Here, we report robust associations of five genetically non-linked MAP4K4
tagging SNPs (rs6543087, rs11674694, rs17801985, rs11678405, rs1003376) with 2-hour plasma glucose levels. The adjusted effect sizes ranged from 0.12 to 0.25 mmol/L (from 2 to 4%) per allele. Upon interrogation of publically available data from the MAGIC consortium (N~77,000), the effect on 2-hour plasma glucose of one of these SNPs, i.e., rs11678405, was concordant and almost reached nominal significance (p
0.055, adjusted for BMI only, effect size 0.05 mmol/L per allele). Since 2-hour glucose is commonly used to classify impaired glucose tolerance and type 2 diabetes 
, common genetic variation within MAP4K4
affects a (pre)diabetes-relevant trait.
In accordance with MAP4K4’s postulated molecular role in inflammation-induced insulin resistance 
, three SNPs (rs11674694, rs13003883, rs2236936) were nominally and specifically associated with altered plasma levels of the inflammatory cytokine IL-6 (adjusted effect sizes 12–20% per allele) and two of the SNPs that increased 2-hour plasma glucose (rs6543087, rs11674694) were also nominally associated with a decrease in insulin sensitivity (adjusted effect sizes ~4% per allele), as assessed by a well-established dynamic OGTT-derived parameter. Such a reduction in insulin sensitivity SNP carriers face their whole life long could represent the causal mechanism how genetic variation in the MAP4K4
locus affects 2-hour plasma glycaemia. This, however, needs further replication in larger, comparably phenotyped study populations.
In addition, we could demonstrate that rs11674694, the only SNP showing consistent associations with all three traits, i.e., elevated plasma IL-6, reduced insulin sensitivity, and increased 2-hour glycaemia, was also associated with a 23–25% increase in type 2 diabetes risk (dominant model) in a prospective setting. This raises the question why MAP4K4 SNPs were not among the top signals for type 2 diabetes detected by array-based genome-wide association (GWA) studies and consortia-driven meta-analyses thereof. This discrepancy might be inherent to differences between hypothesis-driven and hypothesis-free approaches: the hypothesis-free GWA studies provided a series of novel diabetes risk genes with modest effect sizes and largely unknown biological functions, whereas some very strong biological candidate genes with meta-analysis-proven effects on type 2 diabetes risk, such as CAPN10 and ENPP1, have not been replicated by GWA studies. The reasons for the discrepancy regarding MAP4K4 could be manifold and may result, e.g., from (i) the cross-sectional study design of most GWA studies, (ii) divergent selection criteria for control and/or case groups, (iii) confounders that were not accounted for (ethnicity, environment, prediabetic status), or (iv) the heterogeneity across studies combined for meta-analysis.
Notably, two non-linked MAP4K4
SNPs (rs2236936, rs2236935) were associated with decreased insulin release (adjusted effect sizes ~3.5% per allele). This is in keeping with recent in vitro
observations in rat and human primary β-cells showing that MAP4K4 mediates TNF-α effects, such as reduction of cellular IRS-2 protein, inhibition of proliferation, induction of apoptosis, and inhibition of glucose-stimulated insulin secretion 
. Interestingly, these SNPs’ associations with impaired β-cell function were driven by their effects in lean subjects only. Why these SNPs’ effects vanish in overweight and obese subjects is currently unknown, but may be explained by obesity-related overriding non-genetic (e.g., environmental) factors.
All SNPs assessed in this study are located in non-coding regions of the MAP4K4 locus and tag, without exception, non-coding or synonymous common SNPs. Thus, effects of these genetic variants on the function of the MAP4K4 protein are unlikely. Rather, it is conceivable that the SNPs affect cis-acting elements, e.g., transcription factor binding sites, thus enhancing or attenuating MAP4K4 gene transcription. This could also explain the different directions of SNP effects with the minor alleles of three SNPs (rs6543087, rs11674694, rs11678405) increasing and the minor alleles of two SNPs (rs17801985, rs1003376) decreasing 2-hour plasma glycaemia. Different directions of effects were also seen for the associations with plasma IL-6.
Our study has the following limitations: first, due to the limited sample size of the TÜF study, we only analysed common variants with MAFs >0.05; thus, we cannot exclude the existence of rarer variants with direct effects on the MAP4K4’s function (e.g., by amino acid exchange or frameshift mutation); moreover, rarer variants with stronger effects on the gene’s expression and on the tested traits may exist; and secondly, we did not correct our significance level for the number of tested traits because we considered the traits not to be independent; therefore, one or two of our associations may be statistical type I errors; however, the fact that we always found two or more non-linked (i.e., independent) SNPs associated with each trait (2-hour glycaemia, insulin resistance, insulin release, IL-6) clearly argues against spurious findings.
In conclusion, we show here by genetic, but not mechanistic, analysis that common genetic variation in the MAP4K4 locus is associated with the two major pathomechanisms causing type 2 diabetes, i.e., insulin resistance and β-cell failure, and this is possibly mediated by this gene’s role in inflammatory cytokine signalling. This variation’s impact on insulin sensitivity may be more important with regard to a role in the pathogenesis of type 2 diabetes since its effect on insulin release vanishes with increasing BMI.