# Familial hypercholesterolemia screening in children: population impact of phenotype, genotype, and cascade approaches

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2021 · $788,885

## Abstract

Project Summary
 Familial hypercholesterolemia (FH) is a common genetic disorder, affecting every 200-1000 people,
depending on the population and diagnostic criteria. FH leads to lifetime raised low-density lipoprotein (LDL)
cholesterol, a high risk for premature atherosclerosis and downstream coronary heart disease. FH is
designated as Tier 1 disease by the Center for Disease Control and Prevention, notably one of only three such
diseases, because it is common, is associated with a high risk of premature illness, and is treatable with
lifestyle or medications. Great uncertainty exists about the optimal approach to FH screening, which is
reflected in conflicting recommendations in national screening guidelines.
 We propose to synthesize high quality data from national surveys and population-based cohort
studies in a health policy computer simulation model comparing the health and economic value of
different FH screening strategies. This study will prioritize the optimal approaches to FH screening in the
U.S. population, identifying optimal initial screening age and defining the role of genetic testing in screening.
 We have assembled a team of experts in pediatric preventive cardiology, decision analysis, cardiovascular
disease epidemiology, population genetics, biostatistics, health economic evaluation, and computer simulation
modeling in order to evaluate and compare different FH screening strategies in children and adults. We aim to
use this expertise and these methods in order to:
  Quantify diagnostic yield, clinical effectiveness, and economic value of universal FH phenotype
 screening in childhood or adulthood, and the added value of FH genotype screening
  Compare universal FH screening to the alternatives of using family history or a Big Data-based
 algorithm to direct targeted screening limited to children and adults with possible FH diagnosis
  Quantify the health and economic value of cascade screening families of FH cases
 We hypothesize that FH screening in childhood will be the highest value screening strategy in the U.S.
population, and that genetic testing will improve diagnosis and treatment decisions most in cases of diagnostic
uncertainty (e.g., borderline high cholesterol or absent family history). We hypothesize that a machine-learning
algorithm will avoid the costs and complexity of universal screening, while yielding a similar case yield, as long
as cholesterol testing is sufficiently common in children.
 This study will identify the optimal approach to FH screening in the U.S. population and the most
influential data based on current knowledge and set the stage for efficiently designed clinical trials of FH
screening. This study will be a test case for the concept of a “precision” population health approach to
screening for genetically-determined diseases in the general population.

## Key facts

- **NIH application ID:** 10152666
- **Project number:** 5R01HL141823-03
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Sarah D DE FERRANTI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $788,885
- **Award type:** 5
- **Project period:** 2019-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10152666

## Citation

> US National Institutes of Health, RePORTER application 10152666, Familial hypercholesterolemia screening in children: population impact of phenotype, genotype, and cascade approaches (5R01HL141823-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10152666. Licensed CC0.

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