Knowledge Graph (KG) approaches are increasingly being used for data integration processes to combine clinical data with other data sources. Health Data Researchers (HDR) could benefit from these technologies since they require additional types of data outside the health sector, like environmental data, to better understand the extrinsic factors that influence health outcomes in rare disease research. However, using and directly navigating the combined data in the KG can be an obstacle for HDRs. To address this problem, the Semantic Environmental and Rare Disease data Integration Framework (SERDIF) was designed to hide the complexities for these researchers when exploring linked environmental observations with clinical data using a KG approach. The framework was evaluated by HDRs for a case study on Anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) in Ireland, and promising usability and effectiveness results were observed. HDRs studying AAV were able to access, explore and export environmental related data to be used as input for their statistical models. SERDIF has the potential to be a solution for HDRs, who require a flexible methodology to integrate environmental data with longitudinal and geospatial diverse clinical data, in their hypothesis validation of environmental factors for rare disease research.

Recent advances on the environmental determinants of Kawasaki Disease have pointed to the important role of the atmospheric transport of a still unknown agent potentially triggering the disease. The hypothesis arose from an innovative methodology combining expertise in climate dynamics, the analysis of ocean and atmosphere data, the use of dispersion models and the search for biological agents in air samples. The approach offered a new perspective to reveal the identity of the potential trigger, but at the same time, it increased the level of complexity, which could potentially lead to the misinterpretation of the mechanisms. Some years after it was originally formulated, we here provide a brief clarification on the approach and limits of the methodology in order to prevent an eventual misuse of our research ideas and theory, so that further research can better focus on the knowledge gaps that still remain open.

Background The aetiology of ANCA-associated vasculitis (AAV) and triggers of relapse are poorly understood. Vitamin D (vitD) is an important immunomodulator, potentially responsible for the observed latitudinal differences between granulomatous and non-granulomatous AAV phenotypes. A narrow ultraviolet B spectrum induces vitD synthesis (vitD-UVB) via the skin. We hypothesised that prolonged periods of low ambient UVB (and by extension vitD deficiency) are associated with the granulomatous form of the disease and an increased risk of AAV relapse. Methods Patients with AAV recruited to the Irish Rare Kidney Disease (RKD) (n = 439) and UKIVAS (n = 1961) registries were studied. Exposure variables comprised latitude and measures of ambient vitD-UVB, including cumulative weighted UVB dose (CW-D-UVB), a well-validated vitD proxy. An n-of-1 study design was used to examine the relapse risk using only the RKD dataset. Multi-level models and logistic regression were used to examine the effect of predictors on AAV relapse risk, phenotype and serotype. Results Residential latitude was positively correlated (OR 1.41, 95% CI 1.14–1.74, p = 0.002) and average vitD-UVB negatively correlated (0.82, 0.70–0.99, p = 0.04) with relapse risk, with a stronger effect when restricting to winter measurements (0.71, 0.57–0.89, p = 0.002). However, these associations were not restricted to granulomatous phenotypes. We observed no clear relationship between latitude, vitD-UVB or CW-D-UVB and AAV phenotype or serotype. Conclusion Our findings suggest that low winter ambient UVB and prolonged vitD status contribute to AAV relapse risk across all phenotypes. However, the development of a granulomatous phenotype does not appear to be directly vitD-mediated. Further research is needed to determine whether sufficient vitD status would reduce relapse propensity in AAV.

Background The etiology of ANCA-associated vasculitis (AAV) and triggers of relapse are poorly understood. Vitamin D (vitD) is an important immunomodulator, potentially responsible for the observed latitudinal differences between granulomatous and non-granulomatous AAV phenotypes. A narrow ultraviolet B spectrum induces vitD synthesis (vitD-UVB) via the skin. We hypothesised that prolonged periods of low ambient UVB (and by extension vitD deficiency) are associated with the granulomatous form of the disease and an increased risk of AAV relapse. Methods Patients with AAV recruited to the Irish Rare Kidney Disease (RKD) (n = 439) and UKIVAS (n = 1961) registries were studied. Exposure variables comprised latitude and measures of ambient vitD-UVB, including cumulative weighted UVB dose (CW-D-UVB), a well-validated vitD proxy. An n-of-1 study design was used to examine relapse risk. Multi-level models and logistic regression were used to examine the effect of predictors on AAV relapse risk, phenotype and serotype. Results Residential latitude was positively correlated (OR:1.41, 95% CI 1.14–1.74, p = 0.002) and average vitD-UVB negatively correlated (0.82, 0.70–0.99, p = 0.04) with relapse risk, with a stronger effect when restricting to winter measurements (0.71, 0.57–0.89, p = 0.002). However, these associations were not restricted to granulomatous phenotypes. We observed no clear relationship between latitude, vitD-UVB or CW-D-UVB and AAV phenotype or serotype. Conclusion Our findings suggest that low winter ambient UVB and prolonged vitD status contribute to AAV relapse risk across all phenotypes. However, development of a granulomatous phenotype does not appear to be directly vitD-mediated. Further research is needed to determine whether sufficient vitD status would reduce relapse propensity in AAV.

Anthropogenic pollution has frequently been linked to myriad human ailments despite clear mechanistic links are yet lacking, a fact that severely downgraded its actual relevance. Now a prominent unnoticed sub-weekly cycle (SWC) of 3.5 days is uncovered in the long-term epidemiological records of Kawasaki disease (KD) in Japan, a mysterious vasculitis of yet unknown origin. After ruling out the effect of reporting biases, the analysis of Light Detection and Ranging (LIDAR) atmospheric profiles further confirms that this variability is linked to atmospheric particles with an aerodynamic diameter less than 1 micron. SWC accounts for 20% of the variance in KD and its contribution is stable throughout the entire epidemiological record dating back to 1970, both at the prefecture level and for entire Japan. KD maxima in 2010-2016 always occur in full synchrony with LIDAR particle arrival in diverse locations such as Tokyo, Toyama and Tsukuba as well as for the entire of Japan. Rapid intrusion of aerosols from heights up to 6km to the surface is observed with KD admissions co-varying with their metal chemical composition. While regional intensity of winds has not changed in the interval 1979-2015, our study instead points for the first time to increased anthropogenic pollution as a necessary co-factor in the occurrence of KD and sets the field to associate other similar human vasculitis.

Air pollution (urban, industrial or rural) has been linked to a myriad human ailment despite clear mechanistic associations are not often thoroughly established. Daily variability of fine aerosols in a surveillance campaign in south Japan shows a striking coevolution between their trace elements (metal and metalloid, MM) content and Kawasaki Disease (KD) admissions, suggesting a strong dynamical link. These aerosol MM could instigate an immune response that along with genetic susceptibility, would lead to KD development. This association may account to over 40% of the total variability in the disease, being dominated by a clear sub-weekly cycle (SWC1). Thanks to both an unprecedented daily KD epidemiological record going back to 1970, Light Detection and Ranging (LIDAR) atmospheric backscattering profiles for the interval 2010-2016 and HYSPLIT simulations with numerous sensitivity analyses, we can trace this SWC1 variability to occur concomitantly from sub-seasonal to interannual timescales in both KD and aerosols. This SWC1 appears to connect or disconnect Japan to air intrusions from above the planetary boundary layer (PBL), having their source in industrial and agricultural areas in NE Asia and points to a stronger case for an agricultural source for the exposure as opposed to urban pollution. KD maxima always occur in full synchrony with the arrival of very small (<1 µm; PM1) particles showing that ultrafine aerosols appear as a necessary cofactor in the occurrence of KD and sets the field to associate other similar human diseases. Our study shows how signal-detection approaches can be useful to uncover hidden associations between the environment and human health, otherwise unnoticed and help set new early-warning systems for disease prevention.

Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and study of a semantic framework (i.e. Knowledge Graph, Methodology and User Interface) to enable Health Data Researchers (HDR) to link particular health events with environmental data for rare disease research. The usability study includes 17 HDRs with expertise in health data related to Anti-Neutrophil Cytoplasmic Antibody (ANCA)-associated vasculitis (AAV) in Ireland and Kawasaki Disease in Japan, and with no previous practical experience in using Semantic Web (SW) technologies. The evaluation results are promising in that they indicate that the framework is useful in allowing researchers themselves to link health and environmental data whilst hiding the complexities of SW technologies. As a result of this work, we also discuss the limitations of the approach together with the applicability to other domains. Beyond the direct impact on environmental health studies, the description of the evaluation approach can guide researchers in making SW technologies more accessible to domain experts through usability studies.