Chlamydia trachomatis infections and subfertility: Opportunities to translate host pathogen genomic data into public health

J. A. Lal, J. Malogajski, S. P. Verweij, P. De Boer, E. Ambrosino, A. Brand, S. Ouburg, S. A. Morré

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Chlamydia trachomatis (CT) infections in women can result in tubal pathology (TP). Worldwide 10-15% of all couples are subfertile, meaning they did not get pregnant after 1 year. Part of the routine subfertility diagnostics is the Chlamydia Antibody Test (CAT) to decide for laparoscopy or not in order to diagnose TP. The CAT positive and negative predictive value is such that many unneeded laparoscopies are done and many TP cases are missed. Addition of host genetic markers related to infection susceptibility and severity could potentially improve the clinical management of couples who suffer from subfertility. In the present study, the potential translational and clinical value of adding diagnostic host genetic marker profiles on the basis of infection and inflammation to the current clinical management of subfertility was investigated. This review provides an overview of the current state of the art of host genetic markers in relation to CT infection, proposes a new clinical diagnostic approach, and investigates how the Learning-Adapting-Leveling model (LAL, a public health genomic (PHG) model) can be of value and provide insight to see whether these host genetic markers can be translated into public health. This review shows that the preliminary basis of adding host genetic marker profiles to the current diagnostic procedures of subfertility is present but has to be further developed before implementation into health care can be achieved. CT infection is an example in the field of PHG with potential diagnostic to be taken up in the future in the field of subfertility diagnosis with a time line for integration to be dependent on enhanced participation of many stakeholders in the field of PHG which could be advanced through the LAL model.

Original languageEnglish
Pages (from-to)50-61
Number of pages12
JournalPublic Health Genomics
Issue number1-2
Publication statusPublished - 03-2013

All Science Journal Classification (ASJC) codes

  • Genetics(clinical)
  • Public Health, Environmental and Occupational Health


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