The impact of early life antibiotic use on atopic and metabolic disorders

Abstract

Abstract Background and objectives The impact of antibiotics use early in life on later-in-life morbidities has received substantial attention as explanations for atopic and metabolic disorders with a surge as modern lifestyle diseases. The objective of this study was to perform meta-analyses to determine if antibiotics administration during the first 2 years of infant life is associated with increased risks of atopic or metabolic disorders later in life. Methodology We screened more than 100 English-language prospective and retrospective studies published between January 2002 and March 2020 and assessed study quality using the Newcastle–Ottawa scale. We performed overall and subgroup meta-analyses on 31 high-quality comparable studies on atopic and 23 on metabolic disorders, involving more than 3.5 million children. Results Antibiotic exposure prenatally and during the first 2 years of life significantly impacts the risk of developing atopic and metabolic disorders. Exposure during the first 6 months of life appears most critical, consistent with this being the time when the microbiome is most susceptible to irreversible perturbations. The presence of dose−response associations and stronger impacts of broad- than narrow-spectrum antibiotics further point to effects being mediated by microbiota-induced changes. Conclusions and implications Our findings support that antibiotics use is a mismatch to modernity that can negatively affect the symbiotic associations we rely on for proper immune function and metabolism. Improving our understanding of these associations, the underlying proximate mechanisms and the impact of antibiotics use on future human−symbiont evolution will be important to improve human health. Lay Summary The use of antibiotics in infancy has been suggested to increase the risks of atopic and metabolic disorders later in life. Through meta-analyses of more than 100 studies of >3.5 million children, we confirm these risks, and show that patterns are consistent with effects being due to microbiota-driven changes.