# Developing new methods for early detection of Sjogren's syndrome

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2020 · $399,251

## Abstract

Sjogren's syndrome (SS) is a chronic, debilitating, potentially life-threatening autoimmune disorder that
causes irreversible damage to the lacrimal and salivary glands resulting in a loss of tear and saliva production,
severely impairing quality of life. SS affects an estimated 2 to 4 million Americans, with as many as 50% of
individuals with SS remaining undiagnosed and delays of diagnosis of up to 7 years from the initial onset of
symptoms. Early diagnosis of SS is critical to enable early treatment and surveillance for serious
complications such as lymphoma. Dry eye disease, or keratoconjunctivitis sicca (KCS), is highly prevalent in
the general population and is one of the key features of SS, preceding the systemic findings of SS by an
average of 10 years. Approximately 11% of dry eye patients presenting to an eye care professional have
underlying SS. However, because the diagnostic work-up for SS involves collaboration among multiple
specialists, is time-consuming and expensive, it is not feasible to work-up all KCS patients for SS. Because
SS patients often first seek care for dry eye, ophthalmologists have a unique opportunity to screen patients for
SS but are severely hampered by a lack of evidence-based, accurate screening tools. The objective of this
proposal is to develop and validate a new clinical prediction model for detecting SS, and to increase
our understanding of the important relationship between KCS and SS. We propose to leverage clinical
data and biospecimens from the National Institute of Health (NIH)-sponsored Sjogren's International Clinical
Collaborative Alliance (SICCA) study, in order to gain deeper insight into the characteristics of different
subgroups of KCS patients with or without SS. Our overall hypothesis is that the SICCA data and
biospecimens can be used to develop an effective screening tool for dry eye patients to distinguish patients
with KCS-only from those with SS. Moreover, we hypothesize that the assessment of novel serum antibodies
[SP-1 (salivary gland protein-1), CA-6 (carbonic anhydrase-6), and PSP (parotid secretory protein)] will
improve the accuracy of the tool (9). We will evaluate these hypotheses with 3 specific aims:
 Aim 1: Determine if novel candidate SS antibody status distinguishes KCS subjects without SS from
 those with SS, and predicts conversion of KCS patients to SS;
 Aim 2: Develop a clinical prediction model using symptoms (extra-ocular and ocular), ocular signs, and
 novel antibody status for distinguishing KCS patients without SS from those with SS;
 Aim 3: Validate the clinical prediction model in a new cohort of KCS patients.
We anticipate that our new screening tool will shift the current clinical paradigm by allowing ophthalmologists to
efficiently identify and refer dry eye patients with a high likelihood of having SS. We will also establish a new
dry eye cohort and biospecimen bank for future studies. Our overall goal is to reduce the long delays in the
diagnosis of SS that...

## Key facts

- **NIH application ID:** 9996710
- **Project number:** 5R01EY026972-05
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Vatinee Y Bunya
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $399,251
- **Award type:** 5
- **Project period:** 2016-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9996710

## Citation

> US National Institutes of Health, RePORTER application 9996710, Developing new methods for early detection of Sjogren's syndrome (5R01EY026972-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9996710. Licensed CC0.

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