Diversity in EWAS: current state, challenges, and solutions

Breeze, Charles E.; Wong, Jason Y.Y.; Beck, Stephan; Berndt, Sonja I.; Franceschini, Nora

doi:10.1186/s13073-022-01065-3

Cited by 17 publications

(15 citation statements)

References 11 publications

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“…Although there are known differences in the methylation pattern of a number of CpGs between different ethnicities ( 143 ), there is a lack of ethnic diversity in EWAS, which are based mainly on individuals of European ancestry ( 144 , 145 ). A recent multi-ancestry EWAS on kidney function ( 135 ) revealed several population-specific methylation patterns for eGFR in the general population with little overlap between African and European populations.…”

Section: Discussionmentioning

confidence: 99%

Genetic and epigenetic background of diabetic kidney disease

2023

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Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

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Section: Discussionmentioning

confidence: 99%

Genetic and epigenetic background of diabetic kidney disease

2023

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“…Moreover, the lack of diversity in GWAS is raising concerns about exacerbating health inequality now that the clinical translation of PGS is being evaluated [111]. Prospective studies are now starting to show that MPS biomarkers could have clinical utility [46], so more efforts are needed to diversify MWAS data sets [117].…”

Section: Ancestrymentioning

confidence: 99%

An overview of DNA methylation-derived trait score methods and applications

et al. 2023

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Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites (“probes”) and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.

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“…No previous studies investigated the association of methylation aging with CHD risk in the Asian population, despite the mortality rate of CHD has been increasing continuously in the Asian population [ 13 ]. Studies are warranted to increase the genetic diversity of study participants to understand the mechanisms underlying DNA methylation aging across humans [ 14 ]. In addition, the current knowledge of how environmental factors affect methylation aging is still lacking [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Healthy lifestyle, DNA methylation age acceleration, and incident risk of coronary heart disease

Chen²,

Sun³

et al. 2023

Clin Epigenet

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Background DNA methylation clocks emerged as a tool to determine biological aging and have been related to mortality and age-related diseases. Little is known about the association of DNA methylation age (DNAm age) with coronary heart disease (CHD), especially in the Asian population. Results Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip for 491 incident CHD cases and 489 controls in the prospective China Kadoorie Biobank. We calculated the methylation age using a prediction model developed among Chinese. The correlation between chronological age and DNAm age was 0.90. DNA methylation age acceleration (Δage) was defined as the residual of regressing DNA methylation age on the chronological age. After adjustment for multiple risk factors of CHD and cell type proportion, compared with participants in the bottom quartile of Δage, the OR (95% CI) for CHD was 1.84 (1.17, 2.89) for participants in the top quartile. One SD increment in Δage was associated with 30% increased risk of CHD (OR = 1.30; 95% CI 1.09, 1.56; Ptrend = 0.003). The average number of cigarette equivalents consumed per day and waist-to-hip ratio were positively associated with Δage; red meat consumption was negatively associated with Δage, characterized by accelerated aging in those who never or rarely consumed red meat (all P < 0.05). Further mediation analysis revealed that 10%, 5% and 18% of the CHD risk related to smoking, waist-to-hip ratio and never or rarely red meat consumption was mediated through methylation aging, respectively (all P for mediation effect < 0.05). Conclusions We first identified the association between DNAm age acceleration and incident CHD in the Asian population, and provided evidence that unfavorable lifestyle-induced epigenetic aging may play an important part in the underlying pathway to CHD.

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Diversity in EWAS: current state, challenges, and solutions

Cited by 17 publications

References 11 publications

Genetic and epigenetic background of diabetic kidney disease

Genetic and epigenetic background of diabetic kidney disease

An overview of DNA methylation-derived trait score methods and applications

Healthy lifestyle, DNA methylation age acceleration, and incident risk of coronary heart disease

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