State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event

The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother–child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field

Bartonella bacilliformis: a systematic review of the literature to guide the research agenda for elimination.

BACKGROUND: Carrion's disease affects small Andean communities in Peru, Colombia and Ecuador and is characterized by two distinct disease manifestations: an abrupt acute bacteraemic illness (Oroya fever) and an indolent cutaneous eruptive condition (verruga Peruana). Case fatality rates of untreated acute disease can exceed 80% during outbreaks. Despite being an ancient disease that has affected populations since pre-Inca times, research in this area has been limited and diagnostic and treatment guidelines are based on very low evidence reports. The apparently limited geographical distribution and ecology of Bartonella bacilliformis may present an opportunity for disease elimination if a clear understanding of the epidemiology and optimal case and outbreak management can be gained. METHODS: All available databases were searched for English and Spanish language articles on Carrion's disease. In addition, experts in the field were consulted for recent un-published work and conference papers. The highest level evidence studies in the fields of diagnostics, treatment, vector control and epidemiology were critically reviewed and allocated a level of evidence, using the Oxford Centre for Evidence-Based Medicine (CEBM) guidelines. RESULTS: A total of 44 studies were considered to be of sufficient quality to be included in the analysis. The majority of these were level 4 or 5 (low quality) evidence and based on small sample sizes. Few studies had been carried out in endemic areas. CONCLUSIONS: Current approaches to the diagnosis and management of Carrion's disease are based on small retrospective or observational studies and expert opinion. Few studies take a public health perspective or examine vector control and prevention. High quality studies performed in endemic areas are required to define optimal diagnostic and treatment strategies