henhaobio
Sign in

Endocrinology Diabetes & MetabolismGenetic & Genomic MedicinePeer-reviewed journal article

Understanding Patient Perceptions of Genetic Testing to Predict Type 2 Diabetes Risk After Gestational Diabetes

Ria PateliD, Martha ChristodoulouiD, Zoe Taylor, Prajwal Shetty, Julia ZöllneriD

PDFDOIPreprint

Abstract

AimsWomen with gestational diabetes mellitus (GDM) face increased lifetime risk of type 2 diabetes (T2DM). Genetic risk-predictive testing could help identify those at highest risk and guide preventative care. We aimed to assess perceptions of genetic risk scores to help inform future implementation. MethodsAn online survey of 112 women with current or prior GDM assessed willingness for genetic and non-genetic risk testing, attitudes lifestyle motivation, and data-use concerns. Quantitative analyses were complemented by thematic analysis of free-text responses. ResultsOverall, willingness was high for both genetic testing (83.9%) and non- genetic (90.2%), with no significant difference between them (p = 0.083). Participants identifying as White reported greater willingness for genetic testing (p = 0.020) and stronger agreement that testing should be available on the NHS (p = 0.032) than N=non-White participants. Attitudes toward genetic testing were positive and associated with both willingness to test and support for NHS availability (p < 0.001). Younger participants were more motivated to modify lifestyle behaviours (p = 0.015). Overall, concerns around data collection were low; although free-text responses highlighted health insurance implications, psychological burden, actionability of results, and timing of testing as salient themes. ConclusionsWomen with GDM were receptive to genetic risk-prediction for T2DM, with low concerns around data usage. Demographic differences in acceptability and motivation highlight the need for inclusive, targeted communications and lifestyle support alongside integration testing into postnatal-GDM care. What is already known?We know that women with Gestational Diabetes Mellitus (GDM) have an increased risk of developing Type 2 Diabetes Mellitus (T2DM) later in life. Genetic risk scores can stratify women by their likelihood of developing T2DM following GDM. This risk information could help to inform womens lifestyle choices and help prevent progression to T2DM. However, evidence is limited regarding womens willingness to undergo genetic testing, how risk information might shape lifestyle behaviours, and their concerns about data collection and privacy. What this study has found?Our study found that our participants with current or previous GDM were fairly receptive to genetic testing to predict their future risk of T2DM. There was no significant difference between reported acceptability of a non-genetic test and a genetic test. Participants held positive attitudes towards genetic testing and fairly low concerns about data use and privacy. However, the acceptability of this testing and motivation for lifestyle changes varied by participant demographics (including age, education and ethnicity). Additionally, free-text responses identified concerns over implications for health insurance, the timing of testing, psychological burden of knowing results and the actionability of results. What are the implications of the study?To support equitable engagement and uptake of genetic risk-prediction testing, inclusive education and communication strategies are needed - particularly on the actionability of results and data collection/storage policies. Although not directly measured, our findings point to the value of culturally responsive, trust-building communication--delivered with cultural humility and empathy--to address uncertainties and enable informed choice. These findings support the use of genetic predictive testing within postnatal GDM care in addition to targeted interventions to support lifestyle changes and prevent progression to type 2 diabetes.

Citations
0
FWCI
0.00
Field percentile
19th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISHughes '20Lamri '22Zhao '26Hollitt '22Lamri '19Lall '16
68% semantic matchGenetics
Alice E. Hughes, M. Geoffrey Hayes, Aoife Maria Egan+7 more·Wellcome Open Research·Jul 22, 2020· 3 citations