Autismus-Spektrum-Störungen

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.

Relationship between Autism Spectrum Disorder and Pesticides: A Systematic Review of Human and Preclinical Models

Autism spectrum disorder (ASD) is a complex set of neurodevelopmental pathologies characterized by impoverished social and communicative abilities and stereotyped behaviors. Although its genetic basis is unquestionable, the involvement of environmental factors such as exposure to pesticides has also been proposed. Despite the systematic analyses of this relationship in humans, there are no specific reviews including both human and preclinical models. The present systematic review summarizes, analyzes, and discusses recent advances in preclinical and epidemiological studies. We included 45 human and 16 preclinical studies. These studies focused on Organophosphates (OP), Organochlorine (OC), Pyrethroid (PT), Neonicotinoid (NN), Carbamate (CM), and mixed exposures. Preclinical studies, where the OP Chlorpyrifos (CPF) compound is the one most studied, pointed to an association between gestational exposure and increased ASD-like behaviors, although the data are inconclusive with regard to other ages or pesticides. Studies in humans focused on prenatal exposure to OP and OC agents, and report cognitive and behavioral alterations related to ASD symptomatology. The results of both suggest that gestational exposure to certain OP agents could be linked to the clinical signs of ASD. Future experimental studies should focus on extending the analysis of ASD-like behaviors in preclinical models and include exposure patterns similar to those observed in human studies.