Great opportunity to reshare the Big Five facets correlation plot I made earlier, showing how the synthetic data from synthpop matches the original dataset (n = 468). Cheers! :-P

We estimate that ~9–11k common genetic variants contribute to BAG — a level of polygenicity similar to height, but much lower than neuroticism. That’s good news: discovery power scales well, and with ~1 M participants (phew — still quite a way to go!) we could capture most common genetic influences.

⚡ Mendelian randomization suggests causal effects:
Higher blood pressure and type 2 diabetes drive accelerated brain aging — each 1 SD increase in blood pressure corresponds to ~0.5 years older brain age.

🔗 Genetic correlations show broad overlap with lifestyle, mental, physical, and socioeconomic traits:
⬆️ blood pressure, diabetes, drinking, smoking, depressed mood
⬇️ lung function, cognition, longevity, education, income
🧠 Brain aging lies at the intersection of body, mind, and environment.

🧬 A new polygenic score for BAG explains ~10% of variance — a big leap from previous ~2%. Still, prediction in non-European ancestries remains limited, highlighting the urgent need for more diverse genomic data.

💥 We identified 59 genomic loci, including 39 never linked before to brain aging. The strongest signal is at MAPT (tau) — a well-known Alzheimer’s gene — confirming its central role in brain structural aging.

🧠 The brain age gap (BAG) = your brain’s predicted MRI age minus your actual age.

A higher BAG means your brain looks “older” than expected. We show BAG is substantially heritable (~23–29% due to common variants), meaning genes do play a big role — but environment and lifestyle matter too.

A while ago, when I was in my first semester teaching behavioral genetics, I was eager to discuss candidate gene controversies. I created an interactive funnel plot based on the meta-analysis by Karg et al. (2011), who reported strong evidence for an effect of 5-HTTLPR × stress on depression. 1/2