Quantitative analysis of population-scale family trees with millions of relatives
Open accessPublished version of a preprint
Abstract
Quantitative analysis of millions of relatives: Human relationships, as documented by family trees, can elucidate the heritability of a host of medical and biological parameters. Kaplanis et al. collected 86 million publicly available profiles from a crowd-sourced genealogy website and used them to examine the genetic architecture of human longevity and migration patterns (see the Perspective by Lussier and Keinan). Various models of inheritance suggested that life span is predominantly attributable to additive genetic effects, with a smaller component from dominant genetic inheritance. The data also suggested that relatedness between individuals is less attributable to advances in human transportation than to cultural changes. Science , this issue p. 171 ; see also p. 153
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Genetic factors account for only 15-40% of lifespan variability.
“While genetic factors account for only 15–40% of lifespan variability [28,29,30,31,32], environmental exposures—including access to green spaces—play a dominant role in shaping aging trajectories.”
From The Power of Environment: A Comprehensive Review of the Exposome's Role in Healthy Aging, Longevity, and Preventive Medicine-Lessons from Blue Zones and Cilento (2025) · cites this paper as [28]
In “Characterizing the genetic architecture of longevity” (page not available), the paper reports previous heritability estimates of about 15–30% and its own additive-genetic estimate of about 16%. These support a modest genetic contribution to lifespan variability, but not the claimed upper bound of 40%. (LLM, conf=0.88)
Experimental — accuracy not yet measuredEnvironmental exposures-including access to green spaces-play a dominant role in shaping aging trajectories.
“While genetic factors account for only 15–40% of lifespan variability [28,29,30,31,32], environmental exposures—including access to green spaces—play a dominant role in shaping aging trajectories.”
From The Power of Environment: A Comprehensive Review of the Exposome's Role in Healthy Aging, Longevity, and Preventive Medicine-Lessons from Blue Zones and Cilento (2025) · cites this paper as [28]
In “Characterizing the genetic architecture of longevity” (page unavailable), the paper reports an additive genetic contribution of about 16% and cites earlier heritability estimates of 15–30%. This supports the citing sentence’s point that genetics accounts for a limited share of longevity variation, but not its 40% upper bound. The paper does not identify access to green spaces as an exposure shaping aging trajectories. (LLM, conf=0.84)
Experimental — accuracy not yet measuredGenes that regulate lifespan in animal models and human studies, and multiple experimental paradigms, have demonstrated that it is possible to manipulate ageing biology to rejuvenate physiological functioning in complex model organisms.
“Genes that regulate lifespan in animal models6–9 and human studies10–14 as well as multiple experimental paradigms, such as caloric restriction, heterochronic parabiosis and partial epigenetic reprogramming, have demonstrated that it is possible to manipulate ageing biology to ‘rejuvenate’ physiological functioning in complex model organisms15–28.”
From Measuring biological age using omics data (2022) · cites this paper as [10]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 86 · Cited by 245
Research works printed but not linked: 11
- [1]Fisher RA, Trans. R. Soc. Edinb. 52, 399– 433 (1919).
- [5]Lowe JK, PLoS Genet. 5, e1000365 (2009).
- [19]Albright LAC, in AMIA Annual Symposium Proceedings (American Medical Informatics Association, 2006), vol. 2006, p. 1161.
- [22]Kittur A, Chi E, Pendleton BA, Suh B, Mytkowicz T, World Wide Web. 1, 19 (2007).
- [36]Sebastiani P, PloS One. 7, e29848 (2012).
- [43]Shor T, Geiger D, Erlich Y, Weissbrod O, bioRxiv (2018), doi: 10.1101/256396 · DOI
- [54]Cavalli-Sforza LL, Moroni A, Zei G, Consanguinity, Inbreeding, and Genetic Drift in Italy (Princeton University Press, 2004), vol. 39.
- [55]Relethford JH, Brennan ER, Hum. Biol, 315– 327 (1982). 7095798
- [65]Rao D, MacLean C, Morton N, Yee S, Am. J. Hum. Genet. 27, 509 (1975). 1155459 PMC1762799
- [74]Meuwissen T, Luo Z, Genet. Sel. Evol. 24, 305 (1992).
- [75]Chen Y, Davis TA, Hager WW, Rajamanickam S, ACM Trans. Math. Softw. TOMS. 35, 22 (2008).
- Authors
- Kaplanis, J., Gordon, A., Shor, T., Weissbrod, O., Geiger, D., Wahl, M., Gershovits, M., Markus, B., Sheikh, M., Gymrek, M., Bhatia, G., MacArthur, D. G., Price, A. L., & Erlich, Y.
- Affiliations
- New York Genome Center (US)
- Technion – Israel Institute of Technology (IL)
- Weizmann Institute of Science (IL)
- Harvard University (US)
- Whitehead Institute for Biomedical Research (US)
- Broad Institute (US)
- Corresponding author
- Kaplanis, Joanna
- Gordon, Assaf
- Erlich, Yaniv
- ORCID
- Venue
- Science
- Published
- 2018-04-13
- Volume
- 360
- Issue
- 6385
- Pages
- 171-175
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6593158
- OpenAlex
- W2951742207
- Cited by
- 245
- References
- 86
- Citations by year
- 2026: 20 · 2025: 32 · 2024: 31 · 2023: 19 · 2022: 23 · 2021: 26 · 2020: 34 · 2019: 32 · 2018: 26 · 2017: 2
- FWCI
- 18.09
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (R01 MH101244)
- Israel Science Foundation (1678/12)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- family trees, pedigree, human longevity, genetic architecture
- MeSH terms
- Family, Genealogy and Heraldry, Humans, Longevity, Models, Genetic, Pedigree, Population, Datasets as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
