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Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk.
Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups.
Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1–4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79–88%).
These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.
This chapter describes the syndromes of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Many elderly persons exhibit MCI, characterized by memory complaints and mild abnormalities of performance on formal tests, associated with intact general cognition and preserved activities of daily living. The clinical manifestations of AD arise from abnormalities involving brain regions and neural circuits composed of populations of neurons that are essential for memory, learning, and cognitive performance. Early information about the involvement of neurotransmitter-specific circuits damaged by the disease led to the design of early therapies for AD. The genetics of AD are complex, often influencing phenotype in an age-dependent manner. Late onset cases of AD without clear familial association reflect the influences of a variety of risk factors. The chapter emphasizes the need for safe and effective mechanism-based therapies for AD. New treatments will probably require combinatorial approaches.