Dataset Information

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

ABSTRACT: Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

SUBMITTER: Jakubek YA

PROVIDER: S-EPMC10632132 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Jakubek Yasminka A YA Zhou Ying Y Stilp Adrienne A Bacon Jason J Wong Justin W JW Ozcan Zuhal Z Arnett Donna D Barnes Kathleen K Bis Joshua C JC Boerwinkle Eric E Brody Jennifer A JA Carson April P AP Chasman Daniel I DI Chen Jiawen J Cho Michael M Conomos Matthew P MP Cox Nancy N Doyle Margaret F MF Fornage Myriam M Guo Xiuqing X Kardia Sharon L R SLR Lewis Joshua P JP Loos Ruth J F RJF Ma Xiaolong X Machiela Mitchell J MJ Mack Taralynn M TM Mathias Rasika A RA Mitchell Braxton D BD Mychaleckyj Josyf C JC North Kari K Pankratz Nathan N Peyser Patricia A PA Preuss Michael H MH Psaty Bruce B Raffield Laura M LM Vasan Ramachandran S RS Redline Susan S Rich Stephen S SS Rotter Jerome I JI Silverman Edwin K EK Smith Jennifer A JA Smith Aaron P AP Taub Margaret M Taylor Kent D KD Yun Jeong J Li Yun Y Desai Pinkal P Bick Alexander G AG Reiner Alexander P AP Scheet Paul P Auer Paul L PL

Nature genetics 20231030 11

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fra ...[more]

PMID: 37904051

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Project description: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.

Dataset Information

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Publications

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

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