Major depressive disorder (MDD) is a complex mental illness, and a comprehensive understanding of its biological underpinnings can help improve diagnostic accuracy and treatment efficacy. Although significant research has been conducted, there is a lack of consensus regarding the underlying neurobiological mechanisms of MDD (Chen et al., 2021). Coordinate-based meta-analyses (CBMA) are instrumental in adding to our knowledge base of MDD. These techniques can identify the brain structures that are consistently associated with this disorder (Dusi et al., 2018) and allow for the examination of differences across the lifespan, even when the primary studies might not do that. By aggregating studies within different age groups, CBMA allows for comparisons across these groups. For example, in a recent grey matter volume (GMV) meta-analysis, researchers discovered a laterality effect in which adolescent MDD was associated with lower right temporal and parietal GMV, and adult MDD was associated with lower left frontal, temporal, and parietal GMV (Zhang et al., 2023). Since white matter tracts connect and facilitate communication between grey matter regions, further investigation of white matter lateralized abnormalities could contribute to our understanding of the pathophysiology and neuroanatomical correlates of MDD.

Diffusion tensor imaging (DTI) is the preferred structural neuroimaging modality for examining white matter microstructure (Johansen-Berg and Rushworth, 2009; O'Sullivan et al., 2001). White matter structural connectivity has greater test-retest reliability than that computed for functional connectivity and is therefore often used to examine disease-associated neurobiological mechanisms (Liao et al., 2013). Among the various measures of white matter integrity, fractional anisotropy (FA) is the most reliable and commonly used method (Mori and Zhang, 2006). Tract-based spatial statistics (TBSS) and voxel-based analysis (VBA) are preferred for identifying between-group FA differences (Mori and Zhang, 2006; Peters et al., 2012; Wen et al., 2014) due to the following: 1) low inter-subject variability (Smith et al., 2006), 2) high test-retest reliability (Duan et al., 2015), 3) automated voxel-wise analytical methods, and 4) unbiased whole-brain approaches.

Several researchers have explored the possibility of using FA abnormalities as diagnostic biomarkers for MDD. For example, Calesella et al. (2024) created an FA-based diagnostic model with 76 % accuracy in differentiating MDD from bipolar disorder in adults. Existing literature has also found an association between adult MDD subtypes and FA abnormalities. To illustrate, the MDD subtype with impaired delayed visual memory is associated with lower left cingulum, left inferior longitudinal fasciculus, and corpus callosum FA (Liang et al., 2019). Researchers also report an association between lower corpus callosum FA and early age of onset (Kemp et al., 2013).

FA abnormalities may also function as treatment biomarkers that both assess outcomes and improve treatment selection by predicting outcomes. For instance, placebo-controlled trials identified an association between remission in adults after selective serotonin reuptake inhibitor (SSRI) treatment and lower raphe nucleus and amygdala FA (Pillai et al., 2019). Remission in adults is also associated with higher right superior longitudinal fasciculus and cingulate FA and lower right superior fronto-occipital fasciculus and stria terminalis FA (Korgaonkar et al., 2014). In older adult longitudinal studies, lower dorsal anterior cingulate cortex (ACC) and uncinate fasciculus FA at baseline were associated with continued self-critical thoughts after escitalopram treatment (Victoria et al., 2019).

Since white matter continues to change with aging, it is important to determine whether FA abnormalities differ between adolescents, adults, and older adults with MDD. Interestingly, age has been found to increase the prediction accuracy of FA-based remission models from 68.9 % to 74 % (Korgaonkar et al., 2014). According to the literature, FA increases globally from childhood through young adulthood (Bava et al., 2010; Qiu et al., 2008). The internal capsule, corpus callosum, corticospinal tracts, inferior longitudinal fasciculus, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and right cingulum exhibit the greatest changes (Ashtari et al., 2007; Giorgio et al., 2010). FA peaks in the superior longitudinal fasciculus around ages 15–20 and in the uncinate fasciculus and cingulate around ages 21–25 (Lebel et al., 2008). Between ages 41–60, FA decreases significantly in the anterior corona radiata and corpus callosum. Finally, between ages 61–85, FA decreases significantly overall in the brain; but particularly in the stria terminalis, superior longitudinal fasciculus, posterior limb of the internal capsule, sagittal striatum, inferior fronto-occipital fasciculus, and corticospinal peduncles (Rathee et al., 2016).

Existing literature has found an association between adult MDD and lower FA in left prefrontal, subcortical, temporal, and occipital tracts as well as bilateral frontal, parietal, and cerebellar tracts (Jenkins et al., 2016). Meanwhile, meta-analyses examining adolescents and adults together reported lower FA in the following white matter tracts: 1) left corticospinal and insular, 2) right occipital, 3) corpus callosum, and 4) bilateral prefrontal, frontal, subcortical, parietal, and temporal (Chen et al., 2016; Guo et al., 2024; Liao et al., 2013; Murphy and Frodl, 2011; Shu et al., 2024; Wise et al., 2016; Zhou et al., 2022). Finally, meta-analyses examining adolescence through older adulthood found lower FA in the following tracts: 1) right cerebellar, 2) corpus callosum, and 3) bilateral frontal, parietal, subcortical, and temporal (Jiang et al., 2017; Xu et al., 2024). Due to the absence of meta-analyses contrasting FA abnormalities across the lifespan in MDD, it is unclear whether regional FA abnormalities seen in specific age groups differ across them.

The current study is the first MDD voxel-based meta-analysis to examine FA in adolescents and older adults separately and to compare all age groups across the lifespan. Previous MDD FA VBA/TBSS meta-analyses either examined adults only (Jenkins et al., 2016), combined adolescent and adult samples (Chen et al., 2016; Chen et al., 2017; Guo et al., 2024; Liao et al., 2013; Murphy and Frodl, 2011; Shu et al., 2024; Wise et al., 2016; Zhou et al., 2022), or combined samples of adolescents, adults, and older adults (Jiang et al., 2017; Xu et al., 2024). In addition, unlike previous meta-analysis, the current study is generalizable to the overall MDD population because of its significantly larger sample which examines all symptom severities, illness durations, single episode and recurrent MDD, and treatment histories.

The primary aim of this meta-analysis was to identify FA changes across the lifespan in individuals with MDD versus HC. In light of prior meta-analyses, the current meta-analysis hypothesized lower FA in the following: 1) right parietal and right temporal regions in adolescent MDD and 2) left occipital, left subcortical, left temporal, right cerebellar, bilateral frontal, and bilateral parietal regions in adult MDD. In addition, it was expected that different lower FA would be found in older adult MDD.