Connecting late-life depression and cognition with statistical physics based connectomics and sparse Frechet regression

最近，有几条证据支持突触功能障碍是一种 阿尔茨海默病(AD)最早的脑变化导致神经元过度兴奋 电路。然而，与年龄、性别和其他风险因素相关的网络变化，如 载脂蛋白E(ApoE)ε4等位基因与疾病神经病理有重叠的趋势，增加了 难以将疾病特异性改变与正常衰老相关的改变区分开来 男性和女性的轨迹(女性占所有被诊断为AD的人的三分之二 而女性ε4等位基因携带者患阿尔茨海默病的可能性是男性的四倍。 使挑战进一步复杂化的是精神疾病可能会影响这些 两性关系。具体地说，晚年抑郁(LLD)被认为是一种重要的 加速认知衰退和发展为痴呆症的因素。趁它还在的时候 不清楚LLD的哪些神经生物学方面代表了病因学特征，而不是共同的 AD的发生方面，确定它们对功能结局的影响是一个重要的 解开抑郁症与神经退行性变之间关系的机会 晚年生活中的过程。 我们将使用多模式联结来分析激励-抑制平衡(E-I平衡) 在特征良好的ADNI和ADNI-D样本中阐明晚期- 生活抑郁和神经退行性变。我们的流水线将基于一种新的休眠状态 结构连接学(RS-SC)方法产生了一个高激发指标(HI)。 此前，在一组认知正常的载脂蛋白E-ε4携带者和年龄/性别匹配的非 携带者我们证明了性别和年龄的相互作用，以及显著的高度兴奋 随着年龄的增长，只有女性才能观察到，而男性则看不到。特别是，支持的结果 女性携带者在50岁时开始在默认模式网络中表现出过度兴奋 (DMN)。此外，研究表明，过度兴奋的程度与代偿性有关。 空间学习记忆任务中神经元资源的招募(虚拟Morris水 迷宫任务)。在这项初步研究的激励下，我们将研究情绪(晚年)之间的联系 抑郁症)和随后的认知衰退和痴呆的发展 突触功能障碍。

Recently, several lines of evidence have supported that synaptic dysfunction represents one of the earliest brain changes in Alzheimer’s disease (AD), leading to hyper-excitation in neuronal circuits. However, network changes related to age, sex and other risk factors such as the apolipoprotein E (APOE) ε4 allele tend to overlap with disease neuropathology, increasing the difficulty of separating disease-specific alterations from those related to normal aging trajectories in males and females (women comprise two thirds of all persons diagnosed with AD dementia, while female ε4 allele carriers are four times more likely to develop AD than men). Further compounding the challenges is the potential for psychiatric conditions to influence these relationships. Specifically, late life depression (LLD) has been proposed as a significant contributor to accelerated cognitive decline and progression to dementia. While it remains unclear which neurobiological aspects of LLD represent pathognomonic features, versus co- occurring aspects of AD, determining their impact on functional outcomes is a significant opportunity to disentangle the relationship between depression and neurodegenerative processes in late life. We will use multi-modal connectomics to analyze excitation-inhibition balance (E-I balance) in the well-characterized ADNI and ADNI-D samples to elucidate the relationship between late- life depression and neurodegeneration. Our pipeline will be based on a novel resting-state structural connectomics (rs-SC) approach that yields a hyperexcitation indicator (HI). Previously, in a group of cognitively normal APOE-ε4 carriers and age/gender matched non- carriers we demonstrated a sex-by-age-by-genotype interaction, with significant hyperexcitation with increasing age only observable in women, but not in men. In particular, results supported that hyperexcitation in female carriers began to exhibit at age 50 in the default mode network (DMN). Further, the degree of hyperexcitation was shown to be related to compensatory recruitment of neuronal resources during a spatial learning memory task (virtual Morris water maze task). Motivated by this pilot study, we will examine the links between mood (late-life depression) and subsequent cognitive decline and development of dementia in the context of synaptic dysfunction.