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    • br Discussion The Pro Ala variant in PPARG

    2022-02-23


    Discussion The Pro12Ala variant in PPARG has been one of the first candidate SNPs for type 2 diabetes [16], [17]. The rare allele of this variant is associated with a 25% reduced risk for the disease [18]. Given the role of PPARG as both a receptor for NEFA and itself a regulator of fat metabolism, our group had earlier investigated the hypothesis that PPARG-mediated alterations in fatty that signaling could have an impact on insulin secretion. In those hyperglycemic clamp studies, we had compared insulin secretion between Pro/Pro and X/Ala carriers of the PPARG variant in a control and a high-NEFA setting. Only the clamp condition with a concomitant infusion of Intralipid solution, performed to raise NEFA levels, had unmasked striking differences in insulin secretion between PPARG genotypes [11]. However, no explanation could be given for the mechanism of action by that time. Meanwhile, the NEFA receptor FFAR1 has been established as an important stimulator of fatty-acid mediated insulin secretion [4] and genetic variation in FFAR1 has been shown to influence beta-cell function [9], [19]. Therefore, FFAR1 seemed to be a plausible link between PPARG and insulin secretion. By analyzing the previously described 7 FFAR1 tagging SNPs, we now found 2 SNPs, which exert a NEFA and PPARG-dependent effect on insulin secretion. The SNPs rs12462800 and rs10422744 are located 0.8 kb apart in an intergenic regulatory area between the FFAR1 (GPR40) and FFAR3 (GPR41) genes, 3.5 and 3.8 kb from the 3′ end of the single FFAR1 exon. These SNPs are more distal from the gene than the previously described FFAR1 SNP rs1573611 which directly interacts with fasting NEFA in association with insulin secretion [9]. The molecular mechanisms underlying the PPARG–FFAR1 interaction are still speculative. Although the literature is controversial, there is a wealth of data from basic science and clinical studies involving the use of PPARG agonists (thiazolidinediones) indicating that PPARG activation may have a positive impact on beta-cell function and beta-cell survival (reviewed by [20]). The PPARG–FFAR1 interaction, especially in light of the effect modification by NEFA levels, could possibly explain this still poorly understood link between PPARG action and beta-cell function. A recent study demonstrated that PPARG overexpression leads to an increased expression of FFAR1 in rat INS-1 cells and primary rat islets [10]. A possible interaction scenario could thus be a defective PPARG-induced transcriptional or translational activity of the FFAR1 gene in the presence of the FFAR1 minor allele variants, which would consecutively result in a limited compensatory potential to increase insulin secretion when fasting NEFA are elevated. The fundamental human phenotypic alterations associated with the Pro12Ala variant seem to involve lipolysis and its insulin-dependent inhibition [21], [22], [23]. Since FFAR1 is activated by medium and long-chained fatty acids [24], perturbations in NEFA levels or their composition as a consequence of altered PPARG action could modulate insulin secretion through FFAR1. In summary, PPARG and FFAR1 are connected in several ways, and the presented interaction is mechanistically reasonable. Additional investigations are required to elucidate the exact details of the underlying physiology. However, our findings are of immanent importance for the treatment of type 2 diabetes, because the described genotypic interaction between PPARG and FFAR1 could have bearing on the pharmacologic efficacy of FFAR1 agonists. Although a phase 3 clinical trial of the most promising FFAR1-agonist has been recently halted, several of such agents are still under development [8], [25]. We infer that the variants identified in the current study, under the constellation of the minor PPARG Pro12Ala allele, could have relevant impact on the effectiveness of FFAR1 agonists. Identification of variants which are candidates for pharmacogenetic interactions could pave the way for investigating genotype-based therapeutic responses within clinical studies and on the long run in clinical practice. This would eventually lead to an improved selection of individuals who would benefit from specific therapies [26].