# Data Analysis Core for the Dietary Biomarkers Development Center at Harvard University

> **NIH NIH U2C** · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · 2024 · $267,856

## Abstract

ABSTRACT/SUMMARY – DATA ANALYSIS CORE
The Data Analysis Core (DAC) aims to provide statistical expertise and programming support via a
transdisciplinary approach during the design and implementation of the Biomarkers Project (BP). The DAC will
actively participate in the BP and other Core activities, while maximizing the efficiency, avoiding duplication of
efforts, and improving the synergy among the Dietary Biomarker Development Center (DBDC) at Harvard
University. The DAC will participate in the consortium-wide planning activities and provide consultations in
developing common strategies and protocols for the dietary intervention. The DAC will work with the other
DBDCs and Data Coordinating Center (DCC) in determining the final statistical analytical strategies for the
biomarker analysis and performance. The specific aims are: Aim 1: To develop and implement methods for
biomarker discovery and validation across all stages of the Biomarkers Project. We will devise data analysis
strategies for comparing the dietary biomarker performance against the dietary intake assessment data and
benchmark biomarker data in an existing dietary feeding trial and several cohort studies with multi-ethnic
samples. Aim 2: To develop common statistical analytical strategies for the biomarker analysis and
performance applicable across different DBDCs. This Core will work with other DBDCs and the DCC in
determining the final design and analytical strategies for the biomarker analysis and performance evaluation.
Aim 3: To manage and maintain large datasets and ensure timely data sharing and submission to the DCC.
This DAC will be responsible for managing the data entry, cleaning and analyzing the data generated by our
DBDC. The DAC will work together with other DBDCs and DCC to harmonize data across platforms,
standardize data management, QC, and analytic methods across DBDCs. Aim 4: To interface nutrition,
epidemiology, bioinformatics/biostatistics, and metabolomics, and ensure that cutting-edge measurement error
correction models and multi-omics integrations are incorporated into future nutritional epidemiologic studies of
disease outcomes. Whenever appropriate, all analyses will assess specific effects by sex and across different
racial/ethnic groups. As part of the transdisciplinary team of the DBDC at Harvard University, the DAC will
develop and curate calibrated biomarkers, refined clinical phenotypes and summary statistics for use in future
epidemiological analyses of food intake and prospective associations with disease incidence and other clinical
phenotypes of interest, allowing measurement error corrections and further integration with multi-omics
datasets, such as gut microbiota and genome-wide association studies in existing large cohort studies at
Harvard.

## Key facts

- **NIH application ID:** 10898083
- **Project number:** 5U2CDK129670-04
- **Recipient organization:** HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH
- **Principal Investigator:** Liming Liang
- **Activity code:** U2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $267,856
- **Award type:** 5
- **Project period:** 2021-08-16 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10898083

## Citation

> US National Institutes of Health, RePORTER application 10898083, Data Analysis Core for the Dietary Biomarkers Development Center at Harvard University (5U2CDK129670-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10898083. Licensed CC0.

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