The Bio-Psycho-Social Holobiont Model of Health: Integrating the Biopsychosocial Paradigm, Microbiota Science, and Psychoneuroendocrinoimmunology - Massimo Agnoletti (Qeios, 2026)
This article proposes the Bio-Psycho-Social Holobiont Model as a contemporary theoretical framework that integrates the complexity of the traditional biopsychosocial model with recent advances in microbiota science. While the biopsychosocial model has long represented one of the most comprehensive approaches to understanding health and disease, emerging evidence regarding the human microbiota and the holobiont concept suggests the need for a broader conceptual framework capable of incorporating the ecological and functional interdependence between human and microbial components. Within the Bio-Psycho-Social Holobiont Model, health is conceptualized as an emergent property arising from the functional coherence of reciprocal interactions among biological, psychological, social, and microbiotic processes occurring within and between human and non-human cellular systems. In this context, by the term “coherence” of mutual interactions among biological, psychological, social, and microbiotic processes, we mean the informational convergence of the different bio-psycho-social teleonomies[1][2]. The model proposes that health and disease cannot be fully understood by focusing exclusively on human biological processes, but rather require consideration of the dynamic interactions among the host, its microbiota, psychological functioning, and sociocultural environment. The article discusses the theoretical foundations of the model, its implications for the conceptualization of health and disease, its relationship with Psychoneuroendocrinoimmunology (PNEI), and its potential relevance for future interdisciplinary research and clinical practice. The Bio-Psycho-Social Holobiont Model is proposed as a theoretical extension and integration of the traditional biopsychosocial paradigm that is more consistent with contemporary developments in systems biology, complexity science, and microbiota research.