# The Genetic Architecture of Human Facial Morphology

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $172,218

## Abstract

ABSTRACT
As the sharing of large-scale medical image datasets becomes more common, the importance of respecting
individual preferences while protecting privacy and security has moved to the forefront. The NIDCR has a
particular interest in addressing these concerns, because their funded research portfolio includes projects that
collect facial image datasets. The human face is inherently identifiable and recent work has shown that, under
limited circumstances, individuals can be reidentified even from seemingly anonymous MR images. In many
cases, facial image datasets are connected to genomic or other health data (e.g. FaceBase). This trend is
likely to expand considerably as research facilitated by apps and devices will enable selfies and other facial
images to become new “health resources.” Moreover, the way in which biometric data is protected varies
widely from state to state, making a uniform research participant understanding and experience challenging. It
is therefore critical to understand the perspectives of the US public and research professionals as well as the
current and emerging state of relevant biometric data protection policies. The proposed supplement was
designed to be responsive to NIDCR’s stated focus on “Privacy, confidentiality, data re-use and other ethical
issues with clinical and non-clinical data, particularly large scale facial image data and omics data.” ELSI
research on this topic is currently lacking. Accordingly, the overarching goal of this supplement is to assess
awareness, attitudes, and concerns specifically related to facial imaging research and investigate data privacy
and governance issues relevant to datasets containing facial images. We will accomplish this goal though the
following three aims: (1) To assess the status of biometric data protections for facial imaging throughout the
United States through legal mapping. (2) To explore facial imaging privacy perspectives held by the public and
research professionals in the United States through online surveys. (3) To promote improved informed consent
approaches and responsible data stewardship for research involving facial imaging through preparation of
discussion draft guidance for use in future ELSI Research. We expect that the data generated from this
proposal will inform data governance guidelines and hopefully improve the informed consent process for
research involving facial imaging.

## Key facts

- **NIH application ID:** 10125311
- **Project number:** 3R01DE027023-04S1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Peter Claes
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $172,218
- **Award type:** 3
- **Project period:** 2020-08-06 → 2021-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10125311

## Citation

> US National Institutes of Health, RePORTER application 10125311, The Genetic Architecture of Human Facial Morphology (3R01DE027023-04S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10125311. Licensed CC0.

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