Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene–environment interactions. Only a few specific gene–environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene–environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Africa is experiencing a rapid increase in adult obesity and associated cardiometabolic diseases (CMDs). The H3Africa AWI-Gen Collaborative Centre was established to examine genomic and environmental factors that influence body composition, body fat distribution and CMD risk, with the aim to provide insights towards effective treatment and intervention strategies. It provides a research platform of over 10 500 participants, 40–60 years old, from Burkina Faso, Ghana, Kenya and South Africa. Following a process that involved community engagement, training of project staff and participant informed consent, participants were administered detailed questionnaires, anthropometric measurements were taken and biospecimens collected. This generated a wealth of demographic, health history, environmental, behavioural and biomarker data. The H3Africa SNP array will be used for genome-wide association studies. AWI-Gen is building capacity to perform large epidemiological, genomic and epigenomic studies across several African counties and strives to become a valuable resource for research collaborations in Africa.

Objective: Oxidative stress is involved in the pathogenesis of multiple system atrophy (MSA). The aim of this study is to examine oxidant biomarkers including homocysteine (Hcys), bilirubin, uric acid, lipids, and potential environmental risk factors and to ascertain whether these data correlate with MSA in a Chinese population. Methods: In this study, serum levels of Hcys, bilirubin, uric acid, and lipids were studied in 55 MSA patients and 76 healthy controls (HCs). Education, anti-parkinsonian agent usage, smoking, drinking, farming, and living area of the subjects also were analyzed. The Unified MSA Rating Scale (UMSARS), Hoehn & Yahr stage, International Cooperative Ataxia Rating Scale, and Mini-Mental State Examination were used to assess the disease severity, the parkinsonism, ataxia, and the cognitive ability of MSA, respectively. Results: The levels of Hcys were higher (p<0.001) and those of total bilirubin (p=0.007), indirect bilirubin (p=0.011), and total cholesterol (p=0.046) were lower in MSA patients than in healthy controls, whereas uric acid levels did not differ significantly between MSA and healthy controls. Moreover, Hcys levels in MSA patients had positive correlations with illness duration (rs=0.422, p=0.001) and UMSARS-I (rs=0.555, p<0.001), respectively. High-density lipoprotein cholesterol levels were negatively correlated with UMSARS-I (rs=−0.325, p=0.015). Farming was more frequent in MSA patients (1-20 years: odds ratio, 6.36; p<0.001; >20 years: odds ratio, 10.26; p=0.001), whereas current smoking was less frequent (odds ratio, 0.13, p=0.002). Conclusions: Elevated Hcys and decreased high-density lipoprotein cholesterol may be associated with the disease severity of MSA. Environmental exposures such as farming and smoking may contribute to the occurrence but not the progression of MSA.