Genomics and Microbiome Investigation in Cases of Recurrent Pregnancy Losses

NCT ID: NCT06604338

Last Updated: 2024-09-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

20 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-04-14

Study Completion Date

2025-12-31

Brief Summary

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Recurrent pregnancy losses (RPL) are characterized by the occurrence of more than one spontaneous pregnancy loss. It is caused by different known factors, but about half of the cases remain without an explanation. Efforts are being done in the scientific community to solve this cases. In this study, the investigators aim to investigate genetic factors that might predispose to RPL, as well as the influence of the uterine microbiota (microorganisms that normally live in the uterus of women).

Detailed Description

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Recurrent pregnancy losses (RPL) are adverse reproductive outcomes characterized by the occurrence of more than one spontaneous pregnancy loss. It is estimated that RPL occurs in 1 to 5% of couples in reproductive period and is caused by different known factors. Despite this, around half of the cases remain without a defined etiology. In this context, efforts are being done in the scientific community to elucidate idiopathic cases. Among them, robust genomic investigations, such as exome sequencing, stand out for maximizing the chances of identifying causative gene variants rather than a gene-specific approach. Another front of study to understand the factors that modulate complex etiology conditions such RPL is the characterization of the microbiota of different anatomical sites. Each human anatomical site presents a distinct microbiota selected through a long co-evolutionary process and its individual and pathological variability can lead to functional repercussions. Therefore, the aim of this study is to investigate factors predisposing to recurrent pregnancy loss through a genomic evaluation and characterization of the uterine microbiota of patients affected by RPL. To achieve this, two approaches will be conducted: a genomic approach, where the exome of women with RPL will be analyzed and compared with population genomic databases; and a etagenomic approach, where the characterization of the uterine microbiota of women with RPL will be performed and compared with that of fertile women. Using the data produced in this study, the investigators hope to be able to understand more broadly how the genome influences the predisposition to RPL and how changes in certain marker genes can lead to an increased risk for the occurrence of this reproductive condition. Furthermore, based on analyzes of the uterine microbiota, the investigators hope to be able to understand how the variability of microorganisms present in this organ acts during pregnancy, especially in cases of RPL. The results of the investigations proposed in this project will help to understand the predisposing factors to RPL and may lead to the development of new investigative approaches, such as the design of genetic panels and analyzes of the uterine microbiota, which may have an impact on the clinical management of the condition in the future.

Conditions

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Recurrent Pregnancy Loss(RPL)

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

RETROSPECTIVE

Study Groups

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RPL group

The RPL group will include women with a history of at least two spontaneous pregnancy losses, regardless of whether they have living children, and whose etiology for the pregnancy losses was not determined by the care team's protocols.

Exome test

Intervention Type DIAGNOSTIC_TEST

An exome will be performed on the participants of RPL group.

Microbiota analysis

Intervention Type DIAGNOSTIC_TEST

A cervical microbiota analysis will be performed in the RPL and control groups.

Control group

Women with at least two full-term pregnancies and no history of difficulty getting pregnant, pregnancy loss or other infertility factors will be enrolled in the control group.

Microbiota analysis

Intervention Type DIAGNOSTIC_TEST

A cervical microbiota analysis will be performed in the RPL and control groups.

Interventions

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Exome test

An exome will be performed on the participants of RPL group.

Intervention Type DIAGNOSTIC_TEST

Microbiota analysis

A cervical microbiota analysis will be performed in the RPL and control groups.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* RPL group: history of at least two spontaneous pregnancy losses, regardless of whether they have living children, and whose etiology for the pregnancy losses was not determined by the care team\'s protocols;
* Control group: at least two full-term pregnancies and no history of difficulty getting pregnant, pregnancy loss or other infertility factors.

Exclusion Criteria

* RPL group: less than two spontaneous pregnancy losses and those with a known cause for repeated pregnancy losses;
* Control group: N/A
Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL (UFRGS)

UNKNOWN

Sponsor Role collaborator

Hospital de Clinicas de Porto Alegre

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Lucas Rosa Fraga, PhD, Professor

Role: PRINCIPAL_INVESTIGATOR

Hospital de Clínicas de Porto Alegre

Locations

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Hospital de Clínicas de Porto Alegre (HCPA)

Porto Alegre, Rio Grande do Sul, Brazil

Site Status RECRUITING

Countries

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Brazil

Central Contacts

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Lucas Rosa Fraga, PhD, Professor

Role: CONTACT

+555133597661

Luiza Pretto, PhD Student

Role: CONTACT

+555133597661

Facility Contacts

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Lucas Rosa Fraga, PhD, Professor

Role: primary

+555133597661

Luiza Pretto, PhD Student

Role: backup

+555133597661

Lucas Rosa Fraga, PhD, Professor

Role: backup

Other Identifiers

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5364132100005327

Identifier Type: OTHER

Identifier Source: secondary_id

20210575

Identifier Type: -

Identifier Source: org_study_id

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