{
  "abstract": "The discovery by J. Dausset in 1958 (Nobel Prize in 1980) of the Human Leukocyte Antigens (HLA) system enabled organ transplantation by facilitating the matching of the donor's immune system with that of the recipient. Although crucial for transplantation, this discovery highlights a broader, often under-explored potential of the genetic characteristics of the immune system. digitHLA is a software tool designed to assist in the detailed analysis of a patient's HLA haplotype, whether for confirming a diagnosis or generating hypotheses regarding comorbidities (predictive diagnosis). It integrates most of the available data on links between HLA alleles and pathologies. digitHLA's proposals incorporate the patient's immune system genetics (HLA haplotype), epigenetic aspects through a daily lifestyle questionnaire, and medical history. It is capable of defining sensitivity to various predisposing terrains (celiac, psoriatic, xenobiotic), identifying molecular mimicry with regard to heavy metals, various species of viruses (RNA and DNA) as well as bacterial species. digitHLA thus enables precise determination of the patient's reactive mode and therefore prediction of possible pathological evolution among three major classes: dysimmune, cardiovascular and neurodegenerative, tumoral and hematological. digitHLA has been assisting a small number of physicians for three years now, making it de facto one of the earliest tools in personalized medicine. Wider adoption could significantly contribute to advancing personalized medicine and improving patient outcomes.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "Claude Touzet"
    },
    {
      "name": "Tadeusz Nawrocki"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8xw2ct9k2vjvh.bib",
  "cited_by": 0,
  "doi": null,
  "fulltext_url": null,
  "id": "8xw2ct9k2vjvh",
  "issns": [],
  "landing_url": "https://hal.science/hal-05715860v1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.sdv"
    ],
    [
      "hal",
      "1.sdv.imm"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://hal.science/hal-05715860/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8xw2ct9k2vjvh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:21Z",
      "native_id": "hal-05715860",
      "source": "hal",
      "url": "https://hal.science/hal-05715860v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "hal:1.sdv.imm",
      "subfield": "immunology"
    }
  ],
  "title": "digitHLA: an expert system tool that helps to analyze the comorbidities associated to the HLA haplotypes",
  "title_text": "digitHLA: an expert system tool that helps to analyze the comorbidities associated to the HLA haplotypes",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:21Z",
  "url": "https://research.draconitic.com/paper/8xw2ct9k2vjvh",
  "venue": "HAL",
  "versions": []
}