# Polygenic prediction of common, complex diseases

> **NIH NIH K08** · MASSACHUSETTS GENERAL HOSPITAL · 2021 · $264,552

## Abstract

PROJECT SUMMARY
Candidate. Amit V. Khera, MD MSc is a board-certified physician in internal medicine and cardiology at
Massachusetts General Hospital (MGH), an Instructor in Medicine at Harvard Medical School (HMS), and an
affiliated researcher at the Broad Institute of Harvard/MIT. He has a track record of scientific commitment and
productivity at each phase of training and has 11 first-author original research articles. He seeks to expand
upon previous training in clinical medicine and epidemiology to catalyze a career within genomic medicine.
Mentorship, Training Activities, and Environment. Dr. Khera will perform the proposed work at MGH and
the Broad under the primary mentorship of Dr. Sekar Kathiresan, a physician scientist and international leader
in complex trait genetics with an outstanding track record for mentorship. Co-Mentor Dr. Mark Daly will provide
complementary expertise in statistical genetics and mapping human disease loci. This mentorship team will be
complemented by a highly committed and accomplished Advisory Committee of Drs. Benjamin Neale, Nilanjan
Chatterjee, Heidi Rehm, and Daniel MacArthur. Formal coursework will enhance a multi-disciplinary
experiential learning effort to gain requisite skills in clinical informatics, statistical genetics, computational
biology, and responsible research conduct. Research. For any individual, inherited risk can be driven by a
rare, large-effect mutation or the cumulative impact of many common, small-effect genetic variants (`polygenic
risk'). This polygenic risk accounts for a significant proportion of heritability across a range of complex traits
and diseases. However, the optimal approach to constructing such a score, the transferability across
racial/ethnic groups, incremental value in risk prediction, and extent to which polygenic risk is modified by
genetic or non-genetic factors remain uncertain. The PI will first implement several computational algorithms to
derive polygenic scores for coronary artery disease, determine the best score in an independent testing
dataset, and assess the predictive capacity in cohorts of >400,000 multiethnic individuals. Second, he will
generalize this approach to at least 8 additional heritable diseases and determine the extent to which these
scores enhance risk prediction beyond traditional risk factors and family history in >400,000 individuals with
genotyping array or whole genome sequencing data available. Third, he will determine how rare, large effect
mutations and environmental factors interact with polygenic risk for disease to influence disease penetrance.
Successful completion of the proposed studies will lay the scientific foundation for the systematic assessment
of polygenic risk for a range of common diseases and the ultimate disclosure of this risk to individuals and their
health care providers to facilitate disease prevention. Furthermore, the proposal will provide key training of the
PI in several domains (statistical genetics, comp...

## Key facts

- **NIH application ID:** 10232248
- **Project number:** 5K08HG010155-04
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Amit Vikram Khera
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $264,552
- **Award type:** 5
- **Project period:** 2018-09-20 → 2022-04-04

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10232248

## Citation

> US National Institutes of Health, RePORTER application 10232248, Polygenic prediction of common, complex diseases (5K08HG010155-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10232248. Licensed CC0.

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