In:
eLife, eLife Sciences Publications, Ltd, Vol. 8 ( 2019-01-15)
Abstract:
Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.
Type of Medium:
Online Resource
ISSN:
2050-084X
DOI:
10.7554/eLife.39856.001
DOI:
10.7554/eLife.39856.002
DOI:
10.7554/eLife.39856.003
DOI:
10.7554/eLife.39856.004
DOI:
10.7554/eLife.39856.005
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10.7554/eLife.39856.006
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10.7554/eLife.39856.007
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10.7554/eLife.39856.008
DOI:
10.7554/eLife.39856.010
DOI:
10.7554/eLife.39856.009
DOI:
10.7554/eLife.39856.011
DOI:
10.7554/eLife.39856.012
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10.7554/eLife.39856.013
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10.7554/eLife.39856.014
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10.7554/eLife.39856.015
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10.7554/eLife.39856.016
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10.7554/eLife.39856.017
DOI:
10.7554/eLife.39856.018
DOI:
10.7554/eLife.39856.019
DOI:
10.7554/eLife.39856.020
DOI:
10.7554/eLife.39856.021
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10.7554/eLife.39856.022
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10.7554/eLife.39856.023
DOI:
10.7554/eLife.39856.024
DOI:
10.7554/eLife.39856.025
DOI:
10.7554/eLife.39856.026
DOI:
10.7554/eLife.39856.027
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10.7554/eLife.39856.028
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10.7554/eLife.39856.029
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10.7554/eLife.39856.030
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10.7554/eLife.39856.031
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10.7554/eLife.39856.032
DOI:
10.7554/eLife.39856.033
DOI:
10.7554/eLife.39856.034
DOI:
10.7554/eLife.39856.035
DOI:
10.7554/eLife.39856.036
DOI:
10.7554/eLife.39856.037
DOI:
10.7554/eLife.39856.038
DOI:
10.7554/eLife.39856.039
DOI:
10.7554/eLife.39856.040
DOI:
10.7554/eLife.39856.041
DOI:
10.7554/eLife.39856.047
DOI:
10.7554/eLife.39856.048
Language:
English
Publisher:
eLife Sciences Publications, Ltd
Publication Date:
2019
detail.hit.zdb_id:
2687154-3
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