Reviewer #2 (Public Review):

This work conducted a Mendelian randomization analysis between TG and a large number of disease traits in biobanks. They leverage the publicly available summary statistics from the European samples from the UK Biobank and FinnGen. A solid but routine standard summary-statistics based MR study is conducted. Several significant causal associations from TG to phenotypes are called by setting p-value cutoff with some Bonferroni correction. Sensitivity statistical analyses are conducted which generate largely consistent results. The research problem is important and relevant for public health as well we drug development. Overall this is a solid execution of current methods over appropriate data source and yields a convincing result. The interpretation of the results in discussion is also well-balanced.

While the paper does have strengths in principle, a few technical weaknesses are observed.

They used UK Biobank as the discovery and FinnGen as the replication. But the two cohorts are rather used symmetrically. Especially for the Tier 3 (NB), it seems to be an attempt of reusing the replication cohort as the discovery. I wonder if that would create additional multiple testing burden as a greater number of hypotheses are considered.

The replication p-value cutoff is a bit statistically lenient. In a typical discovery-replication setting the two stages are conducted sequentially and replication should go through the Bonferroni adjustment on the number of significant signals from discovery that is tested in the replication. For example, in this case, in tier 2, the cutoff should be 0.05/39. This may make the association of leiomyoma of the uterus slightly non-significant though. Similar cutoff should be applied to tier 3 as well.

The causal effect of TG to leiomyoma of the uterus is weak, as indicated by both the sub-significant in the replication and the non-significant of MR-PRESSO. Similarly, I would recommend more caution on the weak statistical rigor when interpreting Tier 2 and Tier 3 results.

Another methodological choice that might need justification is the use of UKB TG GWAS loci (1,248 SNPs) are the instrument for FinnGen. This may create some subtle interference with the use of UKB as outcomes in the discovery analysis. It may be minor but some justification or at least some discussions of potential limitations should be mentioned. What about the alternative of using GLGC as instruments in replication?

For disease outcomes (line 188), UKB European sample size is ~400,000 rather than ~500,000. Can the author clarify the sample size they used?

It would be reassuring to the reader if the TG measurements were measured in a treatment-naïve manner.

"Phenome-wide MR is a high-throughput extension of MR that, under specific assumptions, estimates the causal effects of an exposure on multiple outcomes simultaneously." - I guess it is more informative to mention the specific assumptions, at least briefly, in the introduction so it is easier for the reader to interpret the results.

Reviewer #2 (Public Review):

In this new exciting manuscript, Möller and colleagues studied different behavioral patterns of human and non-human primate subjects in a transparent social coordination game. In the task, two subjects chose between two visible options, in which each subject preferred a different option. Critically, the reward level also varied based on a payoff matrix. Choosing the non-preferred options by both subjects resulted in the lowest rewards, whereas choosing the preferred options by both resulted in medium-sized rewards for both. However, when both subjects chose the same option (i.e., coordinated), which was preferred by one subject but not preferred by the other subject, both received the highest rewards, with the subject who indicated the preferred option receiving a higher reward than the other. Therefore, the optimal strategy would be a dynamic turn-taking strategy in which both subjects choose the same option while taking turns over time. The authors found that about half of the human pairs adopted the turn-taking strategy. On the other hand, monkeys performed the task mostly in a selfish manner - both monkeys tended to choose their preferred options. Interestingly, in the human-monkey pairing, the monkeys could learn the turn-taking patterns. Furthermore, a detailed examination showed that turn-taking patterns in humans indicated a prosocial strategy, while turn-taking patterns in monkeys reflected a competitive strategy, where a slow-responding monkey followed the option of the fast-responding monkey. Together, the results convincingly demonstrate very interesting similarities and differences between humans and monkeys in carrying out social coordination.

Strength: This study provides convincing results with good sample size and rigorous data analyses. The transparent task design uniquely allowed the authors to examine the visual social aspects underlying social coordination. The direct comparison between human and monkey subjects, as well as examining human-monkey pairs were important and informative. Overall, the results provide novel insights into other studies in non-human primates that aim to understand the common social decision-making mechanism of both human and non-human primates.

Weakness: In the situation when the human subjects were paired with monkey subjects, it was unclear what detailed aspects of this experience directly led to the increase in the turn-taking behavior in the monkey subjects. About half of the human subjects behaved more like the monkey subjects by not exhibiting the dynamic turn-taking behavior, yet the reasons behind this within-group difference were unclear.

Reviewer #2 (Public review):

The present studies by Foster and colleagues use mouse genetics to show that pyruvate kinase 1 and 2 (PKM1 and PKM2) regulate ATP-sensitive K+ channel activity (KATP channel) through mitochondrial PEP-dependent cytoplasmic ATP/ADP increases, leading to first phase insulin secretion. During the second phase of insulin secretion, when ATP hydrolysis is maximal, oxidative phosphorylation is engaged to sustain ATP/ADP ratios and KATP channel closure. As such, the work challenges the consensus view of KATP channel activity, which states that ATP derived from oxidative phosphorylation in the mitochondrial matrix increases cytoplasmic ATP/ADP ratio, thus closing KATP channels and increasing Ca2+ fluxes.

Strengths of the study include: 1) careful experimental design and execution; 2) use of comprehensive mouse genetics to pinpoint roles of PKM1, PKM2 and phosphoenolpyruvate carboxykinase 2 (which produces PEP from oxoaloacetic acid); and 3) multiple lines of corroboratory evidence that the PEP-PKM1/2 system influences KATP channel activity and downstream signaling, via changes in non-mitochondrial ATP/ADP.

Weaknesses include: 1) lack of in vivo data to support a role of PKM1/PKM2 in determining glucose levels; and 2) over-reliance on mouse models, meaning that translational relevance to human biology is unclear.

Nonetheless, on balance, the authors have achieved their aims of showing that PEP and PKM1/PKM2 are critical regulators of KATP channel activity, Ca2+ fluxes and insulin secretion.

Overall, this is a potentially important study, which updates the textbook view of KATP-channel regulation, the major signaling mechanism through which pancreatic beta cells couple blood glucose levels to insulin release.

COVID research updates: Coronavirus antibodies last for months — if you have them. (2021). Nature. https://doi.org/10.1038/d41586-020-00502-w

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