Department of Bioengineering, Lehigh University, Bethlehem, Pennsylvania.
Center for Neuroscience Research, Children's National Hospital, Washington, District of Columbia.
JAMA Netw Open. 2024 Jul 1;7(7):e2420479. doi: 10.1001/jamanetworkopen.2024.20479.
Understanding the heterogeneity of neuropsychiatric symptoms (NPSs) and associated brain abnormalities is essential for effective management and treatment of dementia.
To identify dementia subtypes with distinct functional connectivity associated with neuropsychiatric subsyndromes.
DESIGN, SETTING, AND PARTICIPANTS: Using data from the Open Access Series of Imaging Studies-3 (OASIS-3; recruitment began in 2005) and Alzheimer Disease Neuroimaging Initiative (ADNI; recruitment began in 2004) databases, this cross-sectional study analyzed resting-state functional magnetic resonance imaging (fMRI) scans, clinical assessments, and neuropsychological measures of participants aged 42 to 95 years. The fMRI data were processed from July 2022 to February 2024, with secondary analysis conducted from August 2022 to March 2024. Participants without medical conditions or medical contraindications for MRI were recruited.
A multivariate sparse canonical correlation analysis was conducted to identify functional connectivity-informed NPS subsyndromes, including behavioral and anxiety subsyndromes. Subsequently, a clustering analysis was performed on obtained latent connectivity profiles to reveal neurophysiological subtypes, and differences in abnormal connectivity and phenotypic profiles between subtypes were examined.
Among 1098 participants in OASIS-3, 177 individuals who had fMRI and at least 1 NPS at baseline were included (78 female [44.1%]; median [IQR] age, 72 [67-78] years) as a discovery dataset. There were 2 neuropsychiatric subsyndromes identified: behavioral (r = 0.22; P = .002; P for permutation = .007) and anxiety (r = 0.19; P = .01; P for permutation = .006) subsyndromes from connectivity NPS-associated latent features. The behavioral subsyndrome was characterized by connections predominantly involving the default mode (within-network contribution by summed correlation coefficients = 54) and somatomotor (within-network contribution = 58) networks and NPSs involving nighttime behavior disturbance (R = -0.29; P < .001), agitation (R = -0.28; P = .001), and apathy (R = -0.23; P = .007). The anxiety subsyndrome mainly consisted of connections involving the visual network (within-network contribution = 53) and anxiety-related NPSs (R = 0.36; P < .001). By clustering individuals along these 2 subsyndrome-associated connectivity latent features, 3 subtypes were found (subtype 1: 45 participants; subtype 2: 43 participants; subtype 3: 66 participants). Patients with dementia of subtype 3 exhibited similar brain connectivity and cognitive behavior patterns to those of healthy individuals. However, patients with dementia of subtypes 1 and 2 had different dysfunctional connectivity profiles involving the frontoparietal control network (FPC) and somatomotor network (the difference by summed z values was 230 within the SMN and 173 between the SMN and FPC for subtype 1 and 473 between the SMN and visual network for subtype 2) compared with those of healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity (eg, the median [IQR] of the total score of NPSs was 2 [2-7] for subtype 3 vs 6 [3-8] for subtype 1; P = .04 and 5.5 [3-11] for subtype 2; P = .03) and longitudinal progression of cognitive impairment and behavioral dysfunction (eg, the overall interaction association between time and subtypes to orientation was F = 4.88; P = .008; using the time × subtype 3 interaction item as the reference level: β = 0.05; t = 2.6 for time × subtype 2; P = .01). These findings were further validated using a replication dataset of 193 participants (127 female [65.8%]; median [IQR] age, 74 [69-77] years) consisting of 154 newly released participants from OASIS-3 and 39 participants from ADNI.
These findings may provide a novel framework to disentangle the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the timely development of targeted interventions for patients with dementia.
了解神经精神症状 (NPS) 的异质性和相关的大脑异常对于痴呆症的有效管理和治疗至关重要。
确定与神经精神亚综合征相关的具有不同功能连接的痴呆亚型。
设计、地点和参与者：本横断面研究使用开放获取成像研究系列 3 (OASIS-3; 招募开始于 2005 年) 和阿尔茨海默病神经影像学倡议 (ADNI; 招募开始于 2004 年) 数据库中的数据，分析了 42 至 95 岁参与者的静息态功能磁共振成像 (fMRI) 扫描、临床评估和神经心理学测量结果。从 2022 年 7 月到 2024 年 2 月对 fMRI 数据进行了处理，从 2022 年 8 月到 2024 年 3 月进行了二次分析。招募了没有医学条件或 MRI 医学禁忌症的参与者。
进行了多元稀疏典型相关分析，以确定受功能连接影响的 NPS 亚综合征，包括行为和焦虑亚综合征。随后，对获得的潜在连接特征进行聚类分析，以揭示神经生理亚型，并检查亚型之间异常连接和表型特征的差异。
在 OASIS-3 中的 1098 名参与者中，有 177 名参与者在基线时具有 fMRI 和至少 1 项 NPS (78 名女性 [44.1%]；中位 [IQR] 年龄为 72 [67-78] 岁)，作为发现数据集。确定了 2 种神经精神亚综合征：行为 (r = 0.22；P =.002；置换 P =.007) 和焦虑 (r = 0.19；P =.01；置换 P =.006) 亚综合征来自与连接 NPS 相关的潜在特征。行为亚综合征的特征是连接主要涉及默认模式 (网络内贡献的总和相关系数 = 54) 和躯体运动 (网络内贡献 = 58) 网络，以及涉及夜间行为障碍 (R = -0.29；P <.001)、烦躁 (R = -0.28；P =.001) 和冷漠 (R = -0.23；P =.007) 的 NPS。焦虑亚综合征主要由涉及视觉网络的连接组成 (网络内贡献 = 53) 和与焦虑相关的 NPS (R = 0.36；P <.001)。通过沿着这 2 个与亚综合征相关的连接潜在特征对个体进行聚类，发现了 3 种亚型 (亚型 1：45 名参与者；亚型 2：43 名参与者；亚型 3：66 名参与者)。亚型 3 痴呆患者的大脑连接和认知行为模式与健康个体相似。然而，亚型 1 和 2 的痴呆患者具有不同的功能失调连接模式，涉及额顶叶控制网络 (FPC) 和躯体运动网络 (亚型 1 的 SMN 内的总和 z 值差异为 230，SMN 和 FPC 之间为 173，亚型 2 的 SMN 和视觉网络之间为 473)，与健康个体不同。这些功能失调的连接模式与基线痴呆严重程度的差异有关 (例如，亚型 3 的 NPS 总评分的中位数 [IQR] 为 2 [2-7]，而亚型 1 为 6 [3-8]；P =.04 和 5.5 [3-11]；P =.03)，以及认知障碍和行为功能的纵向进展 (例如，定向的时间和亚型之间的整体交互关联 F = 4.88；P =.008；以时间×亚型 3 交互项为参考水平：β= 0.05；t = 2.6 用于时间×亚型 2；P =.01)。这些发现使用由 193 名参与者组成的复制数据集 (127 名女性 [65.8%]；中位 [IQR] 年龄为 74 [69-77] 岁) 进一步验证，该数据集由 154 名新发布的 OASIS-3 参与者和 39 名 ADNI 参与者组成。
这些发现可能为分解痴呆症的神经精神和大脑功能异质性提供了一个新的框架，为改善临床管理和促进针对痴呆症患者的针对性干预措施的及时开发提供了有希望的途径。
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