FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a semantic schema of essential data elements harmonized with international FAIR initiatives. The FAIR Genomes schema v1.1 contains 110 elements in 9 modules. It reuses common ontologies such as NCIT, DUO and EDAM, only introducing new terms when necessary. The schema is represented by a YAML file that can be transformed into templates for data entry software (EDC) and programmatic interfaces (JSON, RDF) to ease genomic data sharing in research and healthcare. The schema, documentation and MOLGENIS reference implementation are available at https://fairgenomes.org .

Disentangling Variability in Riverbank Macrolitter Observations

Anthropogenic macrolitter (>0.5 cm) in rivers is of increasing concern. It has been found to have an adverse effect on riverine ecosystem health, and the livelihoods of the communities depending on and living next to these ecosystems. Yet, little is known on how macrolitter reaches and propagates through these ecosystems. A better understanding of macrolitter transport dynamics is key in developing effective reduction, preventive, and cleanup measures. In this study, we analyzed a novel dataset of citizen science riverbank macrolitter observations in the Dutch Rhine-Meuse delta, spanning two years of observations on over 200 unique locations, with the litter categorized into 111 item categories according to the river-OSPAR protocol. With the use of regression models, we analyzed how much of the variation in the observations can be explained by hydrometeorology, observer bias, and location, and how much can instead be explained by temporal trends and seasonality. The results show that observation bias is very low, with only a few exceptions, in contrast with the total variance in the observations. Additionally, the models show that precipitation, wind speed, and river flow are all important explanatory variables in litter abundance variability. However, the total number of items that can significantly be explained by the regression models is 19% and only six item categories display an R2 above 0.4. This suggests that a very substantial part of the variability in macrolitter abundance is a product of chance, caused by unaccounted (and often fundamentally unknowable) stochastic processes, rather than being driven by the deterministic processes studied in our analyses. The implications of these findings are that for modeling macrolitter movement through rivers effectively, a probabilistic approach and a strong uncertainty analysis are fundamental. In turn, point observations of macrolitter need to be planned to capture short-term variability.

Psychometric Characteristics of a Patient Reported Outcome Measure on Ego-Integrity and Despair among Cancer Patients

Purpose

To evaluate psychometric characteristics of a questionnaire (the Northwestern Ego-integrity Scale (NEIS)) on ego-integrity (the experience of wholeness and meaning in life, even in spite of negative experiences) and despair (the experience of regret about the life one has led, and feelings of sadness, failure and hopelessness) among cancer patients.

Methods

Cancer patients (n = 164) completed patient reported outcome measures on ego-integrity and despair (NEIS), psychological distress, anxiety and depression (Hospital Anxiety and Depression Scale (HADS)), and quality of life (EORTC QLQ-C30 (cancer survivors, n = 57) or EORTC QLQ-C15-PAL (advanced cancer patients, n = 107)). Confirmatory Factor Analysis was used to assess construct validity. Cronbach’s alpha was used to assess internal consistency. Convergent validity was tested based on a priori defined hypotheses: a higher level of ego-integrity was expected to be related to a higher level of quality of life, and lower levels of distress, depression and anxiety; a higher level of despair was expected to be related to a lower level of quality of life, and higher levels of distress, depression and anxiety.

Results

The majority of all items (94.5%) of the NEIS were completed by patients and single item missing rate was below 2%. The two subscales, labeled as Ego-integrity (5 items) and Despair (4 items) had acceptable internal consistency (Cronbach’s alpha .72 and .61, respectively). The Ego-integrity subscale was not significantly associated with quality of life, distress, anxiety, or depression. The Despair subscale correlated significantly (p <.001) with quality of life (r = -.29), distress (r = .44), anxiety (r = .47) and depression (r = .32).

Conclusion

The NEIS has good psychometric characteristics to assess ego-integrity and despair among cancer patients.