Advancements in Biomarker Genetics: Insights from the Genomics Era

The advent of cost-effective DNA sequencing technologies has spurred significant developments in the identification of genetic variants, considerably enhancing our understanding of genetic markers linked to disease development. Recent breakthroughs in long-read sequencing further enrich our comprehension of the human genome's diversity, contributing to novel insights in population genetics and genomic studies. This evolution facilitates novel examinations of genetic diversity within and across populations, prompting a reevaluation of established practices concerning clinical biomarkers and laboratory reference values. Despite these advances, questions linger regarding the variability of clinical thresholds influenced by factors like pharmaceutical treatments, gender, and ethnicity, and the genetic underpinnings that account for these differences remain underexplored.

This Research Topic aims to bridge the knowledge gap concerning laboratory reference range thresholds in relation to genetic variants. It seeks to understand how genetic diversity affects diagnostic biomarkers and influence clinical outcomes, which could lead to more accurate and personalized medical diagnostics and treatments.

To gather further insights into the genetic mechanisms that underlie variations in clinical biomarker thresholds, we welcome articles addressing, but not limited to, the following themes:

Genetic and epigenetic factors influencing clinical and non-clinical biomarker thresholds.

Application of next-generation sequencing in the study of genes related to clinical biomarkers.

Comparative population genetics analyses of clinical biomarkers.

Integration and implications of biomarker data from pangenomes.

Innovative methodologies in genetic, epigenetic, and proteomic analyses across different ethnic groups.

We also invite submissions of various article types, including Reviews, Original Research, Brief Research Reports, and Perspective articles related to cardiac and metabolic biomarker genetics and associated methodologies.