Prioritizing Genetics to Reduce Existing Health Disparities
to
Nancy J. Cox, Ph.D.
Director, Vanderbilt Genetics Institute
Director, Division of Genetic Medicine
Mary Phillips Edmonds Gray Professor of Genetics
Vanderbilt University, Vanderbilt Brain Institute
Nancy Cox is a quantitative human geneticist with a long-standing research program in identifying and characterizing the genetic component to common human diseases; current research is focused on large-scale integration of genomic with other “-omics” data as well as biobank and electronic medical records data.
https://videocast.nih.gov/watch=51127
Summary
Physicians rely on a variety of commonly used laboratory measurements to understand when patients are beginning to develop disease and how they are responding to disease therapies. Many of these measurements have a quite dynamic component, changing reliably as disease develops and progresses and in response to therapies. However, most laboratory values are also heritable, and a substantial fraction (about 30%) are highly heritable; about half of all heritable labs have significant differences in means and/or variances across continental genetic ancestries. For a minority of these heritable labs, the heritability is a big part of why the biomarker is useful in medicine; for, example, both genetically predicted LDL cholesterol, and its non-genetic residual are predictive of cardiovascular disease risk because high LDL is in the causal pathway for atherosclerosis and myocardial infarction — regardless of whether LDL is high because of genetic or non-genetic factors. But for a surprising fraction of the biomarkers used commonly in medicine, the genetic component to the laboratory value is not predictive of the outcomes for which we use the measure. In these cases, not only is the genetic variability of the laboratory value adding noise to medical assessment, but will also frequently mislead physicians to over or undertreat patients. Because most laboratory reference ranges were developed decades ago in what we would now consider to be quite small samples of white men, the heritability and population differentiation in lab values has led to a variety of institutionalized health disparities that need immediate attention. We cannot help creating new kinds of health disparities as we bring genomic science into medicine because of the inequality of access to expensive technologies, and the historic failure to have included sufficiently diverse populations in genome studies. But we can use genetics now to eliminate institutionalized health disparities that have arisen through the misunderstanding of laboratory values and improve both healthcare overall as well as health equity.
Learning Objectives:
A) Understand how heritability can affect interpretation of laboratory values in medicine
B) Understand why the heritability of lab values disproportionately affects healthcare in diverse populations, leading to institutionalized health disparities
C) Understand alternative approaches for correcting laboratory values: i. genetically corrected laboratory values, or ii. individualized reference ranges
This page was last updated on Thursday, February 1, 2024