COMMENT: Dear Dr. Nebert, I would say that this publication is an “important article.” It has been highlighted in many news reports and scientific conferences –– including last month’s Amercan Society of Human Genetics meeting in San Diego. I think one of the major reasons is that this study showed (some) translational value (‘translational’ = multi-disciplinary, highly collaborative, ‘bench-to-bedside’ approach) and clinical usefulness of large-scale genomic studies. The research community and the general public “need” this type of “good news,” to fuel their hopes of “personalized medicine.”

I agree that the paper showed some value of genomic prediction using polygenic scores; however, it is mainly a “numbers game.” If you look at the overall performance –– evaluated by the area-under-the-curve (AUC) method –– the best score was ~80%, which barely reaches the bottom line for the test to be (statistically) useful in clinical predictive assessment. This is why the authors emphasized only the extreme cases (i.e. those with only very high genetic risk), when they compared those predictive values to those having “monogenic risk.”

In my humble opinion, this is a study that has had a large impact (on the field of clinical genomics) –– much more so than any “real value.” For example, if you take a close look at Supplementary Table 9 [pasted below], their data on five complex diseases suggest that this GPS Model can explain only a very small fraction of the total variance.

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