Abstract

Resting-state functional connectivity is a promising biomarker for Alzheimer's disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimer's disease and amnestic mild cognitive impairment (aMCI) have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from aMCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore combined four datasets collected independently, including 112 healthy controls and 143 patients with aMCI. We systematically tested multiple brain connections for associations with aMCI using a weighted average routinely used in meta-analyses. The largest effects involved the superior medial frontal cortex (including the anterior cingulate), dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with aMCI exhibited significantly decreased connectivity between default mode network nodes and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified common aMCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 140 to upwards of 600 total subjects to achieve adequate statistical power in the context of a multisite study with 5–10 scanning sites and about 10 subjects per group and per site. If our findings can be replicated and associated with other established biomarkers of Alzheimer's disease (e.g., amyloid and tau quantification), then these functional connections may be promising candidate biomarkers for Alzheimer's disease.

Highlights

  • Resting-state connectivity in functional magnetic resonance imaging captures the spatial coherence of spontaneous fluctuations in blood oxygenation

  • If resting-state functional magnetic resonance imaging (fMRI) is to serve as a useful biomarker of Alzheimer’s disease (AD), or any pathology, for clinical practice or research, we must determine if changes in functional connectivity differences between groups of subjects are robust to such variation in study protocols

  • Given that the top four clusters explained nearly half of the findings, they were further characterized in seedbased connectivity analyses, which revealed that amnestic mild cognitive impairment (MCI) (aMCI) showed decreased connectivity between default mode network (DMN) nodes and between areas of the cortico-striatal-thalamic loop (Figure 4)

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Summary

Introduction

Resting-state connectivity in functional magnetic resonance imaging (fMRI) captures the spatial coherence of spontaneous fluctuations in blood oxygenation. These studies showed altered functional connectivity in MCI compared with cognitively normal elderly (CN; Sorg et al, 2007; Bai et al, 2009; Liang et al, 2012; Wu et al, 2014), but they relied on small sample sizes (n = ∼40) and differed in many aspects of their protocols, e.g., recruitment and image acquisition procedures. They may be used as targets to be examined alongside other established AD biomarkers (e.g., amyloid and tau measures) in order to validate resting-state fMRI’s potential as a biomarker for AD

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