Objective To evaluate the existing meta-analytic evidence of associations between exposure to ultra-processed foods, as defined by the Nova food classification system, and adverse health outcomes. Design Systematic umbrella review of existing meta-analyses. Data sources MEDLINE, PsycINFO, Embase, and the Cochrane Database of Systematic Reviews, as well as manual searches of reference lists from 2009 to June 2023. Eligibility criteria for selecting studies Systematic reviews and meta-analyses of cohort, case-control, and/or cross sectional study designs. To evaluate the credibility of evidence, pre-specified evidence classification criteria were applied, graded as convincing (“class I”), highly suggestive (“class II”), suggestive (“class III”), weak (“class IV”), or no evidence (“class V”). The quality of evidence was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework, categorised as “high,” “moderate,” “low,” or “very low” quality. Results The search identified 45 unique pooled analyses, including 13 dose-response associations and 32 non-dose-response associations (n=9 888 373). Overall, direct associations were found between exposure to ultra-processed foods and 32 (71%) health parameters spanning mortality, cancer, and mental, respiratory, cardiovascular, gastrointestinal, and metabolic health outcomes. Based on the pre-specified evidence classification criteria, convincing evidence (class I) supported direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease related mortality (risk ratio 1.50, 95% confidence interval 1.37 to 1.63; GRADE=very low) and type 2 diabetes (dose-response risk ratio 1.12, 1.11 to 1.13; moderate), as well as higher risks of prevalent anxiety outcomes (odds ratio 1.48, 1.37 to 1.59; low) and combined common mental disorder outcomes (odds ratio 1.53, 1.43 to 1.63; low). Highly suggestive (class II) evidence indicated that greater exposure to ultra-processed foods was directly associated with higher risks of incident all cause mortality (risk ratio 1.21, 1.15 to 1.27; low), heart disease related mortality (hazard ratio 1.66, 1.51 to 1.84; low), type 2 diabetes (odds ratio 1.40, 1.23 to 1.59; very low), and depressive outcomes (hazard ratio 1.22, 1.16 to 1.28; low), together with higher risks of prevalent adverse sleep related outcomes (odds ratio 1.41, 1.24 to 1.61; low), wheezing (risk ratio 1.40, 1.27 to 1.55; low), and obesity (odds ratio 1.55, 1.36 to 1.77; low). Of the remaining 34 pooled analyses, 21 were graded as suggestive or weak strength (class III-IV) and 13 were graded as no evidence (class V). Overall, using the GRADE framework, 22 pooled analyses were rated as low quality, with 19 rated as very low quality and four rated as moderate quality. Conclusions Greater exposure to ultra-processed food was associated with a higher risk of adverse health outcomes, especially cardiometabolic, common mental disorder, and mortality outcomes. These findings provide a rationale to develop and evaluate the effectiveness of using population based and public health measures to target and reduce dietary exposure to ultra-processed foods for improved human health. They also inform and provide support for urgent mechanistic research. Systematic review registration PROSPERO CRD42023412732.

The emerging understanding of gut microbiota as ‘metabolic machinery’ influencing many aspects of physiology has gained substantial attention in the field of psychiatry. This is largely due to the many overlapping pathophysiological mechanisms associated with both the potential functionality of the gut microbiota and the biological mechanisms thought to be underpinning mental disorders. In this systematic review, we synthesised the current literature investigating differences in gut microbiota composition in people with the major psychiatric disorders, major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ), compared to ‘healthy’ controls. We also explored gut microbiota composition across disorders in an attempt to elucidate potential commonalities in the microbial signatures associated with these mental disorders. Following the PRISMA guidelines, databases were searched from inception through to December 2021. We identified 44 studies (including a total of 2510 psychiatric cases and 2407 controls) that met inclusion criteria, of which 24 investigated gut microbiota composition in MDD, seven investigated gut microbiota composition in BD, and 15 investigated gut microbiota composition in SZ. Our syntheses provide no strong evidence for a difference in the number or distribution (α-diversity) of bacteria in those with a mental disorder compared to controls. However, studies were relatively consistent in reporting differences in overall community composition (β-diversity) in people with and without mental disorders. Our syntheses also identified specific bacterial taxa commonly associated with mental disorders, including lower levels of bacterial genera that produce short-chain fatty acids (e.g. butyrate), higher levels of lactic acid-producing bacteria, and higher levels of bacteria associated with glutamate and GABA metabolism. We also observed substantial heterogeneity across studies with regards to methodologies and reporting. Further prospective and experimental research using new tools and robust guidelines hold promise for improving our understanding of the role of the gut microbiota in mental and brain health and the development of interventions based on modification of gut microbiota.

Background: Bipolar disorder (BD) is a psychiatric disorder with an uncertain aetiology. Recently, special attention has been given to homocysteine (Hcy), as it has been suggested that alterations in 1-carbon metabolism might be implicated in diverse psychiatric disorders. However, there is uncertainty regarding possible alterations in peripheral Hcy levels in BD.Methods: This study comprises a meta-analysis comparing serum and plasma Hcy levels in persons with BD and healthy controls. We conducted a systematic search for all eligible English and non-English peer-reviewed articles.Results: Nine cross-sectional studies were included in the meta-analyses, providing data on 1547 participants. Random-effects meta-analysis showed that serum and plasma levels of Hcy were increased in subjects with BD in either mania or euthymia when compared to healthy controls, with a large effect size in the mania group (g= 0.98, 95% CI: 0.8–1.17,P< 0.001,n= 495) and a small effect in the euthymia group (g= 0.3, 95% CI: 0.11–0.48,P= 0.002,n= 1052).Conclusions: Our meta-analysis provides evidence that Hcy levels are elevated in persons with BD during mania and euthymia. Peripheral Hcy could be considered as a potential biomarker in BD, both of trait (since it is increased in euthymia), and also of state (since its increase is more accentuated in mania). Longitudinal studies are needed to clarify the relationship between bipolar disorder and Hcy, as well as the usefulness of peripheral Hcy as both a trait and state biomarker in BD.

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

Knowledge of the microbiome-gut-brain axis has revolutionized the field of psychiatry. It is now well recognized that the gut bacteriome is associated with, and likely influences, the pathogenesis of mental disorders, including major depressive disorder and bipolar disorder. However, while substantial advances in the field of microbiome science have been made, we have likely only scratched the surface in our understanding of how these ecosystems might contribute to mental disorder pathophysiology. Beyond the gut bacteriome, research into lesser explored components of the gut microbiome, including the gut virome, mycobiome, archaeome, and parasitome, is increasingly suggesting relevance in psychiatry. The contribution of microbiomes beyond the gut, including the oral, lung, and small intestinal microbiomes, to human health and pathology should not be overlooked. Increasing both our awareness and understanding of these less traversed fields of research are critical to improving the therapeutic benefits of treatments targeting the gut microbiome, including fecal microbiome transplantation, postbiotics and biogenics, and dietary intervention. Interdisciplinary collaborations integrating systems biology approaches are required to fully elucidate how these different microbial components and distinct microbial niches interact with each other and their human hosts. Excitingly, we may be at the start of the next microbiome revolution and thus one step closer to informing the field of precision psychiatry to improve outcomes for those living with mental illness.

Diet quality is associated with depression risk, however the possible role of dairy products in depression risk is unclear. A number of epidemiological studies have examined associations between dairy consumption and depressive symptoms, but results have been inconsistent. Therefore, this systematic review aimed to examine whether an association exists between dairy consumption and depressive symptoms or disorders in adults. Anxiety symptoms were also explored as a secondary outcome. CINAHL, Cochrane, MEDLINE complete, EMBASE, Scopus and PsycINFO databases were searched from database inception to December 2018. Studies were included if they used a case-control, cross-sectional, or cohort study design, and included community dwelling or institutionalized adults (≥18 years). Seven prospective and six cross-sectional studies (N = 58,203 participants) reported on the association between dairy consumption and depressive symptoms or disorders. Findings were mixed, with one study reporting a positive association; five studies reporting no association; and seven studies reporting mixed associations depending on dairy type, gender or population group. We found conflicting and inconsistent associations in studies that were generally of fair quality. Future longitudinal and intervention studies that employ more rigorous dietary assessment methods are warranted.