A network approach to subjective cognitive decline: Exploring multivariate relationships in neuropsychological test performance across Alzheimer’s disease risk states

Abstract

Subjective cognitive decline (SCD) is characterized by subjective concerns of cognitive change despite test performance within normal range. Although those with SCD are at higher risk for developing further cognitive decline, we still lack methods using objective cognitive measures that reliably distinguish SCD from cognitively normal aging at the group level. Network analysis may help to address this by modeling cognitive performance as a web of intertwined cognitive abilities, providing insight into the multivariate associations determining cognitive status. Following previous network studies of mild cognitive impairment (MCI) and Alzheimer’s dementia (AD), the current study centered upon the novel visualization and analysis of the SCD cognitive network compared to cognitively normal (CN) older adult, MCI, and AD group networks. Cross-sectional neuropsychological data from CIMA-Q and COMPASS-ND cohorts were used to construct Gaussian graphical models for CN (n = 122), SCD (n = 207), MCI (n = 210), and AD (n = 79) groups. Group networks were explored in terms of global network structure, prominent edge weights, and strength centrality indices. CN and SCD group networks were contrasted using the Network Comparison Test. Results indicate that CN and SCD groups did not differ in univariate cognitive performance or global network structure. However, measures of strength centrality, principally in executive functioning and processing speed, showed a CN-SCD-MCI gradient where subtle differences within the SCD network suggest that SCD is an intermediary between CN and MCI stages. Additional results may indicate a distinctiveness of network structure in AD, a reversal in network influence between age and general cognitive status as clinical impairment increases, and potential evidence for cognitive reserve. Together, these results provide evidence that network-specific metrics are sensitive to cognitive performance changes across the dementia risk spectrum and can help to objectively distinguish SCD group cognitive performance from that of the CN group.

Plain Language Summary

Some older adults report difficulties with cognitive abilities (e.g., memory, language) before clinical testing detects any changes. This condition is referred to as subjective cognitive decline and is a risk state for developing dementia. Because these subtle changes are not reliably picked up in testing, it is possible that our clinical tools are missing the forest for the trees within subjective cognitive decline. This current project studied cognitive test scores and how they relate to each other within two large participant cohorts (COMPASS-ND and CIMA-Q), uncovering the bigger picture of how cognition evolves over the risk states of dementia. Results show that patterns of association between cognitive test scores in networks may provide information beyond that of any single test score in subjective cognitive decline. Looking at cognitive status from this perspective, subjective cognitive decline is positioned as an intermediate stage between cognitively normal older adults and those with mild cognitive impairment. In other words, these networks appear to visualize data in a unique way, revealing subtle changes in cognition that put some older adults at higher risk for future dementia. The exploratory technique of network analysis that we used here holds promise for studying cognitive abilities in aging. It also allows us to better understand the complexity of conditions such as subjective cognitive decline, one of the earliest clinical manifestations of increased risk for dementia.