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Cited by 70Genetic Associations and EpidemiologyGenomics and Rare DiseasesGenomics and Phylogenetic Studies

The Medical Genome Reference Bank contains whole genome and phenotype data of 2570 healthy elderly

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Pinese, Mark, Lacaze, Paul, Rath, Emma M., Stone, Andrew, Brion, Marie-Jo, Ameur, Adam, Nagpal, Sini, Puttick, Clare +30 more·2020·Nature Communications
DOI 10.1038/s41467-019-14079-0PMC PMC6978518
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Abstract

Population health research is increasingly focused on the genetic determinants of healthy ageing, but there is no public resource of whole genome sequences and phenotype data from healthy elderly individuals. Here we describe the first release of the Medical Genome Reference Bank (MGRB), comprising whole genome sequence and phenotype of 2570 elderly Australians depleted for cancer, cardiovascular disease, and dementia. We analyse the MGRB for single-nucleotide, indel and structural variation in the nuclear and mitochondrial genomes. MGRB individuals have fewer disease-associated common and rare germline variants, relative to both cancer cases and the gnomAD and UK Biobank cohorts, consistent with risk depletion. Age-related somatic changes are correlated with grip strength in men, suggesting blood-derived whole genomes may also provide a biologic measure of age-related functional deterioration. The MGRB provides a broadly applicable reference cohort for clinical genetics and genomic association studies, and for understanding the genetics of healthy ageing.

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  • Aligning whole genomes is non-trivial due to the sheer size of genomes, their complex evolutionary histories, and the computational demands of alignment algorithms.

    “Despite the importance of WGA, aligning whole genomes is non-trivial due to the sheer size of genomes, their complex evolutionary histories, and the computational demands of alignment algorithms [8].”

    From Whole-Genome Alignment: Methods, Challenges, and Future Directions (2024) · cites this paper as [8]

    The Methods section, “Sequence alignment and processing” (page unavailable), describes aligning sequencing reads to a human reference and accelerating pipeline steps. It does not discuss whole-genome alignment or say that genome size, evolutionary history, and algorithmic demands make it difficult. Searches for those terms and close paraphrases found no passage addressing the claimed reasons. (LLM, conf=0.73)

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Cited by

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Authors
Pinese, M., Lacaze, P., Rath, E. M., Stone, A., Brion, M.-J., Ameur, A., Nagpal, S., Puttick, C., Husson, S., Degrave, D., Cristina, T. N., Kahl, V. F. S., Statham, A. L., Woods, R. L., McNeil, J. J., Riaz, M., Barr, M., Nelson, M. R., Reid, C. M., Murray, A. M., Shah, R. C., Wolfe, R., Atkins, J. R., Fitzsimmons, C., Cairns, H. M., Green, M. J., Carr, V. J., Cowley, M. J., Pickett, H. A., James, P. A., Powell, J. E., Kaplan, W., Gibson, G., Gyllensten, U., Cairns, M. J., McNamara, M., Dinger, M. E., & Thomas, D. M.
Affiliations
  • Garvan Institute of Medical Research (AU)
  • Monash University (AU)
  • Uppsala University (SE)
  • Georgia Institute of Technology (US)
  • Sax Institute (AU)
  • The University of Sydney (AU)
  • UNSW Sydney (AU)
  • University of Tasmania (AU)
  • Curtin University (AU)
  • University of Minnesota (US)
  • Rush University Medical Center (US)
  • Hunter Medical Research Institute (AU)
  • The University of Melbourne (AU)
Corresponding author
Thomas, David M.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2020-01-23
Volume
11
Issue
1
Pages
435-435
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-019-14079-0
PMC
PMC6978518
OpenAlex
W3002728042
Cited by
70
References
12
Citations by year
2026: 5 · 2025: 6 · 2024: 17 · 2023: 7 · 2022: 13 · 2021: 16 · 2020: 6
FWCI
6.12
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UTAS Research Repository (acceptedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • Monash University Research Portal (Monash University) (submittedVersion, cc-by)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • eSpace (Curtin University) (submittedVersion, cc-by)
  • Figshare (submittedVersion, cc-by)
  • UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
  • NOVA (University of Newcastle Australia) (submittedVersion)
Funders
  • Department of Health | National Health and Medical Research Council (APP1136372, 1104364)
  • Sylvia and Charles Viertel Charitable Foundation
  • NSW Ministry of Health
  • Ramsay Health Care Schizophrenia Research Institute
  • Science for Life Laboratory
  • Knut och Alice Wallenbergs Stiftelse
  • Kinghorn Foundation
  • NSW Office for Health and Medical Research Genomics Collaborative Grants scheme
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
healthy aging, healthy older adults, whole genome sequencing, germline mutations, somatic variation, mitochondrial genome, grip strength, age-related functional decline, population genomics
MeSH terms
Whole Genome Sequencing, Physical Functional Performance, Aged, Aged, 80 and over, Female, Gene Frequency, Humans, Male, Middle Aged, Mitochondria, Neoplasms, Genetic Variation, Cohort Studies, Genome, Human, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Databases, Genetic, Healthy Volunteers

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