Structural imaging biomarkers for bipolar disorder: Meta‐analyses of whole‐brain voxel‐based morphometry studies

Abstract

Background: Bipolar disorder (BD) is a common and destructive psychiatric illness worldwide.Although it is known that BD is associated with morphological abnormalities of the brain, the regions implicated in BD remain unclear. Therefore, we aimed to update current knowledge on potential structural imaging biomarkers of BD. Methods: Studies published up to January 31, 2018, were identified by a comprehensive literature search of PubMed, EBSCO, and BrainMap voxel-based morphometry (VBM) database. Wholebrain VBM studies that examined gray matter (GM) abnormalities of group comparisons between BD and healthy controls (HC) and reported results as coordinates in a standard reference space were included. Different meta-analyses were performed by activation likelihood estimation (ALE) algorithm.Results: A total of 46 studies with 56 experiments, including 1720 subjects and 268 foci were included. Seven different meta-analyses were calculated separately across experiments reporting decreased or increased GM volume among BD, BDI, BD-adults, and BD-youths groups. Fifteen regions of significantly different GM volume between four groups and HC were identified. There were extensive GM deficits in the prefrontal and temporal cortex, and enlargements in the putamen, cingulate cortex, and precuneus. Conclusions:The results revealed that the thinning of prefrontal cortex was a key region in the pathophysiology of BD. The enlargement of the cingulate cortex may be implicated in a compensatory mechanism. It underscored important differences between BD-adults and BD-youths and specific biomarkers of three subgroups.

Identification of bipolar disorder using a combination of multimodality magnetic resonance imaging and machine learning techniques

“…There have been many proofs that show the limbic system involving emotional processing, memory, and executive functioning, as well as its decreases of gray matter in patients with bipolar disorder [19,23,[67][68][69][70][71]. Besides, we identi ed decreased gray matter volume in the superior temporal gyrus and inferior temporal gyrus; this nding was consistent with most previous structural MRI studies in BPD [26,[72][73][74].Temporal lobe is the brain region related to hearing and vision and thought to play a crucial role in emotional processing, working memory, and social cognition. [75][76].…”

“…They found that BPD patients had a decreased superior temporal gyrus gray matter volume than BPD [74]. Two previous meta-analyses also con rmed decreased gray matter volume in the superior temporal gyrus only in BPD I patients [73,80]. It can be speculated that de cit in superior temporal gyrus is unique to BPD type I.…”

“…However, a series of other types of studies implicated this nding. Researchers have found increased gray matter volume and cerebral blood ow in the basal ganglia [73,89]. Some fMRI studies revealed increased resting-state functional connectivity between basal ganglia and other regions, including the prefrontal cortex, precuneus, and insula [89][90].…”

Lithium attenuates d‐amphetamine‐induced hyperlocomotor activity in mice via inhibition of interaction between cyclooxygenase‐2 and indoleamine‐2,3‐dioxygenase

“…Compelling evidence indicated that prefrontal cortex (PFC) is a key region in the pathophysiology of BD . Furthermore, behavioural and imaging studies supported the proposition that manic episodes are strongly associated with alterations in PFC structure …”

A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders

“…Not only have several meta-analyses of different diseases shown that such reductions are common (Fornito et al, 2009;Bora et al, 2010Bora et al, , 2011Bora et al, , 2012aFusar-Poli et al, 2011;Hallahan et al, 2011;Linkersdörfer et al, 2012;Du et al, 2012;Li et al, 2014Li et al, , 2018Stoodley, 2014;Cauda et al, 2014;Foster et al, 2015;Lin et al, 2016;Wise et al, 2017;Wu et al, 2018), and other work suggests that anatomically distributed yet coordinated GM reductions are tied to the underlying connectivity between regions (Seeley et al, 2009;Raj et al, 2012;Zhou et al, 2012;Crossley et al, 2014;Iturria-Medina et al, 2014;Zeighami et al, 2015, Cauda et al, 2018aYau et al, 2018;Zheng et al, 2019). In contrast, GM increases are less commonly considered in clinical neuroimaging studies (Cauda et al, 2011(Cauda et al, , 2017(Cauda et al, , 2018bTatu et al, 2018, Cauda et al, 2019bDing et al, 2019;Lu et al, 2019), potentially because they might be a rarer consequence of disease and because they can be difficult to explain in the context of pathology. Indeed, while a morphometric decrease can be easily interpreted as a sign of neurodegeneration or neurodevelopmental hyperpruning, the interpretation of a disorder-related GM increase is less clear.…”