Deep Sequencing Test for Intraocular Infections

(OPTICS Trial)

Recruiting in Palo Alto (17 mi)

Overseen by Thuy Doan, MD PhD

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: University of California, San Francisco

Disqualifiers: Pregnancy, Age < 18, others

No Placebo Group

Trial Summary

What is the purpose of this trial?

This is a multi-center randomized controlled evaluator-masked trial designed to compare metagenomic deep sequencing (MDS) versus standard of care testing for improvement of outcomes for intraocular infections. Patients with presumed intraocular infections who meet the eligibility criteria will be randomized to receive MDS testing results or not to receive MDS testing results. All patients will receive standard-of-care testing to guide management. Enrolled patients will be followed at week 2, week 3-6 (randomization visit), and at 4 weeks after the randomization visit. The proportions of patients who received the appropriate therapy and the proportions of patients with improved outcome will be compared between arms. Patient quality of life, MDS performance, and the provider certainly of belief will be collected.

Do I need to stop my current medications for this trial?

The trial protocol does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment Metagenomic Deep Sequencing (MDS) for intraocular infections?

Research shows that Metagenomic Deep Sequencing (MDS) can accurately detect pathogens in eye fluid samples, which helps in diagnosing infections more effectively than traditional methods. ^{1 2 3 4 5}

Is metagenomic deep sequencing safe for humans?

The research articles focus on the effectiveness of metagenomic deep sequencing (mNGS) in diagnosing intraocular infections, but they do not provide specific safety data for humans. However, these studies do not report any safety concerns related to the use of mNGS in humans. ^{1 2 3 6 7}

How does the treatment Metagenomic Deep Sequencing (MDS) differ from other treatments for intraocular infections?

Metagenomic Deep Sequencing (MDS) is unique because it uses advanced genetic sequencing to identify a wide range of pathogens in eye infections, which can be difficult to diagnose with traditional methods. This approach allows for a more accurate and comprehensive detection of bacteria, viruses, fungi, and parasites in intraocular fluid, potentially leading to better-targeted treatments. ^{1 2 3 8 9}

Research Team

Thuy Doan, MD PhD

Principal Investigator

University of California, San Francisco

Eligibility Criteria

This trial is for adults over 18 with suspected infectious uveitis or post-operative endophthalmitis, which are types of eye infections. It's not suitable for those who can't consent, don't have enough specimen for MDS testing, are under 18, or are pregnant.

Inclusion Criteria

I have an eye infection affecting the front, middle, back, or all parts of my eye.

Unilateral or bilateral

I am suspected to have an eye infection after surgery.

Exclusion Criteria

Insufficient specimen for MDS

I am unable to give consent by myself.

I am under 18 years old.

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Randomization and Initial Follow-up

Participants are randomized to receive MDS testing results or not, followed by initial follow-up visits

3-6 weeks

Visits at week 2 and week 3-6

Follow-up

Participants are monitored for safety and effectiveness after randomization

4 weeks

Visit at 4 weeks after randomization

Treatment Details

Interventions

• MDS (Comprehensive Sequencing)
• Standard of Care (SOC) (Diagnostic Test)

Trial Overview The study compares the effectiveness of Metagenomic Deep Sequencing (MDS) to standard tests in improving treatment outcomes for eye infections. Participants will be randomly assigned to either receive MDS test results or not alongside regular care.

Participant Groups

Group I: MDS Experimental Treatment 1 Intervention

Patients enrolled in the trial and randomized to the MDS arm will undergo standard of care testing and MDS testing.

Group II: Standard of Care Active Control 1 Intervention

Patients enrolled in the trial and randomized to the standard of care (SOC) arm will undergo standard of care testing.

Who Is Running the Clinical Trial?

University of California, San Francisco

Lead Sponsor

Trials

2,636

Recruited

19,080,000+

Suresh Gunasekaran

University of California, San Francisco

Chief Executive Officer since 2022

MBA from Southern Methodist University

Dr. Lukejohn Day

University of California, San Francisco

Chief Medical Officer

MD from Stanford University School of Medicine

University of California, Los Angeles

Collaborator

Trials

1,594

Recruited

10,430,000+

Dr. Thomas Rando

University of California, Los Angeles

Chief Medical Officer since 2023

MD from UCLA

Amir Naiberg

University of California, Los Angeles

Chief Executive Officer since 2024

JD from UCLA

University of Utah

Collaborator

Trials

1,169

Recruited

1,623,000+

Jeffrey Wilkins

University of Utah

Chief Medical Officer since 2022

MD from Meharry Medical College

Stephen Tullman

University of Utah

Chief Executive Officer since 2022

BS in Accounting from Rutgers University

University of California, Davis

Collaborator

Trials

958

Recruited

4,816,000+

Rakesh Dixit

University of California, Davis

Chief Executive Officer since 2024

PhD in Biochemistry and Molecular Biology from the University of California, Davis

Suresh Mahabhashyam

University of California, Davis

Chief Medical Officer since 2020

MD from Bangalore Medical College

University of Nebraska

Collaborator

Trials

563

Recruited

1,147,000+

Michael Dixon

University of Nebraska

Chief Executive Officer since 2010

PhD in Molecular Biology

Dr. Makker

University of Nebraska

Chief Medical Officer since 2020

MD from University of Nebraska Medical School

Findings from Research

Unbiased metagenomic deep sequencing (MDS) effectively detected pathogens in intraocular fluid samples from patients with uveitis, accurately identifying known pathogens like Cryptococcus neoformans and Toxoplasma gondii, as well as a previously unknown rubella virus infection in one patient.

The study suggests that MDS can reveal chronic infections in the eye, highlighting its potential as a diagnostic tool for ocular infections that are often difficult to identify, which could improve treatment outcomes and understanding of pathogen reservoirs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens. Doan, T., Wilson, MR., Crawford, ED., et al.[2023]

In a study of 15 patients with suspected intraocular infections, metagenomic next-generation sequencing (mNGS) successfully identified pathogens in 8 samples, confirming its efficacy in diagnosing these infections.

Despite 7 samples returning negative mNGS results, 4 were still diagnosed with intraocular infections through clinical evaluation and other tests, highlighting the need for optimized mNGS protocols to better detect intracellular pathogens.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Application of metagenomic next-generation sequencing in suspected intraocular infections. Qian, Z., Zhang, Y., Wang, L., et al.[2023]

Metagenomic next-generation sequencing (mNGS) identified pathogens in 88.89% of endophthalmitis cases, significantly outperforming traditional culture methods, which only had a positive rate of 27.78%.

mNGS not only detected common pathogens like Staphylococcus epidermidis and Klebsiella pneumoniae but also revealed antibiotic resistance genes in 9 cases, highlighting its potential for improving treatment strategies and understanding visual prognosis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

METAGENOMIC NEXT-GENERATION SEQUENCING DETECTS PATHOGENS IN ENDOPHTHALMITIS PATIENTS. Zhu, J., Xia, H., Tang, R., et al.[2022]

Metagenomic deep sequencing (MDS) was able to identify pathogens in 76% of subjects with infectious keratitis, showing a high diagnostic yield compared to traditional culture methods, which had a 74% agreement with MDS results.

The order of sample collection did not affect the overall yield of MDS; however, collecting MDS samples after other diagnostic tests reduced the agreement with culture results, suggesting potential contamination issues or differences in sensitivity.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Impact of Sample Collection Order on the Diagnostic Performance of Metagenomic Deep Sequencing for Infectious Keratitis. Redd, TK., Lalitha, P., Prajna, NV., et al.[2023]

Nanopore targeted sequencing (NTS) identified pathogens in 89.28% of intraocular fluid samples from 27 patients with endogenous endophthalmitis, significantly outperforming traditional microbial culture, which detected pathogens in only 35.71% of samples (P < 0.001).

NTS provided results much faster, with an average detection time of just 1.11 days compared to 2.50 days for microbial culture, and it was particularly effective in identifying fungal infections, showing a positivity rate of 46.43% versus 7.14% for culture (P = 0.002).

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

IDENTIFICATION OF PATHOGENS IN THE INTRAOCULAR FLUID SAMPLES OF PATIENTS WITH ENDOGENOUS ENDOPHTHALMITIS USING RAPID NANOPORE TARGETED SEQUENCING. Hao, X., Wang, M., Yuan, M., et al.[2023]

The dot hybridization assay (DHA) model allows for effective monitoring of ocular surface microbiota, helping to identify hazardous microorganisms that could lead to endophthalmitis, particularly in male patients undergoing cataract surgery.

The DHA model can detect antibiotic resistance genes, such as mecA, in bacteria that traditional culture methods might miss, enhancing the ability to prevent infections and improve surgical outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Genomic Approach to Investigating Ocular Surface Microorganisms: Monitoring Core Microbiota on Eyelid Margin with a Dot hybridization Assay. Kuo, MT., Chao, TL., Kuo, SF., et al.[2021]

This study highlights the potential of genomics to improve the diagnosis of endophthalmitis by analyzing the microbiome of vitreous fluid from patients, which could lead to better management of this serious eye condition.

By developing a metagenomics workflow and a curated microbial genome database, the researchers were able to accurately identify microorganisms and their antibiotic resistance genes, providing critical information for treating infections effectively.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid. Kirstahler, P., Bjerrum, SS., Friis-Møller, A., et al.[2019]

Metagenomic sequencing successfully identified a variety of microorganisms in 19 vitreous specimens from patients with suspected infectious uveitis, including varicella zoster virus and Candida albicans, demonstrating its efficacy in diagnosing complex infections.

The results from metagenomic sequencing were validated by real-time PCR, confirming its reliability as an alternative diagnostic method for infectious uveitis, which could enhance patient management and treatment outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Identification of pathogens in the vitreous of patients with infectious uveitis by metagenomic sequencing]. Zhang, MX., Peng, XY., Hu, F., et al.[2020]

In a study of 31 patients with secondary glaucoma linked to anterior segment uveitis, viral pathogens were identified in 61.3% of cases using real-time qPCR and WDC evaluation, highlighting the role of viruses like HCMV and VZV in this condition.

Metagenomic deep sequencing (MDS) successfully detected HCMV DNA in three patients, suggesting that MDS could be a valuable tool for diagnosing intraocular viral infections in secondary glaucoma cases.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Comparison of Intraocular Antibody Measurement, Quantitative Pathogen PCR, and Metagenomic Deep Sequencing of Aqueous Humor in Secondary Glaucoma Associated with Anterior Segment Uveitis. Wang, L., Wang, Z., Ma, J., et al.[2022]

References

1. England pubmed.ncbi.nlm.nih.gov

Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

Application of metagenomic next-generation sequencing in suspected intraocular infections. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

METAGENOMIC NEXT-GENERATION SEQUENCING DETECTS PATHOGENS IN ENDOPHTHALMITIS PATIENTS. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Impact of Sample Collection Order on the Diagnostic Performance of Metagenomic Deep Sequencing for Infectious Keratitis. [2023]

5. United States pubmed.ncbi.nlm.nih.gov

IDENTIFICATION OF PATHOGENS IN THE INTRAOCULAR FLUID SAMPLES OF PATIENTS WITH ENDOGENOUS ENDOPHTHALMITIS USING RAPID NANOPORE TARGETED SEQUENCING. [2023]

6. Switzerland pubmed.ncbi.nlm.nih.gov

A Genomic Approach to Investigating Ocular Surface Microorganisms: Monitoring Core Microbiota on Eyelid Margin with a Dot hybridization Assay. [2021]

7. England pubmed.ncbi.nlm.nih.gov

Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid. [2019]

8. China pubmed.ncbi.nlm.nih.gov

[Identification of pathogens in the vitreous of patients with infectious uveitis by metagenomic sequencing]. [2020]

9. England pubmed.ncbi.nlm.nih.gov

Comparison of Intraocular Antibody Measurement, Quantitative Pathogen PCR, and Metagenomic Deep Sequencing of Aqueous Humor in Secondary Glaucoma Associated with Anterior Segment Uveitis. [2022]