Press release
Illumina whole-genome sequencing provides greater insight into genetic signals behind common diseases--according to Nature study
Study shows that rare variants captured by Illumina WGS with DRAGEN™ variant calling explain most of the "missing heritability" in complex human diseases and
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[{"type":"text","content":"\n Study shows that rare variants captured by Illumina WGS with DRAGEN™ variant calling explain most of the \"missing heritability\" in complex human diseases and traits, including those related to blood pressure and cholesterol\n \n \n Results demonstrate the advantages of WGS over WES and genotyping arrays for assessing genetic risk and identifying drug target candidates.\n \n \n SAN DIEGO, Nov. 12, 2025 /PRNewswire/ -- A study published today in Nature, authored by Illumina, Inc. (NASDAQ: ILMN) scientists and by collaborators from The University of Queensland demonstrates the importance of whole-genome sequencing (WGS) to more fully capture the genetics underlying complex human traits and diseases. Across all 34 diseases and traits studied, WGS captured nearly 90% of the genetic signal, based on heritability estimates from family studies. This marks a step toward solving the \"missing heritability\" problem, resolving the gap between family-based heritability and the heritability estimates made by genome wide association studies.\n \n \n \n \n \n \n \n \"This study shows how Illumina's whole-genome sequencing, powered by DRAGEN secondary analysis and cutting-edge statistical and deep-learning tools, get more out of large cohort studies,\" said Rami Mehio, senior vice president and general manager of BioInsight at Illumina. \"Our top-performing WGS reveals much more of the genetic signals underlying common diseases, offering researchers AI driven insights that can predict disease risk and identify drug targets.\"\n \n Solving for missing heritability\n \n Heritability is a critical parameter for researchers, giving them an upper limit for genetics-based risk predictions and pointing them toward traits to target for drug discovery and development. Heritability estimates from large, biobank-based genetic studies typically do not match estimates from family-based genetic studies. The gap between these findings is known as \"missing heritability.\" In the study, analysis of WGS data fully captures heritability for 25 of the 34 selected traits. This includes traits associated with clinical indicators like blood pressure and cholesterol levels as well as physical characteristics like waist-to-height ratio.\n \"Quantifying the relative contribution of rare and common variants behind this heritability gap gives researchers better stra...