| Title: | Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches |
| Journal: | Scientific Reports |
| Published: | 28 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39730838/ |
| DOI: | https://doi.org/10.1038/s41598-024-82278-x |
Publication 14803
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes. In the overall cohort, WGS-based T1DGRS demonstrated strong correlation with TOPMed-imputed array-based score (r = 0.996, average WGS-based score 0.0028 standard deviations (SD) lower, p < 10− 31), while showing lower correlation with 1000 Genomes-imputed array-based scores (r = 0.981, 0.043 SD lower in WGS, p < 10− 300). Ancestry-stratified analyses between WGS-based and TOPMed-imputed array-based score showed the highest correlation with European ancestry (r = 0.996, 0.044 SD lower in WGS, p < 10− 300) followed by African ancestry (r = 0.989, 0.0193 SD lower in WGS, p < 10− 14) and South Asian ancestry (r = 0.986, 0.0129 SD lower in WGS, p < 10 − 6). These differences were more pronounced when comparing WGS based score with 1000 Genomes-imputed array-based scores (r = 0.982, 0.975, 0.957 for European, South Asian, African respectively). Population-level analysis using WGS-based T1DGRS revealed significant ancestry-based stratification, with European ancestry individuals showing the highest scores, followed by South Asian (average 0.28 SD lower than Europeans, p < 10− 58) and African ancestry individuals (average 0.89 SD lower than Europeans, p < 10− 300). Notably, when applying the European ancestry-derived 90th centile risk threshold, only 0.71% (95% CI 0.41-1.13) of African ancestry individuals and 6.4% (95% CI 5.6-7.2) of South Asian individuals were identified as high-risk, substantially below the expected 10%. In conclusion, while WGS is viable for generating T1DGRS, with TOPMed-imputed genotypes offering a cost-effective alternative, the persistence of ancestry-based variations in T1DGRS distribution even using whole genome sequencing emphasises the need for ancestry-specific or pan-ancestry standards in clinical practice.</p>
14 Keywords
- Adult
- Diabetes Mellitus, Type 1
- Female
- Genetic Predisposition to Disease
- Genetic Risk Score
- Genome, Human
- Genome-Wide Association Study
- Genotype
- Humans
- Male
- Middle Aged
- Polymorphism, Single Nucleotide
- Racial Groups
- Whole Genome Sequencing
7 Authors
- Ankit M. Arni
- Diane P. Fraser
- Seth A. Sharp
- Richard A. Oram
- Matthew B. Johnson
- Michael N. Weedon
- Kashyap A. Patel
1 Application
| Application ID | Title |
|---|---|
| 9072 | The Genetics of anthropometric traits ? Height, weight, BMI and waist circumference |
Enabling scientific discoveries that improve human health