June 3, 2021
DNA methylation (DNAm) is known to be linked with kidney function, but earlier research had not revealed whether human diversity affects this association.
Now, a study has reported several new trans-ethnic and ethnic-specific DNAm associations with kidney function. This is an important finding for public health because it informs future steps to understand and address epigenomic diversity.
The study paper, titled “Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci,” was published online April 30 by Genome Medicine.
Corresponding author Nora Franceschini, MD, MPH, is a professor in the Department of Epidemiology at the UNC Gillings School of Global Public Health. Co-authors from the Gillings School are Anna Batorsky, a doctoral student and graduate research assistant in the Department of Biostatistics, and Eric Whitsel, MD, associate professor in the Department of Epidemiology — and the many other co-authors represent institutions in multiple countries.
“To understand ethnic specific and trans ethnic DNAm variation relating to kidney function, we conducted the largest ever epigenome-wide association study (EWAS) of kidney function on more than 10,000 individuals, including European Americans, Hispanics/Latinos and African Americans,” Franceschini explains. “There were significant challenges in analyzing data from such a large study involving different consortia. One of the main issues raised during analysis was that the available epigenomic datasets were mostly from individuals of European ancestry. We managed to find a few non-European samples, but this is a big obstacle for diverse molecular epidemiology.”
The researchers’ in-depth analyses showed that genomic and epigenomic associations with kidney function converge, both affecting regulatory regions involved in kidney function and development. These biomarker associations with kidney function could improve future analyses and tests, which would mean better health care for more people.
“Future frameworks and datasets should strive to capture the epigenomic diversity reported in this study,” Franceschini says. “We need to consider ancestry when doing EWAS, given the evidence for ethnic-specific findings we report. We also need more epigenomic mapping datasets across ethnicities to explore the impact of these differences.”
This diversity matters, she concludes, because “research can only work for all of us if it includes all of us.”
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