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Overall, these results highlight the need to advance towards context-informed clinical implementation of PGSs and to identify contexts where PGSs impose a greater impact on the disease

Notably, as well, the negative predictive values (NPV) are the highest at low-PGS and low-risk contexts, suggesting that unnecessary interventions could be avoided in the lower genetic-risk groups

Consequently, the positive predictive value (PPV) is the highest at high-PGS and high-risk contexts, highlighting the effectiveness of targeting a smaller proportion of the population stratified by both PGS and environmental risk to maximize the intervention benefit.

PNB is typically halved at 70-80th PGS percentile compared to overall population without consideration of genetic risk stratification (~50% gain in benefit).

Finally, considering utility of PGS×C, we introduced the proportion needed to benefit (PNB) as the number of individuals who would need to modify their high-risk exposure for one to benefit(similar to Number Needed to Treat) as a function of PGS threshold vs in overall population

The predominant mechanism for PGS×C interactions is shown to be amplification of genetic effects in the presence of adverse exposures such as low polyunsaturated fatty acids, mediators of obesity, and social determinants of ill health.

The fold change in predictive accuracy across contexts is comparable to that across ancestries. It highlights the need to evaluate PGS portability not only across ancestries, but also across exposures/SDOH & identify contexts where PGS have greater predictive & clinical utility.

PGSs showed greater predictive accuracy in high-risk than low-risk contexts, with further gains in many composite models incorporating PGS×C interactions.

Across all disease-exposures, we find evidence of pervasive PGSxC interactions influencing common disease risk. Eg. for incident CAD, key exposures exhibiting multiple interactions are: sex, weekly beer intake, smoking and omega-6 fatty acids.

Liability threshold disease risk modeling of incidence vs percentile-PGS relationships to assess whether the deviations in disease risk exceed the additive expectation. Low levels of omega6 fatty acids and past tobacco smoking interact with PGS-CAD to exacerbate incident CAD risk

The impact of PGS on the disease is highly context-specific. Shown varied impact of PGS-CAD on CAD incidence with respect to combinations of contexts.

We assessed the polygenic risk scores-by-context interactions (PGSxC) across 7 common disease and pairs of 75 contexts (exposures) in the UK Biobank.

Excited to share our work on "Pervasive interactions between exposures and polygenic risk can inform more effective clinical and behavioral interventions" @genomestake.bsky.social @natgenet.nature.com - www.nature.com/articles/s41...

Also, a special moment to see my mentor, Greg Gibson's @genomestake.bsky.social latest book #NaturalVirtue published - www.greggibsonbooks.com

2. I have joined Koita Centre for Digital Health #KCDH #IITBombay as an Assistant Professor & started my research group: nagpallab.github.io. Our lab develops statistical genetics & integrative genomics approaches to assess human disease risk, with the goal of advancing precision genomic medicine.

www.nature.com/articles/s41...

Excited to share 2 important milestones in my academic journey- Our work on “Pervasive interactions between exposures & polygenic risk can inform more effective clinical & behavioral interventions,” showing PGSxC interactions & their utility, is out in #NatureGenetics @genomestake.bsky.social

In the December issue of #GENETICS, @jeremyjberg.bsky.social et al. introduce an evolutionary model of complex disease susceptibility, identifying how diseases are shaped by selection acting on other pleiotropically related traits. buff.ly/QTZPpYQ

I wrote a little bit about the "missing heritability" question and several recent studies that have brought it to a close. A short 🧵

Excited to share our latest study integrating genetics with gene expression regulation to uncover sex-specific differences in Crohn’s disease recurrence - now out in Gastroenterology. @judyibd.bsky.social @genomestake.bsky.social