Format

Send to

Choose Destination
Hum Brain Mapp. 2015 Oct;36(10):3761-76. doi: 10.1002/hbm.22876. Epub 2015 Jun 19.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

Author information

1
Unidad de Antropología, Departamento de Biología Animal, Facultad de Biología and Instituto de Biomedicina (IBUB), Universitat de Barcelona, Barcelona, Spain.
2
Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), Madrid, Spain.
3
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
4
Medical Image Core facility, the Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
5
Centro de Investigación Biomédica en Red en Bioingeniería, Biomedicina y Nanomedicina (CIBER-BBN), Zaragoza, Spain.
6
Centro de Diagnóstico por Imagen, Hospital Clínico, Barcelona, Spain.
7
Department of Psychiatry and Psychotherapy, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany.
8
Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, Spain.

Abstract

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals.

KEYWORDS:

Hilbert transform; MZ twins; amygdala; depression; environment; resting-state fMRI; signal processing

PMID:
26096943
DOI:
10.1002/hbm.22876
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Wiley
Loading ...
Support Center