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Harv Rev Psychiatry. 2013 Nov-Dec;21(6):296-313. doi: 10.1097/HRP.0000000000000012.

Allostatic load as a tool for monitoring physiological dysregulations and comorbidities in patients with severe mental illnesses.

Author information

1
From the Department of Psychiatry and Center for Neuropsychiatric Research of Traumatic Stress, Charles University, Czech Republic (Dr. Bizik); University of Pennsylvania and Center for Mitochondrial and Epigenomic Medicine, Children's Hospital of Philadelphia, Philadelphia (Dr. Picard); Department of Psychology and Center for Research in Human Development, Concordia University, Canada (Ms. Nijjar); Department of Psychiatry (Drs. Tourjman and Lupien), Fernand-Seguin Research Centre at Louis-H. Lafontaine Hospital (Drs. Tourjman and Lupien, and Mr. Juster), and Center for Studies on Human Stress (Dr. Lupien and Mr. Juster), University of Montreal; Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology, Rockefeller University (Dr. McEwen); Department of Neurology and Neurosurgery, McGill University (Mr. Juster).

Abstract

Severe mental illnesses like schizophrenia and bipolar disorder are disabling, chronic conditions that are often accompanied by medical comorbidities. In this theoretical article, we review the allostatic load model representing the "wear and tear" that chronic stress exacts on the brain and body. We propose an innovative way of monitoring physical and psychiatric comorbidities by integrating the allostatic load model into clinical practice. By interpreting peripheral biomarkers differently, medical professionals can calculate a simple, count-based, allostatic load index known to predict diverse stress-related pathologies. In addition to screening for comorbidities, allostatic load indices can be used to monitor the effects of pharmacological and psychosocial interventions. This framework can also be used to generate a dialogue between patient and practitioner to promote preventive and proactive approaches to health care.

PMID:
24201821
DOI:
10.1097/HRP.0000000000000012
[Indexed for MEDLINE]

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