Medically actionable pathogenic variants in a population of 13,131 healthy elderly individuals



To measure the prevalence of medically actionable pathogenic variants (PVs) among a population of healthy elderly individuals.


We used targeted sequencing to detect pathogenic or likely pathogenic variants in 55 genes associated with autosomal dominant medically actionable conditions, among a population of 13,131 individuals aged 70 or older (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) trial. Participants had no previous diagnosis or current symptoms of cardiovascular disease, physical disability or dementia, and no current diagnosis of life-threatening cancer. Variant curation followed American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) standards.


One in 75 (1.3%) healthy elderly individuals carried a PV. This was lower than rates reported from population-based studies, which have ranged from 1.8% to 3.4%. We detected 20 PV carriers for Lynch syndrome (MSH6/MLH1/MSH2/PMS2) and 13 for familial hypercholesterolemia (LDLR/APOB/PCSK9). Among 7056 female participants, we detected 15 BRCA1/BRCA2 PV carriers (1 in 470 females). We detected 86 carriers of PVs in lower-penetrance genes associated with inherited cardiac disorders.


Medically actionable PVs are carried in a healthy elderly population. Our findings raise questions about the actionability of lower-penetrance genes, especially when PVs are detected in the absence of symptoms and/or family history of disease.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Data and code availability

Data and code can be provided upon reasonable request from the corresponding author.


  1. 1.

    Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19:249–255.

    Article  Google Scholar 

  2. 2.

    Directors ABO. The use of ACMG secondary findings recommendations for general population screening: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2019;21:1467–1468.

    Article  Google Scholar 

  3. 3.

    Linderman MD, Nielsen DE, Green RC. Personal genome sequencing in ostensibly healthy individuals and the PeopleSeq Consortium. J Pers Med. 2016;6:14.

    Article  Google Scholar 

  4. 4.

    Schwartz MLB, McCormick CZ, Lazzeri AL, Lindbuchler DM, Hallquist MLG, Manickam K, et al. A model for genome-first care: returning secondary genomic findings to participants and their healthcare providers in a large research cohort. Am J Hum Genet. 2018;103:328–337.

    CAS  Article  Google Scholar 

  5. 5.

    Carey DJ, Fetterolf SN, Davis FD, Faucett WA, Kirchner HL, Mirshahi U, et al. The Geisinger MyCode community health initiative: an electronic health record-linked biobank for precision medicine research. Genet Med. 2016;18:906–913.

    Article  Google Scholar 

  6. 6.

    Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, et al. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science. 2016;354:aaf6814.

    Article  Google Scholar 

  7. 7.

    Haer-Wigman L, van der Schoot V, Feenstra I, Vulto-van Silfhout AT, Gilissen C, Brunner HG, et al. 1 in 38 individuals at risk of a dominant medically actionable disease. Eur J Hum Genet. 2019;27:325–330.

    Article  Google Scholar 

  8. 8.

    McNeil JJ, Woods RL, Nelson MR, Reid CM, Kirpach B, Wolfe R, et al. Effect of aspirin on disability-free survival in the healthy elderly. N Engl J Med. 2018;379:1499–1508.

    CAS  Article  Google Scholar 

  9. 9.

    Group AI. Study design of ASPirin in Reducing Events in the Elderly (ASPREE): a randomized, controlled trial. Contemp Clin Trials. 2013;36:555–564.

    Article  Google Scholar 

  10. 10.

    Lockery JE, Collyer TA, Abhayaratna WP, Fitzgerald SM, McNeil JJ, Nelson MR, et al. Recruiting general practice patients for large clinical trials: lessons from the Aspirin in Reducing Events in the Elderly (ASPREE) study. Med J Aust. 2019;210:168–173.

    Article  Google Scholar 

  11. 11.

    McNeil JJ, Woods RL, Nelson MR, Murray AM, Reid CM, Kirpach B, et al. Baseline characteristics of participants in the ASPREE (ASPirin in Reducing Events in the Elderly) study. J Gerontol A Biol Sci Med Sci. 2017;72:1586–1593.

    Article  Google Scholar 

  12. 12.

    Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014;42(Database issue):D980–D985.

    CAS  Article  Google Scholar 

  13. 13.

    Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285–291.

    CAS  Article  Google Scholar 

  14. 14.

    Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–424.

    Article  Google Scholar 

  15. 15.

    Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317:2402–2416.

    CAS  Article  Google Scholar 

  16. 16.

    Moller P, Seppala TT, Bernstein I, Holinski-Feder E, Sala P, Gareth Evans D, et al. Cancer risk and survival in path_MMR carriers by gene and gender up to 75 years of age: a report from the Prospective Lynch Syndrome Database. Gut. 2018;67:1306–1316.

    Article  Google Scholar 

  17. 17.

    Lacaze P, Ryan J, Woods R, Winship I, McNeil J. Pathogenic variants in the healthy elderly: unique ethical and practical challenges. J Med Ethics. 2017;43:714–722.

    Article  Google Scholar 

Download references


Supported by a Flagship cluster grant (including the Commonwealth Scientific and Industrial Research Organisation, Monash University, Menzies Research Institute, Australian National University, University of Melbourne), grants U01AG029824 from the National Institute on Aging and the National Cancer Institute at the National Institutes of Health, by grants 334047 and 1127060 from the National Health and Medical Research Council of Australia, and by Monash University and the Victorian Cancer Agency. We thank the trial staff in Australia and the United States, the participants who volunteered for this trial, and the general practitioners and staff of the medical clinics who cared for the participants.

Author information



Corresponding author

Correspondence to Paul Lacaze PhD.

Ethics declarations


The authors declare no conflicts of interest.

Ethics committee approval

This work was approved by the Alfred Hospital Human Research Ethics Committee (project 390/15) in accordance with the National Statement on Ethical Conduct in Human Research (2007).

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Joint first authors: Paul Lacaze, Robert Sebra

Joint senior authors: Ingrid Winship, John J McNeil, Eric Schadt

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lacaze, P., Sebra, R., Riaz, M. et al. Medically actionable pathogenic variants in a population of 13,131 healthy elderly individuals. Genet Med (2020).

Download citation


  • pathogenic variants
  • medical actionability
  • penetrance
  • genetic testing
  • healthy elderly