EJB, M. Kivimäki, DAL, MM, SEH, ADH, and M. Kumari designed the study. EJB, JAC, and MM analyzed the data. MM, GDOL, AR, TS, MGM, and M. Kumari collected data or did experiments for the study. EJB and M Kivimäki wrote the first draft of the paper. EJB, M. Kivimäki, DRW, DAL, GDS, JAC, MM, GDOL, AR, JPC, ADH, MGM, NJT, and M. Kumari contributed to writing the paper. M. Kivimäki helped in conducting the data analysis and interpretation. DRW contributed to the analysis of the data. MM supervised (scientific and administrative roles) the DNA extraction program and genotyping and was responsible for checking genotype results and in particular for verifying concordance of blind duplicates, establishing error rates, etc. GDOL supervised laboratory assays. TS selected CRP tag SNPs and conducted genotyping of these SNPs. NJT helped with analysis.
The authors have declared that no competing interests exist.
Raised C-reactive protein (CRP) is a risk factor for type 2 diabetes. According to the Mendelian randomization method, the association is likely to be causal if genetic variants that affect CRP level are associated with markers of diabetes development and diabetes. Our objective was to examine the nature of the association between CRP phenotype and diabetes development using
We genotyped three tagging SNPs (CRP + 2302G > A; CRP + 1444T > C; CRP + 4899T > G) in the
Observed associations between serum CRP and insulin resistance, glycemia, and diabetes are likely to be noncausal. Inflammation may play a causal role via upstream effectors rather than the downstream marker CRP.
Using a Mendelian randomization approach, Eric Brunner and colleagues show that the associations between serum C-reactive protein and insulin resistance, glycemia, and diabetes are likely to be noncausal.
Diabetes—a common, long-term (chronic) disease that causes heart, kidney, nerve, and eye problems and shortens life expectancy—is characterized by high levels of sugar (glucose) in the blood. In people without diabetes, blood sugar levels are controlled by the hormone insulin. Insulin is released by the pancreas after eating and “instructs” insulin-responsive muscle and fat cells to take up the glucose from the bloodstream that is produced by the digestion of food. In the early stages of type 2 diabetes (the commonest type of diabetes), the muscle and fat cells become nonresponsive to insulin (a condition called insulin resistance), and blood sugar levels increase. The pancreas responds by making more insulin—people with insulin resistance have high blood levels of both insulin and glucose. Eventually, however, the insulin-producing cells in the pancreas start to malfunction, insulin secretion decreases, and frank diabetes develops.
Globally, about 200 million people have diabetes, but experts believe this number will double by 2030. Ways to prevent or delay the onset of diabetes are, therefore, urgently needed. One major risk factor for insulin resistance and diabetes is being overweight. According to one theory, increased body fat causes mild, chronic tissue inflammation, which leads to insulin resistance. Consistent with this idea, people with higher than normal amounts of the inflammatory protein C-reactive protein (CRP) in their blood have a high risk of developing diabetes. If inflammation does cause diabetes, then drugs that inhibit CRP might prevent diabetes. However, simply measuring CRP and determining whether the people with high levels develop diabetes cannot prove that CRP causes diabetes. Those people with high blood levels of CRP might have other unknown factors in common (confounding factors) that are the real causes of diabetes. In this study, the researchers use “Mendelian randomization” to examine whether increased blood CRP causes diabetes. Some variants of
The researchers measured blood CRP levels in more than 5,000 people enrolled in the Whitehall II study, which is investigating factors that affect disease development. They also used the “homeostasis model assessment-insulin resistance” (HOMA-IR) method to estimate insulin sensitivity from blood glucose and insulin measurements, and measured levels of hemoglobin A1c (HbA1c, hemoglobin with sugar attached—a measure of long-term blood sugar control) in these people. Finally, they looked at three “single polynucleotide polymorphisms” (SNPs, single nucleotide changes in a gene's DNA sequence; combinations of SNPs that are inherited as a block are called haplotypes) in
Together, these findings suggest that increased blood CRP levels are not responsible for the development of insulin resistance or diabetes, at least in European populations. It may be that there is a causal relationship between CRP levels and diabetes risk in other ethnic populations—further Mendelian randomization studies are needed to discover whether this is the case. For now, though, these findings suggest that drugs targeted against CRP are unlikely to prevent or delay the onset of diabetes. However, they do not discount the possibility that proteins involved earlier in the inflammatory process might cause diabetes and might thus represent good drug targets for diabetes prevention.
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C-reactive protein (CRP) is a nonspecific marker of systemic inflammation that predicts incident type 2 diabetes. Chronic low-grade inflammation may induce insulin resistance and is a candidate pathway leading from obesity to diabetes [
Mendelian randomization involves comparison of phenotype and genotype effects in observational studies [
We are aware of one previous study of CRP and diabetes employing the Mendelian randomization technique in a European population [
In 1985–1988, all nonindustrial civil servants aged between 35 and 55 y, in 20 departments in central London were invited to a medical examination at their workplace [
Age, sex, body mass index (BMI), waist circumference, blood pressure, smoking, physical activity, socioeconomic position, coronary heart disease, and diabetes status were measured at mean ages 49 and 61 y. Weight was measured in underwear to the nearest 0.1 kg on Soehnle electronic scales. Height was measured in bare feet to the nearest 1 mm using a stadiometer with the participant standing erect with head in the Frankfurt plane. Waist circumference, taken as the smallest circumference at or below the costal margin, was measured with participants unclothed in the standing position utilizing a fiberglass tape measure at 600 g tension. Venous blood was taken in the fasting state or at least 5 h after a light, fat-free breakfast, before undergoing a 2-h 75-g oral glucose tolerance test [
DNA was extracted from blood samples using magnetic bead technology (Geneservice). Using validated genotype data (minor allele frequency >5%) from participants of European descent from the National Heart Lung and Blood Institute (NHLBI) Programs for Genomic Applications (PGA) database (
CRP was measured in serum stored at −80 °C using a high-sensitivity immunonephelometric assay in a BN ProSpec nephelometer (Dade Behring). Values below the detection limit (0.154 mg/l) were assigned a value of 0.077 mg/l (333 [7.1%] at age 49 y, 104 [2.0%] at age 61 y). Samples from both study phases were analyzed at the same time. Intra- and interassay coefficients of variation were 4.7% and 8.3%. To measure short-term biological variation and laboratory error, a repeated sample was taken from a subset of 150 participants at mean age 49 y and 533 participants at mean age 61 y (average time between samples 32 and 24 d, respectively). Reliability between samples was assessed with intraclass correlation:
Diabetes status was determined at mean ages 49, 56, and 61 y on the basis of self-report of doctor diagnosis, use of diabetes medication or 75 g OGTT. Diabetes was defined by 2-h glucose ≥ 11.1 mmol/l or fasting glucose ≥ 7 mmol/l [
HbA1c was measured in EDTA whole blood on a calibrated HPLC system with automated hemolysis prior to injection. HbA1 is resolved as a separate peak, which does not interfere with HbA1c quantitation. HOMA-IR was calculated as (fasting glucose [mmol/l] × fasting insulin [mU/l]/22.5) [
We used age- and sex-adjusted least square regression analysis to assess (1) the association of haplotypes (see below) with circulating CRP levels at baseline and follow-up, and with potential confounding factors; (2) the associations of potential confounding factors with circulating CRP levels and with HbA1c and HOMA-IR at follow-up; and (3) the association between circulating CRP levels with HbA1c and HOMA-IR in a multivariable model. The haplotype-confounder associations were computed to test our underlying hypothesis that genetic variants in
We constructed haplotypes with the genetic data analysis program SIMHAP (see
An instrumental variables analysis, in which
There was no statistical evidence that the associations we examined differed by sex, although previous studies have been inconsistent in this respect [
We replicated our analysis in two independent samples: NPHSII and WTCCC [
Participants were on average 60.9 y of age, the majority was men and from executive officer and senior administrative employment grades (
Participant Characteristics
Association between
Contemporaneous Associations of Risk Factors for Diabetes with Serum CRP Concentration, HbA1c, and HOMA-IR at Mean Age 61 y (Adjusted for Age and Sex)
Baseline serum CRP was a strong predictor of incident diabetes after adjustment for age and sex (hazard ratio [HR] for doubling of CRP 1.39 (95% confidence interval [CI] 1.29–1.51) (
Relation between Serum CRP at Mean Age 49 y and Incident Type 2 Diabetes among Participants of European Origin during 13.1 y Follow-up
Prospective and Cross-Sectional Associations of Serum CRP with HbA1c and HOMA-IR
Median levels of HbA1c and HOMA-IR did not vary by
Relation between
Comparison of Cross-Sectional and Prospective Associations between CRP and HbA1c Concentration Estimated by Linear Regression and with Instrumental Variables (with
Haplotype-serum CRP associations were similar to those observed in Whitehall II (
Pooled analysis of
Pooled Analysis of Association between
Case-control analysis of diabetes and the three SNPs in long-range LD with the SNPs of interest produced no evidence of association. Odds ratios (95% CI) were 0.98 (0.92–1.04) for rs12760041, 1.04 (0.98–1.12) for rs2592889, and 0.91 (0.81–1.03) for rs11265260.
This large study provides evidence that systemic CRP levels are not responsible for development of insulin resistance, hyperglycemia, or diabetes. The finding does not preclude the possibility that inflammatory signals contribute to causal processes leading to diabetes. We obtained a clear signal, using Mendelian randomization, that the association between systemic CRP and diabetes risk is not causal. However, the nature of the prospective relation between serum CRP and diabetes risk points to the potential effects of more proximal mediators in the inflammatory cascade.
Our underlying assumption was confirmed that genetic variants in
In addition to the analysis of Whitehall II data, further support for our conclusion concerning CRP and diabetes is provided by NPHSII and WTCCC. NPHSII haplotype and disease caseness data allowed a pooled haplotype-diabetes analysis with Whitehall II, which confirmed our null findings. Among almost 2,000 cases of diabetes and 3,000 controls in the WTCCC sample, we were able to identify three SNPs distant from the
Several issues may compromise the value of Mendelian randomization approach in assessing causality [
Our findings are consistent with a previous study that examined HOMA-IR as an outcome [
If glucose intolerance and insulin resistance have inflammatory causes, mediators should be sought among cytokines more proximal than CRP to the start of the inflammatory cascade. Gene expression of CRP occurs mainly in hepatocytes, regulated by interleukin (IL)-6 originating from adipocytes and immune tissue. This cytokine and tumor necrosis factor (TNF)-α are candidate mediators for the proposed inflammatory link between increased body fat and induction of insulin resistance locally in adipocytes and in distant tissues [
Rodent models of obesity provide evidence that adipose expression of TNF-α is associated, reversibly, with insulin resistance and reduced glucose uptake and fatty acid oxidation [
In humans, SNPs in
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Whitehall II study: We thank all participating civil service departments and their welfare, personnel, and establishment officers; the Occupational Health and Safety Agency; the Council of Civil Service Unions; all participating civil servants in the Whitehall II study; and all members of the Whitehall II study team.
WTCCC: A full list of investigators who contributed to the generation of the data is available at
body mass index
confidence interval
C-reactive protein
hemoglobin A1c
homeostasis model assessment-insulin resistance
hazard ratio
linkage disequilibrium
Northwick Park Heart Study II
tumor necrosis factor
Wellcome Trust Case Control Consortium