---
title: "Identify Microbiome Biomarkers in Neonatal Obstruction – Case Study – Biomcare"
description: "Researchers at Johns Hopkins Hospital are working to uncover better diagnostic methods for children at risk of urinary tract obstructions and potential kidney damage. As part of this research, tissue and fluid samples were collected using neonatal animal models."
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3.  Neonatal Obstruction Biomarkers 

Life Science & Animals

# Identify Microbiome Biomarkers in Neonatal Obstruction

Client:  Johns Hopkins Hospital 

Services used: 

Bioinformatics & Statistics

Study & Trial Support

Microbiome Profiling

## Problem

Researchers at Johns Hopkins Hospital are working to uncover better diagnostic methods for children at risk of urinary tract obstructions and potential kidney damage. As part of this research, tissue and fluid samples were collected using neonatal animal models. The goal was to investigate microbiome changes associated with urinary tract obstruction and identify microbial biomarkers that could potentially contribute to the development of prognostic tools.

## Question

Could microbiome changes associated with urinary tract obstruction be detected and used to identify microbial biomarkers for future prognostic tools?

## What we did

Biomcare supported the project through microbiome sequencing and data analysis. The work included analysing microbiome data derived from the collected tissue and fluid samples. The study also highlighted the importance of integrating complementary methods such as qPCR or spike-in controls with sequencing projects in order to estimate absolute microbial abundance.

## Insight

Using microbiome sequencing data, it was possible to investigate microbial associations with urinary tract obstruction. It also emphasised the role of absolute microbial abundance measurements in interpreting microbiome data.

## Value

The project showed how microbiome sequencing can add decision-relevant insight to translational disease research when the study setup, sample handling, and data analysis are aligned with the research question. The resulting data became part of the broader effort to identify microbial biomarkers linked to urinary tract obstruction and to support development of future prognostic approaches. It also clarified methodological requirements that can strengthen follow-up studies and improve the practical value of microbiome data in similar projects.

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