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Protein folding in vivo takes place in a highly crowded environment. The resulting excluded volume forces are thought to stabilize folded forms of proteins. In agreement, many in vitro studies have shown that the presence of macromolecular crowding agents increases the stability of folded proteins but often by only a few kJ per mol. Although it should not matter at what position in the transition between folded and unfolded forms the effect of crowding is employed, there have been no studies assessing whether excluded volume forces alone can correctly fold polypeptides that are mostly unfolded. However, some studies have indicated that the effect of crowding becomes larger the more destabilized the protein is (but still being folded), suggesting that the crowding effect may be exaggerated for unfolded proteins. To address this question directly, we turned to a destabilized mutant of protein L that is mostly unfolded in water but can be folded upon addition of salt. We find that the effect of 200 mg/mL Dextran 20 on the folding equilibrium constant for unfolded protein L (ΔΔGU ≈ 2 kJ mol(-1)) matches the crowding effects found on the folded wild type protein and the mutant when prefolded by salt. This result indicates that the excluded volume effect is independent of starting protein stability and that crowding can shift the reaction toward the folded form when the polypeptide is in the transition region between folded and unfolded states.

OBJECTIVE

Meat intake has been consistently shown to be positively associated with incident type 2 diabetes. Part of that association may be mediated by body iron status, which is influenced by genetic factors. We aimed to test for interactions of genetic and dietary factors influencing body iron status in relation to the risk of incident type 2 diabetes.

RESEARCH DESIGN AND METHODS

The case-cohort comprised 9,347 case subjects and 12,301 subcohort participants from eight European countries. Single nucleotide polymorphisms (SNPs) were selected from genome-wide association studies on iron status biomarkers and candidate gene studies. A ferritin-related gene score was constructed. Multiplicative and additive interactions of heme iron and SNPs as well as the gene score were evaluated using Cox proportional hazards regression.

RESULTS

Higher heme iron intake (per 1 SD) was associated with higher ferritin levels (beta = 0.113 [95% CI 0.082; 0.144]), but not with transferrin (-0.019 [-0.043; 0.006]) or transferrin saturation (0.016 [-0.006; 0.037]). Five SNPs located in four genes (rs1799945 [HFE H63D], rs1800562 [HFE C282Y], rs236918 [PCK7], rs744653 [SLC40A1], and rs855791 [TMPRSS6 V736A]) were associated with ferritin. We did not detect an interaction of heme iron and the gene score on the risk of diabetes in the overall study population (P-add = 0.16, P-mult = 0.21) but did detect a trend toward a negative interaction in men (P-add = 0.04, P-mult = 0.03).

CONCLUSIONS

We found no convincing evidence that the interplay of dietary and genetic factors related to body iron status associates with type 2 diabetes risk above the level expected from the sum or product of the two individual exposures.