# Developing the genetics-enhanced model to derive personalized reference ranges for bone density

> **NIH NIH P20** · UNIVERSITY OF NEVADA LAS VEGAS · 2020 · $265,620

## Abstract

ABSTRACT: RESEARCH PROJECT 2 
Clinical reference ranges are typically derived from limited samples, using simplistic statistics. These traditional 
reference ranges do not take into account the normal variability in genes, environment, and other 
characteristics. This “one-size-fits-all” approach has been found to cause misdiagnosis and, in some cases, 
death. Our long-term goal is to develop innovative methodologies to generate a new generation of 
personalized reference ranges. The reference ranges for bone mineral density (BMD) have become 
increasingly controversial, primarily due to the fact that a majority of patients who sustain fragility fractures are 
shown to have a normal BMD value, defined by the commonplace T-score method. This is mainly because the 
T-score method was based on the "one size fits all” paradigm, without taking into account normal variability in 
individual genomic makeup and other characteristics. Genetic factors contribute more than 60% of BMD 
variation. With human longevity on the rise, increased osteoporotic fractures are becoming a major public 
health problem. The objective of this application is to develop an innovative method to derive personalized 
BMD reference ranges for Caucasian women, the group with the highest risk of osteoporotic fracture. On the 
basis of preliminary data produced by the applicant, the central hypothesis of this application is that the 
genetics-enhanced method will be a significantly better predictor of osteoporotic fracture than the T-score 
method and prior model-based methods lacking a genetic component. This hypothesis will be tested by 
pursuing three specific aims: 1) determine the contribution of genetic factors to normal BMD variation in 
Caucasian women; 2) Develop a novel genetics-enhanced method for deriving personalized reference ranges; 
and 3) validate the genetics-enhanced method in cohort data. For Aim 1, this project will leverage existing 
genomic data and findings to conduct an updated meta-analysis. We will identify the best subset of single 
nucleotide polymorphisms (SNPs) and genetic loading scores in predicting normal BMD variation. For Aim 2, 
existing dbGaP data that include large samples of healthy Caucasian women will be used to develop the best- 
performing genetics-enhanced model, which can produce a personalized threshold of BMD for each individual. 
Under Aim 3, Women's Health Initiative data will be utilized to validate the genetics-enhanced method by 
comparing its predictive accuracy for fracture with existing methods. This innovative method will replace the 
traditional, one-size-fits-all approach, fundamentally shifting current research and clinical practice paradigms 
from one static cutoff point for everyone to a personalized threshold that accounts for individual genomic 
makeup and other characteristics. The proposed research will provide personalized BMD reference ranges 
and, as such, is expected to significantly increase the accuracy of oste...

## Key facts

- **NIH application ID:** 9969560
- **Project number:** 5P20GM121325-03
- **Recipient organization:** UNIVERSITY OF NEVADA LAS VEGAS
- **Principal Investigator:** Qing Wu
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $265,620
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9969560

## Citation

> US National Institutes of Health, RePORTER application 9969560, Developing the genetics-enhanced model to derive personalized reference ranges for bone density (5P20GM121325-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9969560. Licensed CC0.

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