{
  "abstract": "BACKGROUND: Cardiovascular disease is a major cause of death in individuals with chronic kidney disease; thus, improving its prediction is critical for cardiovascular disease risk reduction. Studies have not assessed whether a polygenic risk score (PRS) of coronary heart disease (CHD) developed from genetic studies in the general population can improve cardiovascular disease risk prediction in individuals with chronic kidney disease, especially when PRS is added to the American Heart Association Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations. METHODS: Focusing on a 10-year composite CHD event, we applied PRSs of CHD obtained from the polygenic score catalog to the multi-center CRIC (Chronic Renal Insufficiency Cohort) participants, selected the best-performing PRS and evaluated the added value of the best PRS while accounting for PREVENT linear predictors. Three Cox proportional hazard models were fitted with PRS only, PREVENT predictors only, and PRS+PREVENT risk factors. We evaluated the prediction accuracy, discrimination, and calibration of the combined model compared with the PREVENT model. RESULTS: ). The PRS+PREVENT model demonstrated a higher area under the curve (72.4% [95% CI, 0.66-0.79] versus 70.8% [95% CI, 0.64-0.77]), better discrimination ability, and improved calibration compared with the PREVENT model predictors. Individuals were more correctly classified in prediction quartiles using the PRS+PREVENT model for the 10-year CHD event proportions. CONCLUSIONS: Our results demonstrate the added value of a CHD PRS to the PREVENT risk prediction models in individuals with chronic kidney disease. The combined PRS+PREVENT model has the potential to improve clinical decisions on disease prevention and treatment strategies.",
  "abstract_shown": true,
  "affiliations": [
    "Dept of Biostatistics, Univ of North Carolina at Chapel Hill, Chapel Hill, NC",
    "Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Univ of Pennsylvania, Philadelphia, PA",
    "Dept of Pathology and Laboratory Medicine, Univ of Pennsylvania, Philadelphia, PA",
    "Dept of Epidemiology, Univ of North Carolina at Chapel Hill, Chapel Hill, NC",
    "Dept of Genetics, Univ of North Carolina at Chapel Hill, Chapel Hill, NC",
    "College of Medicine, Division of Nephrology, Univ of Illinois at Chicago, Chicago, IL",
    "Division of Research, Kaiser Permanente Northern California, Oakland, CA; Depts of Epidemiology, Biostatistics and Medicine, Univ of California San Francisco, San Francisco, CA",
    "Dept of Medicine, Division of Nephrology, Univ of Michigan, Ann Arbor, Ann Arbor, MI",
    "Dept of Medicine, Case Western Reserve Univ, Cleveland, OH",
    "Dept of Internal Medicine, UT Southwestern Medical Center, Dallas, TX"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Quan Sun"
    },
    {
      "affs": [
        3
      ],
      "name": "Amarnath Marthi"
    },
    {
      "affs": [
        4
      ],
      "name": "Jia Wen"
    },
    {
      "affs": [
        0,
        3
      ],
      "name": "Bridget M. Lin"
    },
    {
      "affs": [
        0
      ],
      "name": "Jiawen Du"
    },
    {
      "affs": [
        5
      ],
      "name": "Ana C. Ricardo"
    },
    {
      "affs": [
        6
      ],
      "name": "Alan S. Go"
    },
    {
      "affs": [
        7
      ],
      "name": "Panduranga S. Rao"
    },
    {
      "affs": [
        8
      ],
      "name": "Mahboob Rahman"
    },
    {
      "affs": [
        9
      ],
      "name": "Jiang He"
    },
    {
      "affs": [
        0,
        4
      ],
      "name": "Yun Li"
    },
    {
      "affs": [
        3
      ],
      "name": "Nora Franceschini"
    },
    {
      "name": "the CRIC Study Investigators"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/29p82vdpaek13.bib",
  "cited_by": 0,
  "doi": "10.1161/circgen.126.005684",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13714751/",
  "id": "29p82vdpaek13",
  "issns": [
    "2574-8300"
  ],
  "landing_url": "https://doi.org/10.1161/circgen.126.005684",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "1311|Genetic Associations and Epidemiology"
    ]
  ],
  "openalex": "W7214912081",
  "pdf_url": null,
  "pmcid": "PMC13714751",
  "pmid": "42813274",
  "published": "2026-09-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/29p82vdpaek13.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:22:11Z",
      "native_id": "PMC13714751",
      "source": "pmc",
      "url": "https://doi.org/10.1161/circgen.126.005684"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1311|Genetic Associations and Epidemiology",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Polygenic Risk Scores of Coronary Heart Disease in Chronic Kidney Disease Population: The CRIC Study",
  "title_text": "Polygenic Risk Scores of Coronary Heart Disease in Chronic Kidney Disease Population: The CRIC Study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:22:11Z",
  "url": "https://research.draconitic.com/paper/29p82vdpaek13",
  "venue": "Circulation. Genomic and precision medicine",
  "versions": []
}