Abstract: Intergenerational Transmission Patterns in the Human Brain (Society for Social Work and Research 20th Annual Conference - Grand Challenges for Social Work: Setting a Research Agenda for the Future)

Intergenerational Transmission Patterns in the Human Brain

Schedule:
Saturday, January 16, 2016: 8:00 AM
Meeting Room Level-Meeting Room 15 (Renaissance Washington, DC Downtown Hotel)
* noted as presenting author
Jessica M. Black, PhD, Assistant Professor, Boston College, Chestnut Hill, MA
Background and Purpose: Intergenerational transmissions of traits are often observed in the psychopathology of major psychiatric conditions. Corticolimbic circuitry, mainly connecting amygdala and ventromedial prefrontal cortex (vmPFC), is highly relevant in a wide range of mental health conditions that show intergenerational effects (e.g., depression). This first of its kind study assesses the sex-specific intergenerational transmission patterns on brain structure in parent-offspring pairs, unlike the common approach of assessing heritability in twins.  We hypothesized that mother-daughter pairs would reveal significantly positive grey matter volume (GMV) associations in the corticolimbic brain regions (implicated in mood and anxiety disorders) compared to other parent-offspring pairs. Our hypothesis was based on extant findings demonstrating that depression exhibits strong female-specific intergenerational transmission patterns. An improved understanding of familial transmission is important for the development of biopsychosocial interventions embedded within a life course framework.

Methods: We investigated the degree of association in gray matter volume (GMV) between parent and offspring using voxel-wise correlation analysis in 34 healthy families by forming 4 biological parent-offspring subgroups: 16 mother-daughter, 18 mother-son, 15 father-daughter, and 18 father-son pairs. We created a corticolimbic region of interest (ROI) using bilateral amygdala and vmPFC. We created brain maps that compared the regression coefficient between different parent-offspring groups on a voxel-wise basis in the corticolimbic ROI where there were significant parent-offspring relationships. We conducted a whole brain voxel-wise analysis to find regions showing greater mother-daughter GMV associations relative to other parent-offspring associations and investigated potential functional networks that co-localized within these brain regions. Next we decoded the psychological processes from these functionally connected networks. To examine whether GMV of the brain regions showing significant positive maternal associations in offspring daughters correlated with behavioral data, correlation analyses were performed between daughters’ GMV data and standardized scores on mental health subscales from the Behavioral Assessment System for Children (BASC-2).

Results: We found positive associations of regional GMV in the corticolimbic circuit including the amygdala and ventromedial prefrontal cortex between biological mothers and daughters. This association was significantly greater than mother-son, father-daughter, and father-son associations (P < 0.05; family-wise-error corrected). Using the Neurosynth database we found that the psychological processes associated with the networks derived from the seed regions identified in the voxel-wise analysis are related to emotion regulation. There was a significant positive correlation between GMV within the vmPFC and BASC-2 T-score of the adaptability (ease of adaptation to changing environments) (r = 0.796, P = 0.006 Bonferroni corrected).

Conclusions and Implications: The current study suggests that the corticolimbic circuitry, which has been implicated in mood regulation, shows a matrilineal specific transmission pattern consistent with what has been found in the behavioral symptoms of mood disorders. Our results give new insights into the potential neuroanatomical basis of sex-specific intergenerational effects of psychiatric conditions, especially for depression and anxiety disorders. Findings such as ours may have important implications for furthering the understanding and creation of developmental-stage specific and circuit-based treatments for numerous mental illnesses ranging from mood and anxiety disorders to autism and addiction that show intergenerational patterns.