PT  - JOURNAL ARTICLE
AU  - Angela Tam
AU  - Christian Dansereau
AU  - AmanPreet Badhwar
AU  - Pierre Orban
AU  - Sylvie Belleville
AU  - Howard Chertkow
AU  - Alain Dagher
AU  - Alexandru Hanganu
AU  - Oury Monchi
AU  - Pedro Rosa-Neto
AU  - Amir Shmuel
AU  - Seqian Wang
AU  - John Breitner
AU  - Pierre Bellec
AU  - Alzheimer’s Disease Neuroimaging Initiative
TI  - Consistent inter-protocol differences in resting-state functional connectomes between normal aging and mild cognitive impairment
AID  - 10.1101/019646
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 019646
4099  - http://biorxiv.org/content/early/2015/07/18/019646.short
4100  - http://biorxiv.org/content/early/2015/07/18/019646.full
AB  - 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 mild cognitive impairment (MCI) 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 MCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore pooled four independent datasets, including 112 healthy controls and 143 patients with MCI, systematically testing multiple brain connections for consistent differences. The largest effects associated with MCI involved the ventromedial and dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with MCI exhibited significantly decreased connectivity within the frontal lobe, between frontal and temporal areas, and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified robust MCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 150 to 400 total subjects to achieve adequate statistical power. 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.