A multifactorial model for the etiology of neuropsychiatric disorders: the role of advanced paternal age.

Mental or neuropsychiatric disorders are widespread within our societies affecting one in every four people in the world. Very often the onset of a mental disorder (MD) occurs in early childhood and substantially reduces the quality of later life. Although the global burden of MDs is rising, mental health care is still suboptimal, partly due to insufficient understanding of the processes of disease development. New insights are needed to respond to this worldwide health problem. Next to the growing burden of MDs, there is a tendency to postpone pregnancy for various economic and practical reasons. In this review, we describe the current knowledge on the potential effect from advanced paternal age (APA) on development of autism spectrum disorder, schizophrenia, attention-deficit/hyperactivity disorder, bipolar disorder, obsessive-compulsive disorder, and Tourette syndrome. Although literature did not clearly define an age cut-off for APA, we here present a comprehensive multifactorial model for the development of MDs, including the role of aging, de novo mutations, epigenetic mechanisms, psychosocial environment, and selection into late fatherhood. Our model is part of the Paternal Origins of Health and Disease paradigm and may serve as a foundation for future epidemiological research designs. This blueprint will increase the understanding of the etiology of MDs and can be used as a practical guide for clinicians favoring early detection and developing a tailored treatment plan. Ultimately, this will help health policy practitioners to prevent the development of MDs and to inform health-care workers and the community about disease determinants. Better knowledge of the proportion of all risk factors, their interactions, and their role in the development of MDs will lead to an optimization of mental health care and management. IMPACT: We design a model of causation for MDs, integrating male aging, (epi)genetics, and environmental influences. It adds new insights into the current knowledge about associations between APA and MDs. In clinical practice, this comprehensive model may be helpful in early diagnosis and in treatment adopting a personal approach. It may help in identifying the proximate cause on an individual level or in a specific subpopulation. Besides the opportunity to measure the attributed proportions of risk factors, this model may be used as a blueprint to design prevention strategies for public health purposes.