C-Reactive Protein and Diabetes: proving a negative, for a change?

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1 C-Reactive Protein and Diabetes: proving a negative, for a change? Eric Brunner PhD FFPH Reader in Epidemiology and Public Health MRC Centre for Causal Analyses in Translational Epidemiology 2 March 2009 Bristol

2 Objective To conduct a definitive study of the relation between CRP and type 2 diabetes with focus on the residual confounding explanation for the adjusted epidemiological effect

3 Background Raised serum hs-crp is a non-specific marker of low-grade inflammation and a risk factor for type 2 diabetes (T2D) Papers in Diabetes, Diabetes Care, Arch Int Med, JAMA suggest CRP may be causally related to insulin resistance Prospective studies Age, sex, BMI adjusted risk ratios Dehghan et al Diabetes 2007

4 Correlated risk factors measured imprecisely: residual confounding writ large HDL-C and TG measured with differing degrees of error Observed correlation r= TG effect Estimated β for CHD HDL effect univ adj for HDL univ adj for TG Observed Repeat r 0.6/ Repeat r 0.7/ Phillips and Davey Smith JCE 1991

5 So how are we to interpret the evidence in the case of C-reactive protein type 2 diabetes?

6 Is the relation between serum CRP and diabetes causal? Ridker s Medical News Brunner et al PLoS Med 2008

7 Hazard ratio (95%CI) for diabetes per doubling of serum CRP at age 49 with sequential adjustments year follow-up Model (279 cases, total N=4291 ) HR 95% CI P Age, sex, CRP>10 mg/l 1.40 ( ) < occupational status 1.39 ( ) < prevalent CHD, infectious symptoms 1.39 ( ) < BMI categories, waist circumference 1.22 ( ) < systolic BP, diastolic BP, BP treatment 1.20 ( ) < serum HDL-cholesterol, TG 1.17 ( ) Whitehall II study

8 Alternative explanations for the observed risk factordisease relation Confounding Reverse causation True causation T2DM β cell T2DM T2DM death Adapted from Hingorani and Humphries 2005

9 Intepretation? CRP-T2D effect attenuated by 53% on adjustment Is the cup half full or half empty? What are the potential explanations?

10 Mendelian randomization Taking advantage of natural genetic randomisation during sexual reproduction MR technique compares the effect of phenotype and genotype Two concepts 1. Random allocation of parental alleles to offspring leads to lifetime exposure to differing levels of the risk factor, in the present case CRP haplotype and heritable CRP level. 2. The genetically-influenced component of variation in the risk factor will generally be unaffected by confounding (Mendel s 2 nd law) and reverse causation, in contrast to the variation associated with environmental influences.

11 Study design: Whitehall II cohort Sample: 5274 white Europeans with CRP haplotype plus HbA1c or HOMA-IR Diabetes: phenotype defined by glucose tolerance tests and self report at baseline and follow-up (13 years) Glycaemia: HbA1c measured at follow-up (2003-4) Insulin resistance: HOMA-IR at follow-up (fasting GLU*INS)/22.5) Phenotype: serum hs-crp by immunonephelometry at baseline & follow-up CRP haplotype: 3 tsnps genotyped in the CRP gene +1444T>C, +2303G>A, +4899T>G ABI Prism sequence detection system; genotyping error rate <1% (n=553) not in HWE (P=0.003) (n=678 repeats)

12 Statistical methods Conventional linear, logistic and Cox regression Instrumental variables analysis CRP haplotypes used as instrumental variables for the unconfounded and unbiased effect of CRP on HbA1c and HOMA-IR Two-stage least squares method. 1. model haplotype-serum CRP-outcome association assuming each of a participant's two haplotypes contributes additively to serum CRP level. Timpson et al Lancet 2005 F-statistic used to evaluate strength of the instruments (F>10 indicates sufficient strength to ensure the validity of instrumental variable methods). Staiger and Stock, Econometrica compare results from the instrumental variable estimates of the association of CRP with HbA1c/HOMA-IR to those from ordinary linear regression using the Durbin form of the Durbin-Wu-Hausman statistic.

13 Analytic framework Age, socioeconomic status, BMI, BP CRP gene (haplotype) serum CRP (phenotype)? insulin resistance hyperglycaemia T2DM Instrumented variable Instrumental variables analysis Test of linear regression effect versus instrumented effect

14 Participants Characteristic N (%) unless otherwise stated Total N Age, mean (SD), y 60.9 (5.9) 5274 Women 1425 (27.0) 5274 BMI, mean (SD), kg/m (4.3) 5251 Physical inactivity 233 (4.5) 5231 Low occupational status* 432 (8.3) 5223 Current smoking 426 (8.1) 5248 Prevalent CHD 695 (13.2) 5274 Serum CRP, mean (SD), mg/l 2.58 (5.21) 5274 Previous serum CRP, mean (SD), mg/l 1.72 (3.21) 4674 Prevalent diabetes** 348 (7.1) 4883 Haemoglobin A1c, mean (SD), % 5.30 (0.60) 5266 HOMA-IR, mean (SD), (mu/l.mmol/l)/ (1.89) 4357 at mean age 49

15 Association between CRP haplotypes and serum CRP Median (IQR) CRP, mg/l Haplotype of +1444, and SNPs At mean age 61 years N=5092 At mean age 49 years N=4594 CAT CGG CGT TGT 0 (n = 2224/2014) 1.28 (0.70 to 2.51) 0.90 (0.46 to 1.79) 1 (n = 2334/2098) 1.14 (0.61 to 2.35) 0.77 (0.39 to 1.53) 2 (n = 534/482) 0.90 (0.47 to 1.89) 0.71 (0.37 to 1.29) P for trend < < (n = 4558/4116) 1.15 (0.61 to 2.33) 0.78 (0.40 to 1.59) 1 (n = 516/461) 1.45 (0.80 to 2.81) 0.96 (0.53 to 1.91) 2 (n = 18/17) 1.78 (1.13 to 3.73) 1.82 (1.47 to 4.35) P for trend < < (n = 2457/2193) 1.20 (0.62 to 2.48) 0.84 (0.43 to 1.67) 1 (n = 2163/1980) 1.16 (0.62 to 2.30) 0.78 (0.40 to 1.58) 2 (n = 472/421) 1.17 (0.67 to 2.45) 0.79 (0.40 to 1.62) P for trend (n = 2403/2169) 1.11 (0.58 to 2.27) 0.77 (0.39 to 1.49) 1 (n = 2262/2047) 1.20 (0.65 to 2.43) 0.83 (0.42 to 1.68) 2 (n = 427/378) 1.43 (0.75 to 2.73) 0.99 (0.54 to 2.06) P for trend < < excludes CRP>10mg/L

16 CRP haplotype is a determinant of serum CRP phenotype, and therefore a potential instrumental variable

17 Associations of risk factors for diabetes with serum CRP, HbA1c and HOMA-IR at age 61 log 2 CRP (mg/l) lnhba1c (%) lnhoma-ir Risk factor Beta* (95% CI) P Beta* (95% CI) P Beta* (95% CI) P Occupational status ( ) < ( ) < ( ) BMI ( ) < ( ) < ( ) < Waist circumference (per 10cm) Diastolic BP (per 10mmHg) Physical inactivity ( ) < ( ) < ( ) < ( ) < ( ) < ( ) < ( ) ( ) ( ) 0.14 linear regression adjusted for age and sex

18 Strong associations between known risk factors and (a) exposure (serum CRP) (b) outcome (HbA1c, HOMA-IR) Risk factors confound CRP-T2D relation

19 Cross-sectional and prospective associations of serum CRP with HbA1c and HOMA-IR Ratio of geometric means (95% CI) * Outcome N Adjusted for age, sex and raised CRP P Age, sex, raised CRP and risk factor adjusted P HbA1c (%) at mean age 61 Per doubling of CRP concentration at mean age 61 Per doubling of CRP concentration at mean age ( ) < ( ) < ( ) < ( ) HOMA-IR at mean age 61 Per doubling of CRP concentration at mean age 61 Per doubling of CRP concentration at mean age ( ) < ( ) ( ) < ( ) < adjusted for age, sex, raised CRP (>10 mg/l), occupational status, prevalent CHD, smoking, physical inactivity, BP, BP medication, BMI categories, waist circumference, serum HDL cholesterol and triglycerides, and additionally at age 61, diabetic medication

20 CRP phenotype link with HbA1c and HOMA-IR considerably attenuated but not abolished Parallel to the findings with serum CRP and incident T2D

21 Relation of CRP haplotypes with HbA1c and HOMA-IR at mean age 61 Trend test p-value adjusted for age group and sex

22 No CRP haplotype effect on HbA1c or HOMA-IR

23 Comparison of cross-sectional and prospective associations of CRP with HbA1c and HOMA-IR estimated by linear regression and instrumental variables analysis Linear regression analysis adjusted for age and sex a Test of equality of linear regression and instrumental variables estimates Durbin-Wu-Hausman test

24 Linear regression finds CRP--T2D/HbA1c/HOMA-IR associations Instrumental variables analysis does not (p > 0.6) Test of difference between estimates highly or borderline significant Upper limits of 95%CI for IV analysis compatible with phenotypic effect adjusted for age and sex

25 CRP haplotype and T2D: POOLED ANALYSIS, WII & NPHSII NPHSII: same haplotypes, 174 T2D cases, 2173 men aged 56 Total 522 T2D cases Logistic regression, adjusted for study, age (and WII sex)

26 REPLICATION ANALYSIS: WTCCC 3 snps, LD with WII/NPHSII tag SNPs (r 2 = ) 1923 Type 2 diabetes cases, 2932 controls OR (95% CI) rs ( ) rs ( ) rs ( )

27 No association between proxy snps and caseness Bounds of 95%CI compatible with 20% effect size

28 DISCUSSION Significant additional evidence against major causal effects of CRP on T2D and quantitative traits, insulin resistance and hyperglycaemia Study approaches proving the null/negative Larger studies? Further genetic analysis might involve low frequency intermediate-penetrance (LFIP) variants if identified (Keavney) Ball is in the CRP advocates court

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