240-2252. doi: 10.1038/s41593-024-01788-z. Epub 2024 Oct 31.
Brain connectivity arises from interactions across biophysical scales, ranging from molecular to cellular to anatomical to network level. To date, there has been little progress toward integrated analysis across these scales. To bridge this gap, from a unique cohort of 98 individuals, we collected antemortem neuroimaging and genetic data, as well as postmortem dendritic spine morphometric, proteomic and gene expression data from the superior frontal and inferior temporal gyri. Through the integration of the molecular and dendritic spine morphology data, we identified hundreds of proteins that explain interindividual differences in functional connectivity and structural covariation. These proteins are enriched for synaptic structures and functions, energy metabolism and RNA processing. By integrating data at the genetic, molecular, subcellular and tissue levels, we link specific biochemical changes at synapses to connectivity between brain regions. These results demonstrate the feasibility of integrating data from vastly different biophysical scales to provide a more comprehensive understanding of brain connectivity.
脑连接产生于从分子到细胞到解剖到网络水平的生物物理尺度的相互作用。迄今为止,在这些尺度上进行综合分析的进展甚微。为了弥合这一差距,我们从一个独特的 98 人队列中收集了生前神经影像学和遗传数据,以及来自额上回和颞下回的死后树突棘形态计量学、蛋白质组学和基因表达数据。通过整合分子和树突棘形态数据,我们确定了数百种蛋白质,这些蛋白质可以解释功能连接和结构共变的个体间差异。这些蛋白质富含突触结构和功能、能量代谢和 RNA 处理。通过整合遗传、分子、亚细胞和组织水平的数据,我们将突触处的特定生化变化与大脑区域之间的连接联系起来。这些结果表明,整合来自不同生物物理尺度的数据是可行的,这为更全面地理解大脑连接提供了可能。