The authors have made FGWAS statistics for 19 such phenotypes publicly available for use: thessgac.com/papers/16

FGWAS statistics are great to use when trying to perform unbiased polygenic risk prediction or genetic causal inference. Exciting to see subjective well-being and self-rated health among the phenotypes analysed in the paper! (relevant to ageing but normally heavily confounded by socioeconomics)

See the original tweet by the last author, Xia Shen: x.com/xiashen/stat...

I've used Sky Follower Bridge for this before www.sky-follower-bridge.dev

Looking forward to discussing #Longevity, #Genomics, #MachineLearning, and #DrugDiscovery with the community here!

https://humandbs.biosciencedbc.jp/en/hum0014-v27#:~:text=GWAS%20for%20survival%20time%20in%20137%2C693%20individuals%20from%20BBJ%201st%20cohort

Also, as always, it's fantastic to see the survival summary statistics made freely available. Can't wait to see what people will do with them!...

This locus was probably missed in European GWAS because the minor allele frequency is ~8.3 times higher in Japanese individuals (i.e. ~69 times as many homozygous carriers)

This once again highlights that inclusion of more diverse genetic ancestries can help boost GWAS findings!

The authors highlight a new locus near BET1L with a non-linear effect on survival - it looks like Japanese individuals carrying two copies of the minor allele are expected to die around 2 years earlier than average (from any cause)

Interested in finding out more? Check out the accompanying @NatureAging News and Views article (https://doi.org/10.1038/s43587-021-00162-z).

Have any questions, or want to #collaborate on #aging research? Get in touch! 😀

5/5

Finally, Mendelian randomization suggests blood levels of LPA and VCAM1 proteins likely have causal, detrimental effects on aging-GIP1 🩸

Drugs lowering these protein levels may be able to extend our healthy years of life!

4/5

Aging-GIP1 captures long life, free from mental and physical illness. We find 27 genetic regions influence this trait and once again show heme metabolism is a key pathway!

(see our previous work on heme and iron in aging: https://doi.org/10.1038/s41467-020-17312-3)

3/5

We combined genetic studies of #healthspan, father and mother #lifespan, exceptional #longevity, #frailty, and self-rated health to create an underlying latent #aging trait (aging-GIP1).

As always, the summary statistics are freely available: https://doi.org/10.7488/ds/2972

2/5