Mapping complex and monogenetic disorders:methods and applications

Steeds meer kennis komt beschikbaar over de invloed van onze genetische kenmerken op het ontstaan van ziekten. Sommige ziekten worden veroorzaakt door één enkel gen (monogene ziekten), andere door een veelheid aan genen. Bij veel ziekten spelen naast genetische eigenschappen ook omgevingsfactoren een rol. Agata Szperl onderzocht welke mogelijkheden nieuwe genetische analysetechnieken bieden bij het ontrafelen van de oorzaken van ziekten. In haar proefschrift presenteert Szperl een breed scala aan technieken die vaak gebruikt worden in het huidige medisch genetisch onderzoek naar genen en mutaties die betrokken zijn bij het ontstaan van verschillende ziekten. Ze bestudeert zowel monogene als complexe ziekten, waarbij zij zich baseert op genetisch materiaal van zowel afzonderlijke families als de algemene bevolking. Door het gebruik van de positionele-kandidaat gen methode, etnische fine-mapping en genoomwijde sequencing identificeerde Szperl de genetische mutaties die ten grondslag liggen aan een aantal ziekten, of wist zij de chromosomale regio waarin het verantwoordelijke gen ligt te versmallen. Szperl gaat uitvoerig in op “next generation sequencing”, een nieuwe techniek die kan worden gebruikt om de meeste monogene en sommige complexe aandoeningen nu en in de toekomst te verklaren

Fine mapping of the celiac disease-associated LPP locus reveals a potential functional variant

Transplantation and immunomodulatio

Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

Background: The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective: We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design: We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case–control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results: Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions: Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD

Reducing Pharmaceuticals in Water, a New Module Integrated in the Pharmacy Game: Evaluating the Module’s Effects on Students’ Knowledge and Attitudes

Pharmaceutical residues end up in surface waters, impacting drinking water sources and contaminating the aquatic ecosystem. Pharmacists can play a role in reducing pharmaceutical residues, yet this is often not addressed in pharmacy undergraduate education. Therefore, we developed the educational module “Reducing Pharmaceuticals in Water” for pharmacy students; this was integrated in our pharmacy simulation game for third year Master of Pharmacy students at the University of Groningen. In this study, we aim to evaluate the effects of the module on students’ knowledge of pharmaceutical residues in water, to describe students’ experiences in taking the module, and to explore their attitudes towards green pharmacy education in general. This mixed-methods study included quantitative measurements, before and after students took the module (intervention group) and in a control group which did not receive the module. Data were collected between February 2023 and June 2023. Overall, 29 students took the module and 36 students were in the control group. The knowledge score of students in the intervention group (N = 29) increased significantly from 9.3 to 12.9 out of 22 (p < 0.001). The knowledge score of the students in the control group was (8.9 out of 22). Students found the e-learning and the patient cases the most exciting part of this module. Students also recognized the need to including environmental issues in pharmacy education. In conclusion, the module contributes towards improved knowledge and increased awareness of the impact of pharmaceuticals found in water. It represents a promising strategy to strengthen pharmacist’s role in mitigating the amount and the effect of pharmaceuticals on water and the environment in the future